Constructing Pairing-Friendly Elliptic Curves under Embedding Degree 1 for Securing Critical Infrastructures

PubMed Central

Dai, Guangming

2016-01-01

Information confidentiality is an essential requirement for cyber security in critical infrastructure. Identity-based cryptography, an increasingly popular branch of cryptography, is widely used to protect the information confidentiality in the critical infrastructure sector due to the ability to directly compute the user’s public key based on the user’s identity. However, computational requirements complicate the practical application of Identity-based cryptography. In order to improve the efficiency of identity-based cryptography, this paper presents an effective method to construct pairing-friendly elliptic curves with low hamming weight 4 under embedding degree 1. Based on the analysis of the Complex Multiplication(CM) method, the soundness of our method to calculate the characteristic of the finite field is proved. And then, three relative algorithms to construct pairing-friendly elliptic curve are put forward. 10 elliptic curves with low hamming weight 4 under 160 bits are presented to demonstrate the utility of our approach. Finally, the evaluation also indicates that it is more efficient to compute Tate pairing with our curves, than that of Bertoni et al. PMID:27564373

Use of agents to implement an integrated computing environment

NASA Technical Reports Server (NTRS)

Hale, Mark A.; Craig, James I.

1995-01-01

Integrated Product and Process Development (IPPD) embodies the simultaneous application to both system and quality engineering methods throughout an iterative design process. The use of IPPD results in the time-conscious, cost-saving development of engineering systems. To implement IPPD, a Decision-Based Design perspective is encapsulated in an approach that focuses on the role of the human designer in product development. The approach has two parts and is outlined in this paper. First, an architecture, called DREAMS, is being developed that facilitates design from a decision-based perspective. Second, a supporting computing infrastructure, called IMAGE, is being designed. Agents are used to implement the overall infrastructure on the computer. Successful agent utilization requires that they be made of three components: the resource, the model, and the wrap. Current work is focused on the development of generalized agent schemes and associated demonstration projects. When in place, the technology independent computing infrastructure will aid the designer in systematically generating knowledge used to facilitate decision-making.

Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics

PubMed Central

Giacomoni, Franck; Le Corguillé, Gildas; Monsoor, Misharl; Landi, Marion; Pericard, Pierre; Pétéra, Mélanie; Duperier, Christophe; Tremblay-Franco, Marie; Martin, Jean-François; Jacob, Daniel; Goulitquer, Sophie; Thévenot, Etienne A.; Caron, Christophe

2015-01-01

Summary: The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation. Availability and implementation: http://workflow4metabolomics.org homepage enables users to open a private account and access the infrastructure. W4M is developed and maintained by the French Bioinformatics Institute (IFB) and the French Metabolomics and Fluxomics Infrastructure (MetaboHUB). Contact: contact@workflow4metabolomics.org PMID:25527831

Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics.

PubMed

Giacomoni, Franck; Le Corguillé, Gildas; Monsoor, Misharl; Landi, Marion; Pericard, Pierre; Pétéra, Mélanie; Duperier, Christophe; Tremblay-Franco, Marie; Martin, Jean-François; Jacob, Daniel; Goulitquer, Sophie; Thévenot, Etienne A; Caron, Christophe

2015-05-01

The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation. http://workflow4metabolomics.org homepage enables users to open a private account and access the infrastructure. W4M is developed and maintained by the French Bioinformatics Institute (IFB) and the French Metabolomics and Fluxomics Infrastructure (MetaboHUB). contact@workflow4metabolomics.org. © The Author 2014. Published by Oxford University Press.

Monitoring performance of a highly distributed and complex computing infrastructure in LHCb

NASA Astrophysics Data System (ADS)

Mathe, Z.; Haen, C.; Stagni, F.

2017-10-01

In order to ensure an optimal performance of the LHCb Distributed Computing, based on LHCbDIRAC, it is necessary to be able to inspect the behavior over time of many components: firstly the agents and services on which the infrastructure is built, but also all the computing tasks and data transfers that are managed by this infrastructure. This consists of recording and then analyzing time series of a large number of observables, for which the usage of SQL relational databases is far from optimal. Therefore within DIRAC we have been studying novel possibilities based on NoSQL databases (ElasticSearch, OpenTSDB and InfluxDB) as a result of this study we developed a new monitoring system based on ElasticSearch. It has been deployed on the LHCb Distributed Computing infrastructure for which it collects data from all the components (agents, services, jobs) and allows creating reports through Kibana and a web user interface, which is based on the DIRAC web framework. In this paper we describe this new implementation of the DIRAC monitoring system. We give details on the ElasticSearch implementation within the DIRAC general framework, as well as an overview of the advantages of the pipeline aggregation used for creating a dynamic bucketing of the time series. We present the advantages of using the ElasticSearch DSL high-level library for creating and running queries. Finally we shall present the performances of that system.

Integration of Cloud resources in the LHCb Distributed Computing

NASA Astrophysics Data System (ADS)

Úbeda García, Mario; Méndez Muñoz, Víctor; Stagni, Federico; Cabarrou, Baptiste; Rauschmayr, Nathalie; Charpentier, Philippe; Closier, Joel

2014-06-01

This contribution describes how Cloud resources have been integrated in the LHCb Distributed Computing. LHCb is using its specific Dirac extension (LHCbDirac) as an interware for its Distributed Computing. So far, it was seamlessly integrating Grid resources and Computer clusters. The cloud extension of DIRAC (VMDIRAC) allows the integration of Cloud computing infrastructures. It is able to interact with multiple types of infrastructures in commercial and institutional clouds, supported by multiple interfaces (Amazon EC2, OpenNebula, OpenStack and CloudStack) - instantiates, monitors and manages Virtual Machines running on this aggregation of Cloud resources. Moreover, specifications for institutional Cloud resources proposed by Worldwide LHC Computing Grid (WLCG), mainly by the High Energy Physics Unix Information Exchange (HEPiX) group, have been taken into account. Several initiatives and computing resource providers in the eScience environment have already deployed IaaS in production during 2013. Keeping this on mind, pros and cons of a cloud based infrasctructure have been studied in contrast with the current setup. As a result, this work addresses four different use cases which represent a major improvement on several levels of our infrastructure. We describe the solution implemented by LHCb for the contextualisation of the VMs based on the idea of Cloud Site. We report on operational experience of using in production several institutional Cloud resources that are thus becoming integral part of the LHCb Distributed Computing resources. Furthermore, we describe as well the gradual migration of our Service Infrastructure towards a fully distributed architecture following the Service as a Service (SaaS) model.

Large-scale parallel genome assembler over cloud computing environment.

PubMed

Das, Arghya Kusum; Koppa, Praveen Kumar; Goswami, Sayan; Platania, Richard; Park, Seung-Jong

2017-06-01

The size of high throughput DNA sequencing data has already reached the terabyte scale. To manage this huge volume of data, many downstream sequencing applications started using locality-based computing over different cloud infrastructures to take advantage of elastic (pay as you go) resources at a lower cost. However, the locality-based programming model (e.g. MapReduce) is relatively new. Consequently, developing scalable data-intensive bioinformatics applications using this model and understanding the hardware environment that these applications require for good performance, both require further research. In this paper, we present a de Bruijn graph oriented Parallel Giraph-based Genome Assembler (GiGA), as well as the hardware platform required for its optimal performance. GiGA uses the power of Hadoop (MapReduce) and Giraph (large-scale graph analysis) to achieve high scalability over hundreds of compute nodes by collocating the computation and data. GiGA achieves significantly higher scalability with competitive assembly quality compared to contemporary parallel assemblers (e.g. ABySS and Contrail) over traditional HPC cluster. Moreover, we show that the performance of GiGA is significantly improved by using an SSD-based private cloud infrastructure over traditional HPC cluster. We observe that the performance of GiGA on 256 cores of this SSD-based cloud infrastructure closely matches that of 512 cores of traditional HPC cluster.

Towards a Multi-Mission, Airborne Science Data System Environment

NASA Astrophysics Data System (ADS)

Crichton, D. J.; Hardman, S.; Law, E.; Freeborn, D.; Kay-Im, E.; Lau, G.; Oswald, J.

2011-12-01

NASA earth science instruments are increasingly relying on airborne missions. However, traditionally, there has been limited common infrastructure support available to principal investigators in the area of science data systems. As a result, each investigator has been required to develop their own computing infrastructures for the science data system. Typically there is little software reuse and many projects lack sufficient resources to provide a robust infrastructure to capture, process, distribute and archive the observations acquired from airborne flights. At NASA's Jet Propulsion Laboratory (JPL), we have been developing a multi-mission data system infrastructure for airborne instruments called the Airborne Cloud Computing Environment (ACCE). ACCE encompasses the end-to-end lifecycle covering planning, provisioning of data system capabilities, and support for scientific analysis in order to improve the quality, cost effectiveness, and capabilities to enable new scientific discovery and research in earth observation. This includes improving data system interoperability across each instrument. A principal characteristic is being able to provide an agile infrastructure that is architected to allow for a variety of configurations of the infrastructure from locally installed compute and storage services to provisioning those services via the "cloud" from cloud computer vendors such as Amazon.com. Investigators often have different needs that require a flexible configuration. The data system infrastructure is built on the Apache's Object Oriented Data Technology (OODT) suite of components which has been used for a number of spaceborne missions and provides a rich set of open source software components and services for constructing science processing and data management systems. In 2010, a partnership was formed between the ACCE team and the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) mission to support the data processing and data management needs. A principal goal is to provide support for the Fourier Transform Spectrometer (FTS) instrument which will produce over 700,000 soundings over the life of their three-year mission. The cost to purchase and operate a cluster-based system in order to generate Level 2 Full Physics products from this data was prohibitive. Through an evaluation of cloud computing solutions, Amazon's Elastic Compute Cloud (EC2) was selected for the CARVE deployment. As the ACCE infrastructure is developed and extended to form an infrastructure for airborne missions, the experience of working with CARVE has provided a number of lessons learned and has proven to be important in reinforcing the unique aspects of airborne missions and the importance of the ACCE infrastructure in developing a cost effective, flexible multi-mission capability that leverages emerging capabilities in cloud computing, workflow management, and distributed computing.

Evolution of the Virtualized HPC Infrastructure of Novosibirsk Scientific Center

NASA Astrophysics Data System (ADS)

Adakin, A.; Anisenkov, A.; Belov, S.; Chubarov, D.; Kalyuzhny, V.; Kaplin, V.; Korol, A.; Kuchin, N.; Lomakin, S.; Nikultsev, V.; Skovpen, K.; Sukharev, A.; Zaytsev, A.

2012-12-01

Novosibirsk Scientific Center (NSC), also known worldwide as Akademgorodok, is one of the largest Russian scientific centers hosting Novosibirsk State University (NSU) and more than 35 research organizations of the Siberian Branch of Russian Academy of Sciences including Budker Institute of Nuclear Physics (BINP), Institute of Computational Technologies, and Institute of Computational Mathematics and Mathematical Geophysics (ICM&MG). Since each institute has specific requirements on the architecture of computing farms involved in its research field, currently we've got several computing facilities hosted by NSC institutes, each optimized for a particular set of tasks, of which the largest are the NSU Supercomputer Center, Siberian Supercomputer Center (ICM&MG), and a Grid Computing Facility of BINP. A dedicated optical network with the initial bandwidth of 10 Gb/s connecting these three facilities was built in order to make it possible to share the computing resources among the research communities, thus increasing the efficiency of operating the existing computing facilities and offering a common platform for building the computing infrastructure for future scientific projects. Unification of the computing infrastructure is achieved by extensive use of virtualization technology based on XEN and KVM platforms. This contribution gives a thorough review of the present status and future development prospects for the NSC virtualized computing infrastructure and the experience gained while using it for running production data analysis jobs related to HEP experiments being carried out at BINP, especially the KEDR detector experiment at the VEPP-4M electron-positron collider.

A scalable infrastructure for CMS data analysis based on OpenStack Cloud and Gluster file system

NASA Astrophysics Data System (ADS)

Toor, S.; Osmani, L.; Eerola, P.; Kraemer, O.; Lindén, T.; Tarkoma, S.; White, J.

2014-06-01

The challenge of providing a resilient and scalable computational and data management solution for massive scale research environments requires continuous exploration of new technologies and techniques. In this project the aim has been to design a scalable and resilient infrastructure for CERN HEP data analysis. The infrastructure is based on OpenStack components for structuring a private Cloud with the Gluster File System. We integrate the state-of-the-art Cloud technologies with the traditional Grid middleware infrastructure. Our test results show that the adopted approach provides a scalable and resilient solution for managing resources without compromising on performance and high availability.

Analysis of Pervasive Mobile Ad Hoc Routing Protocols

NASA Astrophysics Data System (ADS)

Qadri, Nadia N.; Liotta, Antonio

Mobile ad hoc networks (MANETs) are a fundamental element of pervasive networks and therefore, of pervasive systems that truly support pervasive computing, where user can communicate anywhere, anytime and on-the-fly. In fact, future advances in pervasive computing rely on advancements in mobile communication, which includes both infrastructure-based wireless networks and non-infrastructure-based MANETs. MANETs introduce a new communication paradigm, which does not require a fixed infrastructure - they rely on wireless terminals for routing and transport services. Due to highly dynamic topology, absence of established infrastructure for centralized administration, bandwidth constrained wireless links, and limited resources in MANETs, it is challenging to design an efficient and reliable routing protocol. This chapter reviews the key studies carried out so far on the performance of mobile ad hoc routing protocols. We discuss performance issues and metrics required for the evaluation of ad hoc routing protocols. This leads to a survey of existing work, which captures the performance of ad hoc routing algorithms and their behaviour from different perspectives and highlights avenues for future research.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hale, M.A.; Craig, J.I.

Integrated Product and Process Development (IPPD) embodies the simultaneous application to both system and quality engineering methods throughout an iterative design process. The use of IPPD results in the time-conscious, cost-saving development of engineering systems. To implement IPPD, a Decision-Based Design perspective is encapsulated in an approach that focuses on the role of the human designer in product development. The approach has two parts and is outlined in this paper. First, an architecture, called DREAMS, is being developed that facilitates design from a decision-based perspective. Second, a supporting computing infrastructure, called IMAGE, is being designed. Agents are used to implementmore » the overall infrastructure on the computer. Successful agent utilization requires that they be made of three components: the resource, the model, and the wrap. Current work is focused on the development of generalized agent schemes and associated demonstration projects. When in place, the technology independent computing infrastructure will aid the designer in systematically generating knowledge used to facilitate decision-making.« less

S3DB core: a framework for RDF generation and management in bioinformatics infrastructures

PubMed Central

2010-01-01

Background Biomedical research is set to greatly benefit from the use of semantic web technologies in the design of computational infrastructure. However, beyond well defined research initiatives, substantial issues of data heterogeneity, source distribution, and privacy currently stand in the way towards the personalization of Medicine. Results A computational framework for bioinformatic infrastructure was designed to deal with the heterogeneous data sources and the sensitive mixture of public and private data that characterizes the biomedical domain. This framework consists of a logical model build with semantic web tools, coupled with a Markov process that propagates user operator states. An accompanying open source prototype was developed to meet a series of applications that range from collaborative multi-institution data acquisition efforts to data analysis applications that need to quickly traverse complex data structures. This report describes the two abstractions underlying the S3DB-based infrastructure, logical and numerical, and discusses its generality beyond the immediate confines of existing implementations. Conclusions The emergence of the "web as a computer" requires a formal model for the different functionalities involved in reading and writing to it. The S3DB core model proposed was found to address the design criteria of biomedical computational infrastructure, such as those supporting large scale multi-investigator research, clinical trials, and molecular epidemiology. PMID:20646315

GLIDE: a grid-based light-weight infrastructure for data-intensive environments

NASA Technical Reports Server (NTRS)

Mattmann, Chris A.; Malek, Sam; Beckman, Nels; Mikic-Rakic, Marija; Medvidovic, Nenad; Chrichton, Daniel J.

2005-01-01

The promise of the grid is that it will enable public access and sharing of immense amounts of computational and data resources among dynamic coalitions of individuals and institutions. However, the current grid solutions make several limiting assumptions that curtail their widespread adoption. To address these limitations, we present GLIDE, a prototype light-weight, data-intensive middleware infrastructure that enables access to the robust data and computational power of the grid on DREAM platforms.

Advanced Optical Burst Switched Network Concepts

NASA Astrophysics Data System (ADS)

Nejabati, Reza; Aracil, Javier; Castoldi, Piero; de Leenheer, Marc; Simeonidou, Dimitra; Valcarenghi, Luca; Zervas, Georgios; Wu, Jian

In recent years, as the bandwidth and the speed of networks have increased significantly, a new generation of network-based applications using the concept of distributed computing and collaborative services is emerging (e.g., Grid computing applications). The use of the available fiber and DWDM infrastructure for these applications is a logical choice offering huge amounts of cheap bandwidth and ensuring global reach of computing resources [230]. Currently, there is a great deal of interest in deploying optical circuit (wavelength) switched network infrastructure for distributed computing applications that require long-lived wavelength paths and address the specific needs of a small number of well-known users. Typical users are particle physicists who, due to their international collaborations and experiments, generate enormous amounts of data (Petabytes per year). These users require a network infrastructures that can support processing and analysis of large datasets through globally distributed computing resources [230]. However, providing wavelength granularity bandwidth services is not an efficient and scalable solution for applications and services that address a wider base of user communities with different traffic profiles and connectivity requirements. Examples of such applications may be: scientific collaboration in smaller scale (e.g., bioinformatics, environmental research), distributed virtual laboratories (e.g., remote instrumentation), e-health, national security and defense, personalized learning environments and digital libraries, evolving broadband user services (i.e., high resolution home video editing, real-time rendering, high definition interactive TV). As a specific example, in e-health services and in particular mammography applications due to the size and quantity of images produced by remote mammography, stringent network requirements are necessary. Initial calculations have shown that for 100 patients to be screened remotely, the network would have to securely transport 1.2 GB of data every 30 s [230]. According to the above explanation it is clear that these types of applications need a new network infrastructure and transport technology that makes large amounts of bandwidth at subwavelength granularity, storage, computation, and visualization resources potentially available to a wide user base for specified time durations. As these types of collaborative and network-based applications evolve addressing a wide range and large number of users, it is infeasible to build dedicated networks for each application type or category. Consequently, there should be an adaptive network infrastructure able to support all application types, each with their own access, network, and resource usage patterns. This infrastructure should offer flexible and intelligent network elements and control mechanism able to deploy new applications quickly and efficiently.

An Open Computing Infrastructure that Facilitates Integrated Product and Process Development from a Decision-Based Perspective

NASA Technical Reports Server (NTRS)

Hale, Mark A.

1996-01-01

Computer applications for design have evolved rapidly over the past several decades, and significant payoffs are being achieved by organizations through reductions in design cycle times. These applications are overwhelmed by the requirements imposed during complex, open engineering systems design. Organizations are faced with a number of different methodologies, numerous legacy disciplinary tools, and a very large amount of data. Yet they are also faced with few interdisciplinary tools for design collaboration or methods for achieving the revolutionary product designs required to maintain a competitive advantage in the future. These organizations are looking for a software infrastructure that integrates current corporate design practices with newer simulation and solution techniques. Such an infrastructure must be robust to changes in both corporate needs and enabling technologies. In addition, this infrastructure must be user-friendly, modular and scalable. This need is the motivation for the research described in this dissertation. The research is focused on the development of an open computing infrastructure that facilitates product and process design. In addition, this research explicitly deals with human interactions during design through a model that focuses on the role of a designer as that of decision-maker. The research perspective here is taken from that of design as a discipline with a focus on Decision-Based Design, Theory of Languages, Information Science, and Integration Technology. Given this background, a Model of IPPD is developed and implemented along the lines of a traditional experimental procedure: with the steps of establishing context, formalizing a theory, building an apparatus, conducting an experiment, reviewing results, and providing recommendations. Based on this Model, Design Processes and Specification can be explored in a structured and implementable architecture. An architecture for exploring design called DREAMS (Developing Robust Engineering Analysis Models and Specifications) has been developed which supports the activities of both meta-design and actual design execution. This is accomplished through a systematic process which is comprised of the stages of Formulation, Translation, and Evaluation. During this process, elements from a Design Specification are integrated into Design Processes. In addition, a software infrastructure was developed and is called IMAGE (Intelligent Multidisciplinary Aircraft Generation Environment). This represents a virtual apparatus in the Design Experiment conducted in this research. IMAGE is an innovative architecture because it explicitly supports design-related activities. This is accomplished through a GUI driven and Agent-based implementation of DREAMS. A HSCT design has been adopted from the Framework for Interdisciplinary Design Optimization (FIDO) and is implemented in IMAGE. This problem shows how Design Processes and Specification interact in a design system. In addition, the problem utilizes two different solution models concurrently: optimal and satisfying. The satisfying model allows for more design flexibility and allows a designer to maintain design freedom. As a result of following this experimental procedure, this infrastructure is an open system that it is robust to changes in both corporate needs and computer technologies. The development of this infrastructure leads to a number of significant intellectual contributions: 1) A new approach to implementing IPPD with the aid of a computer; 2) A formal Design Experiment; 3) A combined Process and Specification architecture that is language-based; 4) An infrastructure for exploring design; 5) An integration strategy for implementing computer resources; and 6) A seamless modeling language. The need for these contributions is emphasized by the demand by industry and government agencies for the development of these technologies.

The Czech National Grid Infrastructure

NASA Astrophysics Data System (ADS)

Chudoba, J.; Křenková, I.; Mulač, M.; Ruda, M.; Sitera, J.

2017-10-01

The Czech National Grid Infrastructure is operated by MetaCentrum, a CESNET department responsible for coordinating and managing activities related to distributed computing. CESNET as the Czech National Research and Education Network (NREN) provides many e-infrastructure services, which are used by 94% of the scientific and research community in the Czech Republic. Computing and storage resources owned by different organizations are connected by fast enough network to provide transparent access to all resources. We describe in more detail the computing infrastructure, which is based on several different technologies and covers grid, cloud and map-reduce environment. While the largest part of CPUs is still accessible via distributed torque servers, providing environment for long batch jobs, part of infrastructure is available via standard EGI tools in EGI, subset of NGI resources is provided into EGI FedCloud environment with cloud interface and there is also Hadoop cluster provided by the same e-infrastructure.A broad spectrum of computing servers is offered; users can choose from standard 2 CPU servers to large SMP machines with up to 6 TB of RAM or servers with GPU cards. Different groups have different priorities on various resources, resource owners can even have an exclusive access. The software is distributed via AFS. Storage servers offering up to tens of terabytes of disk space to individual users are connected via NFS4 on top of GPFS and access to long term HSM storage with peta-byte capacity is also provided. Overview of available resources and recent statistics of usage will be given.

An adaptive process-based cloud infrastructure for space situational awareness applications

NASA Astrophysics Data System (ADS)

Liu, Bingwei; Chen, Yu; Shen, Dan; Chen, Genshe; Pham, Khanh; Blasch, Erik; Rubin, Bruce

2014-06-01

Space situational awareness (SSA) and defense space control capabilities are top priorities for groups that own or operate man-made spacecraft. Also, with the growing amount of space debris, there is an increase in demand for contextual understanding that necessitates the capability of collecting and processing a vast amount sensor data. Cloud computing, which features scalable and flexible storage and computing services, has been recognized as an ideal candidate that can meet the large data contextual challenges as needed by SSA. Cloud computing consists of physical service providers and middleware virtual machines together with infrastructure, platform, and software as service (IaaS, PaaS, SaaS) models. However, the typical Virtual Machine (VM) abstraction is on a per operating systems basis, which is at too low-level and limits the flexibility of a mission application architecture. In responding to this technical challenge, a novel adaptive process based cloud infrastructure for SSA applications is proposed in this paper. In addition, the details for the design rationale and a prototype is further examined. The SSA Cloud (SSAC) conceptual capability will potentially support space situation monitoring and tracking, object identification, and threat assessment. Lastly, the benefits of a more granular and flexible cloud computing resources allocation are illustrated for data processing and implementation considerations within a representative SSA system environment. We show that the container-based virtualization performs better than hypervisor-based virtualization technology in an SSA scenario.

The Mediated Museum: Computer-Based Technology and Museum Infrastructure.

ERIC Educational Resources Information Center

Sterman, Nanette T.; Allen, Brockenbrough S.

1991-01-01

Describes the use of computer-based tools and techniques in museums. The integration of realia with media-based advice and interpretation is described, electronic replicas of ancient Greek vases in the J. Paul Getty Museum are explained, examples of mediated exhibits are presented, and the use of hypermedia is discussed. (five references) (LRW)

A modular (almost) automatic set-up for elastic multi-tenants cloud (micro)infrastructures

NASA Astrophysics Data System (ADS)

Amoroso, A.; Astorino, F.; Bagnasco, S.; Balashov, N. A.; Bianchi, F.; Destefanis, M.; Lusso, S.; Maggiora, M.; Pellegrino, J.; Yan, L.; Yan, T.; Zhang, X.; Zhao, X.

2017-10-01

An auto-installing tool on an usb drive can allow for a quick and easy automatic deployment of OpenNebula-based cloud infrastructures remotely managed by a central VMDIRAC instance. A single team, in the main site of an HEP Collaboration or elsewhere, can manage and run a relatively large network of federated (micro-)cloud infrastructures, making an highly dynamic and elastic use of computing resources. Exploiting such an approach can lead to modular systems of cloud-bursting infrastructures addressing complex real-life scenarios.

Autonomic Management of Application Workflows on Hybrid Computing Infrastructure

DOE PAGES

Kim, Hyunjoo; el-Khamra, Yaakoub; Rodero, Ivan; ...

2011-01-01

In this paper, we present a programming and runtime framework that enables the autonomic management of complex application workflows on hybrid computing infrastructures. The framework is designed to address system and application heterogeneity and dynamics to ensure that application objectives and constraints are satisfied. The need for such autonomic system and application management is becoming critical as computing infrastructures become increasingly heterogeneous, integrating different classes of resources from high-end HPC systems to commodity clusters and clouds. For example, the framework presented in this paper can be used to provision the appropriate mix of resources based on application requirements and constraints.more » The framework also monitors the system/application state and adapts the application and/or resources to respond to changing requirements or environment. To demonstrate the operation of the framework and to evaluate its ability, we employ a workflow used to characterize an oil reservoir executing on a hybrid infrastructure composed of TeraGrid nodes and Amazon EC2 instances of various types. Specifically, we show how different applications objectives such as acceleration, conservation and resilience can be effectively achieved while satisfying deadline and budget constraints, using an appropriate mix of dynamically provisioned resources. Our evaluations also demonstrate that public clouds can be used to complement and reinforce the scheduling and usage of traditional high performance computing infrastructure.« less

Models of Educational Computing @ Home: New Frontiers for Research on Technology in Learning.

ERIC Educational Resources Information Center

Kafai, Yasmin B.; Fishman, Barry J.; Bruckman, Amy S.; Rockman, Saul

2002-01-01

Discusses models of home educational computing that are linked to learning in school and recommends the need for research that addresses the home as a computer-based learning environment. Topics include a history of research on educational computing at home; technological infrastructure, including software and compatibility; Internet access;…

Evaluation of Service Level Agreement Approaches for Portfolio Management in the Financial Industry

NASA Astrophysics Data System (ADS)

Pontz, Tobias; Grauer, Manfred; Kuebert, Roland; Tenschert, Axel; Koller, Bastian

The idea of service-oriented Grid computing seems to have the potential for fundamental paradigm change and a new architectural alignment concerning the design of IT infrastructures. There is a wide range of technical approaches from scientific communities which describe basic infrastructures and middlewares for integrating Grid resources in order that by now Grid applications are technically realizable. Hence, Grid computing needs viable business models and enhanced infrastructures to move from academic application right up to commercial application. For a commercial usage of these evolutions service level agreements are needed. The developed approaches are primary of academic interest and mostly have not been put into practice. Based on a business use case of the financial industry, five service level agreement approaches have been evaluated in this paper. Based on the evaluation, a management architecture has been designed and implemented as a prototype.

AstroCloud, a Cyber-Infrastructure for Astronomy Research: Cloud Computing Environments

NASA Astrophysics Data System (ADS)

Li, C.; Wang, J.; Cui, C.; He, B.; Fan, D.; Yang, Y.; Chen, J.; Zhang, H.; Yu, C.; Xiao, J.; Wang, C.; Cao, Z.; Fan, Y.; Hong, Z.; Li, S.; Mi, L.; Wan, W.; Wang, J.; Yin, S.

2015-09-01

AstroCloud is a cyber-Infrastructure for Astronomy Research initiated by Chinese Virtual Observatory (China-VO) under funding support from NDRC (National Development and Reform commission) and CAS (Chinese Academy of Sciences). Based on CloudStack, an open source software, we set up the cloud computing environment for AstroCloud Project. It consists of five distributed nodes across the mainland of China. Users can use and analysis data in this cloud computing environment. Based on GlusterFS, we built a scalable cloud storage system. Each user has a private space, which can be shared among different virtual machines and desktop systems. With this environments, astronomer can access to astronomical data collected by different telescopes and data centers easily, and data producers can archive their datasets safely.

iSERVO: Implementing the International Solid Earth Research Virtual Observatory by Integrating Computational Grid and Geographical Information Web Services

NASA Astrophysics Data System (ADS)

Aktas, Mehmet; Aydin, Galip; Donnellan, Andrea; Fox, Geoffrey; Granat, Robert; Grant, Lisa; Lyzenga, Greg; McLeod, Dennis; Pallickara, Shrideep; Parker, Jay; Pierce, Marlon; Rundle, John; Sayar, Ahmet; Tullis, Terry

2006-12-01

We describe the goals and initial implementation of the International Solid Earth Virtual Observatory (iSERVO). This system is built using a Web Services approach to Grid computing infrastructure and is accessed via a component-based Web portal user interface. We describe our implementations of services used by this system, including Geographical Information System (GIS)-based data grid services for accessing remote data repositories and job management services for controlling multiple execution steps. iSERVO is an example of a larger trend to build globally scalable scientific computing infrastructures using the Service Oriented Architecture approach. Adoption of this approach raises a number of research challenges in millisecond-latency message systems suitable for internet-enabled scientific applications. We review our research in these areas.

Three-Dimensional Space to Assess Cloud Interoperability

DTIC Science & Technology

2013-03-01

12 1. Portability and Mobility ...collection of network-enabled services that guarantees to provide a scalable, easy accessible, reliable, and personalized computing infrastructure , based on...are used in research to describe cloud models, such as SaaS (Software as a Service), PaaS (Platform as a service), IaaS ( Infrastructure as a Service

Resilient workflows for computational mechanics platforms

NASA Astrophysics Data System (ADS)

Nguyên, Toàn; Trifan, Laurentiu; Désidéri, Jean-Antoine

2010-06-01

Workflow management systems have recently been the focus of much interest and many research and deployment for scientific applications worldwide [26, 27]. Their ability to abstract the applications by wrapping application codes have also stressed the usefulness of such systems for multidiscipline applications [23, 24]. When complex applications need to provide seamless interfaces hiding the technicalities of the computing infrastructures, their high-level modeling, monitoring and execution functionalities help giving production teams seamless and effective facilities [25, 31, 33]. Software integration infrastructures based on programming paradigms such as Python, Mathlab and Scilab have also provided evidence of the usefulness of such approaches for the tight coupling of multidisciplne application codes [22, 24]. Also high-performance computing based on multi-core multi-cluster infrastructures open new opportunities for more accurate, more extensive and effective robust multi-discipline simulations for the decades to come [28]. This supports the goal of full flight dynamics simulation for 3D aircraft models within the next decade, opening the way to virtual flight-tests and certification of aircraft in the future [23, 24, 29].

Ubiquitous Green Computing Techniques for High Demand Applications in Smart Environments

PubMed Central

Zapater, Marina; Sanchez, Cesar; Ayala, Jose L.; Moya, Jose M.; Risco-Martín, José L.

2012-01-01

Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in WSNs infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the WSN infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time. PMID:23112621

Ubiquitous green computing techniques for high demand applications in Smart environments.

PubMed

Zapater, Marina; Sanchez, Cesar; Ayala, Jose L; Moya, Jose M; Risco-Martín, José L

2012-01-01

Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in WSNs infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the WSN infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time.

Evolution of a Materials Data Infrastructure

NASA Astrophysics Data System (ADS)

Warren, James A.; Ward, Charles H.

2018-06-01

The field of materials science and engineering is writing a new chapter in its evolution, one of digitally empowered materials discovery, development, and deployment. The 2008 Integrated Computational Materials Engineering (ICME) study report helped usher in this paradigm shift, making a compelling case and strong recommendations for an infrastructure supporting ICME that would enable access to precompetitive materials data for both scientific and engineering applications. With the launch of the Materials Genome Initiative in 2011, which drew substantial inspiration from the ICME study, digital data was highlighted as a core component of a Materials Innovation Infrastructure, along with experimental and computational tools. Over the past 10 years, our understanding of what it takes to provide accessible materials data has matured and rapid progress has been made in establishing a Materials Data Infrastructure (MDI). We are learning that the MDI is essential to eliminating the seams between experiment and computation by providing a means for them to connect effortlessly. Additionally, the MDI is becoming an enabler, allowing materials engineering to tie into a much broader model-based engineering enterprise for product design.

Grid Computing at GSI for ALICE and FAIR - present and future

NASA Astrophysics Data System (ADS)

Schwarz, Kilian; Uhlig, Florian; Karabowicz, Radoslaw; Montiel-Gonzalez, Almudena; Zynovyev, Mykhaylo; Preuss, Carsten

2012-12-01

The future FAIR experiments CBM and PANDA have computing requirements that fall in a category that could currently not be satisfied by one single computing centre. One needs a larger, distributed computing infrastructure to cope with the amount of data to be simulated and analysed. Since 2002, GSI operates a tier2 center for ALICE@CERN. The central component of the GSI computing facility and hence the core of the ALICE tier2 centre is a LSF/SGE batch farm, currently split into three subclusters with a total of 15000 CPU cores shared by the participating experiments, and accessible both locally and soon also completely via Grid. In terms of data storage, a 5.5 PB Lustre file system, directly accessible from all worker nodes is maintained, as well as a 300 TB xrootd-based Grid storage element. Based on this existing expertise, and utilising ALICE's middleware ‘AliEn’, the Grid infrastructure for PANDA and CBM is being built. Besides a tier0 centre at GSI, the computing Grids of the two FAIR collaborations encompass now more than 17 sites in 11 countries and are constantly expanding. The operation of the distributed FAIR computing infrastructure benefits significantly from the experience gained with the ALICE tier2 centre. A close collaboration between ALICE Offline and FAIR provides mutual advantages. The employment of a common Grid middleware as well as compatible simulation and analysis software frameworks ensure significant synergy effects.

On the Development of a Computing Infrastructure that Facilitates IPPD from a Decision-Based Design Perspective

NASA Technical Reports Server (NTRS)

Hale, Mark A.; Craig, James I.; Mistree, Farrokh; Schrage, Daniel P.

1995-01-01

Integrated Product and Process Development (IPPD) embodies the simultaneous application of both system and quality engineering methods throughout an iterative design process. The use of IPPD results in the time-conscious, cost-saving development of engineering systems. Georgia Tech has proposed the development of an Integrated Design Engineering Simulator that will merge Integrated Product and Process Development with interdisciplinary analysis techniques and state-of-the-art computational technologies. To implement IPPD, a Decision-Based Design perspective is encapsulated in an approach that focuses on the role of the human designer in product development. The approach has two parts and is outlined in this paper. First, an architecture, called DREAMS, is being developed that facilitates design from a decision-based perspective. Second, a supporting computing infrastructure, called IMAGE, is being designed. The current status of development is given and future directions are outlined.

An Infrastructure for Web-Based Computer Assisted Learning

ERIC Educational Resources Information Center

Joy, Mike; Muzykantskii, Boris; Rawles, Simon; Evans, Michael

2002-01-01

We describe an initiative under way at Warwick to provide a technical foundation for computer aided learning and computer-assisted assessment tools, which allows a rich dialogue sensitive to individual students' response patterns. The system distinguishes between dialogues for individual problems and the linking of problems. This enables a subject…

GreenView and GreenLand Applications Development on SEE-GRID Infrastructure

NASA Astrophysics Data System (ADS)

Mihon, Danut; Bacu, Victor; Gorgan, Dorian; Mészáros, Róbert; Gelybó, Györgyi; Stefanut, Teodor

2010-05-01

The GreenView and GreenLand applications [1] have been developed through the SEE-GRID-SCI (SEE-GRID eInfrastructure for regional eScience) FP7 project co-funded by the European Commission [2]. The development of environment applications is a challenge for Grid technologies and software development methodologies. This presentation exemplifies the development of the GreenView and GreenLand applications over the SEE-GRID infrastructure by the Grid Application Development Methodology [3]. Today's environmental applications are used in vary domains of Earth Science such as meteorology, ground and atmospheric pollution, ground metal detection or weather prediction. These applications run on satellite images (e.g. Landsat, MERIS, MODIS, etc.) and the accuracy of output results depends mostly of the quality of these images. The main drawback of such environmental applications regards the need of computation power and storage power (some images are almost 1GB in size), in order to process such a large data volume. Actually, almost applications requiring high computation resources have approached the migration onto the Grid infrastructure. This infrastructure offers the computing power by running the atomic application components on different Grid nodes in sequential or parallel mode. The middleware used between the Grid infrastructure and client applications is ESIP (Environment Oriented Satellite Image Processing Platform), which is based on gProcess platform [4]. In its current format, gProcess is used for launching new processes on the Grid nodes, but also for monitoring the execution status of these processes. This presentation highlights two case studies of Grid based environmental applications, GreenView and GreenLand [5]. GreenView is used in correlation with MODIS (Moderate Resolution Imaging Spectroradiometer) satellite images and meteorological datasets, in order to produce pseudo colored temperature and vegetation maps for different geographical CEE (Central Eastern Europe) regions. On the other hand, GreenLand is used for generating maps for different vegetation indexes (e.g. NDVI, EVI, SAVI, GEMI) based on Landsat satellite images. Both applications are using interpolation and random value generation algorithms, but also specific formulas for computing vegetation index values. The GreenView and GreenLand applications have been experimented over the SEE-GRID infrastructure and the performance evaluation is reported in [6]. The improvement of the execution time (obtained through a better parallelization of jobs), the extension of geographical areas to other parts of the Earth, and new user interaction techniques on spatial data and large set of satellite images are the goals of the future work. References [1] GreenView application on Wiki, http://wiki.egee-see.org/index.php/GreenView [2] SEE-GRID-SCI Project, http://www.see-grid-sci.eu/ [3] Gorgan D., Stefanut T., Bâcu V., Mihon D., Grid based Environment Application Development Methodology, SCICOM, 7th International Conference on "Large-Scale Scientific Computations", 4-8 June, 2009, Sozopol, Bulgaria, (To be published by Springer), (2009). [4] Gorgan D., Bacu V., Stefanut T., Rodila D., Mihon D., Grid based Satellite Image Processing Platform for Earth Observation Applications Development. IDAACS'2009 - IEEE Fifth International Workshop on "Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications", 21-23 September, Cosenza, Italy, IEEE Published in Computer Press, 247-252 (2009). [5] Mihon D., Bacu V., Stefanut T., Gorgan D., "Grid Based Environment Application Development - GreenView Application". ICCP2009 - IEEE 5th International Conference on Intelligent Computer Communication and Processing, 27 Aug, 2009 Cluj-Napoca. Published by IEEE Computer Press, pp. 275-282 (2009). [6] Danut Mihon, Victor Bacu, Dorian Gorgan, Róbert Mészáros, Györgyi Gelybó, Teodor Stefanut, Practical Considerations on the GreenView Application Development and Execution over SEE-GRID. SEE-GRID-SCI User Forum, 9-10 Dec 2009, Bogazici University, Istanbul, Turkey, ISBN: 978-975-403-510-0, pp. 167-175 (2009).

Knowledge Cultures and the Shaping of Work-Based Learning: The Case of Computer Engineering

ERIC Educational Resources Information Center

Nerland, Monika

2008-01-01

This paper examines how the knowledge culture of computer engineering--that is, the ways in which knowledge is produced, distributed, accumulated and collectively approached within this profession--serve to construct work-based learning in specific ways. Typically, the epistemic infrastructures take the form of information structures with a global…

Investigations into Gravitational Wave Emission from Compact Body Inspiral Into Massive Black Holes

NASA Technical Reports Server (NTRS)

Hughes, Scott A.

2004-01-01

Much of the grant's support (and associated time) was used in developmental activity, building infrastructure for the core of the work that the grant supports. Though infrastructure development was the bulk of the activity supported this year, important progress was made in research as well. The two most important "infrastructure" items were in computing hardware and personnel. Research activities were primarily focused on improving and extending. Hughes' Teukolsky-equation-based gravitational-wave generator. Several improvements have been incorporated into this generator.

Cloud Bursting with GlideinWMS: Means to satisfy ever increasing computing needs for Scientific Workflows

NASA Astrophysics Data System (ADS)

Mhashilkar, Parag; Tiradani, Anthony; Holzman, Burt; Larson, Krista; Sfiligoi, Igor; Rynge, Mats

2014-06-01

Scientific communities have been in the forefront of adopting new technologies and methodologies in the computing. Scientific computing has influenced how science is done today, achieving breakthroughs that were impossible to achieve several decades ago. For the past decade several such communities in the Open Science Grid (OSG) and the European Grid Infrastructure (EGI) have been using GlideinWMS to run complex application workflows to effectively share computational resources over the grid. GlideinWMS is a pilot-based workload management system (WMS) that creates on demand, a dynamically sized overlay HTCondor batch system on grid resources. At present, the computational resources shared over the grid are just adequate to sustain the computing needs. We envision that the complexity of the science driven by "Big Data" will further push the need for computational resources. To fulfill their increasing demands and/or to run specialized workflows, some of the big communities like CMS are investigating the use of cloud computing as Infrastructure-As-A-Service (IAAS) with GlideinWMS as a potential alternative to fill the void. Similarly, communities with no previous access to computing resources can use GlideinWMS to setup up a batch system on the cloud infrastructure. To enable this, the architecture of GlideinWMS has been extended to enable support for interfacing GlideinWMS with different Scientific and commercial cloud providers like HLT, FutureGrid, FermiCloud and Amazon EC2. In this paper, we describe a solution for cloud bursting with GlideinWMS. The paper describes the approach, architectural changes and lessons learned while enabling support for cloud infrastructures in GlideinWMS.

Cloud Bursting with GlideinWMS: Means to satisfy ever increasing computing needs for Scientific Workflows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mhashilkar, Parag; Tiradani, Anthony; Holzman, Burt

Scientific communities have been in the forefront of adopting new technologies and methodologies in the computing. Scientific computing has influenced how science is done today, achieving breakthroughs that were impossible to achieve several decades ago. For the past decade several such communities in the Open Science Grid (OSG) and the European Grid Infrastructure (EGI) have been using GlideinWMS to run complex application workflows to effectively share computational resources over the grid. GlideinWMS is a pilot-based workload management system (WMS) that creates on demand, a dynamically sized overlay HTCondor batch system on grid resources. At present, the computational resources shared overmore » the grid are just adequate to sustain the computing needs. We envision that the complexity of the science driven by 'Big Data' will further push the need for computational resources. To fulfill their increasing demands and/or to run specialized workflows, some of the big communities like CMS are investigating the use of cloud computing as Infrastructure-As-A-Service (IAAS) with GlideinWMS as a potential alternative to fill the void. Similarly, communities with no previous access to computing resources can use GlideinWMS to setup up a batch system on the cloud infrastructure. To enable this, the architecture of GlideinWMS has been extended to enable support for interfacing GlideinWMS with different Scientific and commercial cloud providers like HLT, FutureGrid, FermiCloud and Amazon EC2. In this paper, we describe a solution for cloud bursting with GlideinWMS. The paper describes the approach, architectural changes and lessons learned while enabling support for cloud infrastructures in GlideinWMS.« less

A global distributed storage architecture

NASA Technical Reports Server (NTRS)

Lionikis, Nemo M.; Shields, Michael F.

1996-01-01

NSA architects and planners have come to realize that to gain the maximum benefit from, and keep pace with, emerging technologies, we must move to a radically different computing architecture. The compute complex of the future will be a distributed heterogeneous environment, where, to a much greater extent than today, network-based services are invoked to obtain resources. Among the rewards of implementing the services-based view are that it insulates the user from much of the complexity of our multi-platform, networked, computer and storage environment and hides its diverse underlying implementation details. In this paper, we will describe one of the fundamental services being built in our envisioned infrastructure; a global, distributed archive with near-real-time access characteristics. Our approach for adapting mass storage services to this infrastructure will become clear as the service is discussed.

Benchmarking infrastructure for mutation text mining

PubMed Central

2014-01-01

Background Experimental research on the automatic extraction of information about mutations from texts is greatly hindered by the lack of consensus evaluation infrastructure for the testing and benchmarking of mutation text mining systems. Results We propose a community-oriented annotation and benchmarking infrastructure to support development, testing, benchmarking, and comparison of mutation text mining systems. The design is based on semantic standards, where RDF is used to represent annotations, an OWL ontology provides an extensible schema for the data and SPARQL is used to compute various performance metrics, so that in many cases no programming is needed to analyze results from a text mining system. While large benchmark corpora for biological entity and relation extraction are focused mostly on genes, proteins, diseases, and species, our benchmarking infrastructure fills the gap for mutation information. The core infrastructure comprises (1) an ontology for modelling annotations, (2) SPARQL queries for computing performance metrics, and (3) a sizeable collection of manually curated documents, that can support mutation grounding and mutation impact extraction experiments. Conclusion We have developed the principal infrastructure for the benchmarking of mutation text mining tasks. The use of RDF and OWL as the representation for corpora ensures extensibility. The infrastructure is suitable for out-of-the-box use in several important scenarios and is ready, in its current state, for initial community adoption. PMID:24568600

Benchmarking infrastructure for mutation text mining.

PubMed

Klein, Artjom; Riazanov, Alexandre; Hindle, Matthew M; Baker, Christopher Jo

2014-02-25

Experimental research on the automatic extraction of information about mutations from texts is greatly hindered by the lack of consensus evaluation infrastructure for the testing and benchmarking of mutation text mining systems. We propose a community-oriented annotation and benchmarking infrastructure to support development, testing, benchmarking, and comparison of mutation text mining systems. The design is based on semantic standards, where RDF is used to represent annotations, an OWL ontology provides an extensible schema for the data and SPARQL is used to compute various performance metrics, so that in many cases no programming is needed to analyze results from a text mining system. While large benchmark corpora for biological entity and relation extraction are focused mostly on genes, proteins, diseases, and species, our benchmarking infrastructure fills the gap for mutation information. The core infrastructure comprises (1) an ontology for modelling annotations, (2) SPARQL queries for computing performance metrics, and (3) a sizeable collection of manually curated documents, that can support mutation grounding and mutation impact extraction experiments. We have developed the principal infrastructure for the benchmarking of mutation text mining tasks. The use of RDF and OWL as the representation for corpora ensures extensibility. The infrastructure is suitable for out-of-the-box use in several important scenarios and is ready, in its current state, for initial community adoption.

The Next Generation of Lab and Classroom Computing - The Silver Lining

DTIC Science & Technology

2016-12-01

desktop infrastructure (VDI) solution, as well as the computing solutions at three universities, was selected as the basis for comparison. The research... infrastructure , VDI, hardware cost, software cost, manpower, availability, cloud computing, private cloud, bring your own device, BYOD, thin client...virtual desktop infrastructure (VDI) solution, as well as the computing solutions at three universities, was selected as the basis for comparison. The

Application of large-scale computing infrastructure for diverse environmental research applications using GC3Pie

NASA Astrophysics Data System (ADS)

Maffioletti, Sergio; Dawes, Nicholas; Bavay, Mathias; Sarni, Sofiane; Lehning, Michael

2013-04-01

The Swiss Experiment platform (SwissEx: http://www.swiss-experiment.ch) provides a distributed storage and processing infrastructure for environmental research experiments. The aim of the second phase project (the Open Support Platform for Environmental Research, OSPER, 2012-2015) is to develop the existing infrastructure to provide scientists with an improved workflow. This improved workflow will include pre-defined, documented and connected processing routines. A large-scale computing and data facility is required to provide reliable and scalable access to data for analysis, and it is desirable that such an infrastructure should be free of traditional data handling methods. Such an infrastructure has been developed using the cloud-based part of the Swiss national infrastructure SMSCG (http://www.smscg.ch) and Academic Cloud. The infrastructure under construction supports two main usage models: 1) Ad-hoc data analysis scripts: These scripts are simple processing scripts, written by the environmental researchers themselves, which can be applied to large data sets via the high power infrastructure. Examples of this type of script are spatial statistical analysis scripts (R-based scripts), mostly computed on raw meteorological and/or soil moisture data. These provide processed output in the form of a grid, a plot, or a kml. 2) Complex models: A more intense data analysis pipeline centered (initially) around the physical process model, Alpine3D, and the MeteoIO plugin; depending on the data set, this may require a tightly coupled infrastructure. SMSCG already supports Alpine3D executions as both regular grid jobs and as virtual software appliances. A dedicated appliance with the Alpine3D specific libraries has been created and made available through the SMSCG infrastructure. The analysis pipelines are activated and supervised by simple control scripts that, depending on the data fetched from the meteorological stations, launch new instances of the Alpine3D appliance, execute location-based subroutines at each grid point and store the results back into the central repository for post-processing. An optional extension of this infrastructure will be to provide a 'ring buffer'-type database infrastructure, such that model results (e.g. test runs made to check parameter dependency or for development) can be visualised and downloaded after completion without submitting them to a permanent storage infrastructure. Data organization Data collected from sensors are archived and classified in distributed sites connected with an open-source software middleware, GSN. Publicly available data are available through common web services and via a cloud storage server (based on Swift). Collocation of the data and processing in the cloud would eventually eliminate data transfer requirements. Execution control logic Execution of the data analysis pipelines (for both the R-based analysis and the Alpine3D simulations) has been implemented using the GC3Pie framework developed by UZH. (https://code.google.com/p/gc3pie/). This allows large-scale, fault-tolerant execution of the pipelines to be described in terms of software appliances. GC3Pie also allows supervision of the execution of large campaigns of appliances as a single simulation. This poster will present the fundamental architectural components of the data analysis pipelines together with initial experimental results.

A new algorithm for grid-based hydrologic analysis by incorporating stormwater infrastructure

NASA Astrophysics Data System (ADS)

Choi, Yosoon; Yi, Huiuk; Park, Hyeong-Dong

2011-08-01

We developed a new algorithm, the Adaptive Stormwater Infrastructure (ASI) algorithm, to incorporate ancillary data sets related to stormwater infrastructure into the grid-based hydrologic analysis. The algorithm simultaneously considers the effects of the surface stormwater collector network (e.g., diversions, roadside ditches, and canals) and underground stormwater conveyance systems (e.g., waterway tunnels, collector pipes, and culverts). The surface drainage flows controlled by the surface runoff collector network are superimposed onto the flow directions derived from a DEM. After examining the connections between inlets and outfalls in the underground stormwater conveyance system, the flow accumulation and delineation of watersheds are calculated based on recursive computations. Application of the algorithm to the Sangdong tailings dam in Korea revealed superior performance to that of a conventional D8 single-flow algorithm in terms of providing reasonable hydrologic information on watersheds with stormwater infrastructure.

The dependence of educational infrastructure on clinical infrastructure.

PubMed Central

Cimino, C.

1998-01-01

The Albert Einstein College of Medicine needed to assess the growth of its infrastructure for educational computing as a first step to determining if student needs were being met. Included in computing infrastructure are space, equipment, software, and computing services. The infrastructure was assessed by reviewing purchasing and support logs for a six year period from 1992 to 1998. This included equipment, software, and e-mail accounts provided to students and to faculty for educational purposes. Student space has grown at a constant rate (averaging 14% increase each year respectively). Student equipment on campus has grown by a constant amount each year (average 8.3 computers each year). Student infrastructure off campus and educational support of faculty has not kept pace. It has either declined or remained level over the six year period. The availability of electronic mail clearly demonstrates this with accounts being used by 99% of students, 78% of Basic Science Course Leaders, 38% of Clerkship Directors, 18% of Clerkship Site Directors, and 8% of Clinical Elective Directors. The collection of the initial descriptive infrastructure data has revealed problems that may generalize to other medical schools. The discrepancy between infrastructure available to students and faculty on campus and students and faculty off campus creates a setting where students perceive a paradoxical declining support for computer use as they progress through medical school. While clinical infrastructure may be growing, it is at the expense of educational infrastructure at affiliate hospitals. PMID:9929262

!CHAOS: A cloud of controls

NASA Astrophysics Data System (ADS)

Angius, S.; Bisegni, C.; Ciuffetti, P.; Di Pirro, G.; Foggetta, L. G.; Galletti, F.; Gargana, R.; Gioscio, E.; Maselli, D.; Mazzitelli, G.; Michelotti, A.; Orrù, R.; Pistoni, M.; Spagnoli, F.; Spigone, D.; Stecchi, A.; Tonto, T.; Tota, M. A.; Catani, L.; Di Giulio, C.; Salina, G.; Buzzi, P.; Checcucci, B.; Lubrano, P.; Piccini, M.; Fattibene, E.; Michelotto, M.; Cavallaro, S. R.; Diana, B. F.; Enrico, F.; Pulvirenti, S.

2016-01-01

The paper is aimed to present the !CHAOS open source project aimed to develop a prototype of a national private Cloud Computing infrastructure, devoted to accelerator control systems and large experiments of High Energy Physics (HEP). The !CHAOS project has been financed by MIUR (Italian Ministry of Research and Education) and aims to develop a new concept of control system and data acquisition framework by providing, with a high level of aaabstraction, all the services needed for controlling and managing a large scientific, or non-scientific, infrastructure. A beta version of the !CHAOS infrastructure will be released at the end of December 2015 and will run on private Cloud infrastructures based on OpenStack.

Bioinformatics clouds for big data manipulation.

PubMed

Dai, Lin; Gao, Xin; Guo, Yan; Xiao, Jingfa; Zhang, Zhang

2012-11-28

As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics. This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.

iTools: a framework for classification, categorization and integration of computational biology resources.

PubMed

Dinov, Ivo D; Rubin, Daniel; Lorensen, William; Dugan, Jonathan; Ma, Jeff; Murphy, Shawn; Kirschner, Beth; Bug, William; Sherman, Michael; Floratos, Aris; Kennedy, David; Jagadish, H V; Schmidt, Jeanette; Athey, Brian; Califano, Andrea; Musen, Mark; Altman, Russ; Kikinis, Ron; Kohane, Isaac; Delp, Scott; Parker, D Stott; Toga, Arthur W

2008-05-28

The advancement of the computational biology field hinges on progress in three fundamental directions--the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources--data, software tools and web-services. The iTools design, implementation and resource meta-data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu.

iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources

PubMed Central

Dinov, Ivo D.; Rubin, Daniel; Lorensen, William; Dugan, Jonathan; Ma, Jeff; Murphy, Shawn; Kirschner, Beth; Bug, William; Sherman, Michael; Floratos, Aris; Kennedy, David; Jagadish, H. V.; Schmidt, Jeanette; Athey, Brian; Califano, Andrea; Musen, Mark; Altman, Russ; Kikinis, Ron; Kohane, Isaac; Delp, Scott; Parker, D. Stott; Toga, Arthur W.

2008-01-01

The advancement of the computational biology field hinges on progress in three fundamental directions – the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources–data, software tools and web-services. The iTools design, implementation and resource meta - data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu. PMID:18509477

Advanced Computational Methods for Optimization of Non-Periodic Inspection Intervals for Aging Infrastructure

DTIC Science & Technology

2017-01-05

AFRL-AFOSR-JP-TR-2017-0002 Advanced Computational Methods for Optimization of Non-Periodic Inspection Intervals for Aging Infrastructure Manabu...Computational Methods for Optimization of Non-Periodic Inspection Intervals for Aging Infrastructure 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA2386...UNLIMITED: PB Public Release 13. SUPPLEMENTARY NOTES 14. ABSTRACT This report for the project titled ’Advanced Computational Methods for Optimization of

Enabling Data Intensive Science through Service Oriented Science: Virtual Laboratories and Science Gateways

NASA Astrophysics Data System (ADS)

Lescinsky, D. T.; Wyborn, L. A.; Evans, B. J. K.; Allen, C.; Fraser, R.; Rankine, T.

2014-12-01

We present collaborative work on a generic, modular infrastructure for virtual laboratories (VLs, similar to science gateways) that combine online access to data, scientific code, and computing resources as services that support multiple data intensive scientific computing needs across a wide range of science disciplines. We are leveraging access to 10+ PB of earth science data on Lustre filesystems at Australia's National Computational Infrastructure (NCI) Research Data Storage Infrastructure (RDSI) node, co-located with NCI's 1.2 PFlop Raijin supercomputer and a 3000 CPU core research cloud. The development, maintenance and sustainability of VLs is best accomplished through modularisation and standardisation of interfaces between components. Our approach has been to break up tightly-coupled, specialised application packages into modules, with identified best techniques and algorithms repackaged either as data services or scientific tools that are accessible across domains. The data services can be used to manipulate, visualise and transform multiple data types whilst the scientific tools can be used in concert with multiple scientific codes. We are currently designing a scalable generic infrastructure that will handle scientific code as modularised services and thereby enable the rapid/easy deployment of new codes or versions of codes. The goal is to build open source libraries/collections of scientific tools, scripts and modelling codes that can be combined in specially designed deployments. Additional services in development include: provenance, publication of results, monitoring, workflow tools, etc. The generic VL infrastructure will be hosted at NCI, but can access alternative computing infrastructures (i.e., public/private cloud, HPC).The Virtual Geophysics Laboratory (VGL) was developed as a pilot project to demonstrate the underlying technology. This base is now being redesigned and generalised to develop a Virtual Hazards Impact and Risk Laboratory (VHIRL); any enhancements and new capabilities will be incorporated into a generic VL infrastructure. At same time, we are scoping seven new VLs and in the process, identifying other common components to prioritise and focus development.

Improving the analysis, storage and sharing of neuroimaging data using relational databases and distributed computing.

PubMed

Hasson, Uri; Skipper, Jeremy I; Wilde, Michael J; Nusbaum, Howard C; Small, Steven L

2008-01-15

The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data.

Improving the Analysis, Storage and Sharing of Neuroimaging Data using Relational Databases and Distributed Computing

PubMed Central

Hasson, Uri; Skipper, Jeremy I.; Wilde, Michael J.; Nusbaum, Howard C.; Small, Steven L.

2007-01-01

The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data. PMID:17964812

Helix Nebula: Enabling federation of existing data infrastructures and data services to an overarching cross-domain e-infrastructure

NASA Astrophysics Data System (ADS)

Lengert, Wolfgang; Farres, Jordi; Lanari, Riccardo; Casu, Francesco; Manunta, Michele; Lassalle-Balier, Gerard

2014-05-01

Helix Nebula has established a growing public private partnership of more than 30 commercial cloud providers, SMEs, and publicly funded research organisations and e-infrastructures. The Helix Nebula strategy is to establish a federated cloud service across Europe. Three high-profile flagships, sponsored by CERN (high energy physics), EMBL (life sciences) and ESA/DLR/CNES/CNR (earth science), have been deployed and extensively tested within this federated environment. The commitments behind these initial flagships have created a critical mass that attracts suppliers and users to the initiative, to work together towards an "Information as a Service" market place. Significant progress in implementing the following 4 programmatic goals (as outlined in the strategic Plan Ref.1) has been achieved: × Goal #1 Establish a Cloud Computing Infrastructure for the European Research Area (ERA) serving as a platform for innovation and evolution of the overall infrastructure. × Goal #2 Identify and adopt suitable policies for trust, security and privacy on a European-level can be provided by the European Cloud Computing framework and infrastructure. × Goal #3 Create a light-weight governance structure for the future European Cloud Computing Infrastructure that involves all the stakeholders and can evolve over time as the infrastructure, services and user-base grows. × Goal #4 Define a funding scheme involving the three stake-holder groups (service suppliers, users, EC and national funding agencies) into a Public-Private-Partnership model to implement a Cloud Computing Infrastructure that delivers a sustainable business environment adhering to European level policies. Now in 2014 a first version of this generic cross-domain e-infrastructure is ready to go into operations building on federation of European industry and contributors (data, tools, knowledge, ...). This presentation describes how Helix Nebula is being used in the domain of earth science focusing on geohazards. The so called "Supersite Exploitation Platform" (SSEP) provides scientists an overarching federated e-infrastructure with a very fast access to (i) large volume of data (EO/non-space data), (ii) computing resources (e.g. hybrid cloud/grid), (iii) processing software (e.g. toolboxes, RTMs, retrieval baselines, visualization routines), and (iv) general platform capabilities (e.g. user management and access control, accounting, information portal, collaborative tools, social networks etc.). In this federation each data provider remains in full control of the implementation of its data policy. This presentation outlines the Architecture (technical and services) supporting very heterogeneous science domains as well as the procedures for new-comers to join the Helix Nebula Market Place. Ref.1 http://cds.cern.ch/record/1374172/files/CERN-OPEN-2011-036.pdf

INFN-Pisa scientific computation environment (GRID, HPC and Interactive Analysis)

NASA Astrophysics Data System (ADS)

Arezzini, S.; Carboni, A.; Caruso, G.; Ciampa, A.; Coscetti, S.; Mazzoni, E.; Piras, S.

2014-06-01

The INFN-Pisa Tier2 infrastructure is described, optimized not only for GRID CPU and Storage access, but also for a more interactive use of the resources in order to provide good solutions for the final data analysis step. The Data Center, equipped with about 6700 production cores, permits the use of modern analysis techniques realized via advanced statistical tools (like RooFit and RooStat) implemented in multicore systems. In particular a POSIX file storage access integrated with standard SRM access is provided. Therefore the unified storage infrastructure is described, based on GPFS and Xrootd, used both for SRM data repository and interactive POSIX access. Such a common infrastructure allows a transparent access to the Tier2 data to the users for their interactive analysis. The organization of a specialized many cores CPU facility devoted to interactive analysis is also described along with the login mechanism integrated with the INFN-AAI (National INFN Infrastructure) to extend the site access and use to a geographical distributed community. Such infrastructure is used also for a national computing facility in use to the INFN theoretical community, it enables a synergic use of computing and storage resources. Our Center initially developed for the HEP community is now growing and includes also HPC resources fully integrated. In recent years has been installed and managed a cluster facility (1000 cores, parallel use via InfiniBand connection) and we are now updating this facility that will provide resources for all the intermediate level HPC computing needs of the INFN theoretical national community.

Managing competing elastic Grid and Cloud scientific computing applications using OpenNebula

NASA Astrophysics Data System (ADS)

Bagnasco, S.; Berzano, D.; Lusso, S.; Masera, M.; Vallero, S.

2015-12-01

Elastic cloud computing applications, i.e. applications that automatically scale according to computing needs, work on the ideal assumption of infinite resources. While large public cloud infrastructures may be a reasonable approximation of this condition, scientific computing centres like WLCG Grid sites usually work in a saturated regime, in which applications compete for scarce resources through queues, priorities and scheduling policies, and keeping a fraction of the computing cores idle to allow for headroom is usually not an option. In our particular environment one of the applications (a WLCG Tier-2 Grid site) is much larger than all the others and cannot autoscale easily. Nevertheless, other smaller applications can benefit of automatic elasticity; the implementation of this property in our infrastructure, based on the OpenNebula cloud stack, will be described and the very first operational experiences with a small number of strategies for timely allocation and release of resources will be discussed.

A Roadmap for the Development of Applied Computational Psychiatry.

PubMed

Paulus, Martin P; Huys, Quentin J M; Maia, Tiago V

2016-09-01

Computational psychiatry is a burgeoning field that utilizes mathematical approaches to investigate psychiatric disorders, derive quantitative predictions, and integrate data across multiple levels of description. Computational psychiatry has already led to many new insights into the neurobehavioral mechanisms that underlie several psychiatric disorders, but its usefulness from a clinical standpoint is only now starting to be considered. Examples of computational psychiatry are highlighted, and a phase-based pipeline for the development of clinical computational-psychiatry applications is proposed, similar to the phase-based pipeline used in drug development. It is proposed that each phase has unique endpoints and deliverables, which will be important milestones to move tasks, procedures, computational models, and algorithms from the laboratory to clinical practice. Application of computational approaches should be tested on healthy volunteers in Phase I, transitioned to target populations in Phase IB and Phase IIA, and thoroughly evaluated using randomized clinical trials in Phase IIB and Phase III. Successful completion of these phases should be the basis of determining whether computational models are useful tools for prognosis, diagnosis, or treatment of psychiatric patients. A new type of infrastructure will be necessary to implement the proposed pipeline. This infrastructure should consist of groups of investigators with diverse backgrounds collaborating to make computational psychiatry relevant for the clinic.

Cloud Computing Based E-Learning System

ERIC Educational Resources Information Center

Al-Zoube, Mohammed; El-Seoud, Samir Abou; Wyne, Mudasser F.

2010-01-01

Cloud computing technologies although in their early stages, have managed to change the way applications are going to be developed and accessed. These technologies are aimed at running applications as services over the internet on a flexible infrastructure. Microsoft office applications, such as word processing, excel spreadsheet, access database…

The cloud services innovation platform- enabling service-based environmental modelling using infrastructure-as-a-service cloud computing

USDA-ARS?s Scientific Manuscript database

Service oriented architectures allow modelling engines to be hosted over the Internet abstracting physical hardware configuration and software deployments from model users. Many existing environmental models are deployed as desktop applications running on user's personal computers (PCs). Migration ...

Integrating multiple scientific computing needs via a Private Cloud infrastructure

NASA Astrophysics Data System (ADS)

Bagnasco, S.; Berzano, D.; Brunetti, R.; Lusso, S.; Vallero, S.

2014-06-01

In a typical scientific computing centre, diverse applications coexist and share a single physical infrastructure. An underlying Private Cloud facility eases the management and maintenance of heterogeneous use cases such as multipurpose or application-specific batch farms, Grid sites catering to different communities, parallel interactive data analysis facilities and others. It allows to dynamically and efficiently allocate resources to any application and to tailor the virtual machines according to the applications' requirements. Furthermore, the maintenance of large deployments of complex and rapidly evolving middleware and application software is eased by the use of virtual images and contextualization techniques; for example, rolling updates can be performed easily and minimizing the downtime. In this contribution we describe the Private Cloud infrastructure at the INFN-Torino Computer Centre, that hosts a full-fledged WLCG Tier-2 site and a dynamically expandable PROOF-based Interactive Analysis Facility for the ALICE experiment at the CERN LHC and several smaller scientific computing applications. The Private Cloud building blocks include the OpenNebula software stack, the GlusterFS filesystem (used in two different configurations for worker- and service-class hypervisors) and the OpenWRT Linux distribution (used for network virtualization). A future integration into a federated higher-level infrastructure is made possible by exposing commonly used APIs like EC2 and by using mainstream contextualization tools like CloudInit.

Cloud Computing in Support of Applied Learning: A Baseline Study of Infrastructure Design at Southern Polytechnic State University

ERIC Educational Resources Information Center

Conn, Samuel S.; Reichgelt, Han

2013-01-01

Cloud computing represents an architecture and paradigm of computing designed to deliver infrastructure, platforms, and software as constructible computing resources on demand to networked users. As campuses are challenged to better accommodate academic needs for applications and computing environments, cloud computing can provide an accommodating…

GISpark: A Geospatial Distributed Computing Platform for Spatiotemporal Big Data

NASA Astrophysics Data System (ADS)

Wang, S.; Zhong, E.; Wang, E.; Zhong, Y.; Cai, W.; Li, S.; Gao, S.

2016-12-01

Geospatial data are growing exponentially because of the proliferation of cost effective and ubiquitous positioning technologies such as global remote-sensing satellites and location-based devices. Analyzing large amounts of geospatial data can provide great value for both industrial and scientific applications. Data- and compute- intensive characteristics inherent in geospatial big data increasingly pose great challenges to technologies of data storing, computing and analyzing. Such challenges require a scalable and efficient architecture that can store, query, analyze, and visualize large-scale spatiotemporal data. Therefore, we developed GISpark - a geospatial distributed computing platform for processing large-scale vector, raster and stream data. GISpark is constructed based on the latest virtualized computing infrastructures and distributed computing architecture. OpenStack and Docker are used to build multi-user hosting cloud computing infrastructure for GISpark. The virtual storage systems such as HDFS, Ceph, MongoDB are combined and adopted for spatiotemporal data storage management. Spark-based algorithm framework is developed for efficient parallel computing. Within this framework, SuperMap GIScript and various open-source GIS libraries can be integrated into GISpark. GISpark can also integrated with scientific computing environment (e.g., Anaconda), interactive computing web applications (e.g., Jupyter notebook), and machine learning tools (e.g., TensorFlow/Orange). The associated geospatial facilities of GISpark in conjunction with the scientific computing environment, exploratory spatial data analysis tools, temporal data management and analysis systems make up a powerful geospatial computing tool. GISpark not only provides spatiotemporal big data processing capacity in the geospatial field, but also provides spatiotemporal computational model and advanced geospatial visualization tools that deals with other domains related with spatial property. We tested the performance of the platform based on taxi trajectory analysis. Results suggested that GISpark achieves excellent run time performance in spatiotemporal big data applications.

Bioinformatics clouds for big data manipulation

PubMed Central

2012-01-01

Abstract As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics. Reviewers This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor. PMID:23190475

Computing and data processing

NASA Technical Reports Server (NTRS)

Smarr, Larry; Press, William; Arnett, David W.; Cameron, Alastair G. W.; Crutcher, Richard M.; Helfand, David J.; Horowitz, Paul; Kleinmann, Susan G.; Linsky, Jeffrey L.; Madore, Barry F.

1991-01-01

The applications of computers and data processing to astronomy are discussed. Among the topics covered are the emerging national information infrastructure, workstations and supercomputers, supertelescopes, digital astronomy, astrophysics in a numerical laboratory, community software, archiving of ground-based observations, dynamical simulations of complex systems, plasma astrophysics, and the remote control of fourth dimension supercomputers.

Cybersecurity Workforce Development and the Protection of Critical Infrastructure

DTIC Science & Technology

2017-03-31

communicat ions products, and limited travel for site visits and conferencing. The CSCC contains a developed web-based coordination site, computer ...the CSCC. The Best Practices Ana~yst position maintains a lisr of best practices, computer related patches. and standard operating procedures (SOP...involved in conducting vulnerability assessments of computer networks. To adequately exercise and experiment with industry standard software, it was

Heterogeneous concurrent computing with exportable services

NASA Technical Reports Server (NTRS)

Sunderam, Vaidy

1995-01-01

Heterogeneous concurrent computing, based on the traditional process-oriented model, is approaching its functionality and performance limits. An alternative paradigm, based on the concept of services, supporting data driven computation, and built on a lightweight process infrastructure, is proposed to enhance the functional capabilities and the operational efficiency of heterogeneous network-based concurrent computing. TPVM is an experimental prototype system supporting exportable services, thread-based computation, and remote memory operations that is built as an extension of and an enhancement to the PVM concurrent computing system. TPVM offers a significantly different computing paradigm for network-based computing, while maintaining a close resemblance to the conventional PVM model in the interest of compatibility and ease of transition Preliminary experiences have demonstrated that the TPVM framework presents a natural yet powerful concurrent programming interface, while being capable of delivering performance improvements of upto thirty percent.

LEMON - LHC Era Monitoring for Large-Scale Infrastructures

NASA Astrophysics Data System (ADS)

Marian, Babik; Ivan, Fedorko; Nicholas, Hook; Hector, Lansdale Thomas; Daniel, Lenkes; Miroslav, Siket; Denis, Waldron

2011-12-01

At the present time computer centres are facing a massive rise in virtualization and cloud computing as these solutions bring advantages to service providers and consolidate the computer centre resources. However, as a result the monitoring complexity is increasing. Computer centre management requires not only to monitor servers, network equipment and associated software but also to collect additional environment and facilities data (e.g. temperature, power consumption, cooling efficiency, etc.) to have also a good overview of the infrastructure performance. The LHC Era Monitoring (Lemon) system is addressing these requirements for a very large scale infrastructure. The Lemon agent that collects data on every client and forwards the samples to the central measurement repository provides a flexible interface that allows rapid development of new sensors. The system allows also to report on behalf of remote devices such as switches and power supplies. Online and historical data can be visualized via a web-based interface or retrieved via command-line tools. The Lemon Alarm System component can be used for notifying the operator about error situations. In this article, an overview of the Lemon monitoring is provided together with a description of the CERN LEMON production instance. No direct comparison is made with other monitoring tool.

@neurIST: infrastructure for advanced disease management through integration of heterogeneous data, computing, and complex processing services.

PubMed

Benkner, Siegfried; Arbona, Antonio; Berti, Guntram; Chiarini, Alessandro; Dunlop, Robert; Engelbrecht, Gerhard; Frangi, Alejandro F; Friedrich, Christoph M; Hanser, Susanne; Hasselmeyer, Peer; Hose, Rod D; Iavindrasana, Jimison; Köhler, Martin; Iacono, Luigi Lo; Lonsdale, Guy; Meyer, Rodolphe; Moore, Bob; Rajasekaran, Hariharan; Summers, Paul E; Wöhrer, Alexander; Wood, Steven

2010-11-01

The increasing volume of data describing human disease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the @neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the system's architecture is generic enough that it could be adapted to the treatment of other diseases. Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers clinicians the tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medical researchers gain access to a critical mass of aneurysm related data due to the system's ability to federate distributed information sources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access and work on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand for performing computationally intensive simulations for treatment planning and research.

2008 Defense Industrial Base Critical Infrastructure Protection Conference (DIB-CBIP)

DTIC Science & Technology

2008-04-09

a cloak -and- dagger thing. It’s about computer architecture and the soundness of electronic systems." Joel Brenner, ODNI Counterintelligence Office...to support advanced network exploitation and launch attacks on the informational and physical elements of our cyber infrastructure. In order to...entities and is vulnerable to attacks and manipulation. Operations in the cyber domain have the ability to impact operations in other war-fighting

The framework for simulation of bioinspired security mechanisms against network infrastructure attacks.

PubMed

Shorov, Andrey; Kotenko, Igor

2014-01-01

The paper outlines a bioinspired approach named "network nervous system" and methods of simulation of infrastructure attacks and protection mechanisms based on this approach. The protection mechanisms based on this approach consist of distributed procedures of information collection and processing, which coordinate the activities of the main devices of a computer network, identify attacks, and determine necessary countermeasures. Attacks and protection mechanisms are specified as structural models using a set-theoretic approach. An environment for simulation of protection mechanisms based on the biological metaphor is considered; the experiments demonstrating the effectiveness of the protection mechanisms are described.

Cyber-Physical Correlations for Infrastructure Resilience: A Game-Theoretic Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rao, Nageswara S; He, Fei; Ma, Chris Y. T.

In several critical infrastructures, the cyber and physical parts are correlated so that disruptions to one affect the other and hence the whole system. These correlations may be exploited to strategically launch components attacks, and hence must be accounted for ensuring the infrastructure resilience, specified by its survival probability. We characterize the cyber-physical interactions at two levels: (i) the failure correlation function specifies the conditional survival probability of cyber sub-infrastructure given the physical sub-infrastructure as a function of their marginal probabilities, and (ii) the individual survival probabilities of both sub-infrastructures are characterized by first-order differential conditions. We formulate a resiliencemore » problem for infrastructures composed of discrete components as a game between the provider and attacker, wherein their utility functions consist of an infrastructure survival probability term and a cost term expressed in terms of the number of components attacked and reinforced. We derive Nash Equilibrium conditions and sensitivity functions that highlight the dependence of infrastructure resilience on the cost term, correlation function and sub-infrastructure survival probabilities. These results generalize earlier ones based on linear failure correlation functions and independent component failures. We apply the results to models of cloud computing infrastructures and energy grids.« less

Lowering the barriers to computational modeling of Earth's surface: coupling Jupyter Notebooks with Landlab, HydroShare, and CyberGIS for research and education.

NASA Astrophysics Data System (ADS)

Bandaragoda, C.; Castronova, A. M.; Phuong, J.; Istanbulluoglu, E.; Strauch, R. L.; Nudurupati, S. S.; Tarboton, D. G.; Wang, S. W.; Yin, D.; Barnhart, K. R.; Tucker, G. E.; Hutton, E.; Hobley, D. E. J.; Gasparini, N. M.; Adams, J. M.

2017-12-01

The ability to test hypotheses about hydrology, geomorphology and atmospheric processes is invaluable to research in the era of big data. Although community resources are available, there remain significant educational, logistical and time investment barriers to their use. Knowledge infrastructure is an emerging intellectual framework to understand how people are creating, sharing and distributing knowledge - which has been dramatically transformed by Internet technologies. In addition to the technical and social components in a cyberinfrastructure system, knowledge infrastructure considers educational, institutional, and open source governance components required to advance knowledge. We are designing an infrastructure environment that lowers common barriers to reproducing modeling experiments for earth surface investigation. Landlab is an open-source modeling toolkit for building, coupling, and exploring two-dimensional numerical models. HydroShare is an online collaborative environment for sharing hydrologic data and models. CyberGIS-Jupyter is an innovative cyberGIS framework for achieving data-intensive, reproducible, and scalable geospatial analytics using the Jupyter Notebook based on ROGER - the first cyberGIS supercomputer, so that models that can be elastically reproduced through cloud computing approaches. Our team of geomorphologists, hydrologists, and computer geoscientists has created a new infrastructure environment that combines these three pieces of software to enable knowledge discovery. Through this novel integration, any user can interactively execute and explore their shared data and model resources. Landlab on HydroShare with CyberGIS-Jupyter supports the modeling continuum from fully developed modelling applications, prototyping new science tools, hands on research demonstrations for training workshops, and classroom applications. Computational geospatial models based on big data and high performance computing can now be more efficiently developed, improved, scaled, and seamlessly reproduced among multidisciplinary users, thereby expanding the active learning curriculum and research opportunities for students in earth surface modeling and informatics.

Sustaining a Community Computing Infrastructure for Online Teacher Professional Development: A Case Study of Designing Tapped In

NASA Astrophysics Data System (ADS)

Farooq, Umer; Schank, Patricia; Harris, Alexandra; Fusco, Judith; Schlager, Mark

Community computing has recently grown to become a major research area in human-computer interaction. One of the objectives of community computing is to support computer-supported cooperative work among distributed collaborators working toward shared professional goals in online communities of practice. A core issue in designing and developing community computing infrastructures — the underlying sociotechnical layer that supports communitarian activities — is sustainability. Many community computing initiatives fail because the underlying infrastructure does not meet end user requirements; the community is unable to maintain a critical mass of users consistently over time; it generates insufficient social capital to support significant contributions by members of the community; or, as typically happens with funded initiatives, financial and human capital resource become unavailable to further maintain the infrastructure. On the basis of more than 9 years of design experience with Tapped In-an online community of practice for education professionals — we present a case study that discusses four design interventions that have sustained the Tapped In infrastructure and its community to date. These interventions represent broader design strategies for developing online environments for professional communities of practice.

Implementation of Grid Tier 2 and Tier 3 facilities on a Distributed OpenStack Cloud

NASA Astrophysics Data System (ADS)

Limosani, Antonio; Boland, Lucien; Coddington, Paul; Crosby, Sean; Huang, Joanna; Sevior, Martin; Wilson, Ross; Zhang, Shunde

2014-06-01

The Australian Government is making a AUD 100 million investment in Compute and Storage for the academic community. The Compute facilities are provided in the form of 30,000 CPU cores located at 8 nodes around Australia in a distributed virtualized Infrastructure as a Service facility based on OpenStack. The storage will eventually consist of over 100 petabytes located at 6 nodes. All will be linked via a 100 Gb/s network. This proceeding describes the development of a fully connected WLCG Tier-2 grid site as well as a general purpose Tier-3 computing cluster based on this architecture. The facility employs an extension to Torque to enable dynamic allocations of virtual machine instances. A base Scientific Linux virtual machine (VM) image is deployed in the OpenStack cloud and automatically configured as required using Puppet. Custom scripts are used to launch multiple VMs, integrate them into the dynamic Torque cluster and to mount remote file systems. We report on our experience in developing this nation-wide ATLAS and Belle II Tier 2 and Tier 3 computing infrastructure using the national Research Cloud and storage facilities.

Managing a tier-2 computer centre with a private cloud infrastructure

NASA Astrophysics Data System (ADS)

Bagnasco, Stefano; Berzano, Dario; Brunetti, Riccardo; Lusso, Stefano; Vallero, Sara

2014-06-01

In a typical scientific computing centre, several applications coexist and share a single physical infrastructure. An underlying Private Cloud infrastructure eases the management and maintenance of such heterogeneous applications (such as multipurpose or application-specific batch farms, Grid sites, interactive data analysis facilities and others), allowing dynamic allocation resources to any application. Furthermore, the maintenance of large deployments of complex and rapidly evolving middleware and application software is eased by the use of virtual images and contextualization techniques. Such infrastructures are being deployed in some large centres (see e.g. the CERN Agile Infrastructure project), but with several open-source tools reaching maturity this is becoming viable also for smaller sites. In this contribution we describe the Private Cloud infrastructure at the INFN-Torino Computer Centre, that hosts a full-fledged WLCG Tier-2 centre, an Interactive Analysis Facility for the ALICE experiment at the CERN LHC and several smaller scientific computing applications. The private cloud building blocks include the OpenNebula software stack, the GlusterFS filesystem and the OpenWRT Linux distribution (used for network virtualization); a future integration into a federated higher-level infrastructure is made possible by exposing commonly used APIs like EC2 and OCCI.

Controlling Infrastructure Costs: Right-Sizing the Mission Control Facility

NASA Technical Reports Server (NTRS)

Martin, Keith; Sen-Roy, Michael; Heiman, Jennifer

2009-01-01

Johnson Space Center's Mission Control Center is a space vehicle, space program agnostic facility. The current operational design is essentially identical to the original facility architecture that was developed and deployed in the mid-90's. In an effort to streamline the support costs of the mission critical facility, the Mission Operations Division (MOD) of Johnson Space Center (JSC) has sponsored an exploratory project to evaluate and inject current state-of-the-practice Information Technology (IT) tools, processes and technology into legacy operations. The general push in the IT industry has been trending towards a data-centric computer infrastructure for the past several years. Organizations facing challenges with facility operations costs are turning to creative solutions combining hardware consolidation, virtualization and remote access to meet and exceed performance, security, and availability requirements. The Operations Technology Facility (OTF) organization at the Johnson Space Center has been chartered to build and evaluate a parallel Mission Control infrastructure, replacing the existing, thick-client distributed computing model and network architecture with a data center model utilizing virtualization to provide the MCC Infrastructure as a Service. The OTF will design a replacement architecture for the Mission Control Facility, leveraging hardware consolidation through the use of blade servers, increasing utilization rates for compute platforms through virtualization while expanding connectivity options through the deployment of secure remote access. The architecture demonstrates the maturity of the technologies generally available in industry today and the ability to successfully abstract the tightly coupled relationship between thick-client software and legacy hardware into a hardware agnostic "Infrastructure as a Service" capability that can scale to meet future requirements of new space programs and spacecraft. This paper discusses the benefits and difficulties that a migration to cloud-based computing philosophies has uncovered when compared to the legacy Mission Control Center architecture. The team consists of system and software engineers with extensive experience with the MCC infrastructure and software currently used to support the International Space Station (ISS) and Space Shuttle program (SSP).

Development of a telemedicine model for emerging countries: a case study on pediatric oncology in Brazil.

PubMed

Hira, A Y; Nebel de Mello, A; Faria, R A; Odone Filho, V; Lopes, R D; Zuffo, M K

2006-01-01

This article discusses a telemedicine model for emerging countries, through the description of ONCONET, a telemedicine initiative applied to pediatric oncology in Brazil. The ONCONET core technology is a Web-based system that offers health information and other services specialized in childhood cancer such as electronic medical records and cooperative protocols for complex treatments. All Web-based services are supported by the use of high performance computing infrastructure based on clusters of commodity computers. The system was fully implemented on an open-source and free-software approach. Aspects of modeling, implementation and integration are covered. A model, both technologically and economically viable, was created through the research and development of in-house solutions adapted to the emerging countries reality and with focus on scalability both in the total number of patients and in the national infrastructure.

Active Computer Network Defense: An Assessment

DTIC Science & Technology

2001-04-01

sufficient base of knowledge in information technology can be assumed to be working on some form of computer network warfare, even if only defensive in...the Defense Information Infrastructure (DII) to attack. Transmission Control Protocol/ Internet Protocol (TCP/IP) networks are inherently resistant to...aims to create this part of information superiority, and computer network defense is one of its fundamental components. Most of these efforts center

Architectural Implications of Cloud Computing

DTIC Science & Technology

2011-10-24

Public Cloud Infrastructure-as-a- Service (IaaS) Software -as-a- Service ( SaaS ) Cloud Computing Types Platform-as-a- Service (PaaS) Based on Type of...Twitter #SEIVirtualForum © 2011 Carnegie Mellon University Software -as-a- Service ( SaaS ) Model of software deployment in which a third-party...and System Solutions (RTSS) Program. Her current interests and projects are in service -oriented architecture (SOA), cloud computing, and context

Complete distributed computing environment for a HEP experiment: experience with ARC-connected infrastructure for ATLAS

NASA Astrophysics Data System (ADS)

Read, A.; Taga, A.; O-Saada, F.; Pajchel, K.; Samset, B. H.; Cameron, D.

2008-07-01

Computing and storage resources connected by the Nordugrid ARC middleware in the Nordic countries, Switzerland and Slovenia are a part of the ATLAS computing Grid. This infrastructure is being commissioned with the ongoing ATLAS Monte Carlo simulation production in preparation for the commencement of data taking in 2008. The unique non-intrusive architecture of ARC, its straightforward interplay with the ATLAS Production System via the Dulcinea executor, and its performance during the commissioning exercise is described. ARC support for flexible and powerful end-user analysis within the GANGA distributed analysis framework is also shown. Whereas the storage solution for this Grid was earlier based on a large, distributed collection of GridFTP-servers, the ATLAS computing design includes a structured SRM-based system with a limited number of storage endpoints. The characteristics, integration and performance of the old and new storage solutions are presented. Although the hardware resources in this Grid are quite modest, it has provided more than double the agreed contribution to the ATLAS production with an efficiency above 95% during long periods of stable operation.

Survey of Collaboration Technologies in Multi-level Security Environments

DTIC Science & Technology

2014-04-28

infrastructure or resources. In this research program, the security implications of the US Air Force GeoBase (the US The problem is that in many cases...design structure. ORA uses a Java interface for ease of use, and a C++ computational backend . The current version ORA1.2 software is available on the...information: culture, policy, governance, economics and resources, and technology and infrastructure . This plan, the DoD Information Sharing

OOI CyberInfrastructure - Next Generation Oceanographic Research

NASA Astrophysics Data System (ADS)

Farcas, C.; Fox, P.; Arrott, M.; Farcas, E.; Klacansky, I.; Krueger, I.; Meisinger, M.; Orcutt, J.

2008-12-01

Software has become a key enabling technology for scientific discovery, observation, modeling, and exploitation of natural phenomena. New value emerges from the integration of individual subsystems into networked federations of capabilities exposed to the scientific community. Such data-intensive interoperability networks are crucial for future scientific collaborative research, as they open up new ways of fusing data from different sources and across various domains, and analysis on wide geographic areas. The recently established NSF OOI program, through its CyberInfrastructure component addresses this challenge by providing broad access from sensor networks for data acquisition up to computational grids for massive computations and binding infrastructure facilitating policy management and governance of the emerging system-of-scientific-systems. We provide insight into the integration core of this effort, namely, a hierarchic service-oriented architecture for a robust, performant, and maintainable implementation. We first discuss the relationship between data management and CI crosscutting concerns such as identity management, policy and governance, which define the organizational contexts for data access and usage. Next, we detail critical services including data ingestion, transformation, preservation, inventory, and presentation. To address interoperability issues between data represented in various formats we employ a semantic framework derived from the Earth System Grid technology, a canonical representation for scientific data based on DAP/OPeNDAP, and related data publishers such as ERDDAP. Finally, we briefly present the underlying transport based on a messaging infrastructure over the AMQP protocol, and the preservation based on a distributed file system through SDSC iRODS.

Sensor4PRI: A Sensor Platform for the Protection of Railway Infrastructures

PubMed Central

Cañete, Eduardo; Chen, Jaime; Díaz, Manuel; Llopis, Luis; Rubio, Bartolomé

2015-01-01

Wireless Sensor Networks constitute pervasive and distributed computing systems and are potentially one of the most important technologies of this century. They have been specifically identified as a good candidate to become an integral part of the protection of critical infrastructures. In this paper we focus on railway infrastructure protection and we present the details of a sensor platform designed to be integrated into a slab track system in order to carry out both installation and maintenance monitoring activities. In the installation phase, the platform helps operators to install the slab tracks in the right position. In the maintenance phase, the platform collects information about the structural health and behavior of the infrastructure when a train travels along it and relays the readings to a base station. The base station uses trains as data mules to upload the information to the internet. The use of a train as a data mule is especially suitable for collecting information from remote or inaccessible places which do not have a direct connection to the internet and require less network infrastructure. The overall aim of the system is to deploy a permanent economically viable monitoring system to improve the safety of railway infrastructures. PMID:25734648

EC FP6 Enviro-RISKS project outcomes in area of Earth and Space Science Informatics applications

NASA Astrophysics Data System (ADS)

Gordov, E. P.; Zakarin, E. A.

2009-04-01

Nowadays the community acknowledged that to understand dynamics of regional environment properly and perform its assessment on the base of monitoring and modeling more strong involvement of information-computational technologies (ICT) is required, which should lead to development of information-computational infrastructure as an inherent part of such investigations. This paper is based on the Report&Recommendations (www.dmi.dk/dmi/sr08-05-4.pdf) of the Enviro-RISKS (Man-induced Environmental Risks: Monitoring, Management and Remediation of Man-made Changes in Siberia) Project Thematic expert group for Information Systems, Integration and Synthesis Focus and presents results of activities of Project Partners in area of Information Technologies for Environmental Sciences development and usage. Approaches used the web-based Information Technologies and the GIS-based Information Technologies are described and a way to their integration is outlined. In particular, developed in course of the Project carrying out Enviro-RISKS web portal and its Climate site (http://climate.risks.scert.ru/), providing an access to interactive web-system for regional climate assessment on the base of standard meteorological data archives, which is a key element of the information-computational infrastructure of the Siberia Integrated Regional Study (SIRS), is described in details as well as developed on the base of GIS technology system for monitoring and modeling air and water pollutions transport and transformations. The later is quite useful for practical applications realization of geoinformation modeling, in which relevant mathematical models are plunged into GIS and all the modeling and analysis phases are accomplished in the informational sphere, based on the real data including those coming from satellites. Major efforts currently are undertaken in attempt to integrate GIS based environmental applications with web accessibility, computing power and data interoperability thus to exploit completely huge potential of web bases technologies. In particular, development of a region devoted web portal using approached suggested by the Open Geospatial Consortium has been started recently. The state of the art of the information-computational infrastructure in the targeted region is quite a step in the process of development of a distributed collaborative information-computational environment to support multidisciplinary investigations of Earth regional environment, especially those required meteorology, atmospheric pollution transport and climate modeling. Established in process of the Project carrying out cooperative links, new Partners initiatives, and gained expertise allow us to hope that this infrastructure rather soon will make significant input into understanding regional environmental processes in their relationships with Global Change. In particular, this infrastructure will play a role of the 'underlying mechanics' of the research work, leaving the earth scientists to concentrate on their investigations as well as providing the environment to make research results available and understandable to everyone. Additionally to the core FP6 Enviro-RISKS project (INCO-CT-2004-013427) support this activity was partially supported by SB RAS Integration Project 34, SB RAS Basic Program Project 4.5.2.2 and APN Project CBA2007-08NSY. Valuable input into the expert group work and elaborated outcomes of Profs. V. Lykosov and A. Starchenko, Drs. D. Belikov, , M. Korets, S. Kostrykin, B. Mirkarimova, I. Okladnikov, , A. Titov and A. Tridvornov is acknowledged.

Optical fibre multi-parameter sensing with secure cloud based signal capture and processing

NASA Astrophysics Data System (ADS)

Newe, Thomas; O'Connell, Eoin; Meere, Damien; Yuan, Hongwei; Leen, Gabriel; O'Keeffe, Sinead; Lewis, Elfed

2016-05-01

Recent advancements in cloud computing technologies in the context of optical and optical fibre based systems are reported. The proliferation of real time and multi-channel based sensor systems represents significant growth in data volume. This coupled with a growing need for security presents many challenges and presents a huge opportunity for an evolutionary step in the widespread application of these sensing technologies. A tiered infrastructural system approach is adopted that is designed to facilitate the delivery of Optical Fibre-based "SENsing as a Service- SENaaS". Within this infrastructure, novel optical sensing platforms, deployed within different environments, are interfaced with a Cloud-based backbone infrastructure which facilitates the secure collection, storage and analysis of real-time data. Feedback systems, which harness this data to affect a change within the monitored location/environment/condition, are also discussed. The cloud based system presented here can also be used with chemical and physical sensors that require real-time data analysis, processing and feedback.

Flexible services for the support of research.

PubMed

Turilli, Matteo; Wallom, David; Williams, Chris; Gough, Steve; Curran, Neal; Tarrant, Richard; Bretherton, Dan; Powell, Andy; Johnson, Matt; Harmer, Terry; Wright, Peter; Gordon, John

2013-01-28

Cloud computing has been increasingly adopted by users and providers to promote a flexible, scalable and tailored access to computing resources. Nonetheless, the consolidation of this paradigm has uncovered some of its limitations. Initially devised by corporations with direct control over large amounts of computational resources, cloud computing is now being endorsed by organizations with limited resources or with a more articulated, less direct control over these resources. The challenge for these organizations is to leverage the benefits of cloud computing while dealing with limited and often widely distributed computing resources. This study focuses on the adoption of cloud computing by higher education institutions and addresses two main issues: flexible and on-demand access to a large amount of storage resources, and scalability across a heterogeneous set of cloud infrastructures. The proposed solutions leverage a federated approach to cloud resources in which users access multiple and largely independent cloud infrastructures through a highly customizable broker layer. This approach allows for a uniform authentication and authorization infrastructure, a fine-grained policy specification and the aggregation of accounting and monitoring. Within a loosely coupled federation of cloud infrastructures, users can access vast amount of data without copying them across cloud infrastructures and can scale their resource provisions when the local cloud resources become insufficient.

Grid infrastructure for automatic processing of SAR data for flood applications

NASA Astrophysics Data System (ADS)

Kussul, Natalia; Skakun, Serhiy; Shelestov, Andrii

2010-05-01

More and more geosciences applications are being put on to the Grids. Due to the complexity of geosciences applications that is caused by complex workflow, the use of computationally intensive environmental models, the need of management and integration of heterogeneous data sets, Grid offers solutions to tackle these problems. Many geosciences applications, especially those related to the disaster management and mitigations require the geospatial services to be delivered in proper time. For example, information on flooded areas should be provided to corresponding organizations (local authorities, civil protection agencies, UN agencies etc.) no more than in 24 h to be able to effectively allocate resources required to mitigate the disaster. Therefore, providing infrastructure and services that will enable automatic generation of products based on the integration of heterogeneous data represents the tasks of great importance. In this paper we present Grid infrastructure for automatic processing of synthetic-aperture radar (SAR) satellite images to derive flood products. In particular, we use SAR data acquired by ESA's ENVSAT satellite, and neural networks to derive flood extent. The data are provided in operational mode from ESA rolling archive (within ESA Category-1 grant). We developed a portal that is based on OpenLayers frameworks and provides access point to the developed services. Through the portal the user can define geographical region and search for the required data. Upon selection of data sets a workflow is automatically generated and executed on the resources of Grid infrastructure. For workflow execution and management we use Karajan language. The workflow of SAR data processing consists of the following steps: image calibration, image orthorectification, image processing with neural networks, topographic effects removal, geocoding and transformation to lat/long projection, and visualisation. These steps are executed by different software, and can be executed by different resources of the Grid system. The resulting geospatial services are available in various OGC standards such as KML and WMS. Currently, the Grid infrastructure integrates the resources of several geographically distributed organizations, in particular: Space Research Institute NASU-NSAU (Ukraine) with deployed computational and storage nodes based on Globus Toolkit 4 (htpp://www.globus.org) and gLite 3 (http://glite.web.cern.ch) middleware, access to geospatial data and a Grid portal; Institute of Cybernetics of NASU (Ukraine) with deployed computational and storage nodes (SCIT-1/2/3 clusters) based on Globus Toolkit 4 middleware and access to computational resources (approximately 500 processors); Center of Earth Observation and Digital Earth Chinese Academy of Sciences (CEODE-CAS, China) with deployed computational nodes based on Globus Toolkit 4 middleware and access to geospatial data (approximately 16 processors). We are currently adding new geospatial services based on optical satellite data, namely MODIS. This work is carried out jointly with the CEODE-CAS. Using workflow patterns that were developed for SAR data processing we are building new workflows for optical data processing.

Implementing Computer-Aided Instruction in Distance Education: An Infrastructure. RR/89-06.

ERIC Educational Resources Information Center

Kotze, Paula

The infrastructure required for the implementation of computer aided instruction is described with particular reference to the distance education environment at the University of South Africa. A review of the state of the art of online distance education in the United States and Europe is followed by an outline of the proposed infrastructure for…

Open Component Portability Infrastructure (OPENCPI)

DTIC Science & Technology

2009-11-01

Disk Drive 7 1 www.antec.com P182 $120. ATX Mid Tower Computer Case 8 1 www.xilinx.com HW-V5-ML555-G $2200. Xilinx ML555 V5 Dev Kit Notes: Cost...s/ GEORGE RAMSEYER EDWARD J. JONES, Deputy Chief Work Unit Manager Advanced Computing ...uniquely positioned to meet the goals of the Software Systems Stockroom (S3) since in some sense component-based systems are computer -science’s

Elastic Cloud Computing Infrastructures in the Open Cirrus Testbed Implemented via Eucalyptus

NASA Astrophysics Data System (ADS)

Baun, Christian; Kunze, Marcel

Cloud computing realizes the advantages and overcomes some restrictionsof the grid computing paradigm. Elastic infrastructures can easily be createdand managed by cloud users. In order to accelerate the research ondata center management and cloud services the OpenCirrusTM researchtestbed has been started by HP, Intel and Yahoo!. Although commercialcloud offerings are proprietary, Open Source solutions exist in the field ofIaaS with Eucalyptus, PaaS with AppScale and at the applications layerwith Hadoop MapReduce. This paper examines the I/O performance ofcloud computing infrastructures implemented with Eucalyptus in contrastto Amazon S3.

NCI's High Performance Computing (HPC) and High Performance Data (HPD) Computing Platform for Environmental and Earth System Data Science

NASA Astrophysics Data System (ADS)

Evans, Ben; Allen, Chris; Antony, Joseph; Bastrakova, Irina; Gohar, Kashif; Porter, David; Pugh, Tim; Santana, Fabiana; Smillie, Jon; Trenham, Claire; Wang, Jingbo; Wyborn, Lesley

2015-04-01

The National Computational Infrastructure (NCI) has established a powerful and flexible in-situ petascale computational environment to enable both high performance computing and Data-intensive Science across a wide spectrum of national environmental and earth science data collections - in particular climate, observational data and geoscientific assets. This paper examines 1) the computational environments that supports the modelling and data processing pipelines, 2) the analysis environments and methods to support data analysis, and 3) the progress so far to harmonise the underlying data collections for future interdisciplinary research across these large volume data collections. NCI has established 10+ PBytes of major national and international data collections from both the government and research sectors based on six themes: 1) weather, climate, and earth system science model simulations, 2) marine and earth observations, 3) geosciences, 4) terrestrial ecosystems, 5) water and hydrology, and 6) astronomy, social and biosciences. Collectively they span the lithosphere, crust, biosphere, hydrosphere, troposphere, and stratosphere. The data is largely sourced from NCI's partners (which include the custodians of many of the major Australian national-scale scientific collections), leading research communities, and collaborating overseas organisations. New infrastructures created at NCI mean the data collections are now accessible within an integrated High Performance Computing and Data (HPC-HPD) environment - a 1.2 PFlop supercomputer (Raijin), a HPC class 3000 core OpenStack cloud system and several highly connected large-scale high-bandwidth Lustre filesystems. The hardware was designed at inception to ensure that it would allow the layered software environment to flexibly accommodate the advancement of future data science. New approaches to software technology and data models have also had to be developed to enable access to these large and exponentially increasing data volumes at NCI. Traditional HPC and data environments are still made available in a way that flexibly provides the tools, services and supporting software systems on these new petascale infrastructures. But to enable the research to take place at this scale, the data, metadata and software now need to evolve together - creating a new integrated high performance infrastructure. The new infrastructure at NCI currently supports a catalogue of integrated, reusable software and workflows from earth system and ecosystem modelling, weather research, satellite and other observed data processing and analysis. One of the challenges for NCI has been to support existing techniques and methods, while carefully preparing the underlying infrastructure for the transition needed for the next class of Data-intensive Science. In doing so, a flexible range of techniques and software can be made available for application across the corpus of data collections available, and to provide a new infrastructure for future interdisciplinary research.

The Framework for Simulation of Bioinspired Security Mechanisms against Network Infrastructure Attacks

PubMed Central

Kotenko, Igor

2014-01-01

The paper outlines a bioinspired approach named “network nervous system" and methods of simulation of infrastructure attacks and protection mechanisms based on this approach. The protection mechanisms based on this approach consist of distributed prosedures of information collection and processing, which coordinate the activities of the main devices of a computer network, identify attacks, and determine nessesary countermeasures. Attacks and protection mechanisms are specified as structural models using a set-theoretic approach. An environment for simulation of protection mechanisms based on the biological metaphor is considered; the experiments demonstrating the effectiveness of the protection mechanisms are described. PMID:25254229

Network and computing infrastructure for scientific applications in Georgia

NASA Astrophysics Data System (ADS)

Kvatadze, R.; Modebadze, Z.

2016-09-01

Status of network and computing infrastructure and available services for research and education community of Georgia are presented. Research and Educational Networking Association - GRENA provides the following network services: Internet connectivity, network services, cyber security, technical support, etc. Computing resources used by the research teams are located at GRENA and at major state universities. GE-01-GRENA site is included in European Grid infrastructure. Paper also contains information about programs of Learning Center and research and development projects in which GRENA is participating.

Toward Information Infrastructure Studies: Ways of Knowing in a Networked Environment

NASA Astrophysics Data System (ADS)

Bowker, Geoffrey C.; Baker, Karen; Millerand, Florence; Ribes, David

This article presents Information Infrastructure Studies, a research area that takes up some core issues in digital information and organization research. Infrastructure Studies simultaneously addresses the technical, social, and organizational aspects of the development, usage, and maintenance of infrastructures in local communities as well as global arenas. While infrastructure is understood as a broad category referring to a variety of pervasive, enabling network resources such as railroad lines, plumbing and pipes, electrical power plants and wires, this article focuses on information infrastructure, such as computational services and help desks, or federating activities such as scientific data repositories and archives spanning the multiple disciplines needed to address such issues as climate warming and the biodiversity crisis. These are elements associated with the internet and, frequently today, associated with cyberinfrastructure or e-science endeavors. We argue that a theoretical understanding of infrastructure provides the context for needed dialogue between design, use, and sustainability of internet-based infrastructure services. This article outlines a research area and outlines overarching themes of Infrastructure Studies. Part one of the paper presents definitions for infrastructure and cyberinfrastructure, reviewing salient previous work. Part two portrays key ideas from infrastructure studies (knowledge work, social and political values, new forms of sociality, etc.). In closing, the character of the field today is considered.

Towards International and Interdisciplinary Research Collaboration for the Measurements of Quality of Life

ERIC Educational Resources Information Center

Mizohata, Sachie; Jadoul, Raynald

2013-01-01

This paper focuses on three main subjects: (1) monitoring quality of life (QoL) in old age; (2) international and interdisciplinary collaboration for QoL research; and (3) computer-based technology and infrastructure assisting (1) and (2). This type of computer-supported cooperative work in the social sciences has been termed eHumanities or…

DIRAC universal pilots

NASA Astrophysics Data System (ADS)

Stagni, F.; McNab, A.; Luzzi, C.; Krzemien, W.; Consortium, DIRAC

2017-10-01

In the last few years, new types of computing models, such as IAAS (Infrastructure as a Service) and IAAC (Infrastructure as a Client), gained popularity. New resources may come as part of pledged resources, while others are in the form of opportunistic ones. Most but not all of these new infrastructures are based on virtualization techniques. In addition, some of them, present opportunities for multi-processor computing slots to the users. Virtual Organizations are therefore facing heterogeneity of the available resources and the use of an Interware software like DIRAC to provide the transparent, uniform interface has become essential. The transparent access to the underlying resources is realized by implementing the pilot model. DIRAC’s newest generation of generic pilots (the so-called Pilots 2.0) are the “pilots for all the skies”, and have been successfully released in production more than a year ago. They use a plugin mechanism that makes them easily adaptable. Pilots 2.0 have been used for fetching and running jobs on every type of resource, being it a Worker Node (WN) behind a CREAM/ARC/HTCondor/DIRAC Computing element, a Virtual Machine running on IaaC infrastructures like Vac or BOINC, on IaaS cloud resources managed by Vcycle, the LHCb High Level Trigger farm nodes, and any type of opportunistic computing resource. Make a machine a “Pilot Machine”, and all diversities between them will disappear. This contribution describes how pilots are made suitable for different resources, and the recent steps taken towards a fully unified framework, including monitoring. Also, the cases of multi-processor computing slots either on real or virtual machines, with the whole node or a partition of it, is discussed.

NiftyNet: a deep-learning platform for medical imaging.

PubMed

Gibson, Eli; Li, Wenqi; Sudre, Carole; Fidon, Lucas; Shakir, Dzhoshkun I; Wang, Guotai; Eaton-Rosen, Zach; Gray, Robert; Doel, Tom; Hu, Yipeng; Whyntie, Tom; Nachev, Parashkev; Modat, Marc; Barratt, Dean C; Ourselin, Sébastien; Cardoso, M Jorge; Vercauteren, Tom

2018-05-01

Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functionality for medical image analysis and adapting them for this domain of application requires substantial implementation effort. Consequently, there has been substantial duplication of effort and incompatible infrastructure developed across many research groups. This work presents the open-source NiftyNet platform for deep learning in medical imaging. The ambition of NiftyNet is to accelerate and simplify the development of these solutions, and to provide a common mechanism for disseminating research outputs for the community to use, adapt and build upon. The NiftyNet infrastructure provides a modular deep-learning pipeline for a range of medical imaging applications including segmentation, regression, image generation and representation learning applications. Components of the NiftyNet pipeline including data loading, data augmentation, network architectures, loss functions and evaluation metrics are tailored to, and take advantage of, the idiosyncracies of medical image analysis and computer-assisted intervention. NiftyNet is built on the TensorFlow framework and supports features such as TensorBoard visualization of 2D and 3D images and computational graphs by default. We present three illustrative medical image analysis applications built using NiftyNet infrastructure: (1) segmentation of multiple abdominal organs from computed tomography; (2) image regression to predict computed tomography attenuation maps from brain magnetic resonance images; and (3) generation of simulated ultrasound images for specified anatomical poses. The NiftyNet infrastructure enables researchers to rapidly develop and distribute deep learning solutions for segmentation, regression, image generation and representation learning applications, or extend the platform to new applications. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Bootstrapping and Maintaining Trust in the Cloud

DTIC Science & Technology

2016-03-16

of infrastructure-as-a- service (IaaS) cloud computing services such as Ama- zon Web Services, Google Compute Engine, Rackspace, et. al. means that...Implementation We implemented keylime in ∼3.2k lines of Python in four components: registrar, node, CV, and tenant. The registrar offers a REST-based web ...bootstrap key K. It provides an unencrypted REST-based web service for these two functions. As described earlier, the pro- tocols for exchanging data

SCALING AN URBAN EMERGENCY EVACUATION FRAMEWORK: CHALLENGES AND PRACTICES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karthik, Rajasekar; Lu, Wei

2014-01-01

Critical infrastructure disruption, caused by severe weather events, natural disasters, terrorist attacks, etc., has significant impacts on urban transportation systems. We built a computational framework to simulate urban transportation systems under critical infrastructure disruption in order to aid real-time emergency evacuation. This framework will use large scale datasets to provide a scalable tool for emergency planning and management. Our framework, World-Wide Emergency Evacuation (WWEE), integrates population distribution and urban infrastructure networks to model travel demand in emergency situations at global level. Also, a computational model of agent-based traffic simulation is used to provide an optimal evacuation plan for traffic operationmore » purpose [1]. In addition, our framework provides a web-based high resolution visualization tool for emergency evacuation modelers and practitioners. We have successfully tested our framework with scenarios in both United States (Alexandria, VA) and Europe (Berlin, Germany) [2]. However, there are still some major drawbacks for scaling this framework to handle big data workloads in real time. On our back-end, lack of proper infrastructure limits us in ability to process large amounts of data, run the simulation efficiently and quickly, and provide fast retrieval and serving of data. On the front-end, the visualization performance of microscopic evacuation results is still not efficient enough due to high volume data communication between server and client. We are addressing these drawbacks by using cloud computing and next-generation web technologies, namely Node.js, NoSQL, WebGL, Open Layers 3 and HTML5 technologies. We will describe briefly about each one and how we are using and leveraging these technologies to provide an efficient tool for emergency management organizations. Our early experimentation demonstrates that using above technologies is a promising approach to build a scalable and high performance urban emergency evacuation framework that can improve traffic mobility and safety under critical infrastructure disruption in today s socially connected world.« less

Structural health monitoring of civil infrastructure.

PubMed

Brownjohn, J M W

2007-02-15

Structural health monitoring (SHM) is a term increasingly used in the last decade to describe a range of systems implemented on full-scale civil infrastructures and whose purposes are to assist and inform operators about continued 'fitness for purpose' of structures under gradual or sudden changes to their state, to learn about either or both of the load and response mechanisms. Arguably, various forms of SHM have been employed in civil infrastructure for at least half a century, but it is only in the last decade or two that computer-based systems are being designed for the purpose of assisting owners/operators of ageing infrastructure with timely information for their continued safe and economic operation. This paper describes the motivations for and recent history of SHM applications to various forms of civil infrastructure and provides case studies on specific types of structure. It ends with a discussion of the present state-of-the-art and future developments in terms of instrumentation, data acquisition, communication systems and data mining and presentation procedures for diagnosis of infrastructural 'health'.

Evaluating Commercial and Private Cloud Services for Facility-Scale Geodetic Data Access, Analysis, and Services

NASA Astrophysics Data System (ADS)

Meertens, C. M.; Boler, F. M.; Ertz, D. J.; Mencin, D.; Phillips, D.; Baker, S.

2017-12-01

UNAVCO, in its role as a NSF facility for geodetic infrastructure and data, has succeeded for over two decades using on-premises infrastructure, and while the promise of cloud-based infrastructure is well-established, significant questions about suitability of such infrastructure for facility-scale services remain. Primarily through the GeoSciCloud award from NSF EarthCube, UNAVCO is investigating the costs, advantages, and disadvantages of providing its geodetic data and services in the cloud versus using UNAVCO's on-premises infrastructure. (IRIS is a collaborator on the project and is performing its own suite of investigations). In contrast to the 2-3 year time scale for the research cycle, the time scale of operation and planning for NSF facilities is for a minimum of five years and for some services extends to a decade or more. Planning for on-premises infrastructure is deliberate, and migrations typically take months to years to fully implement. Migrations to a cloud environment can only go forward with similar deliberate planning and understanding of all costs and benefits. The EarthCube GeoSciCloud project is intended to address the uncertainties of facility-level operations in the cloud. Investigations are being performed in a commercial cloud environment (Amazon AWS) during the first year of the project and in a private cloud environment (NSF XSEDE resource at the Texas Advanced Computing Center) during the second year. These investigations are expected to illuminate the potential as well as the limitations of running facility scale production services in the cloud. The work includes running parallel equivalent cloud-based services to on premises services and includes: data serving via ftp from a large data store, operation of a metadata database, production scale processing of multiple months of geodetic data, web services delivery of quality checked data and products, large-scale compute services for event post-processing, and serving real time data from a network of 700-plus GPS stations. The evaluation is based on a suite of metrics that we have developed to elucidate the effectiveness of cloud-based services in price, performance, and management. Services are currently running in AWS and evaluation is underway.

Cloud Environment Automation: from infrastructure deployment to application monitoring

NASA Astrophysics Data System (ADS)

Aiftimiei, C.; Costantini, A.; Bucchi, R.; Italiano, A.; Michelotto, D.; Panella, M.; Pergolesi, M.; Saletta, M.; Traldi, S.; Vistoli, C.; Zizzi, G.; Salomoni, D.

2017-10-01

The potential offered by the cloud paradigm is often limited by technical issues, rules and regulations. In particular, the activities related to the design and deployment of the Infrastructure as a Service (IaaS) cloud layer can be difficult to apply and time-consuming for the infrastructure maintainers. In this paper the research activity, carried out during the Open City Platform (OCP) research project [1], aimed at designing and developing an automatic tool for cloud-based IaaS deployment is presented. Open City Platform is an industrial research project funded by the Italian Ministry of University and Research (MIUR), started in 2014. It intends to research, develop and test new technological solutions open, interoperable and usable on-demand in the field of Cloud Computing, along with new sustainable organizational models that can be deployed for and adopted by the Public Administrations (PA). The presented work and the related outcomes are aimed at simplifying the deployment and maintenance of a complete IaaS cloud-based infrastructure.

Modeling the Cloud to Enhance Capabilities for Crises and Catastrophe Management

DTIC Science & Technology

2016-11-16

order for cloud computing infrastructures to be successfully deployed in real world scenarios as tools for crisis and catastrophe management, where...Statement of the Problem Studied As cloud computing becomes the dominant computational infrastructure[1] and cloud technologies make a transition to hosting...1. Formulate rigorous mathematical models representing technological capabilities and resources in cloud computing for performance modeling and

Infrastructure Systems for Advanced Computing in E-science applications

NASA Astrophysics Data System (ADS)

Terzo, Olivier

2013-04-01

In the e-science field are growing needs for having computing infrastructure more dynamic and customizable with a model of use "on demand" that follow the exact request in term of resources and storage capacities. The integration of grid and cloud infrastructure solutions allows us to offer services that can adapt the availability in terms of up scaling and downscaling resources. The main challenges for e-sciences domains will on implement infrastructure solutions for scientific computing that allow to adapt dynamically the demands of computing resources with a strong emphasis on optimizing the use of computing resources for reducing costs of investments. Instrumentation, data volumes, algorithms, analysis contribute to increase the complexity for applications who require high processing power and storage for a limited time and often exceeds the computational resources that equip the majority of laboratories, research Unit in an organization. Very often it is necessary to adapt or even tweak rethink tools, algorithms, and consolidate existing applications through a phase of reverse engineering in order to adapt them to a deployment on Cloud infrastructure. For example, in areas such as rainfall monitoring, meteorological analysis, Hydrometeorology, Climatology Bioinformatics Next Generation Sequencing, Computational Electromagnetic, Radio occultation, the complexity of the analysis raises several issues such as the processing time, the scheduling of tasks of processing, storage of results, a multi users environment. For these reasons, it is necessary to rethink the writing model of E-Science applications in order to be already adapted to exploit the potentiality of cloud computing services through the uses of IaaS, PaaS and SaaS layer. An other important focus is on create/use hybrid infrastructure typically a federation between Private and public cloud, in fact in this way when all resources owned by the organization are all used it will be easy with a federate cloud infrastructure to add some additional resources form the Public cloud for following the needs in term of computational and storage resources and release them where process are finished. Following the hybrid model, the scheduling approach is important for managing both cloud models. Thanks to this model infrastructure every time resources are available for additional request in term of IT capacities that can used "on demand" for a limited time without having to proceed to purchase additional servers.

Cloud Infrastructure & Applications - CloudIA

NASA Astrophysics Data System (ADS)

Sulistio, Anthony; Reich, Christoph; Doelitzscher, Frank

The idea behind Cloud Computing is to deliver Infrastructure-as-a-Services and Software-as-a-Service over the Internet on an easy pay-per-use business model. To harness the potentials of Cloud Computing for e-Learning and research purposes, and to small- and medium-sized enterprises, the Hochschule Furtwangen University establishes a new project, called Cloud Infrastructure & Applications (CloudIA). The CloudIA project is a market-oriented cloud infrastructure that leverages different virtualization technologies, by supporting Service-Level Agreements for various service offerings. This paper describes the CloudIA project in details and mentions our early experiences in building a private cloud using an existing infrastructure.

A bioinformatics knowledge discovery in text application for grid computing

PubMed Central

Castellano, Marcello; Mastronardi, Giuseppe; Bellotti, Roberto; Tarricone, Gianfranco

2009-01-01

Background A fundamental activity in biomedical research is Knowledge Discovery which has the ability to search through large amounts of biomedical information such as documents and data. High performance computational infrastructures, such as Grid technologies, are emerging as a possible infrastructure to tackle the intensive use of Information and Communication resources in life science. The goal of this work was to develop a software middleware solution in order to exploit the many knowledge discovery applications on scalable and distributed computing systems to achieve intensive use of ICT resources. Methods The development of a grid application for Knowledge Discovery in Text using a middleware solution based methodology is presented. The system must be able to: perform a user application model, process the jobs with the aim of creating many parallel jobs to distribute on the computational nodes. Finally, the system must be aware of the computational resources available, their status and must be able to monitor the execution of parallel jobs. These operative requirements lead to design a middleware to be specialized using user application modules. It included a graphical user interface in order to access to a node search system, a load balancing system and a transfer optimizer to reduce communication costs. Results A middleware solution prototype and the performance evaluation of it in terms of the speed-up factor is shown. It was written in JAVA on Globus Toolkit 4 to build the grid infrastructure based on GNU/Linux computer grid nodes. A test was carried out and the results are shown for the named entity recognition search of symptoms and pathologies. The search was applied to a collection of 5,000 scientific documents taken from PubMed. Conclusion In this paper we discuss the development of a grid application based on a middleware solution. It has been tested on a knowledge discovery in text process to extract new and useful information about symptoms and pathologies from a large collection of unstructured scientific documents. As an example a computation of Knowledge Discovery in Database was applied on the output produced by the KDT user module to extract new knowledge about symptom and pathology bio-entities. PMID:19534749

A bioinformatics knowledge discovery in text application for grid computing.

PubMed

Castellano, Marcello; Mastronardi, Giuseppe; Bellotti, Roberto; Tarricone, Gianfranco

2009-06-16

A fundamental activity in biomedical research is Knowledge Discovery which has the ability to search through large amounts of biomedical information such as documents and data. High performance computational infrastructures, such as Grid technologies, are emerging as a possible infrastructure to tackle the intensive use of Information and Communication resources in life science. The goal of this work was to develop a software middleware solution in order to exploit the many knowledge discovery applications on scalable and distributed computing systems to achieve intensive use of ICT resources. The development of a grid application for Knowledge Discovery in Text using a middleware solution based methodology is presented. The system must be able to: perform a user application model, process the jobs with the aim of creating many parallel jobs to distribute on the computational nodes. Finally, the system must be aware of the computational resources available, their status and must be able to monitor the execution of parallel jobs. These operative requirements lead to design a middleware to be specialized using user application modules. It included a graphical user interface in order to access to a node search system, a load balancing system and a transfer optimizer to reduce communication costs. A middleware solution prototype and the performance evaluation of it in terms of the speed-up factor is shown. It was written in JAVA on Globus Toolkit 4 to build the grid infrastructure based on GNU/Linux computer grid nodes. A test was carried out and the results are shown for the named entity recognition search of symptoms and pathologies. The search was applied to a collection of 5,000 scientific documents taken from PubMed. In this paper we discuss the development of a grid application based on a middleware solution. It has been tested on a knowledge discovery in text process to extract new and useful information about symptoms and pathologies from a large collection of unstructured scientific documents. As an example a computation of Knowledge Discovery in Database was applied on the output produced by the KDT user module to extract new knowledge about symptom and pathology bio-entities.

The Cloud Area Padovana: from pilot to production

NASA Astrophysics Data System (ADS)

Andreetto, P.; Costa, F.; Crescente, A.; Dorigo, A.; Fantinel, S.; Fanzago, F.; Sgaravatto, M.; Traldi, S.; Verlato, M.; Zangrando, L.

2017-10-01

The Cloud Area Padovana has been running for almost two years. This is an OpenStack-based scientific cloud, spread across two different sites: the INFN Padova Unit and the INFN Legnaro National Labs. The hardware resources have been scaled horizontally and vertically, by upgrading some hypervisors and by adding new ones: currently it provides about 1100 cores. Some in-house developments were also integrated in the OpenStack dashboard, such as a tool for user and project registrations with direct support for the INFN-AAI Identity Provider as a new option for the user authentication. In collaboration with the EU-funded Indigo DataCloud project, the integration with Docker-based containers has been experimented with and will be available in production soon. This computing facility now satisfies the computational and storage demands of more than 70 users affiliated with about 20 research projects. We present here the architecture of this Cloud infrastructure, the tools and procedures used to operate it. We also focus on the lessons learnt in these two years, describing the problems that were found and the corrective actions that had to be applied. We also discuss about the chosen strategy for upgrades, which combines the need to promptly integrate the OpenStack new developments, the demand to reduce the downtimes of the infrastructure, and the need to limit the effort requested for such updates. We also discuss how this Cloud infrastructure is being used. In particular we focus on two big physics experiments which are intensively exploiting this computing facility: CMS and SPES. CMS deployed on the cloud a complex computational infrastructure, composed of several user interfaces for job submission in the Grid environment/local batch queues or for interactive processes; this is fully integrated with the local Tier-2 facility. To avoid a static allocation of the resources, an elastic cluster, based on cernVM, has been configured: it allows to automatically create and delete virtual machines according to the user needs. SPES, using a client-server system called TraceWin, exploits INFN’s virtual resources performing a very large number of simulations on about a thousand nodes elastically managed.

Cloud access to interoperable IVOA-compliant VOSpace storage

NASA Astrophysics Data System (ADS)

Bertocco, S.; Dowler, P.; Gaudet, S.; Major, B.; Pasian, F.; Taffoni, G.

2018-07-01

Handling, processing and archiving the huge amount of data produced by the new generation of experiments and instruments in Astronomy and Astrophysics are among the more exciting challenges to address in designing the future data management infrastructures and computing services. We investigated the feasibility of a data management and computation infrastructure, available world-wide, with the aim of merging the FAIR data management provided by IVOA standards with the efficiency and reliability of a cloud approach. Our work involved the Canadian Advanced Network for Astronomy Research (CANFAR) infrastructure and the European EGI federated cloud (EFC). We designed and deployed a pilot data management and computation infrastructure that provides IVOA-compliant VOSpace storage resources and wide access to interoperable federated clouds. In this paper, we detail the main user requirements covered, the technical choices and the implemented solutions and we describe the resulting Hybrid cloud Worldwide infrastructure, its benefits and limitations.

Calibration of controlling input models for pavement management system.

DOT National Transportation Integrated Search

2013-07-01

The Oklahoma Department of Transportation (ODOT) is currently using the Deighton Total Infrastructure Management System (dTIMS) software for pavement management. This system is based on several input models which are computational backbones to dev...

A cyber infrastructure for the SKA Telescope Manager

NASA Astrophysics Data System (ADS)

Barbosa, Domingos; Barraca, João. P.; Carvalho, Bruno; Maia, Dalmiro; Gupta, Yashwant; Natarajan, Swaminathan; Le Roux, Gerhard; Swart, Paul

2016-07-01

The Square Kilometre Array Telescope Manager (SKA TM) will be responsible for assisting the SKA Operations and Observation Management, carrying out System diagnosis and collecting Monitoring and Control data from the SKA subsystems and components. To provide adequate compute resources, scalability, operation continuity and high availability, as well as strict Quality of Service, the TM cyber-infrastructure (embodied in the Local Infrastructure - LINFRA) consists of COTS hardware and infrastructural software (for example: server monitoring software, host operating system, virtualization software, device firmware), providing a specially tailored Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) solution. The TM infrastructure provides services in the form of computational power, software defined networking, power, storage abstractions, and high level, state of the art IaaS and PaaS management interfaces. This cyber platform will be tailored to each of the two SKA Phase 1 telescopes (SKA_MID in South Africa and SKA_LOW in Australia) instances, each presenting different computational and storage infrastructures and conditioned by location. This cyber platform will provide a compute model enabling TM to manage the deployment and execution of its multiple components (observation scheduler, proposal submission tools, MandC components, Forensic tools and several Databases, etc). In this sense, the TM LINFRA is primarily focused towards the provision of isolated instances, mostly resorting to virtualization technologies, while defaulting to bare hardware if specifically required due to performance, security, availability, or other requirement.

A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure

PubMed Central

Fontaine, Michael D.

2013-01-01

Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing. PMID:23766690

A Cyber-ITS framework for massive traffic data analysis using cyber infrastructure.

PubMed

Xia, Yingjie; Hu, Jia; Fontaine, Michael D

2013-01-01

Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing.

The High-Performance Computing and Communications program, the national information infrastructure and health care.

PubMed Central

Lindberg, D A; Humphreys, B L

1995-01-01

The High-Performance Computing and Communications (HPCC) program is a multiagency federal effort to advance the state of computing and communications and to provide the technologic platform on which the National Information Infrastructure (NII) can be built. The HPCC program supports the development of high-speed computers, high-speed telecommunications, related software and algorithms, education and training, and information infrastructure technology and applications. The vision of the NII is to extend access to high-performance computing and communications to virtually every U.S. citizen so that the technology can be used to improve the civil infrastructure, lifelong learning, energy management, health care, etc. Development of the NII will require resolution of complex economic and social issues, including information privacy. Health-related applications supported under the HPCC program and NII initiatives include connection of health care institutions to the Internet; enhanced access to gene sequence data; the "Visible Human" Project; and test-bed projects in telemedicine, electronic patient records, shared informatics tool development, and image systems. PMID:7614116

Distributed telemedicine for the National Information Infrastructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Forslund, D.W.; Lee, Seong H.; Reverbel, F.C.

1997-08-01

TeleMed is an advanced system that provides a distributed multimedia electronic medical record available over a wide area network. It uses object-based computing, distributed data repositories, advanced graphical user interfaces, and visualization tools along with innovative concept extraction of image information for storing and accessing medical records developed in a separate project from 1994-5. In 1996, we began the transition to Java, extended the infrastructure, and worked to begin deploying TeleMed-like technologies throughout the nation. Other applications are mentioned.

Structural Health Monitoring of Civil Infrastructure Using Optical Fiber Sensing Technology: A Comprehensive Review

PubMed Central

Ye, X. W.; Su, Y. H.; Han, J. P.

2014-01-01

In the last two decades, a significant number of innovative sensing systems based on optical fiber sensors have been exploited in the engineering community due to their inherent distinctive advantages such as small size, light weight, immunity to electromagnetic interference (EMI) and corrosion, and embedding capability. A lot of optical fiber sensor-based monitoring systems have been developed for continuous measurement and real-time assessment of diversified engineering structures such as bridges, buildings, tunnels, pipelines, wind turbines, railway infrastructure, and geotechnical structures. The purpose of this review article is devoted to presenting a summary of the basic principles of various optical fiber sensors, innovation in sensing and computational methodologies, development of novel optical fiber sensors, and the practical application status of the optical fiber sensing technology in structural health monitoring (SHM) of civil infrastructure. PMID:25133250

Structural health monitoring of civil infrastructure using optical fiber sensing technology: a comprehensive review.

PubMed

Ye, X W; Su, Y H; Han, J P

2014-01-01

In the last two decades, a significant number of innovative sensing systems based on optical fiber sensors have been exploited in the engineering community due to their inherent distinctive advantages such as small size, light weight, immunity to electromagnetic interference (EMI) and corrosion, and embedding capability. A lot of optical fiber sensor-based monitoring systems have been developed for continuous measurement and real-time assessment of diversified engineering structures such as bridges, buildings, tunnels, pipelines, wind turbines, railway infrastructure, and geotechnical structures. The purpose of this review article is devoted to presenting a summary of the basic principles of various optical fiber sensors, innovation in sensing and computational methodologies, development of novel optical fiber sensors, and the practical application status of the optical fiber sensing technology in structural health monitoring (SHM) of civil infrastructure.

The multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research

PubMed Central

Goscinski, Wojtek J.; McIntosh, Paul; Felzmann, Ulrich; Maksimenko, Anton; Hall, Christopher J.; Gureyev, Timur; Thompson, Darren; Janke, Andrew; Galloway, Graham; Killeen, Neil E. B.; Raniga, Parnesh; Kaluza, Owen; Ng, Amanda; Poudel, Govinda; Barnes, David G.; Nguyen, Toan; Bonnington, Paul; Egan, Gary F.

2014-01-01

The Multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) is a national imaging and visualization facility established by Monash University, the Australian Synchrotron, the Commonwealth Scientific Industrial Research Organization (CSIRO), and the Victorian Partnership for Advanced Computing (VPAC), with funding from the National Computational Infrastructure and the Victorian Government. The MASSIVE facility provides hardware, software, and expertise to drive research in the biomedical sciences, particularly advanced brain imaging research using synchrotron x-ray and infrared imaging, functional and structural magnetic resonance imaging (MRI), x-ray computer tomography (CT), electron microscopy and optical microscopy. The development of MASSIVE has been based on best practice in system integration methodologies, frameworks, and architectures. The facility has: (i) integrated multiple different neuroimaging analysis software components, (ii) enabled cross-platform and cross-modality integration of neuroinformatics tools, and (iii) brought together neuroimaging databases and analysis workflows. MASSIVE is now operational as a nationally distributed and integrated facility for neuroinfomatics and brain imaging research. PMID:24734019

Future Naval Use of COTS Networking Infrastructure

DTIC Science & Technology

2009-07-01

user to benefit from Google’s vast databases and computational resources. Obviously, the ability to harness the full power of the Cloud could be... Computing Impact Findings Action Items Take-Aways Appendices: Pages 54-68 A. Terms of Reference Document B. Sample Definitions of Cloud ...and definition of Cloud Computing . While Cloud Computing is developing in many variations – including Infrastructure as a Service (IaaS), Platform as

A case study for cloud based high throughput analysis of NGS data using the globus genomics system

DOE PAGES

Bhuvaneshwar, Krithika; Sulakhe, Dinanath; Gauba, Robinder; ...

2015-01-01

Next generation sequencing (NGS) technologies produce massive amounts of data requiring a powerful computational infrastructure, high quality bioinformatics software, and skilled personnel to operate the tools. We present a case study of a practical solution to this data management and analysis challenge that simplifies terabyte scale data handling and provides advanced tools for NGS data analysis. These capabilities are implemented using the “Globus Genomics” system, which is an enhanced Galaxy workflow system made available as a service that offers users the capability to process and transfer data easily, reliably and quickly to address end-to-end NGS analysis requirements. The Globus Genomicsmore » system is built on Amazon's cloud computing infrastructure. The system takes advantage of elastic scaling of compute resources to run multiple workflows in parallel and it also helps meet the scale-out analysis needs of modern translational genomics research.« less

Interactions among human behavior, social networks, and societal infrastructures: A Case Study in Computational Epidemiology

NASA Astrophysics Data System (ADS)

Barrett, Christopher L.; Bisset, Keith; Chen, Jiangzhuo; Eubank, Stephen; Lewis, Bryan; Kumar, V. S. Anil; Marathe, Madhav V.; Mortveit, Henning S.

Human behavior, social networks, and the civil infrastructures are closely intertwined. Understanding their co-evolution is critical for designing public policies and decision support for disaster planning. For example, human behaviors and day to day activities of individuals create dense social interactions that are characteristic of modern urban societies. These dense social networks provide a perfect fabric for fast, uncontrolled disease propagation. Conversely, people’s behavior in response to public policies and their perception of how the crisis is unfolding as a result of disease outbreak can dramatically alter the normally stable social interactions. Effective planning and response strategies must take these complicated interactions into account. In this chapter, we describe a computer simulation based approach to study these issues using public health and computational epidemiology as an illustrative example. We also formulate game-theoretic and stochastic optimization problems that capture many of the problems that we study empirically.

A case study for cloud based high throughput analysis of NGS data using the globus genomics system

PubMed Central

Bhuvaneshwar, Krithika; Sulakhe, Dinanath; Gauba, Robinder; Rodriguez, Alex; Madduri, Ravi; Dave, Utpal; Lacinski, Lukasz; Foster, Ian; Gusev, Yuriy; Madhavan, Subha

2014-01-01

Next generation sequencing (NGS) technologies produce massive amounts of data requiring a powerful computational infrastructure, high quality bioinformatics software, and skilled personnel to operate the tools. We present a case study of a practical solution to this data management and analysis challenge that simplifies terabyte scale data handling and provides advanced tools for NGS data analysis. These capabilities are implemented using the “Globus Genomics” system, which is an enhanced Galaxy workflow system made available as a service that offers users the capability to process and transfer data easily, reliably and quickly to address end-to-endNGS analysis requirements. The Globus Genomics system is built on Amazon 's cloud computing infrastructure. The system takes advantage of elastic scaling of compute resources to run multiple workflows in parallel and it also helps meet the scale-out analysis needs of modern translational genomics research. PMID:26925205

Analysis of CERN computing infrastructure and monitoring data

NASA Astrophysics Data System (ADS)

Nieke, C.; Lassnig, M.; Menichetti, L.; Motesnitsalis, E.; Duellmann, D.

2015-12-01

Optimizing a computing infrastructure on the scale of LHC requires a quantitative understanding of a complex network of many different resources and services. For this purpose the CERN IT department and the LHC experiments are collecting a large multitude of logs and performance probes, which are already successfully used for short-term analysis (e.g. operational dashboards) within each group. The IT analytics working group has been created with the goal to bring data sources from different services and on different abstraction levels together and to implement a suitable infrastructure for mid- to long-term statistical analysis. It further provides a forum for joint optimization across single service boundaries and the exchange of analysis methods and tools. To simplify access to the collected data, we implemented an automated repository for cleaned and aggregated data sources based on the Hadoop ecosystem. This contribution describes some of the challenges encountered, such as dealing with heterogeneous data formats, selecting an efficient storage format for map reduce and external access, and will describe the repository user interface. Using this infrastructure we were able to quantitatively analyze the relationship between CPU/wall fraction, latency/throughput constraints of network and disk and the effective job throughput. In this contribution we will first describe the design of the shared analysis infrastructure and then present a summary of first analysis results from the combined data sources.

Scientific Services on the Cloud

NASA Astrophysics Data System (ADS)

Chapman, David; Joshi, Karuna P.; Yesha, Yelena; Halem, Milt; Yesha, Yaacov; Nguyen, Phuong

Scientific Computing was one of the first every applications for parallel and distributed computation. To this date, scientific applications remain some of the most compute intensive, and have inspired creation of petaflop compute infrastructure such as the Oak Ridge Jaguar and Los Alamos RoadRunner. Large dedicated hardware infrastructure has become both a blessing and a curse to the scientific community. Scientists are interested in cloud computing for much the same reason as businesses and other professionals. The hardware is provided, maintained, and administrated by a third party. Software abstraction and virtualization provide reliability, and fault tolerance. Graduated fees allow for multi-scale prototyping and execution. Cloud computing resources are only a few clicks away, and by far the easiest high performance distributed platform to gain access to. There may still be dedicated infrastructure for ultra-scale science, but the cloud can easily play a major part of the scientific computing initiative.

Knowledge base for v-Embryo: Information Infrastructure for in silico modeling

EPA Science Inventory

Computers, imaging technologies, and the worldwide web have assumed an important role in augmenting traditional learning. Resources to disseminate multimedia information across platforms, and the emergence of communal knowledge environments, facilitate the visualization of diffi...

Genomic cloud computing: legal and ethical points to consider

PubMed Central

Dove, Edward S; Joly, Yann; Tassé, Anne-Marie; Burton, Paul; Chisholm, Rex; Fortier, Isabel; Goodwin, Pat; Harris, Jennifer; Hveem, Kristian; Kaye, Jane; Kent, Alistair; Knoppers, Bartha Maria; Lindpaintner, Klaus; Little, Julian; Riegman, Peter; Ripatti, Samuli; Stolk, Ronald; Bobrow, Martin; Cambon-Thomsen, Anne; Dressler, Lynn; Joly, Yann; Kato, Kazuto; Knoppers, Bartha Maria; Rodriguez, Laura Lyman; McPherson, Treasa; Nicolás, Pilar; Ouellette, Francis; Romeo-Casabona, Carlos; Sarin, Rajiv; Wallace, Susan; Wiesner, Georgia; Wilson, Julia; Zeps, Nikolajs; Simkevitz, Howard; De Rienzo, Assunta; Knoppers, Bartha M

2015-01-01

The biggest challenge in twenty-first century data-intensive genomic science, is developing vast computer infrastructure and advanced software tools to perform comprehensive analyses of genomic data sets for biomedical research and clinical practice. Researchers are increasingly turning to cloud computing both as a solution to integrate data from genomics, systems biology and biomedical data mining and as an approach to analyze data to solve biomedical problems. Although cloud computing provides several benefits such as lower costs and greater efficiency, it also raises legal and ethical issues. In this article, we discuss three key ‘points to consider' (data control; data security, confidentiality and transfer; and accountability) based on a preliminary review of several publicly available cloud service providers' Terms of Service. These ‘points to consider' should be borne in mind by genomic research organizations when negotiating legal arrangements to store genomic data on a large commercial cloud service provider's servers. Diligent genomic cloud computing means leveraging security standards and evaluation processes as a means to protect data and entails many of the same good practices that researchers should always consider in securing their local infrastructure. PMID:25248396

Genomic cloud computing: legal and ethical points to consider.

PubMed

Dove, Edward S; Joly, Yann; Tassé, Anne-Marie; Knoppers, Bartha M

2015-10-01

The biggest challenge in twenty-first century data-intensive genomic science, is developing vast computer infrastructure and advanced software tools to perform comprehensive analyses of genomic data sets for biomedical research and clinical practice. Researchers are increasingly turning to cloud computing both as a solution to integrate data from genomics, systems biology and biomedical data mining and as an approach to analyze data to solve biomedical problems. Although cloud computing provides several benefits such as lower costs and greater efficiency, it also raises legal and ethical issues. In this article, we discuss three key 'points to consider' (data control; data security, confidentiality and transfer; and accountability) based on a preliminary review of several publicly available cloud service providers' Terms of Service. These 'points to consider' should be borne in mind by genomic research organizations when negotiating legal arrangements to store genomic data on a large commercial cloud service provider's servers. Diligent genomic cloud computing means leveraging security standards and evaluation processes as a means to protect data and entails many of the same good practices that researchers should always consider in securing their local infrastructure.

Consolidation and development roadmap of the EMI middleware

NASA Astrophysics Data System (ADS)

Kónya, B.; Aiftimiei, C.; Cecchi, M.; Field, L.; Fuhrmann, P.; Nilsen, J. K.; White, J.

2012-12-01

Scientific research communities have benefited recently from the increasing availability of computing and data infrastructures with unprecedented capabilities for large scale distributed initiatives. These infrastructures are largely defined and enabled by the middleware they deploy. One of the major issues in the current usage of research infrastructures is the need to use similar but often incompatible middleware solutions. The European Middleware Initiative (EMI) is a collaboration of the major European middleware providers ARC, dCache, gLite and UNICORE. EMI aims to: deliver a consolidated set of middleware components for deployment in EGI, PRACE and other Distributed Computing Infrastructures; extend the interoperability between grids and other computing infrastructures; strengthen the reliability of the services; establish a sustainable model to maintain and evolve the middleware; fulfil the requirements of the user communities. This paper presents the consolidation and development objectives of the EMI software stack covering the last two years. The EMI development roadmap is introduced along the four technical areas of compute, data, security and infrastructure. The compute area plan focuses on consolidation of standards and agreements through a unified interface for job submission and management, a common format for accounting, the wide adoption of GLUE schema version 2.0 and the provision of a common framework for the execution of parallel jobs. The security area is working towards a unified security model and lowering the barriers to Grid usage by allowing users to gain access with their own credentials. The data area is focusing on implementing standards to ensure interoperability with other grids and industry components and to reuse already existing clients in operating systems and open source distributions. One of the highlights of the infrastructure area is the consolidation of the information system services via the creation of a common information backbone.

CLIMB (the Cloud Infrastructure for Microbial Bioinformatics): an online resource for the medical microbiology community

PubMed Central

Smith, Andy; Southgate, Joel; Poplawski, Radoslaw; Bull, Matthew J.; Richardson, Emily; Ismail, Matthew; Thompson, Simon Elwood-; Kitchen, Christine; Guest, Martyn; Bakke, Marius

2016-01-01

The increasing availability and decreasing cost of high-throughput sequencing has transformed academic medical microbiology, delivering an explosion in available genomes while also driving advances in bioinformatics. However, many microbiologists are unable to exploit the resulting large genomics datasets because they do not have access to relevant computational resources and to an appropriate bioinformatics infrastructure. Here, we present the Cloud Infrastructure for Microbial Bioinformatics (CLIMB) facility, a shared computing infrastructure that has been designed from the ground up to provide an environment where microbiologists can share and reuse methods and data. PMID:28785418

CLIMB (the Cloud Infrastructure for Microbial Bioinformatics): an online resource for the medical microbiology community.

PubMed

Connor, Thomas R; Loman, Nicholas J; Thompson, Simon; Smith, Andy; Southgate, Joel; Poplawski, Radoslaw; Bull, Matthew J; Richardson, Emily; Ismail, Matthew; Thompson, Simon Elwood-; Kitchen, Christine; Guest, Martyn; Bakke, Marius; Sheppard, Samuel K; Pallen, Mark J

2016-09-01

The increasing availability and decreasing cost of high-throughput sequencing has transformed academic medical microbiology, delivering an explosion in available genomes while also driving advances in bioinformatics. However, many microbiologists are unable to exploit the resulting large genomics datasets because they do not have access to relevant computational resources and to an appropriate bioinformatics infrastructure. Here, we present the Cloud Infrastructure for Microbial Bioinformatics (CLIMB) facility, a shared computing infrastructure that has been designed from the ground up to provide an environment where microbiologists can share and reuse methods and data.

Minimizing Overhead for Secure Computation and Fully Homomorphic Encryption: Overhead

DTIC Science & Technology

2015-11-01

many inputs. We also improved our compiler infrastructure to handle very large circuits in a more scalable way. In Jan’13, we employed the AESNI and...Amazon’s elastic compute infrastructure , and is running under a Xen hypervisor. Since we do not have direct access to the bare metal, we cannot...creating novel opportunities for compressing au- thentication overhead. It is especially compelling that existing public key infrastructures can be used

Model-as-a-service (MaaS) using the cloud service innovation platform (CSIP)

USDA-ARS?s Scientific Manuscript database

Cloud infrastructures for modelling activities such as data processing, performing environmental simulations, or conducting model calibrations/optimizations provide a cost effective alternative to traditional high performance computing approaches. Cloud-based modelling examples emerged into the more...

A Computing Infrastructure for Supporting Climate Studies

NASA Astrophysics Data System (ADS)

Yang, C.; Bambacus, M.; Freeman, S. M.; Huang, Q.; Li, J.; Sun, M.; Xu, C.; Wojcik, G. S.; Cahalan, R. F.; NASA Climate @ Home Project Team

2011-12-01

Climate change is one of the major challenges facing us on the Earth planet in the 21st century. Scientists build many models to simulate the past and predict the climate change for the next decades or century. Most of the models are at a low resolution with some targeting high resolution in linkage to practical climate change preparedness. To calibrate and validate the models, millions of model runs are needed to find the best simulation and configuration. This paper introduces the NASA effort on Climate@Home project to build a supercomputer based-on advanced computing technologies, such as cloud computing, grid computing, and others. Climate@Home computing infrastructure includes several aspects: 1) a cloud computing platform is utilized to manage the potential spike access to the centralized components, such as grid computing server for dispatching and collecting models runs results; 2) a grid computing engine is developed based on MapReduce to dispatch models, model configuration, and collect simulation results and contributing statistics; 3) a portal serves as the entry point for the project to provide the management, sharing, and data exploration for end users; 4) scientists can access customized tools to configure model runs and visualize model results; 5) the public can access twitter and facebook to get the latest about the project. This paper will introduce the latest progress of the project and demonstrate the operational system during the AGU fall meeting. It will also discuss how this technology can become a trailblazer for other climate studies and relevant sciences. It will share how the challenges in computation and software integration were solved.

Using OSG Computing Resources with (iLC)Dirac

NASA Astrophysics Data System (ADS)

Sailer, A.; Petric, M.; CLICdp Collaboration

2017-10-01

CPU cycles for small experiments and projects can be scarce, thus making use of all available resources, whether dedicated or opportunistic, is mandatory. While enabling uniform access to the LCG computing elements (ARC, CREAM), the DIRAC grid interware was not able to use OSG computing elements (GlobusCE, HTCondor-CE) without dedicated support at the grid site through so called ‘SiteDirectors’, which directly submit to the local batch system. This in turn requires additional dedicated effort for small experiments on the grid site. Adding interfaces to the OSG CEs through the respective grid middleware is therefore allowing accessing them within the DIRAC software without additional site-specific infrastructure. This enables greater use of opportunistic resources for experiments and projects without dedicated clusters or an established computing infrastructure with the DIRAC software. To allow sending jobs to HTCondor-CE and legacy Globus computing elements inside DIRAC the required wrapper classes were developed. Not only is the usage of these types of computing elements now completely transparent for all DIRAC instances, which makes DIRAC a flexible solution for OSG based virtual organisations, but it also allows LCG Grid Sites to move to the HTCondor-CE software, without shutting DIRAC based VOs out of their site. In these proceedings we detail how we interfaced the DIRAC system to the HTCondor-CE and Globus computing elements and explain the encountered obstacles and solutions developed, and how the linear collider community uses resources in the OSG.

[Design and study of parallel computing environment of Monte Carlo simulation for particle therapy planning using a public cloud-computing infrastructure].

PubMed

Yokohama, Noriya

2013-07-01

This report was aimed at structuring the design of architectures and studying performance measurement of a parallel computing environment using a Monte Carlo simulation for particle therapy using a high performance computing (HPC) instance within a public cloud-computing infrastructure. Performance measurements showed an approximately 28 times faster speed than seen with single-thread architecture, combined with improved stability. A study of methods of optimizing the system operations also indicated lower cost.

75 FR 70899 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-19

... submit to the Office of Management and Budget (OMB) for clearance the following proposal for collection... Annual Burden Hours: 2,952. Public Computer Center Reports (Quarterly and Annually) Number of Respondents... specific to Infrastructure and Comprehensive Community Infrastructure, Public Computer Center, and...

Computation Directorate Annual Report 2003

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crawford, D L; McGraw, J R; Ashby, S F

Big computers are icons: symbols of the culture, and of the larger computing infrastructure that exists at Lawrence Livermore. Through the collective effort of Laboratory personnel, they enable scientific discovery and engineering development on an unprecedented scale. For more than three decades, the Computation Directorate has supplied the big computers that enable the science necessary for Laboratory missions and programs. Livermore supercomputing is uniquely mission driven. The high-fidelity weapon simulation capabilities essential to the Stockpile Stewardship Program compel major advances in weapons codes and science, compute power, and computational infrastructure. Computation's activities align with this vital mission of the Departmentmore » of Energy. Increasingly, non-weapons Laboratory programs also rely on computer simulation. World-class achievements have been accomplished by LLNL specialists working in multi-disciplinary research and development teams. In these teams, Computation personnel employ a wide array of skills, from desktop support expertise, to complex applications development, to advanced research. Computation's skilled professionals make the Directorate the success that it has become. These individuals know the importance of the work they do and the many ways it contributes to Laboratory missions. They make appropriate and timely decisions that move the entire organization forward. They make Computation a leader in helping LLNL achieve its programmatic milestones. I dedicate this inaugural Annual Report to the people of Computation in recognition of their continuing contributions. I am proud that we perform our work securely and safely. Despite increased cyber attacks on our computing infrastructure from the Internet, advanced cyber security practices ensure that our computing environment remains secure. Through Integrated Safety Management (ISM) and diligent oversight, we address safety issues promptly and aggressively. The safety of our employees, whether at work or at home, is a paramount concern. Even as the Directorate meets today's supercomputing requirements, we are preparing for the future. We are investigating open-source cluster technology, the basis of our highly successful Mulitprogrammatic Capability Resource (MCR). Several breakthrough discoveries have resulted from MCR calculations coupled with theory and experiment, prompting Laboratory scientists to demand ever-greater capacity and capability. This demand is being met by a new 23-TF system, Thunder, with architecture modeled on MCR. In preparation for the ''after-next'' computer, we are researching technology even farther out on the horizon--cell-based computers. Assuming that the funding and the technology hold, we will acquire the cell-based machine BlueGene/L within the next 12 months.« less

caCORE version 3: Implementation of a model driven, service-oriented architecture for semantic interoperability.

PubMed

Komatsoulis, George A; Warzel, Denise B; Hartel, Francis W; Shanbhag, Krishnakant; Chilukuri, Ram; Fragoso, Gilberto; Coronado, Sherri de; Reeves, Dianne M; Hadfield, Jillaine B; Ludet, Christophe; Covitz, Peter A

2008-02-01

One of the requirements for a federated information system is interoperability, the ability of one computer system to access and use the resources of another system. This feature is particularly important in biomedical research systems, which need to coordinate a variety of disparate types of data. In order to meet this need, the National Cancer Institute Center for Bioinformatics (NCICB) has created the cancer Common Ontologic Representation Environment (caCORE), an interoperability infrastructure based on Model Driven Architecture. The caCORE infrastructure provides a mechanism to create interoperable biomedical information systems. Systems built using the caCORE paradigm address both aspects of interoperability: the ability to access data (syntactic interoperability) and understand the data once retrieved (semantic interoperability). This infrastructure consists of an integrated set of three major components: a controlled terminology service (Enterprise Vocabulary Services), a standards-based metadata repository (the cancer Data Standards Repository) and an information system with an Application Programming Interface (API) based on Domain Model Driven Architecture. This infrastructure is being leveraged to create a Semantic Service-Oriented Architecture (SSOA) for cancer research by the National Cancer Institute's cancer Biomedical Informatics Grid (caBIG).

caCORE version 3: Implementation of a model driven, service-oriented architecture for semantic interoperability

PubMed Central

Komatsoulis, George A.; Warzel, Denise B.; Hartel, Frank W.; Shanbhag, Krishnakant; Chilukuri, Ram; Fragoso, Gilberto; de Coronado, Sherri; Reeves, Dianne M.; Hadfield, Jillaine B.; Ludet, Christophe; Covitz, Peter A.

2008-01-01

One of the requirements for a federated information system is interoperability, the ability of one computer system to access and use the resources of another system. This feature is particularly important in biomedical research systems, which need to coordinate a variety of disparate types of data. In order to meet this need, the National Cancer Institute Center for Bioinformatics (NCICB) has created the cancer Common Ontologic Representation Environment (caCORE), an interoperability infrastructure based on Model Driven Architecture. The caCORE infrastructure provides a mechanism to create interoperable biomedical information systems. Systems built using the caCORE paradigm address both aspects of interoperability: the ability to access data (syntactic interoperability) and understand the data once retrieved (semantic interoperability). This infrastructure consists of an integrated set of three major components: a controlled terminology service (Enterprise Vocabulary Services), a standards-based metadata repository (the cancer Data Standards Repository) and an information system with an Application Programming Interface (API) based on Domain Model Driven Architecture. This infrastructure is being leveraged to create a Semantic Service Oriented Architecture (SSOA) for cancer research by the National Cancer Institute’s cancer Biomedical Informatics Grid (caBIG™). PMID:17512259

Neural Network Based Intrusion Detection System for Critical Infrastructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Todd Vollmer; Ondrej Linda; Milos Manic

2009-07-01

Resiliency and security in control systems such as SCADA and Nuclear plant’s in today’s world of hackers and malware are a relevant concern. Computer systems used within critical infrastructures to control physical functions are not immune to the threat of cyber attacks and may be potentially vulnerable. Tailoring an intrusion detection system to the specifics of critical infrastructures can significantly improve the security of such systems. The IDS-NNM – Intrusion Detection System using Neural Network based Modeling, is presented in this paper. The main contributions of this work are: 1) the use and analyses of real network data (data recordedmore » from an existing critical infrastructure); 2) the development of a specific window based feature extraction technique; 3) the construction of training dataset using randomly generated intrusion vectors; 4) the use of a combination of two neural network learning algorithms – the Error-Back Propagation and Levenberg-Marquardt, for normal behavior modeling. The presented algorithm was evaluated on previously unseen network data. The IDS-NNM algorithm proved to be capable of capturing all intrusion attempts presented in the network communication while not generating any false alerts.« less

Defense of Cyber Infrastructures Against Cyber-Physical Attacks Using Game-Theoretic Models

DOE PAGES

Rao, Nageswara S. V.; Poole, Stephen W.; Ma, Chris Y. T.; ...

2015-04-06

The operation of cyber infrastructures relies on both cyber and physical components, which are subject to incidental and intentional degradations of different kinds. Within the context of network and computing infrastructures, we study the strategic interactions between an attacker and a defender using game-theoretic models that take into account both cyber and physical components. The attacker and defender optimize their individual utilities expressed as sums of cost and system terms. First, we consider a Boolean attack-defense model, wherein the cyber and physical sub-infrastructures may be attacked and reinforced as individual units. Second, we consider a component attack-defense model wherein theirmore » components may be attacked and defended, and the infrastructure requires minimum numbers of both to function. We show that the Nash equilibrium under uniform costs in both cases is computable in polynomial time, and it provides high-level deterministic conditions for the infrastructure survival. When probabilities of successful attack and defense, and of incidental failures are incorporated into the models, the results favor the attacker but otherwise remain qualitatively similar. This approach has been motivated and validated by our experiences with UltraScience Net infrastructure, which was built to support high-performance network experiments. In conclusion, the analytical results, however, are more general, and we apply them to simplified models of cloud and high-performance computing infrastructures.« less

Defense of Cyber Infrastructures Against Cyber-Physical Attacks Using Game-Theoretic Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rao, Nageswara S. V.; Poole, Stephen W.; Ma, Chris Y. T.

The operation of cyber infrastructures relies on both cyber and physical components, which are subject to incidental and intentional degradations of different kinds. Within the context of network and computing infrastructures, we study the strategic interactions between an attacker and a defender using game-theoretic models that take into account both cyber and physical components. The attacker and defender optimize their individual utilities expressed as sums of cost and system terms. First, we consider a Boolean attack-defense model, wherein the cyber and physical sub-infrastructures may be attacked and reinforced as individual units. Second, we consider a component attack-defense model wherein theirmore » components may be attacked and defended, and the infrastructure requires minimum numbers of both to function. We show that the Nash equilibrium under uniform costs in both cases is computable in polynomial time, and it provides high-level deterministic conditions for the infrastructure survival. When probabilities of successful attack and defense, and of incidental failures are incorporated into the models, the results favor the attacker but otherwise remain qualitatively similar. This approach has been motivated and validated by our experiences with UltraScience Net infrastructure, which was built to support high-performance network experiments. In conclusion, the analytical results, however, are more general, and we apply them to simplified models of cloud and high-performance computing infrastructures.« less

An Assessment of Vulnerabilities for Ship-based Control Systems

DTIC Science & Technology

2009-09-01

VULNERABILITIES FOR SHIP- BASED CONTROL SYSTEMS by Richard Bensing September 2009 Thesis Advisor: Karen Burke Co-Advisor: George Dinolt...COVERED Master’s Thesis 4. TITLE AND SUBTITLE: An Assessment of Vulnerabilities for Ship- based Control Systems 6. AUTHOR(S) Richard Bensing 5...soft underbelly. Computer- based control systems form the heart of the critical infrastructure, and these control systems are riddled with rampant

Critical infrastructure protection : significant challenges in developing national capabilities

DOT National Transportation Integrated Search

2001-04-01

To address the concerns about protecting the nation's critical computer-dependent infrastructure, this General Accounting Office (GOA) report describes the progress of the National Infrastructure Protection Center (NIPC) in (1) developing national ca...

Distributed Accounting on the Grid

NASA Technical Reports Server (NTRS)

Thigpen, William; Hacker, Thomas J.; McGinnis, Laura F.; Athey, Brian D.

2001-01-01

By the late 1990s, the Internet was adequately equipped to move vast amounts of data between HPC (High Performance Computing) systems, and efforts were initiated to link together the national infrastructure of high performance computational and data storage resources together into a general computational utility 'grid', analogous to the national electrical power grid infrastructure. The purpose of the Computational grid is to provide dependable, consistent, pervasive, and inexpensive access to computational resources for the computing community in the form of a computing utility. This paper presents a fully distributed view of Grid usage accounting and a methodology for allocating Grid computational resources for use on a Grid computing system.

ChemCalc: a building block for tomorrow's chemical infrastructure.

PubMed

Patiny, Luc; Borel, Alain

2013-05-24

Web services, as an aspect of cloud computing, are becoming an important part of the general IT infrastructure, and scientific computing is no exception to this trend. We propose a simple approach to develop chemical Web services, through which servers could expose the essential data manipulation functionality that students and researchers need for chemical calculations. These services return their results as JSON (JavaScript Object Notation) objects, which facilitates their use for Web applications. The ChemCalc project http://www.chemcalc.org demonstrates this approach: we present three Web services related with mass spectrometry, namely isotopic distribution simulation, peptide fragmentation simulation, and molecular formula determination. We also developed a complete Web application based on these three Web services, taking advantage of modern HTML5 and JavaScript libraries (ChemDoodle and jQuery).

Sustainable mobile information infrastructures in low resource settings.

PubMed

Braa, Kristin; Purkayastha, Saptarshi

2010-01-01

Developing countries represent the fastest growing mobile markets in the world. For people with no computing access, a mobile will be their first computing device. Mobile technologies offer a significant potential to strengthen health systems in developing countries with respect to community based monitoring, reporting, feedback to service providers, and strengthening communication and coordination between different health functionaries, medical officers and the community. However, there are various challenges in realizing this potential including technological such as lack of power, social, institutional and use issues. In this paper a case study from India on mobile health implementation and use will be reported. An underlying principle guiding this paper is to see mobile technology not as a "stand alone device" but potentially an integral component of an integrated mobile supported health information infrastructure.

Multimedia courseware in an open-systems environment: a DoD strategy

NASA Astrophysics Data System (ADS)

Welsch, Lawrence A.

1991-03-01

The federal government is about to invest billions of dollars to develop multimedia training materials for delivery on computer-based interactive training systems. Acquisition of a variety of computers and peripheral devices hosting various operating systems and suites of authoring system software will be necessary to facilitate the development of this courseware. There is no single source that will satisfy all needs. Although high-performance, low-cost interactive training hardware is available, the products have proprietary software interfaces. Because the interfaces are proprietary, expensive reprogramming is usually required to adapt such software products to other platforms. This costly reprogramming could be eliminated by adopting standard software interfaces. DoD's Portable Courseware Project (PORTCO) is typical of projects worldwide that require standard software interfaces. This paper articulates the strategy whereby PORTCO leverages the open systems movement and the new realities of information technology. These realities encompass changes in the pace at which new technology becomes available, changes in organizational goals and philosophy, new roles of vendors and users, changes in the procurement process, and acceleration toward open system environments. The PORTCO strategy is applicable to all projects and systems that require open systems to achieve mission objectives. The federal goal is to facilitate the creation of an environment in which high quality portable courseware is available as commercial off-the-shelf products and is competitively supplied by a variety of vendors. In order to achieve this goal a system architecture incorporating standards to meet the users' needs must be established. The Request for Architecture (RFA) developed cooperatively by DoD and the National Institute of Standards and Technology (NIST) will generate the PORTCO systems architecture. This architecture must freely integrate the courseware and authoring software from the lower levels of machine architecture and systems service implementation. In addition, the systems architecture will establish how the application-specific technologies relate to other technologies. Further, a computer-based interactive training applications profile must be developed. This profile, along with the systems architecture derived as a result of the RFA, provides the basis for identifying the needed standards. NIST will then accelerate the development of these standards using, but not restricted to, existing standards activities within established standards forums. The federal multimedia courseware effort has adopted the Interactive Multimedia Association (INA) Recommended Practices for Interactive Video Portability as the baseline for the migration of computer-based interactive training systems to an open systems environment based upon international standards. The PORTCO strategy includes an evolutionary migration to a standards-based, Open System Environments (OSE). An important aspect of this migration strategy is to move to open systems via stepwise evolution rather than via quantum leaps. Another area of concern is that of infrastructure issues, such as maintaining and supporting the technologies required for computer-based interactive training. The federal multimedia initiative will use the RFA-based architecture to differentiate between those technologies that can be maintained and supported by existing infrastructure mechanisms and those that require new mechanisms. Existing infrastructure mechanisms will be used and where infrastructure mechanisms do not exist, the approach will be to place high priority on establishing the appropriate mechanisms. Establishing an infrastructure mechanism is a nontrivial task requiring sustained investment of resources.

Waggle: A Framework for Intelligent Attentive Sensing and Actuation

NASA Astrophysics Data System (ADS)

Sankaran, R.; Jacob, R. L.; Beckman, P. H.; Catlett, C. E.; Keahey, K.

2014-12-01

Advances in sensor-driven computation and computationally steered sensing will greatly enable future research in fields including environmental and atmospheric sciences. We will present "Waggle," an open-source hardware and software infrastructure developed with two goals: (1) reducing the separation and latency between sensing and computing and (2) improving the reliability and longevity of sensing-actuation platforms in challenging and costly deployments. Inspired by "deep-space probe" systems, the Waggle platform design includes features that can support longitudinal studies, deployments with varying communication links, and remote management capabilities. Waggle lowers the barrier for scientists to incorporate real-time data from their sensors into their computations and to manipulate the sensors or provide feedback through actuators. A standardized software and hardware design allows quick addition of new sensors/actuators and associated software in the nodes and enables them to be coupled with computational codes both insitu and on external compute infrastructure. The Waggle framework currently drives the deployment of two observational systems - a portable and self-sufficient weather platform for study of small-scale effects in Chicago's urban core and an open-ended distributed instrument in Chicago that aims to support several research pursuits across a broad range of disciplines including urban planning, microbiology and computer science. Built around open-source software, hardware, and Linux OS, the Waggle system comprises two components - the Waggle field-node and Waggle cloud-computing infrastructure. Waggle field-node affords a modular, scalable, fault-tolerant, secure, and extensible platform for hosting sensors and actuators in the field. It supports insitu computation and data storage, and integration with cloud-computing infrastructure. The Waggle cloud infrastructure is designed with the goal of scaling to several hundreds of thousands of Waggle nodes. It supports aggregating data from sensors hosted by the nodes, staging computation, relaying feedback to the nodes and serving data to end-users. We will discuss the Waggle design principles and their applicability to various observational research pursuits, and demonstrate its capabilities.

Beyond the Workshop: Educational Policy in Situated Practice.

ERIC Educational Resources Information Center

Jenson, Jennifer; Lewis, Brian

2001-01-01

Identifies questions arising from implementation of computer-based technologies in Canadian schools--questions of public policy in an increasingly technocentric and commercialized environment, of investment in technological infrastructure, and of teachers' professional development and its effectiveness. Lists necessary factors for the success of…

Collaborative Working Architecture for IoT-Based Applications.

PubMed

Mora, Higinio; Signes-Pont, María Teresa; Gil, David; Johnsson, Magnus

2018-05-23

The new sensing applications need enhanced computing capabilities to handle the requirements of complex and huge data processing. The Internet of Things (IoT) concept brings processing and communication features to devices. In addition, the Cloud Computing paradigm provides resources and infrastructures for performing the computations and outsourcing the work from the IoT devices. This scenario opens new opportunities for designing advanced IoT-based applications, however, there is still much research to be done to properly gear all the systems for working together. This work proposes a collaborative model and an architecture to take advantage of the available computing resources. The resulting architecture involves a novel network design with different levels which combines sensing and processing capabilities based on the Mobile Cloud Computing (MCC) paradigm. An experiment is included to demonstrate that this approach can be used in diverse real applications. The results show the flexibility of the architecture to perform complex computational tasks of advanced applications.

Editorial [Special issue on software defined networks and infrastructures, network function virtualisation, autonomous systems and network management

DOE PAGES

Biswas, Amitava; Liu, Chen; Monga, Inder; ...

2016-01-01

For last few years, there has been a tremendous growth in data traffic due to high adoption rate of mobile devices and cloud computing. Internet of things (IoT) will stimulate even further growth. This is increasing scale and complexity of telecom/internet service provider (SP) and enterprise data centre (DC) compute and network infrastructures. As a result, managing these large network-compute converged infrastructures is becoming complex and cumbersome. To cope up, network and DC operators are trying to automate network and system operations, administrations and management (OAM) functions. OAM includes all non-functional mechanisms which keep the network running.

Cloud computing can simplify HIT infrastructure management.

PubMed

Glaser, John

2011-08-01

Software as a Service (SaaS), built on cloud computing technology, is emerging as the forerunner in IT infrastructure because it helps healthcare providers reduce capital investments. Cloud computing leads to predictable, monthly, fixed operating expenses for hospital IT staff. Outsourced cloud computing facilities are state-of-the-art data centers boasting some of the most sophisticated networking equipment on the market. The SaaS model helps hospitals safeguard against technology obsolescence, minimizes maintenance requirements, and simplifies management.

A Computation Infrastructure for Knowledge-Based Development of Reliable Software Systems

DTIC Science & Technology

2006-11-10

Grant number: F045-023-0029 * Principal Investigator: David Gaspari, ATC-NY * Duration: May 2007 (assuming a successful review in 2005) * Source of... David Guaspari, Verifying Chain Replication in Event Logic Cornell University Technical Report, to be published 2006 "* Eli Barzilay, Implementing...and Reasoning, volume 2452 of Lecture Notes in Computer Science, pages 449-465, 2005. "* Mark Bickford and David Guaspari, A Programming Logic for

Douglass Rationalization: An Evaluation of a Team Environment and a Computer-Based Task in Academic Libraries

ERIC Educational Resources Information Center

Denda, Kayo; Smulewitz, Gracemary

2004-01-01

In the contemporary library environment, the presence of the Internet and the infrastructure of the integrated library system suggest an integrated internal organization. The article describes the example of Douglass Rationalization, a team-based collaborative project to refocus the collection of Rutgers' Douglass Library, taking advantage of the…

An Infrastructure to Enable Lightweight Context-Awareness for Mobile Users

PubMed Central

Curiel, Pablo; Lago, Ana B.

2013-01-01

Mobile phones enable us to carry out a wider range of tasks every day, and as a result they have become more ubiquitous than ever. However, they are still more limited in terms of processing power and interaction capabilities than traditional computers, and the often distracting and time-constricted scenarios in which we use them do not help in alleviating these limitations. Context-awareness is a valuable technique to address these issues, as it enables to adapt application behaviour to each situation. In this paper we present a context management infrastructure for mobile environments, aimed at controlling context information life-cycle in this kind of scenarios, with the main goal of enabling application and services to adapt their behaviour to better meet end-user needs. This infrastructure relies on semantic technologies and open standards to improve interoperability, and is based on a central element, the context manager. This element acts as a central context repository and takes most of the computational burden derived from dealing with this kind of information, thus relieving from these tasks to more resource-scarce devices in the system. PMID:23899932

Resource Aware Intelligent Network Services (RAINS) Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lehman, Tom; Yang, Xi

The Resource Aware Intelligent Network Services (RAINS) project conducted research and developed technologies in the area of cyber infrastructure resource modeling and computation. The goal of this work was to provide a foundation to enable intelligent, software defined services which spanned the network AND the resources which connect to the network. A Multi-Resource Service Plane (MRSP) was defined, which allows resource owners/managers to locate and place themselves from a topology and service availability perspective within the dynamic networked cyberinfrastructure ecosystem. The MRSP enables the presentation of integrated topology views and computation results which can include resources across the spectrum ofmore » compute, storage, and networks. The RAINS project developed MSRP includes the following key components: i) Multi-Resource Service (MRS) Ontology/Multi-Resource Markup Language (MRML), ii) Resource Computation Engine (RCE), iii) Modular Driver Framework (to allow integration of a variety of external resources). The MRS/MRML is a general and extensible modeling framework that allows for resource owners to model, or describe, a wide variety of resource types. All resources are described using three categories of elements: Resources, Services, and Relationships between the elements. This modeling framework defines a common method for the transformation of cyber infrastructure resources into data in the form of MRML models. In order to realize this infrastructure datification, the RAINS project developed a model based computation system, i.e. “RAINS Computation Engine (RCE)”. The RCE has the ability to ingest, process, integrate, and compute based on automatically generated MRML models. The RCE interacts with the resources thru system drivers which are specific to the type of external network or resource controller. The RAINS project developed a modular and pluggable driver system which facilities a variety of resource controllers to automatically generate, maintain, and distribute MRML based resource descriptions. Once all of the resource topologies are absorbed by the RCE, a connected graph of the full distributed system topology is constructed, which forms the basis for computation and workflow processing. The RCE includes a Modular Computation Element (MCE) framework which allows for tailoring of the computation process to the specific set of resources under control, and the services desired. The input and output of an MCE are both model data based on MRS/MRML ontology and schema. Some of the RAINS project accomplishments include: Development of general and extensible multi-resource modeling framework; Design of a Resource Computation Engine (RCE) system which includes the following key capabilities; Absorb a variety of multi-resource model types and build integrated models; Novel architecture which uses model based communications across the full stack for all Flexible provision of abstract or intent based user facing interfaces; Workflow processing based on model descriptions; Release of the RCE as an open source software; Deployment of RCE in the University of Maryland/Mid-Atlantic Crossroad ScienceDMZ in prototype mode with a plan under way to transition to production; Deployment at the Argonne National Laboratory DTN Facility in prototype mode; Selection of RCE by the DOE SENSE (SDN for End-to-end Networked Science at the Exascale) project as the basis for their orchestration service.« less

e-Infrastructures for e-Sciences 2013 A CHAIN-REDS Workshop organised under the aegis of the European Commission

NASA Astrophysics Data System (ADS)

The CHAIN-REDS Project is organising a workshop on "e-Infrastructures for e-Sciences" focusing on Cloud Computing and Data Repositories under the aegis of the European Commission and in co-location with the International Conference on e-Science 2013 (IEEE2013) that will be held in Beijing, P.R. of China on October 17-22, 2013. The core objective of the CHAIN-REDS project is to promote, coordinate and support the effort of a critical mass of non-European e-Infrastructures for Research and Education to collaborate with Europe addressing interoperability and interoperation of Grids and other Distributed Computing Infrastructures (DCI). From this perspective, CHAIN-REDS will optimise the interoperation of European infrastructures with those present in 6 other regions of the world, both from a development and use point of view, and catering to different communities. Overall, CHAIN-REDS will provide input for future strategies and decision-making regarding collaboration with other regions on e-Infrastructure deployment and availability of related data; it will raise the visibility of e-Infrastructures towards intercontinental audiences, covering most of the world and will provide support to establish globally connected and interoperable infrastructures, in particular between the EU and the developing regions. Organised by IHEP, INFN and Sigma Orionis with the support of all project partners, this workshop will aim at: - Presenting the state of the art of Cloud computing in Europe and in China and discussing the opportunities offered by having interoperable and federated e-Infrastructures; - Exploring the existing initiatives of Data Infrastructures in Europe and China, and highlighting the Data Repositories of interest for the Virtual Research Communities in several domains such as Health, Agriculture, Climate, etc.

Critical Infrastructure Protection II, The International Federation for Information Processing, Volume 290.

NASA Astrophysics Data System (ADS)

Papa, Mauricio; Shenoi, Sujeet

The information infrastructure -- comprising computers, embedded devices, networks and software systems -- is vital to day-to-day operations in every sector: information and telecommunications, banking and finance, energy, chemicals and hazardous materials, agriculture, food, water, public health, emergency services, transportation, postal and shipping, government and defense. Global business and industry, governments, indeed society itself, cannot function effectively if major components of the critical information infrastructure are degraded, disabled or destroyed. Critical Infrastructure Protection II describes original research results and innovative applications in the interdisciplinary field of critical infrastructure protection. Also, it highlights the importance of weaving science, technology and policy in crafting sophisticated, yet practical, solutions that will help secure information, computer and network assets in the various critical infrastructure sectors. Areas of coverage include: - Themes and Issues - Infrastructure Security - Control Systems Security - Security Strategies - Infrastructure Interdependencies - Infrastructure Modeling and Simulation This book is the second volume in the annual series produced by the International Federation for Information Processing (IFIP) Working Group 11.10 on Critical Infrastructure Protection, an international community of scientists, engineers, practitioners and policy makers dedicated to advancing research, development and implementation efforts focused on infrastructure protection. The book contains a selection of twenty edited papers from the Second Annual IFIP WG 11.10 International Conference on Critical Infrastructure Protection held at George Mason University, Arlington, Virginia, USA in the spring of 2008.

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaskey, Alexander J.

Hybrid programming models for beyond-CMOS technologies will prove critical for integrating new computing technologies alongside our existing infrastructure. Unfortunately the software infrastructure required to enable this is lacking or not available. XACC is a programming framework for extreme-scale, post-exascale accelerator architectures that integrates alongside existing conventional applications. It is a pluggable framework for programming languages developed for next-gen computing hardware architectures like quantum and neuromorphic computing. It lets computational scientists efficiently off-load classically intractable work to attached accelerators through user-friendly Kernel definitions. XACC makes post-exascale hybrid programming approachable for domain computational scientists.

Architecture of a spatial data service system for statistical analysis and visualization of regional climate changes

NASA Astrophysics Data System (ADS)

Titov, A. G.; Okladnikov, I. G.; Gordov, E. P.

2017-11-01

The use of large geospatial datasets in climate change studies requires the development of a set of Spatial Data Infrastructure (SDI) elements, including geoprocessing and cartographical visualization web services. This paper presents the architecture of a geospatial OGC web service system as an integral part of a virtual research environment (VRE) general architecture for statistical processing and visualization of meteorological and climatic data. The architecture is a set of interconnected standalone SDI nodes with corresponding data storage systems. Each node runs a specialized software, such as a geoportal, cartographical web services (WMS/WFS), a metadata catalog, and a MySQL database of technical metadata describing geospatial datasets available for the node. It also contains geospatial data processing services (WPS) based on a modular computing backend realizing statistical processing functionality and, thus, providing analysis of large datasets with the results of visualization and export into files of standard formats (XML, binary, etc.). Some cartographical web services have been developed in a system’s prototype to provide capabilities to work with raster and vector geospatial data based on OGC web services. The distributed architecture presented allows easy addition of new nodes, computing and data storage systems, and provides a solid computational infrastructure for regional climate change studies based on modern Web and GIS technologies.

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid.

PubMed

Li, Yuancheng; Qiu, Rixuan; Jing, Sitong

2018-01-01

Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

Maintaining Privacy in Pervasive Computing - Enabling Acceptance of Sensor-based Services

NASA Astrophysics Data System (ADS)

Soppera, A.; Burbridge, T.

During the 1980s, Mark Weiser [1] predicted a world in which computing was so pervasive that devices embedded in the environment could sense their relationship to us and to each other. These tiny ubiquitous devices would continually feed information from the physical world into the information world. Twenty years ago, this vision was the exclusive territory of academic computer scientists and science fiction writers. Today this subject has become of interest to business, government, and society. Governmental authorities exercise their power through the networked environment. Credit card databases maintain our credit history and decide whether we are allowed to rent a house or obtain a loan. Mobile telephones can locate us in real time so that we do not miss calls. Within another 10 years, all sorts of devices will be connected through the network. Our fridge, our food, together with our health information, may all be networked for the purpose of maintaining diet and well-being. The Internet will move from being an infrastructure to connect computers, to being an infrastructure to connect everything [2, 3].

Galaxy CloudMan: delivering cloud compute clusters.

PubMed

Afgan, Enis; Baker, Dannon; Coraor, Nate; Chapman, Brad; Nekrutenko, Anton; Taylor, James

2010-12-21

Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is "cloud computing", which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate "as is" use by experimental biologists. We present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon's EC2 cloud infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs. The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge.

Desktop Virtualization: Applications and Considerations

ERIC Educational Resources Information Center

Hodgman, Matthew R.

2013-01-01

As educational technology continues to rapidly become a vital part of a school district's infrastructure, desktop virtualization promises to provide cost-effective and education-enhancing solutions to school-based computer technology problems in school systems locally and abroad. This article outlines the history of and basic concepts behind…

Tony Magri | NREL

Science.gov Websites

Windows System Engineer with the Computational Science Center. He implements, supports, and integrates Windows-based technology solutions at the ESIF and manages a portion of the VMware infrastructure . Throughout his career, Tony has built a strong skillset in enterprise Windows Engineering and Active

The JASMIN Cloud: specialised and hybrid to meet the needs of the Environmental Sciences Community

NASA Astrophysics Data System (ADS)

Kershaw, Philip; Lawrence, Bryan; Churchill, Jonathan; Pritchard, Matt

2014-05-01

Cloud computing provides enormous opportunities for the research community. The large public cloud providers provide near-limitless scaling capability. However, adapting Cloud to scientific workloads is not without its problems. The commodity nature of the public cloud infrastructure can be at odds with the specialist requirements of the research community. Issues such as trust, ownership of data, WAN bandwidth and costing models make additional barriers to more widespread adoption. Alongside the application of public cloud for scientific applications, a number of private cloud initiatives are underway in the research community of which the JASMIN Cloud is one example. Here, cloud service models are being effectively super-imposed over more established services such as data centres, compute cluster facilities and Grids. These have the potential to deliver the specialist infrastructure needed for the science community coupled with the benefits of a Cloud service model. The JASMIN facility based at the Rutherford Appleton Laboratory was established in 2012 to support the data analysis requirements of the climate and Earth Observation community. In its first year of operation, the 5PB of available storage capacity was filled and the hosted compute capability used extensively. JASMIN has modelled the concept of a centralised large-volume data analysis facility. Key characteristics have enabled success: peta-scale fast disk connected via low latency networks to compute resources and the use of virtualisation for effective management of the resources for a range of users. A second phase is now underway funded through NERC's (Natural Environment Research Council) Big Data initiative. This will see significant expansion to the resources available with a doubling of disk-based storage to 12PB and an increase of compute capacity by a factor of ten to over 3000 processing cores. This expansion is accompanied by a broadening in the scope for JASMIN, as a service available to the entire UK environmental science community. Experience with the first phase demonstrated the range of user needs. A trade-off is needed between access privileges to resources, flexibility of use and security. This has influenced the form and types of service under development for the new phase. JASMIN will deploy a specialised private cloud organised into "Managed" and "Unmanaged" components. In the Managed Cloud, users have direct access to the storage and compute resources for optimal performance but for reasons of security, via a more restrictive PaaS (Platform-as-a-Service) interface. The Unmanaged Cloud is deployed in an isolated part of the network but co-located with the rest of the infrastructure. This enables greater liberty to tenants - full IaaS (Infrastructure-as-a-Service) capability to provision customised infrastructure - whilst at the same time protecting more sensitive parts of the system from direct access using these elevated privileges. The private cloud will be augmented with cloud-bursting capability so that it can exploit the resources available from public clouds, making it effectively a hybrid solution. A single interface will overlay the functionality of both the private cloud and external interfaces to public cloud providers giving users the flexibility to migrate resources between infrastructures as requirements dictate.

Development of a Dynamically Configurable,Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation

NASA Technical Reports Server (NTRS)

Afjeh, Abdollah A.; Reed, John A.

2003-01-01

This research is aimed at developing a neiv and advanced simulation framework that will significantly improve the overall efficiency of aerospace systems design and development. This objective will be accomplished through an innovative integration of object-oriented and Web-based technologies ivith both new and proven simulation methodologies. The basic approach involves Ihree major areas of research: Aerospace system and component representation using a hierarchical object-oriented component model which enables the use of multimodels and enforces component interoperability. Collaborative software environment that streamlines the process of developing, sharing and integrating aerospace design and analysis models. . Development of a distributed infrastructure which enables Web-based exchange of models to simplify the collaborative design process, and to support computationally intensive aerospace design and analysis processes. Research for the first year dealt with the design of the basic architecture and supporting infrastructure, an initial implementation of that design, and a demonstration of its application to an example aircraft engine system simulation.

Software Reuse Methods to Improve Technological Infrastructure for e-Science

NASA Technical Reports Server (NTRS)

Marshall, James J.; Downs, Robert R.; Mattmann, Chris A.

2011-01-01

Social computing has the potential to contribute to scientific research. Ongoing developments in information and communications technology improve capabilities for enabling scientific research, including research fostered by social computing capabilities. The recent emergence of e-Science practices has demonstrated the benefits from improvements in the technological infrastructure, or cyber-infrastructure, that has been developed to support science. Cloud computing is one example of this e-Science trend. Our own work in the area of software reuse offers methods that can be used to improve new technological development, including cloud computing capabilities, to support scientific research practices. In this paper, we focus on software reuse and its potential to contribute to the development and evaluation of information systems and related services designed to support new capabilities for conducting scientific research.

Message Efficient Checkpointing and Rollback Recovery in Heterogeneous Mobile Networks

NASA Astrophysics Data System (ADS)

Jaggi, Parmeet Kaur; Singh, Awadhesh Kumar

2016-06-01

Heterogeneous networks provide an appealing way of expanding the computing capability of mobile networks by combining infrastructure-less mobile ad-hoc networks with the infrastructure-based cellular mobile networks. The nodes in such a network range from low-power nodes to macro base stations and thus, vary greatly in their capabilities such as computation power and battery power. The nodes are susceptible to different types of transient and permanent failures and therefore, the algorithms designed for such networks need to be fault-tolerant. The article presents a checkpointing algorithm for the rollback recovery of mobile hosts in a heterogeneous mobile network. Checkpointing is a well established approach to provide fault tolerance in static and cellular mobile distributed systems. However, the use of checkpointing for fault tolerance in a heterogeneous environment remains to be explored. The proposed protocol is based on the results of zigzag paths and zigzag cycles by Netzer-Xu. Considering the heterogeneity prevalent in the network, an uncoordinated checkpointing technique is employed. Yet, useless checkpoints are avoided without causing a high message overhead.

RAPPORT: running scientific high-performance computing applications on the cloud.

PubMed

Cohen, Jeremy; Filippis, Ioannis; Woodbridge, Mark; Bauer, Daniela; Hong, Neil Chue; Jackson, Mike; Butcher, Sarah; Colling, David; Darlington, John; Fuchs, Brian; Harvey, Matt

2013-01-28

Cloud computing infrastructure is now widely used in many domains, but one area where there has been more limited adoption is research computing, in particular for running scientific high-performance computing (HPC) software. The Robust Application Porting for HPC in the Cloud (RAPPORT) project took advantage of existing links between computing researchers and application scientists in the fields of bioinformatics, high-energy physics (HEP) and digital humanities, to investigate running a set of scientific HPC applications from these domains on cloud infrastructure. In this paper, we focus on the bioinformatics and HEP domains, describing the applications and target cloud platforms. We conclude that, while there are many factors that need consideration, there is no fundamental impediment to the use of cloud infrastructure for running many types of HPC applications and, in some cases, there is potential for researchers to benefit significantly from the flexibility offered by cloud platforms.

Internet-based computer technology on radiotherapy.

PubMed

Chow, James C L

2017-01-01

Recent rapid development of Internet-based computer technologies has made possible many novel applications in radiation dose delivery. However, translational speed of applying these new technologies in radiotherapy could hardly catch up due to the complex commissioning process and quality assurance protocol. Implementing novel Internet-based technology in radiotherapy requires corresponding design of algorithm and infrastructure of the application, set up of related clinical policies, purchase and development of software and hardware, computer programming and debugging, and national to international collaboration. Although such implementation processes are time consuming, some recent computer advancements in the radiation dose delivery are still noticeable. In this review, we will present the background and concept of some recent Internet-based computer technologies such as cloud computing, big data processing and machine learning, followed by their potential applications in radiotherapy, such as treatment planning and dose delivery. We will also discuss the current progress of these applications and their impacts on radiotherapy. We will explore and evaluate the expected benefits and challenges in implementation as well.

Enabling BOINC in infrastructure as a service cloud system

NASA Astrophysics Data System (ADS)

Montes, Diego; Añel, Juan A.; Pena, Tomás F.; Uhe, Peter; Wallom, David C. H.

2017-02-01

Volunteer or crowd computing is becoming increasingly popular for solving complex research problems from an increasingly diverse range of areas. The majority of these have been built using the Berkeley Open Infrastructure for Network Computing (BOINC) platform, which provides a range of different services to manage all computation aspects of a project. The BOINC system is ideal in those cases where not only does the research community involved need low-cost access to massive computing resources but also where there is a significant public interest in the research being done.We discuss the way in which cloud services can help BOINC-based projects to deliver results in a fast, on demand manner. This is difficult to achieve using volunteers, and at the same time, using scalable cloud resources for short on demand projects can optimize the use of the available resources. We show how this design can be used as an efficient distributed computing platform within the cloud, and outline new approaches that could open up new possibilities in this field, using Climateprediction.net (http://www.climateprediction.net/) as a case study.

A Framework for Debugging Geoscience Projects in a High Performance Computing Environment

NASA Astrophysics Data System (ADS)

Baxter, C.; Matott, L.

2012-12-01

High performance computing (HPC) infrastructure has become ubiquitous in today's world with the emergence of commercial cloud computing and academic supercomputing centers. Teams of geoscientists, hydrologists and engineers can take advantage of this infrastructure to undertake large research projects - for example, linking one or more site-specific environmental models with soft computing algorithms, such as heuristic global search procedures, to perform parameter estimation and predictive uncertainty analysis, and/or design least-cost remediation systems. However, the size, complexity and distributed nature of these projects can make identifying failures in the associated numerical experiments using conventional ad-hoc approaches both time- consuming and ineffective. To address these problems a multi-tiered debugging framework has been developed. The framework allows for quickly isolating and remedying a number of potential experimental failures, including: failures in the HPC scheduler; bugs in the soft computing code; bugs in the modeling code; and permissions and access control errors. The utility of the framework is demonstrated via application to a series of over 200,000 numerical experiments involving a suite of 5 heuristic global search algorithms and 15 mathematical test functions serving as cheap analogues for the simulation-based optimization of pump-and-treat subsurface remediation systems.

Processing LHC data in the UK

PubMed Central

Colling, D.; Britton, D.; Gordon, J.; Lloyd, S.; Doyle, A.; Gronbech, P.; Coles, J.; Sansum, A.; Patrick, G.; Jones, R.; Middleton, R.; Kelsey, D.; Cass, A.; Geddes, N.; Clark, P.; Barnby, L.

2013-01-01

The Large Hadron Collider (LHC) is one of the greatest scientific endeavours to date. The construction of the collider itself and the experiments that collect data from it represent a huge investment, both financially and in terms of human effort, in our hope to understand the way the Universe works at a deeper level. Yet the volumes of data produced are so large that they cannot be analysed at any single computing centre. Instead, the experiments have all adopted distributed computing models based on the LHC Computing Grid. Without the correct functioning of this grid infrastructure the experiments would not be able to understand the data that they have collected. Within the UK, the Grid infrastructure needed by the experiments is provided by the GridPP project. We report on the operations, performance and contributions made to the experiments by the GridPP project during the years of 2010 and 2011—the first two significant years of the running of the LHC. PMID:23230163

Cloud Infrastructures for In Silico Drug Discovery: Economic and Practical Aspects

PubMed Central

Clematis, Andrea; Quarati, Alfonso; Cesini, Daniele; Milanesi, Luciano; Merelli, Ivan

2013-01-01

Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements. PMID:24106693

Using Swarming Agents for Scalable Security in Large Network Environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crouse, Michael; White, Jacob L.; Fulp, Errin W.

2011-09-23

The difficulty of securing computer infrastructures increases as they grow in size and complexity. Network-based security solutions such as IDS and firewalls cannot scale because of exponentially increasing computational costs inherent in detecting the rapidly growing number of threat signatures. Hostbased solutions like virus scanners and IDS suffer similar issues, and these are compounded when enterprises try to monitor these in a centralized manner. Swarm-based autonomous agent systems like digital ants and artificial immune systems can provide a scalable security solution for large network environments. The digital ants approach offers a biologically inspired design where each ant in the virtualmore » colony can detect atoms of evidence that may help identify a possible threat. By assembling the atomic evidences from different ant types the colony may detect the threat. This decentralized approach can require, on average, fewer computational resources than traditional centralized solutions; however there are limits to its scalability. This paper describes how dividing a large infrastructure into smaller managed enclaves allows the digital ant framework to effectively operate in larger environments. Experimental results will show that using smaller enclaves allows for more consistent distribution of agents and results in faster response times.« less

Facilitating NASA Earth Science Data Processing Using Nebula Cloud Computing

NASA Technical Reports Server (NTRS)

Pham, Long; Chen, Aijun; Kempler, Steven; Lynnes, Christopher; Theobald, Michael; Asghar, Esfandiari; Campino, Jane; Vollmer, Bruce

2011-01-01

Cloud Computing has been implemented in several commercial arenas. The NASA Nebula Cloud Computing platform is an Infrastructure as a Service (IaaS) built in 2008 at NASA Ames Research Center and 2010 at GSFC. Nebula is an open source Cloud platform intended to: a) Make NASA realize significant cost savings through efficient resource utilization, reduced energy consumption, and reduced labor costs. b) Provide an easier way for NASA scientists and researchers to efficiently explore and share large and complex data sets. c) Allow customers to provision, manage, and decommission computing capabilities on an as-needed bases

Design and Implement of Astronomical Cloud Computing Environment In China-VO

NASA Astrophysics Data System (ADS)

Li, Changhua; Cui, Chenzhou; Mi, Linying; He, Boliang; Fan, Dongwei; Li, Shanshan; Yang, Sisi; Xu, Yunfei; Han, Jun; Chen, Junyi; Zhang, Hailong; Yu, Ce; Xiao, Jian; Wang, Chuanjun; Cao, Zihuang; Fan, Yufeng; Liu, Liang; Chen, Xiao; Song, Wenming; Du, Kangyu

2017-06-01

Astronomy cloud computing environment is a cyber-Infrastructure for Astronomy Research initiated by Chinese Virtual Observatory (China-VO) under funding support from NDRC (National Development and Reform commission) and CAS (Chinese Academy of Sciences). Based on virtualization technology, astronomy cloud computing environment was designed and implemented by China-VO team. It consists of five distributed nodes across the mainland of China. Astronomer can get compuitng and storage resource in this cloud computing environment. Through this environments, astronomer can easily search and analyze astronomical data collected by different telescopes and data centers , and avoid the large scale dataset transportation.

A real-time KLT implementation for radio-SETI applications

NASA Astrophysics Data System (ADS)

Melis, Andrea; Concu, Raimondo; Pari, Pierpaolo; Maccone, Claudio; Montebugnoli, Stelio; Possenti, Andrea; Valente, Giuseppe; Antonietti, Nicoló; Perrodin, Delphine; Migoni, Carlo; Murgia, Matteo; Trois, Alessio; Barbaro, Massimo; Bocchinu, Alessandro; Casu, Silvia; Lunesu, Maria Ilaria; Monari, Jader; Navarrini, Alessandro; Pisanu, Tonino; Schilliró, Francesco; Vacca, Valentina

2016-07-01

SETI, the Search for ExtraTerrestrial Intelligence, is the search for radio signals emitted by alien civilizations living in the Galaxy. Narrow-band FFT-based approaches have been preferred in SETI, since their computation time only grows like N*lnN, where N is the number of time samples. On the contrary, a wide-band approach based on the Kahrunen-Lo`eve Transform (KLT) algorithm would be preferable, but it would scale like N*N. In this paper, we describe a hardware-software infrastructure based on FPGA boards and GPU-based PCs that circumvents this computation-time problem allowing for a real-time KLT.

A PACS archive architecture supported on cloud services.

PubMed

Silva, Luís A Bastião; Costa, Carlos; Oliveira, José Luis

2012-05-01

Diagnostic imaging procedures have continuously increased over the last decade and this trend may continue in coming years, creating a great impact on storage and retrieval capabilities of current PACS. Moreover, many smaller centers do not have financial resources or requirements that justify the acquisition of a traditional infrastructure. Alternative solutions, such as cloud computing, may help address this emerging need. A tremendous amount of ubiquitous computational power, such as that provided by Google and Amazon, are used every day as a normal commodity. Taking advantage of this new paradigm, an architecture for a Cloud-based PACS archive that provides data privacy, integrity, and availability is proposed. The solution is independent from the cloud provider and the core modules were successfully instantiated in examples of two cloud computing providers. Operational metrics for several medical imaging modalities were tabulated and compared for Google Storage, Amazon S3, and LAN PACS. A PACS-as-a-Service archive that provides storage of medical studies using the Cloud was developed. The results show that the solution is robust and that it is possible to store, query, and retrieve all desired studies in a similar way as in a local PACS approach. Cloud computing is an emerging solution that promises high scalability of infrastructures, software, and applications, according to a "pay-as-you-go" business model. The presented architecture uses the cloud to setup medical data repositories and can have a significant impact on healthcare institutions by reducing IT infrastructures.

International Symposium on Grids and Clouds (ISGC) 2016

NASA Astrophysics Data System (ADS)

The International Symposium on Grids and Clouds (ISGC) 2016 will be held at Academia Sinica in Taipei, Taiwan from 13-18 March 2016, with co-located events and workshops. The conference is hosted by the Academia Sinica Grid Computing Centre (ASGC). The theme of ISGC 2016 focuses on“Ubiquitous e-infrastructures and Applications”. Contemporary research is impossible without a strong IT component - researchers rely on the existence of stable and widely available e-infrastructures and their higher level functions and properties. As a result of these expectations, e-Infrastructures are becoming ubiquitous, providing an environment that supports large scale collaborations that deal with global challenges as well as smaller and temporal research communities focusing on particular scientific problems. To support those diversified communities and their needs, the e-Infrastructures themselves are becoming more layered and multifaceted, supporting larger groups of applications. Following the call for the last year conference, ISGC 2016 continues its aim to bring together users and application developers with those responsible for the development and operation of multi-purpose ubiquitous e-Infrastructures. Topics of discussion include Physics (including HEP) and Engineering Applications, Biomedicine & Life Sciences Applications, Earth & Environmental Sciences & Biodiversity Applications, Humanities, Arts, and Social Sciences (HASS) Applications, Virtual Research Environment (including Middleware, tools, services, workflow, etc.), Data Management, Big Data, Networking & Security, Infrastructure & Operations, Infrastructure Clouds and Virtualisation, Interoperability, Business Models & Sustainability, Highly Distributed Computing Systems, and High Performance & Technical Computing (HPTC), etc.

Defense of Cyber Infrastructures Against Cyber-Physical Attacks Using Game-Theoretic Models.

PubMed

Rao, Nageswara S V; Poole, Stephen W; Ma, Chris Y T; He, Fei; Zhuang, Jun; Yau, David K Y

2016-04-01

The operation of cyber infrastructures relies on both cyber and physical components, which are subject to incidental and intentional degradations of different kinds. Within the context of network and computing infrastructures, we study the strategic interactions between an attacker and a defender using game-theoretic models that take into account both cyber and physical components. The attacker and defender optimize their individual utilities, expressed as sums of cost and system terms. First, we consider a Boolean attack-defense model, wherein the cyber and physical subinfrastructures may be attacked and reinforced as individual units. Second, we consider a component attack-defense model wherein their components may be attacked and defended, and the infrastructure requires minimum numbers of both to function. We show that the Nash equilibrium under uniform costs in both cases is computable in polynomial time, and it provides high-level deterministic conditions for the infrastructure survival. When probabilities of successful attack and defense, and of incidental failures, are incorporated into the models, the results favor the attacker but otherwise remain qualitatively similar. This approach has been motivated and validated by our experiences with UltraScience Net infrastructure, which was built to support high-performance network experiments. The analytical results, however, are more general, and we apply them to simplified models of cloud and high-performance computing infrastructures. © 2015 Society for Risk Analysis.

WISDOM-II: screening against multiple targets implicated in malaria using computational grid infrastructures.

PubMed

Kasam, Vinod; Salzemann, Jean; Botha, Marli; Dacosta, Ana; Degliesposti, Gianluca; Isea, Raul; Kim, Doman; Maass, Astrid; Kenyon, Colin; Rastelli, Giulio; Hofmann-Apitius, Martin; Breton, Vincent

2009-05-01

Despite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the Plasmodium parasite, some are promising targets to carry out rational drug discovery. Recent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR), and on a new promising one, glutathione-S-transferase. In silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate in silico docking and in information technology to design and operate large scale grid infrastructures. On the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, In vitro results are underway for all the targets against which screening is performed. The current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software on computational grids in finding hits against three different targets (PfGST, PfDHFR, PvDHFR (wild type and mutant forms) implicated in malaria. Grid-enabled virtual screening approach is proposed to produce focus compound libraries for other biological targets relevant to fight the infectious diseases of the developing world.

Computer-aided drug discovery research at a global contract research organization

NASA Astrophysics Data System (ADS)

Kitchen, Douglas B.

2017-03-01

Computer-aided drug discovery started at Albany Molecular Research, Inc in 1997. Over nearly 20 years the role of cheminformatics and computational chemistry has grown throughout the pharmaceutical industry and at AMRI. This paper will describe the infrastructure and roles of CADD throughout drug discovery and some of the lessons learned regarding the success of several methods. Various contributions provided by computational chemistry and cheminformatics in chemical library design, hit triage, hit-to-lead and lead optimization are discussed. Some frequently used computational chemistry techniques are described. The ways in which they may contribute to discovery projects are presented based on a few examples from recent publications.

Computer-aided drug discovery research at a global contract research organization.

PubMed

Kitchen, Douglas B

2017-03-01

Computer-aided drug discovery started at Albany Molecular Research, Inc in 1997. Over nearly 20 years the role of cheminformatics and computational chemistry has grown throughout the pharmaceutical industry and at AMRI. This paper will describe the infrastructure and roles of CADD throughout drug discovery and some of the lessons learned regarding the success of several methods. Various contributions provided by computational chemistry and cheminformatics in chemical library design, hit triage, hit-to-lead and lead optimization are discussed. Some frequently used computational chemistry techniques are described. The ways in which they may contribute to discovery projects are presented based on a few examples from recent publications.

An infrastructure with a unified control plane to integrate IP into optical metro networks to provide flexible and intelligent bandwidth on demand for cloud computing

NASA Astrophysics Data System (ADS)

Yang, Wei; Hall, Trevor

2012-12-01

The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users and the nature of the Internet traffic will undertake a fundamental transformation. Consequently, the current Internet will no longer suffice for serving cloud traffic in metro areas. This work proposes an infrastructure with a unified control plane that integrates simple packet aggregation technology with optical express through the interoperation between IP routers and electrical traffic controllers in optical metro networks. The proposed infrastructure provides flexible, intelligent, and eco-friendly bandwidth on demand for cloud computing in metro areas.

Towards Portable Large-Scale Image Processing with High-Performance Computing.

PubMed

Huo, Yuankai; Blaber, Justin; Damon, Stephen M; Boyd, Brian D; Bao, Shunxing; Parvathaneni, Prasanna; Noguera, Camilo Bermudez; Chaganti, Shikha; Nath, Vishwesh; Greer, Jasmine M; Lyu, Ilwoo; French, William R; Newton, Allen T; Rogers, Baxter P; Landman, Bennett A

2018-05-03

High-throughput, large-scale medical image computing demands tight integration of high-performance computing (HPC) infrastructure for data storage, job distribution, and image processing. The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has constructed a large-scale image storage and processing infrastructure that is composed of (1) a large-scale image database using the eXtensible Neuroimaging Archive Toolkit (XNAT), (2) a content-aware job scheduling platform using the Distributed Automation for XNAT pipeline automation tool (DAX), and (3) a wide variety of encapsulated image processing pipelines called "spiders." The VUIIS CCI medical image data storage and processing infrastructure have housed and processed nearly half-million medical image volumes with Vanderbilt Advanced Computing Center for Research and Education (ACCRE), which is the HPC facility at the Vanderbilt University. The initial deployment was natively deployed (i.e., direct installations on a bare-metal server) within the ACCRE hardware and software environments, which lead to issues of portability and sustainability. First, it could be laborious to deploy the entire VUIIS CCI medical image data storage and processing infrastructure to another HPC center with varying hardware infrastructure, library availability, and software permission policies. Second, the spiders were not developed in an isolated manner, which has led to software dependency issues during system upgrades or remote software installation. To address such issues, herein, we describe recent innovations using containerization techniques with XNAT/DAX which are used to isolate the VUIIS CCI medical image data storage and processing infrastructure from the underlying hardware and software environments. The newly presented XNAT/DAX solution has the following new features: (1) multi-level portability from system level to the application level, (2) flexible and dynamic software development and expansion, and (3) scalable spider deployment compatible with HPC clusters and local workstations.

cOSPREY: A Cloud-Based Distributed Algorithm for Large-Scale Computational Protein Design

PubMed Central

Pan, Yuchao; Dong, Yuxi; Zhou, Jingtian; Hallen, Mark; Donald, Bruce R.; Xu, Wei

2016-01-01

Abstract Finding the global minimum energy conformation (GMEC) of a huge combinatorial search space is the key challenge in computational protein design (CPD) problems. Traditional algorithms lack a scalable and efficient distributed design scheme, preventing researchers from taking full advantage of current cloud infrastructures. We design cloud OSPREY (cOSPREY), an extension to a widely used protein design software OSPREY, to allow the original design framework to scale to the commercial cloud infrastructures. We propose several novel designs to integrate both algorithm and system optimizations, such as GMEC-specific pruning, state search partitioning, asynchronous algorithm state sharing, and fault tolerance. We evaluate cOSPREY on three different cloud platforms using different technologies and show that it can solve a number of large-scale protein design problems that have not been possible with previous approaches. PMID:27154509

Design of an air traffic computer simulation system to support investigation of civil tiltrotor aircraft operations

NASA Technical Reports Server (NTRS)

Rogers, Ralph V.

1992-01-01

This research project addresses the need to provide an efficient and safe mechanism to investigate the effects and requirements of the tiltrotor aircraft's commercial operations on air transportation infrastructures, particularly air traffic control. The mechanism of choice is computer simulation. Unfortunately, the fundamental paradigms of the current air traffic control simulation models do not directly support the broad range of operational options and environments necessary to study tiltrotor operations. Modification of current air traffic simulation models to meet these requirements does not appear viable given the range and complexity of issues needing resolution. As a result, the investigation of systemic, infrastructure issues surrounding the effects of tiltrotor commercial operations requires new approaches to simulation modeling. These models should be based on perspectives and ideas closer to those associated with tiltrotor air traffic operations.

Cloud Computing Boosts Business Intelligence of Telecommunication Industry

NASA Astrophysics Data System (ADS)

Xu, Meng; Gao, Dan; Deng, Chao; Luo, Zhiguo; Sun, Shaoling

Business Intelligence becomes an attracting topic in today's data intensive applications, especially in telecommunication industry. Meanwhile, Cloud Computing providing IT supporting Infrastructure with excellent scalability, large scale storage, and high performance becomes an effective way to implement parallel data processing and data mining algorithms. BC-PDM (Big Cloud based Parallel Data Miner) is a new MapReduce based parallel data mining platform developed by CMRI (China Mobile Research Institute) to fit the urgent requirements of business intelligence in telecommunication industry. In this paper, the architecture, functionality and performance of BC-PDM are presented, together with the experimental evaluation and case studies of its applications. The evaluation result demonstrates both the usability and the cost-effectiveness of Cloud Computing based Business Intelligence system in applications of telecommunication industry.

Galaxy CloudMan: delivering cloud compute clusters

PubMed Central

2010-01-01

Background Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is “cloud computing”, which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate “as is” use by experimental biologists. Results We present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon’s EC2 cloud infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs. Conclusions The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge. PMID:21210983

A primer on precision medicine informatics.

PubMed

Sboner, Andrea; Elemento, Olivier

2016-01-01

In this review, we describe key components of a computational infrastructure for a precision medicine program that is based on clinical-grade genomic sequencing. Specific aspects covered in this review include software components and hardware infrastructure, reporting, integration into Electronic Health Records for routine clinical use and regulatory aspects. We emphasize informatics components related to reproducibility and reliability in genomic testing, regulatory compliance, traceability and documentation of processes, integration into clinical workflows, privacy requirements, prioritization and interpretation of results to report based on clinical needs, rapidly evolving knowledge base of genomic alterations and clinical treatments and return of results in a timely and predictable fashion. We also seek to differentiate between the use of precision medicine in germline and cancer. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Information security system based on virtual-optics imaging methodology and public key infrastructure

NASA Astrophysics Data System (ADS)

Peng, Xiang; Zhang, Peng; Cai, Lilong

In this paper, we present a virtual-optical based information security system model with the aid of public-key-infrastructure (PKI) techniques. The proposed model employs a hybrid architecture in which our previously published encryption algorithm based on virtual-optics imaging methodology (VOIM) can be used to encipher and decipher data while an asymmetric algorithm, for example RSA, is applied for enciphering and deciphering the session key(s). For an asymmetric system, given an encryption key, it is computationally infeasible to determine the decryption key and vice versa. The whole information security model is run under the framework of PKI, which is on basis of public-key cryptography and digital signatures. This PKI-based VOIM security approach has additional features like confidentiality, authentication, and integrity for the purpose of data encryption under the environment of network.

Towards a sustainable framework for computer based health information systems (CHIS) for least developed countries (LDCs).

PubMed

Gordon, Abekah Nkrumah; Hinson, Robert Ebo

2007-01-01

The purpose of this paper is to argue for a theoretical framework by which development of computer based health information systems (CHIS) can be made sustainable. Health Management and promotion thrive on well-articulated CHIS. There are high levels of risk associated with the development of CHIS in the context of least developed countries (LDC), thereby making them unsustainable. This paper is based largely on literature survey on health promotion and information systems. The main factors accounting for the sustainability problem in less developed countries include poor infrastructure, inappropriate donor policies and strategies, poor infrastructure and inadequate human resource capacity. To counter these challenges and to ensure that CHIS deployment in LDCs is sustainable, it is proposed that the activities involved in the implementation of these systems be incorporated into organizational routines. This will ensure and secure the needed resources as well as the relevant support from all stakeholders of the system; on a continuous basis. This paper sets out to look at the issue of CHIS sustainability in LDCs, theoretically explains the factors that account for the sustainability problem and develops a conceptual model based on theoretical literature and existing empirical findings.

Sparse maps—A systematic infrastructure for reduced-scaling electronic structure methods. I. An efficient and simple linear scaling local MP2 method that uses an intermediate basis of pair natural orbitals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pinski, Peter; Riplinger, Christoph; Neese, Frank, E-mail: evaleev@vt.edu, E-mail: frank.neese@cec.mpg.de

2015-07-21

In this work, a systematic infrastructure is described that formalizes concepts implicit in previous work and greatly simplifies computer implementation of reduced-scaling electronic structure methods. The key concept is sparse representation of tensors using chains of sparse maps between two index sets. Sparse map representation can be viewed as a generalization of compressed sparse row, a common representation of a sparse matrix, to tensor data. By combining few elementary operations on sparse maps (inversion, chaining, intersection, etc.), complex algorithms can be developed, illustrated here by a linear-scaling transformation of three-center Coulomb integrals based on our compact code library that implementsmore » sparse maps and operations on them. The sparsity of the three-center integrals arises from spatial locality of the basis functions and domain density fitting approximation. A novel feature of our approach is the use of differential overlap integrals computed in linear-scaling fashion for screening products of basis functions. Finally, a robust linear scaling domain based local pair natural orbital second-order Möller-Plesset (DLPNO-MP2) method is described based on the sparse map infrastructure that only depends on a minimal number of cutoff parameters that can be systematically tightened to approach 100% of the canonical MP2 correlation energy. With default truncation thresholds, DLPNO-MP2 recovers more than 99.9% of the canonical resolution of the identity MP2 (RI-MP2) energy while still showing a very early crossover with respect to the computational effort. Based on extensive benchmark calculations, relative energies are reproduced with an error of typically <0.2 kcal/mol. The efficiency of the local MP2 (LMP2) method can be drastically improved by carrying out the LMP2 iterations in a basis of pair natural orbitals. While the present work focuses on local electron correlation, it is of much broader applicability to computation with sparse tensors in quantum chemistry and beyond.« less

Sparse maps—A systematic infrastructure for reduced-scaling electronic structure methods. I. An efficient and simple linear scaling local MP2 method that uses an intermediate basis of pair natural orbitals.

PubMed

Pinski, Peter; Riplinger, Christoph; Valeev, Edward F; Neese, Frank

2015-07-21

In this work, a systematic infrastructure is described that formalizes concepts implicit in previous work and greatly simplifies computer implementation of reduced-scaling electronic structure methods. The key concept is sparse representation of tensors using chains of sparse maps between two index sets. Sparse map representation can be viewed as a generalization of compressed sparse row, a common representation of a sparse matrix, to tensor data. By combining few elementary operations on sparse maps (inversion, chaining, intersection, etc.), complex algorithms can be developed, illustrated here by a linear-scaling transformation of three-center Coulomb integrals based on our compact code library that implements sparse maps and operations on them. The sparsity of the three-center integrals arises from spatial locality of the basis functions and domain density fitting approximation. A novel feature of our approach is the use of differential overlap integrals computed in linear-scaling fashion for screening products of basis functions. Finally, a robust linear scaling domain based local pair natural orbital second-order Möller-Plesset (DLPNO-MP2) method is described based on the sparse map infrastructure that only depends on a minimal number of cutoff parameters that can be systematically tightened to approach 100% of the canonical MP2 correlation energy. With default truncation thresholds, DLPNO-MP2 recovers more than 99.9% of the canonical resolution of the identity MP2 (RI-MP2) energy while still showing a very early crossover with respect to the computational effort. Based on extensive benchmark calculations, relative energies are reproduced with an error of typically <0.2 kcal/mol. The efficiency of the local MP2 (LMP2) method can be drastically improved by carrying out the LMP2 iterations in a basis of pair natural orbitals. While the present work focuses on local electron correlation, it is of much broader applicability to computation with sparse tensors in quantum chemistry and beyond.

Computational analysis of water entry of a circular section at constant velocity based on Reynold's averaged Navier-Stokes method

NASA Astrophysics Data System (ADS)

Uddin, M. Maruf; Fuad, Muzaddid-E.-Zaman; Rahaman, Md. Mashiur; Islam, M. Rabiul

2017-12-01

With the rapid decrease in the cost of computational infrastructure with more efficient algorithm for solving non-linear problems, Reynold's averaged Navier-Stokes (RaNS) based Computational Fluid Dynamics (CFD) has been used widely now-a-days. As a preliminary evaluation tool, CFD is used to calculate the hydrodynamic loads on offshore installations, ships, and other structures in the ocean at initial design stages. Traditionally, wedges have been studied more than circular cylinders because cylinder section has zero deadrise angle at the instant of water impact, which increases with increase of submergence. In Present study, RaNS based commercial code ANSYS Fluent is used to simulate the water entry of a circular section at constant velocity. It is seen that present computational results were compared with experiment and other numerical method.

The Quality in Quantity - Enhancing Text-based Research -

NASA Astrophysics Data System (ADS)

Harms, Patrick; Smith, Kathleen; Aschenbrenner, Andreas; Pempe, Wolfgang; Hedges, Mark; Roberts, Angus; Ács, Bernie; Blanke, Tobias

Computers are becoming more and more a tool for researchers in the humanities. There are already several projects which aim to implement environments and infrastructures to support research. However, they either address qualitative or quantitative research methods, and there has been less work considering support for both methodologies in one environment. This paper analyzes the difference between qualitative and quantitative research in the humanities, outlines some examples and respective projects, and states why the support for both methodologies needs to be combined and how it might be used to form an integrated research infrastructure for the humanities.

Blast2GO goes grid: developing a grid-enabled prototype for functional genomics analysis.

PubMed

Aparicio, G; Götz, S; Conesa, A; Segrelles, D; Blanquer, I; García, J M; Hernandez, V; Robles, M; Talon, M

2006-01-01

The vast amount in complexity of data generated in Genomic Research implies that new dedicated and powerful computational tools need to be developed to meet their analysis requirements. Blast2GO (B2G) is a bioinformatics tool for Gene Ontology-based DNA or protein sequence annotation and function-based data mining. The application has been developed with the aim of affering an easy-to-use tool for functional genomics research. Typical B2G users are middle size genomics labs carrying out sequencing, ETS and microarray projects, handling datasets up to several thousand sequences. In the current version of B2G. The power and analytical potential of both annotation and function data-mining is somehow restricted to the computational power behind each particular installation. In order to be able to offer the possibility of an enhanced computational capacity within this bioinformatics application, a Grid component is being developed. A prototype has been conceived for the particular problem of speeding up the Blast searches to obtain fast results for large datasets. Many efforts have been done in the literature concerning the speeding up of Blast searches, but few of them deal with the use of large heterogeneous production Grid Infrastructures. These are the infrastructures that could reach the largest number of resources and the best load balancing for data access. The Grid Service under development will analyse requests based on the number of sequences, splitting them accordingly to the available resources. Lower-level computation will be performed through MPIBLAST. The software architecture is based on the WSRF standard.

UNH Data Cooperative: A Cyber Infrastructure for Earth System Studies

NASA Astrophysics Data System (ADS)

Braswell, B. H.; Fekete, B. M.; Prusevich, A.; Gliden, S.; Magill, A.; Vorosmarty, C. J.

2007-12-01

Earth system scientists and managers have a continuously growing demand for a wide array of earth observations derived from various data sources including (a) modern satellite retrievals, (b) "in-situ" records, (c) various simulation outputs, and (d) assimilated data products combining model results with observational records. The sheer quantity of data, and formatting inconsistencies make it difficult for users to take full advantage of this important information resource. Thus the system could benefit from a thorough retooling of our current data processing procedures and infrastructure. Emerging technologies, like OPeNDAP and OGC map services, open standard data formats (NetCDF, HDF) data cataloging systems (NASA-Echo, Global Change Master Directory, etc.) are providing the basis for a new approach in data management and processing, where web- services are increasingly designed to serve computer-to-computer communications without human interactions and complex analysis can be carried out over distributed computer resources interconnected via cyber infrastructure. The UNH Earth System Data Collaborative is designed to utilize the aforementioned emerging web technologies to offer new means of access to earth system data. While the UNH Data Collaborative serves a wide array of data ranging from weather station data (Climate Portal) to ocean buoy records and ship tracks (Portsmouth Harbor Initiative) to land cover characteristics, etc. the underlaying data architecture shares common components for data mining and data dissemination via web-services. Perhaps the most unique element of the UNH Data Cooperative's IT infrastructure is its prototype modeling environment for regional ecosystem surveillance over the Northeast corridor, which allows the integration of complex earth system model components with the Cooperative's data services. While the complexity of the IT infrastructure to perform complex computations is continuously increasing, scientists are often forced to spend considerable amount of time to solve basic data management and preprocessing tasks and deal with low level computational design problems like parallelization of model codes. Our modeling infrastructure is designed to take care the bulk of the common tasks found in complex earth system models like I/O handling, computational domain and time management, parallel execution of the modeling tasks, etc. The modeling infrastructure allows scientists to focus on the numerical implementation of the physical processes on a single computational objects(typically grid cells) while the framework takes care of the preprocessing of input data, establishing of the data exchange between computation objects and the execution of the science code. In our presentation, we will discuss the key concepts of our modeling infrastructure. We will demonstrate integration of our modeling framework with data services offered by the UNH Earth System Data Collaborative via web interfaces. We will layout the road map to turn our prototype modeling environment into a truly community framework for wide range of earth system scientists and environmental managers.

Key Lessons in Building "Data Commons": The Open Science Data Cloud Ecosystem

NASA Astrophysics Data System (ADS)

Patterson, M.; Grossman, R.; Heath, A.; Murphy, M.; Wells, W.

2015-12-01

Cloud computing technology has created a shift around data and data analysis by allowing researchers to push computation to data as opposed to having to pull data to an individual researcher's computer. Subsequently, cloud-based resources can provide unique opportunities to capture computing environments used both to access raw data in its original form and also to create analysis products which may be the source of data for tables and figures presented in research publications. Since 2008, the Open Cloud Consortium (OCC) has operated the Open Science Data Cloud (OSDC), which provides scientific researchers with computational resources for storing, sharing, and analyzing large (terabyte and petabyte-scale) scientific datasets. OSDC has provided compute and storage services to over 750 researchers in a wide variety of data intensive disciplines. Recently, internal users have logged about 2 million core hours each month. The OSDC also serves the research community by colocating these resources with access to nearly a petabyte of public scientific datasets in a variety of fields also accessible for download externally by the public. In our experience operating these resources, researchers are well served by "data commons," meaning cyberinfrastructure that colocates data archives, computing, and storage infrastructure and supports essential tools and services for working with scientific data. In addition to the OSDC public data commons, the OCC operates a data commons in collaboration with NASA and is developing a data commons for NOAA datasets. As cloud-based infrastructures for distributing and computing over data become more pervasive, we ask, "What does it mean to publish data in a data commons?" Here we present the OSDC perspective and discuss several services that are key in architecting data commons, including digital identifier services.

Cloud-Based Perception and Control of Sensor Nets and Robot Swarms

DTIC Science & Technology

2016-04-01

distributed stream processing framework provides the necessary API and infrastructure to develop and execute such applications in a cluster of computation...streaming DDDAS applications based on challenges they present to the backend Cloud control system. Figure 2 Parallel SLAM Application 3 1) Set of...the art deep learning- based object detectors can recognize among hundreds of object classes and this capability would be very useful for mobile

Multi-Dimensional Optimization for Cloud Based Multi-Tier Applications

ERIC Educational Resources Information Center

Jung, Gueyoung

2010-01-01

Emerging trends toward cloud computing and virtualization have been opening new avenues to meet enormous demands of space, resource utilization, and energy efficiency in modern data centers. By being allowed to host many multi-tier applications in consolidated environments, cloud infrastructure providers enable resources to be shared among these…

Dynamic VM Provisioning for TORQUE in a Cloud Environment

NASA Astrophysics Data System (ADS)

Zhang, S.; Boland, L.; Coddington, P.; Sevior, M.

2014-06-01

Cloud computing, also known as an Infrastructure-as-a-Service (IaaS), is attracting more interest from the commercial and educational sectors as a way to provide cost-effective computational infrastructure. It is an ideal platform for researchers who must share common resources but need to be able to scale up to massive computational requirements for specific periods of time. This paper presents the tools and techniques developed to allow the open source TORQUE distributed resource manager and Maui cluster scheduler to dynamically integrate OpenStack cloud resources into existing high throughput computing clusters.

Increasing the impact of medical image computing using community-based open-access hackathons: The NA-MIC and 3D Slicer experience.

PubMed

Kapur, Tina; Pieper, Steve; Fedorov, Andriy; Fillion-Robin, J-C; Halle, Michael; O'Donnell, Lauren; Lasso, Andras; Ungi, Tamas; Pinter, Csaba; Finet, Julien; Pujol, Sonia; Jagadeesan, Jayender; Tokuda, Junichi; Norton, Isaiah; Estepar, Raul San Jose; Gering, David; Aerts, Hugo J W L; Jakab, Marianna; Hata, Nobuhiko; Ibanez, Luiz; Blezek, Daniel; Miller, Jim; Aylward, Stephen; Grimson, W Eric L; Fichtinger, Gabor; Wells, William M; Lorensen, William E; Schroeder, Will; Kikinis, Ron

2016-10-01

The National Alliance for Medical Image Computing (NA-MIC) was launched in 2004 with the goal of investigating and developing an open source software infrastructure for the extraction of information and knowledge from medical images using computational methods. Several leading research and engineering groups participated in this effort that was funded by the US National Institutes of Health through a variety of infrastructure grants. This effort transformed 3D Slicer from an internal, Boston-based, academic research software application into a professionally maintained, robust, open source platform with an international leadership and developer and user communities. Critical improvements to the widely used underlying open source libraries and tools-VTK, ITK, CMake, CDash, DCMTK-were an additional consequence of this effort. This project has contributed to close to a thousand peer-reviewed publications and a growing portfolio of US and international funded efforts expanding the use of these tools in new medical computing applications every year. In this editorial, we discuss what we believe are gaps in the way medical image computing is pursued today; how a well-executed research platform can enable discovery, innovation and reproducible science ("Open Science"); and how our quest to build such a software platform has evolved into a productive and rewarding social engineering exercise in building an open-access community with a shared vision. Copyright © 2016 Elsevier B.V. All rights reserved.

Technography and Design-Actuality Gap-Analysis of Internet Computer Technologies-Assisted Education: Western Expectations and Global Education

ERIC Educational Resources Information Center

Greenhalgh-Spencer, Heather; Jerbi, Moja

2017-01-01

In this paper, we provide a design-actuality gap-analysis of the internet infrastructure that exists in developing nations and nations in the global South with the deployed internet computer technologies (ICT)-assisted programs that are designed to use internet infrastructure to provide educational opportunities. Programs that specifically…

Closing the Gap: Cybersecurity for U.S. Forces and Commands

DTIC Science & Technology

2017-03-30

Dickson, Ph.D. Professor of Military Studies , JAWS Thesis Advisor Kevin Therrien, Col, USAF Committee Member Stephen Rogers, Colonel, USA Director...infrastructures, and includes the Internet, telecommunications networks, computer systems, and embedded processors and controllers in critical industries.”5...of information technology infrastructures, including the Internet, telecommunications networks, computer systems, and embedded processors and

Intelligent systems technology infrastructure for integrated systems

NASA Technical Reports Server (NTRS)

Lum, Henry

1991-01-01

A system infrastructure must be properly designed and integrated from the conceptual development phase to accommodate evolutionary intelligent technologies. Several technology development activities were identified that may have application to rendezvous and capture systems. Optical correlators in conjunction with fuzzy logic control might be used for the identification, tracking, and capture of either cooperative or non-cooperative targets without the intensive computational requirements associated with vision processing. A hybrid digital/analog system was developed and tested with a robotic arm. An aircraft refueling application demonstration is planned within two years. Initially this demonstration will be ground based with a follow-on air based demonstration. System dependability measurement and modeling techniques are being developed for fault management applications. This involves usage of incremental solution/evaluation techniques and modularized systems to facilitate reuse and to take advantage of natural partitions in system models. Though not yet commercially available and currently subject to accuracy limitations, technology is being developed to perform optical matrix operations to enhance computational speed. Optical terrain recognition using camera image sequencing processed with optical correlators is being developed to determine position and velocity in support of lander guidance. The system is planned for testing in conjunction with Dryden Flight Research Facility. Advanced architecture technology is defining open architecture design constraints, test bed concepts (processors, multiple hardware/software and multi-dimensional user support, knowledge/tool sharing infrastructure), and software engineering interface issues.

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid

PubMed Central

Li, Yuancheng; Jing, Sitong

2018-01-01

Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can’t satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy. PMID:29485990

The National Information Infrastructure: Agenda for Action.

ERIC Educational Resources Information Center

Department of Commerce, Washington, DC. Information Infrastructure Task Force.

The National Information Infrastructure (NII) is planned as a web of communications networks, computers, databases, and consumer electronics that will put vast amounts of information at the users' fingertips. Private sector firms are beginning to develop this infrastructure, but essential roles remain for the Federal Government. The National…

The virtual machine (VM) scaler: an infrastructure manager supporting environmental modeling on IaaS clouds

USDA-ARS?s Scientific Manuscript database

Infrastructure-as-a-service (IaaS) clouds provide a new medium for deployment of environmental modeling applications. Harnessing advancements in virtualization, IaaS clouds can provide dynamic scalable infrastructure to better support scientific modeling computational demands. Providing scientific m...

The Computing and Data Grid Approach: Infrastructure for Distributed Science Applications

NASA Technical Reports Server (NTRS)

Johnston, William E.

2002-01-01

With the advent of Grids - infrastructure for using and managing widely distributed computing and data resources in the science environment - there is now an opportunity to provide a standard, large-scale, computing, data, instrument, and collaboration environment for science that spans many different projects and provides the required infrastructure and services in a relatively uniform and supportable way. Grid technology has evolved over the past several years to provide the services and infrastructure needed for building 'virtual' systems and organizations. We argue that Grid technology provides an excellent basis for the creation of the integrated environments that can combine the resources needed to support the large- scale science projects located at multiple laboratories and universities. We present some science case studies that indicate that a paradigm shift in the process of science will come about as a result of Grids providing transparent and secure access to advanced and integrated information and technologies infrastructure: powerful computing systems, large-scale data archives, scientific instruments, and collaboration tools. These changes will be in the form of services that can be integrated with the user's work environment, and that enable uniform and highly capable access to these computers, data, and instruments, regardless of the location or exact nature of these resources. These services will integrate transient-use resources like computing systems, scientific instruments, and data caches (e.g., as they are needed to perform a simulation or analyze data from a single experiment); persistent-use resources. such as databases, data catalogues, and archives, and; collaborators, whose involvement will continue for the lifetime of a project or longer. While we largely address large-scale science in this paper, Grids, particularly when combined with Web Services, will address a broad spectrum of science scenarios. both large and small scale.

Geospatial Data as a Service: Towards planetary scale real-time analytics

NASA Astrophysics Data System (ADS)

Evans, B. J. K.; Larraondo, P. R.; Antony, J.; Richards, C. J.

2017-12-01

The rapid growth of earth systems, environmental and geophysical datasets poses a challenge to both end-users and infrastructure providers. For infrastructure and data providers, tasks like managing, indexing and storing large collections of geospatial data needs to take into consideration the various use cases by which consumers will want to access and use the data. Considerable investment has been made by the Earth Science community to produce suitable real-time analytics platforms for geospatial data. There are currently different interfaces that have been defined to provide data services. Unfortunately, there is considerable difference on the standards, protocols or data models which have been designed to target specific communities or working groups. The Australian National University's National Computational Infrastructure (NCI) is used for a wide range of activities in the geospatial community. Earth observations, climate and weather forecasting are examples of these communities which generate large amounts of geospatial data. The NCI has been carrying out significant effort to develop a data and services model that enables the cross-disciplinary use of data. Recent developments in cloud and distributed computing provide a publicly accessible platform where new infrastructures can be built. One of the key components these technologies offer is the possibility of having "limitless" compute power next to where the data is stored. This model is rapidly transforming data delivery from centralised monolithic services towards ubiquitous distributed services that scale up and down adapting to fluctuations in the demand. NCI has developed GSKY, a scalable, distributed server which presents a new approach for geospatial data discovery and delivery based on OGC standards. We will present the architecture and motivating use-cases that drove GSKY's collaborative design, development and production deployment. We show our approach offers the community valuable exploratory analysis capabilities, for dealing with petabyte-scale geospatial data collections.

Federation in genomics pipelines: techniques and challenges.

PubMed

Chaterji, Somali; Koo, Jinkyu; Li, Ninghui; Meyer, Folker; Grama, Ananth; Bagchi, Saurabh

2017-08-29

Federation is a popular concept in building distributed cyberinfrastructures, whereby computational resources are provided by multiple organizations through a unified portal, decreasing the complexity of moving data back and forth among multiple organizations. Federation has been used in bioinformatics only to a limited extent, namely, federation of datastores, e.g. SBGrid Consortium for structural biology and Gene Expression Omnibus (GEO) for functional genomics. Here, we posit that it is important to federate both computational resources (CPU, GPU, FPGA, etc.) and datastores to support popular bioinformatics portals, with fast-increasing data volumes and increasing processing requirements. A prime example, and one that we discuss here, is in genomics and metagenomics. It is critical that the processing of the data be done without having to transport the data across large network distances. We exemplify our design and development through our experience with metagenomics-RAST (MG-RAST), the most popular metagenomics analysis pipeline. Currently, it is hosted completely at Argonne National Laboratory. However, through a recently started collaborative National Institutes of Health project, we are taking steps toward federating this infrastructure. Being a widely used resource, we have to move toward federation without disrupting 50 K annual users. In this article, we describe the computational tools that will be useful for federating a bioinformatics infrastructure and the open research challenges that we see in federating such infrastructures. It is hoped that our manuscript can serve to spur greater federation of bioinformatics infrastructures by showing the steps involved, and thus, allow them to scale to support larger user bases. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The SCEC Community Modeling Environment(SCEC/CME): A Collaboratory for Seismic Hazard Analysis

NASA Astrophysics Data System (ADS)

Maechling, P. J.; Jordan, T. H.; Minster, J. B.; Moore, R.; Kesselman, C.

2005-12-01

The SCEC Community Modeling Environment (SCEC/CME) Project is an NSF-supported Geosciences/IT partnership that is actively developing an advanced information infrastructure for system-level earthquake science in Southern California. This partnership includes SCEC, USC's Information Sciences Institute (ISI), the San Diego Supercomputer Center (SDSC), the Incorporated Institutions for Research in Seismology (IRIS), and the U.S. Geological Survey. The goal of the SCEC/CME is to develop seismological applications and information technology (IT) infrastructure to support the development of Seismic Hazard Analysis (SHA) programs and other geophysical simulations. The SHA application programs developed on the Project include a Probabilistic Seismic Hazard Analysis system called OpenSHA. OpenSHA computational elements that are currently available include a collection of attenuation relationships, and several Earthquake Rupture Forecasts (ERFs). Geophysicists in the collaboration have also developed Anelastic Wave Models (AWMs) using both finite-difference and finite-element approaches. Earthquake simulations using these codes have been run for a variety of earthquake sources. Rupture Dynamic Model (RDM) codes have also been developed that simulate friction-based fault slip. The SCEC/CME collaboration has also developed IT software and hardware infrastructure to support the development, execution, and analysis of these SHA programs. To support computationally expensive simulations, we have constructed a grid-based scientific workflow system. Using the SCEC grid, project collaborators can submit computations from the SCEC/CME servers to High Performance Computers at USC and TeraGrid High Performance Computing Centers. Data generated and archived by the SCEC/CME is stored in a digital library system, the Storage Resource Broker (SRB). This system provides a robust and secure system for maintaining the association between the data seta and their metadata. To provide an easy-to-use system for constructing SHA computations, a browser-based workflow assembly web portal has been developed. Users can compose complex SHA calculations, specifying SCEC/CME data sets as inputs to calculations, and calling SCEC/CME computational programs to process the data and the output. Knowledge-based software tools have been implemented that utilize ontological descriptions of SHA software and data can validate workflows created with this pathway assembly tool. Data visualization software developed by the collaboration supports analysis and validation of data sets. Several programs have been developed to visualize SCEC/CME data including GMT-based map making software for PSHA codes, 4D wavefield propagation visualization software based on OpenGL, and 3D Geowall-based visualization of earthquakes, faults, and seismic wave propagation. The SCEC/CME Project also helps to sponsor the SCEC UseIT Intern program. The UseIT Intern Program provides research opportunities in both Geosciences and Information Technology to undergraduate students in a variety of fields. The UseIT group has developed a 3D data visualization tool, called SCEC-VDO, as a part of this undergraduate research program.

Hydrodynamic modeling of urban flooding taking into account detailed data about city infrastructure

NASA Astrophysics Data System (ADS)

Belikov, Vitaly; Norin, Sergey; Aleksyuk, Andrey; Krylenko, Inna; Borisova, Natalya; Rumyantsev, Alexey

2017-04-01

Flood waves moving across urban areas have specific features. Thus, the linear objects of infrastructure (such as embankments, roads, dams) can change the direction of flow or block the water movement. On the contrary, paved avenues and wide streets in the cities contribute to the concentration of flood waters. Buildings create an additional resistance to the movement of water, which depends on the urban density and the type of constructions; this effect cannot be completely described by Manning's resistance law. In addition, part of the earth surface, occupied by buildings, is excluded from the flooded area, which results in a substantial (relative to undeveloped areas) increase of the depth of flooding, especially for unsteady flow conditions. An approach to numerical simulation of urban areas flooding that consists in direct allocating of all buildings and structures on the computational grid are proposed. This can be done in almost full automatic way with usage of modern software. Real geometry of all objects of infrastructure can be taken into account on the base of highly detailed digital maps and satellite images. The calculations based on two-dimensional Saint-Venant equations on irregular adaptive computational meshes, which can contain millions of cells and take into account tens of thousands of buildings and other objects of infrastructure. Flood maps, received as result of modeling, are the basis for the damage and risk assessment for urban areas. The main advantage of the developed method is high-precision calculations, realistic modeling results and appropriate graphical display of the flood dynamics and dam-break wave's propagation on urban areas. Verification of this method has been done on the experimental data and real events simulations, including catastrophic flooding of the Krymsk city in 2012 year.

Tele-Medicine Applications of an ISDN-Based Tele-Working Platform

DTIC Science & Technology

2001-10-25

developed over the Hellenic Integrated Services Digital Network (ISDN), is based on user terminals (personal computers), networking apparatus, and a...key infrastructure, ready to offer enhanced message switching and translation in response to market trends [8]. Three (3) years ago, the Hellenic PTT...should outcome to both an integrated Tele- Working platform, a main central database (completed with maintenance facilities), and a ready-to-be

Architecture Design of Healthcare Software-as-a-Service Platform for Cloud-Based Clinical Decision Support Service.

PubMed

Oh, Sungyoung; Cha, Jieun; Ji, Myungkyu; Kang, Hyekyung; Kim, Seok; Heo, Eunyoung; Han, Jong Soo; Kang, Hyunggoo; Chae, Hoseok; Hwang, Hee; Yoo, Sooyoung

2015-04-01

To design a cloud computing-based Healthcare Software-as-a-Service (SaaS) Platform (HSP) for delivering healthcare information services with low cost, high clinical value, and high usability. We analyzed the architecture requirements of an HSP, including the interface, business services, cloud SaaS, quality attributes, privacy and security, and multi-lingual capacity. For cloud-based SaaS services, we focused on Clinical Decision Service (CDS) content services, basic functional services, and mobile services. Microsoft's Azure cloud computing for Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) was used. The functional and software views of an HSP were designed in a layered architecture. External systems can be interfaced with the HSP using SOAP and REST/JSON. The multi-tenancy model of the HSP was designed as a shared database, with a separate schema for each tenant through a single application, although healthcare data can be physically located on a cloud or in a hospital, depending on regulations. The CDS services were categorized into rule-based services for medications, alert registration services, and knowledge services. We expect that cloud-based HSPs will allow small and mid-sized hospitals, in addition to large-sized hospitals, to adopt information infrastructures and health information technology with low system operation and maintenance costs.

Security policies and trust in ubiquitous computing.

PubMed

Joshi, Anupam; Finin, Tim; Kagal, Lalana; Parker, Jim; Patwardhan, Anand

2008-10-28

Ubiquitous environments comprise resource-constrained mobile and wearable devices and computational elements embedded in everyday artefacts. These are connected to each other using both infrastructure-based as well as short-range ad hoc networks. Limited Internet connectivity limits the use of conventional security mechanisms such as public key infrastructures and other forms of server-centric authentication. Under these circumstances, peer-to-peer interactions are well suited for not just information interchange, but also managing security and privacy. However, practical solutions for protecting mobile devices, preserving privacy, evaluating trust and determining the reliability and accuracy of peer-provided data in such interactions are still in their infancy. Our research is directed towards providing stronger assurances of the reliability and trustworthiness of information and services, and the use of declarative policy-driven approaches to handle the open and dynamic nature of such systems. This paper provides an overview of some of the challenges and issues, and points out directions for progress.

Event heap: a coordination infrastructure for dynamic heterogeneous application interactions in ubiquitous computing environments

DOEpatents

Johanson, Bradley E.; Fox, Armando; Winograd, Terry A.; Hanrahan, Patrick M.

2010-04-20

An efficient and adaptive middleware infrastructure called the Event Heap system dynamically coordinates application interactions and communications in a ubiquitous computing environment, e.g., an interactive workspace, having heterogeneous software applications running on various machines and devices across different platforms. Applications exchange events via the Event Heap. Each event is characterized by a set of unordered, named fields. Events are routed by matching certain attributes in the fields. The source and target versions of each field are automatically set when an event is posted or used as a template. The Event Heap system implements a unique combination of features, both intrinsic to tuplespaces and specific to the Event Heap, including content based addressing, support for routing patterns, standard routing fields, limited data persistence, query persistence/registration, transparent communication, self-description, flexible typing, logical/physical centralization, portable client API, at most once per source first-in-first-out ordering, and modular restartability.

Geospatial-enabled Data Exploration and Computation through Data Infrastructure Building Blocks

NASA Astrophysics Data System (ADS)

Song, C. X.; Biehl, L. L.; Merwade, V.; Villoria, N.

2015-12-01

Geospatial data are present everywhere today with the proliferation of location-aware computing devices and sensors. This is especially true in the scientific community where large amounts of data are driving research and education activities in many domains. Collaboration over geospatial data, for example, in modeling, data analysis and visualization, must still overcome the barriers of specialized software and expertise among other challenges. The GABBs project aims at enabling broader access to geospatial data exploration and computation by developing spatial data infrastructure building blocks that leverage capabilities of end-to-end application service and virtualized computing framework in HUBzero. Funded by NSF Data Infrastructure Building Blocks (DIBBS) initiative, GABBs provides a geospatial data architecture that integrates spatial data management, mapping and visualization and will make it available as open source. The outcome of the project will enable users to rapidly create tools and share geospatial data and tools on the web for interactive exploration of data without requiring significant software development skills, GIS expertise or IT administrative privileges. This presentation will describe the development of geospatial data infrastructure building blocks and the scientific use cases that help drive the software development, as well as seek feedback from the user communities.

Design for Run-Time Monitor on Cloud Computing

NASA Astrophysics Data System (ADS)

Kang, Mikyung; Kang, Dong-In; Yun, Mira; Park, Gyung-Leen; Lee, Junghoon

Cloud computing is a new information technology trend that moves computing and data away from desktops and portable PCs into large data centers. The basic principle of cloud computing is to deliver applications as services over the Internet as well as infrastructure. A cloud is the type of a parallel and distributed system consisting of a collection of inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resources. The large-scale distributed applications on a cloud require adaptive service-based software, which has the capability of monitoring the system status change, analyzing the monitored information, and adapting its service configuration while considering tradeoffs among multiple QoS features simultaneously. In this paper, we design Run-Time Monitor (RTM) which is a system software to monitor the application behavior at run-time, analyze the collected information, and optimize resources on cloud computing. RTM monitors application software through library instrumentation as well as underlying hardware through performance counter optimizing its computing configuration based on the analyzed data.

Centre for Research Infrastructure of Polish GNSS Data - response and possible contribution to EPOS

NASA Astrophysics Data System (ADS)

Araszkiewicz, Andrzej; Rohm, Witold; Bosy, Jaroslaw; Szolucha, Marcin; Kaplon, Jan; Kroszczynski, Krzysztof

2017-04-01

In the frame of the first call under Action 4.2: Development of modern research infrastructure of the science sector in the Smart Growth Operational Programme 2014-2020 in the late of 2016 the "EPOS-PL" project has launched. Following institutes are responsible for the implementation of this project: Institute of Geophysics, Polish Academy of Sciences - Project Leader, Academic Computer Centre Cyfronet AGH University of Science and Technology, Central Mining Institute, the Institute of Geodesy and Cartography, Wrocław University of Environmental and Life Sciences, Military University of Technology. In addition, resources constituting entrepreneur's own contribution will come from the Polish Mining Group. Research Infrastructure EPOS-PL will integrate both existing and newly built National Research Infrastructures (Theme Centre for Research Infrastructures), which, under the premise of the program EPOS, are financed exclusively by the national founds. In addition, the e-science platform will be developed. The Centre for Research Infrastructure of GNSS Data (CIBDG - Task 5) will be built based on the experience and facilities of two institutions: Military University of Technology and Wrocław University of Environmental and Life Sciences. The project includes the construction of the National GNNS Repository with data QC procedures and adaptation of two Regional GNNS Analysis Centres for rapid and long-term geodynamical monitoring.

KODAMA and VPC based Framework for Ubiquitous Systems and its Experiment

NASA Astrophysics Data System (ADS)

Takahashi, Kenichi; Amamiya, Satoshi; Iwao, Tadashige; Zhong, Guoqiang; Kainuma, Tatsuya; Amamiya, Makoto

Recently, agent technologies have attracted a lot of interest as an emerging programming paradigm. With such agent technologies, services are provided through collaboration among agents. At the same time, the spread of mobile technologies and communication infrastructures has made it possible to access the network anytime and from anywhere. Using agents and mobile technologies to realize ubiquitous computing systems, we propose a new framework based on KODAMA and VPC. KODAMA provides distributed management mechanisms by using the concept of community and communication infrastructure to deliver messages among agents without agents being aware of the physical network. VPC provides a method of defining peer-to-peer services based on agent communication with policy packages. By merging the characteristics of both KODAMA and VPC functions, we propose a new framework for ubiquitous computing environments. It provides distributed management functions according to the concept of agent communities, agent communications which are abstracted from the physical environment, and agent collaboration with policy packages. Using our new framework, we conducted a large-scale experiment in shopping malls in Nagoya, which sent advertisement e-mails to users' cellular phones according to user location and attributes. The empirical results showed that our new framework worked effectively for sales in shopping malls.

A Security Monitoring Framework For Virtualization Based HEP Infrastructures

NASA Astrophysics Data System (ADS)

Gomez Ramirez, A.; Martinez Pedreira, M.; Grigoras, C.; Betev, L.; Lara, C.; Kebschull, U.; ALICE Collaboration

2017-10-01

High Energy Physics (HEP) distributed computing infrastructures require automatic tools to monitor, analyze and react to potential security incidents. These tools should collect and inspect data such as resource consumption, logs and sequence of system calls for detecting anomalies that indicate the presence of a malicious agent. They should also be able to perform automated reactions to attacks without administrator intervention. We describe a novel framework that accomplishes these requirements, with a proof of concept implementation for the ALICE experiment at CERN. We show how we achieve a fully virtualized environment that improves the security by isolating services and Jobs without a significant performance impact. We also describe a collected dataset for Machine Learning based Intrusion Prevention and Detection Systems on Grid computing. This dataset is composed of resource consumption measurements (such as CPU, RAM and network traffic), logfiles from operating system services, and system call data collected from production Jobs running in an ALICE Grid test site and a big set of malware samples. This malware set was collected from security research sites. Based on this dataset, we will proceed to develop Machine Learning algorithms able to detect malicious Jobs.

Computational simulation of concurrent engineering for aerospace propulsion systems

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Singhal, S. N.

1992-01-01

Results are summarized of an investigation to assess the infrastructure available and the technology readiness in order to develop computational simulation methods/software for concurrent engineering. These results demonstrate that development of computational simulations methods for concurrent engineering is timely. Extensive infrastructure, in terms of multi-discipline simulation, component-specific simulation, system simulators, fabrication process simulation, and simulation of uncertainties - fundamental in developing such methods, is available. An approach is recommended which can be used to develop computational simulation methods for concurrent engineering for propulsion systems and systems in general. Benefits and facets needing early attention in the development are outlined.

Computational simulation for concurrent engineering of aerospace propulsion systems

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Singhal, S. N.

1993-01-01

Results are summarized for an investigation to assess the infrastructure available and the technology readiness in order to develop computational simulation methods/software for concurrent engineering. These results demonstrate that development of computational simulation methods for concurrent engineering is timely. Extensive infrastructure, in terms of multi-discipline simulation, component-specific simulation, system simulators, fabrication process simulation, and simulation of uncertainties--fundamental to develop such methods, is available. An approach is recommended which can be used to develop computational simulation methods for concurrent engineering of propulsion systems and systems in general. Benefits and issues needing early attention in the development are outlined.

Computational simulation for concurrent engineering of aerospace propulsion systems

NASA Astrophysics Data System (ADS)

Chamis, C. C.; Singhal, S. N.

1993-02-01

Results are summarized for an investigation to assess the infrastructure available and the technology readiness in order to develop computational simulation methods/software for concurrent engineering. These results demonstrate that development of computational simulation methods for concurrent engineering is timely. Extensive infrastructure, in terms of multi-discipline simulation, component-specific simulation, system simulators, fabrication process simulation, and simulation of uncertainties--fundamental to develop such methods, is available. An approach is recommended which can be used to develop computational simulation methods for concurrent engineering of propulsion systems and systems in general. Benefits and issues needing early attention in the development are outlined.

Testing the Test: A Study of PARCC Field Trials in Two School Districts. Policy Brief

ERIC Educational Resources Information Center

Rennie Center for Education Research & Policy, 2015

2015-01-01

The potential use of computer-based assessments has raised concerns from educators, policymakers, and parents about information technology infrastructure in school districts and the preparation of staff and students to use new technologies for assessment purposes, and the potential impact of testing activities on core school functions,…

Efficient Mining and Detection of Sequential Intrusion Patterns for Network Intrusion Detection Systems

NASA Astrophysics Data System (ADS)

Shyu, Mei-Ling; Huang, Zifang; Luo, Hongli

In recent years, pervasive computing infrastructures have greatly improved the interaction between human and system. As we put more reliance on these computing infrastructures, we also face threats of network intrusion and/or any new forms of undesirable IT-based activities. Hence, network security has become an extremely important issue, which is closely connected with homeland security, business transactions, and people's daily life. Accurate and efficient intrusion detection technologies are required to safeguard the network systems and the critical information transmitted in the network systems. In this chapter, a novel network intrusion detection framework for mining and detecting sequential intrusion patterns is proposed. The proposed framework consists of a Collateral Representative Subspace Projection Modeling (C-RSPM) component for supervised classification, and an inter-transactional association rule mining method based on Layer Divided Modeling (LDM) for temporal pattern analysis. Experiments on the KDD99 data set and the traffic data set generated by a private LAN testbed show promising results with high detection rates, low processing time, and low false alarm rates in mining and detecting sequential intrusion detections.

GOES-R GS Product Generation Infrastructure Operations

NASA Astrophysics Data System (ADS)

Blanton, M.; Gundy, J.

2012-12-01

GOES-R GS Product Generation Infrastructure Operations: The GOES-R Ground System (GS) will produce a much larger set of products with higher data density than previous GOES systems. This requires considerably greater compute and memory resources to achieve the necessary latency and availability for these products. Over time, new algorithms could be added and existing ones removed or updated, but the GOES-R GS cannot go down during this time. To meet these GOES-R GS processing needs, the Harris Corporation will implement a Product Generation (PG) infrastructure that is scalable, extensible, extendable, modular and reliable. The primary parts of the PG infrastructure are the Service Based Architecture (SBA), which includes the Distributed Data Fabric (DDF). The SBA is the middleware that encapsulates and manages science algorithms that generate products. The SBA is divided into three parts, the Executive, which manages and configures the algorithm as a service, the Dispatcher, which provides data to the algorithm, and the Strategy, which determines when the algorithm can execute with the available data. The SBA is a distributed architecture, with services connected to each other over a compute grid and is highly scalable. This plug-and-play architecture allows algorithms to be added, removed, or updated without affecting any other services or software currently running and producing data. Algorithms require product data from other algorithms, so a scalable and reliable messaging is necessary. The SBA uses the DDF to provide this data communication layer between algorithms. The DDF provides an abstract interface over a distributed and persistent multi-layered storage system (memory based caching above disk-based storage) and an event system that allows algorithm services to know when data is available and to get the data that they need to begin processing when they need it. Together, the SBA and the DDF provide a flexible, high performance architecture that can meet the needs of product processing now and as they grow in the future.

Grids, virtualization, and clouds at Fermilab

DOE PAGES

Timm, S.; Chadwick, K.; Garzoglio, G.; ...

2014-06-11

Fermilab supports a scientific program that includes experiments and scientists located across the globe. To better serve this community, in 2004, the (then) Computing Division undertook the strategy of placing all of the High Throughput Computing (HTC) resources in a Campus Grid known as FermiGrid, supported by common shared services. In 2007, the FermiGrid Services group deployed a service infrastructure that utilized Xen virtualization, LVS network routing and MySQL circular replication to deliver highly available services that offered significant performance, reliability and serviceability improvements. This deployment was further enhanced through the deployment of a distributed redundant network core architecture andmore » the physical distribution of the systems that host the virtual machines across multiple buildings on the Fermilab Campus. In 2010, building on the experience pioneered by FermiGrid in delivering production services in a virtual infrastructure, the Computing Sector commissioned the FermiCloud, General Physics Computing Facility and Virtual Services projects to serve as platforms for support of scientific computing (FermiCloud 6 GPCF) and core computing (Virtual Services). Lastly, this work will present the evolution of the Fermilab Campus Grid, Virtualization and Cloud Computing infrastructure together with plans for the future.« less

Grids, virtualization, and clouds at Fermilab

NASA Astrophysics Data System (ADS)

Timm, S.; Chadwick, K.; Garzoglio, G.; Noh, S.

2014-06-01

Fermilab supports a scientific program that includes experiments and scientists located across the globe. To better serve this community, in 2004, the (then) Computing Division undertook the strategy of placing all of the High Throughput Computing (HTC) resources in a Campus Grid known as FermiGrid, supported by common shared services. In 2007, the FermiGrid Services group deployed a service infrastructure that utilized Xen virtualization, LVS network routing and MySQL circular replication to deliver highly available services that offered significant performance, reliability and serviceability improvements. This deployment was further enhanced through the deployment of a distributed redundant network core architecture and the physical distribution of the systems that host the virtual machines across multiple buildings on the Fermilab Campus. In 2010, building on the experience pioneered by FermiGrid in delivering production services in a virtual infrastructure, the Computing Sector commissioned the FermiCloud, General Physics Computing Facility and Virtual Services projects to serve as platforms for support of scientific computing (FermiCloud 6 GPCF) and core computing (Virtual Services). This work will present the evolution of the Fermilab Campus Grid, Virtualization and Cloud Computing infrastructure together with plans for the future.

Phenomenology tools on cloud infrastructures using OpenStack

NASA Astrophysics Data System (ADS)

Campos, I.; Fernández-del-Castillo, E.; Heinemeyer, S.; Lopez-Garcia, A.; Pahlen, F.; Borges, G.

2013-04-01

We present a new environment for computations in particle physics phenomenology employing recent developments in cloud computing. On this environment users can create and manage "virtual" machines on which the phenomenology codes/tools can be deployed easily in an automated way. We analyze the performance of this environment based on "virtual" machines versus the utilization of physical hardware. In this way we provide a qualitative result for the influence of the host operating system on the performance of a representative set of applications for phenomenology calculations.

CERN's Common Unix and X Terminal Environment

NASA Astrophysics Data System (ADS)

Cass, Tony

The Desktop Infrastructure Group of CERN's Computing and Networks Division has developed a Common Unix and X Terminal Environment to ease the migration to Unix based Interactive Computing. The CUTE architecture relies on a distributed filesystem—currently Trans arc's AFS—to enable essentially interchangeable client work-stations to access both "home directory" and program files transparently. Additionally, we provide a suite of programs to configure workstations for CUTE and to ensure continued compatibility. This paper describes the different components and the development of the CUTE architecture.

Estuarine wetland evolution including sea-level rise and infrastructure effects.

NASA Astrophysics Data System (ADS)

Rodriguez, Jose Fernando; Trivisonno, Franco; Rojas, Steven Sandi; Riccardi, Gerardo; Stenta, Hernan; Saco, Patricia Mabel

2015-04-01

Estuarine wetlands are an extremely valuable resource in terms of biotic diversity, flood attenuation, storm surge protection, groundwater recharge, filtering of surface flows and carbon sequestration. On a large scale the survival of these systems depends on the slope of the land and a balance between the rates of accretion and sea-level rise, but local man-made flow disturbances can have comparable effects. Climate change predictions for most of Australia include an accelerated sea level rise, which may challenge the survival of estuarine wetlands. Furthermore, coastal infrastructure poses an additional constraint on the adaptive capacity of these ecosystems. Numerical models are increasingly being used to assess wetland dynamics and to help manage some of these situations. We present results of a wetland evolution model that is based on computed values of hydroperiod and tidal range that drive vegetation preference. Our first application simulates the long term evolution of an Australian wetland heavily constricted by infrastructure that is undergoing the effects of predicted accelerated sea level rise. The wetland presents a vegetation zonation sequence mudflats - mangrove - saltmarsh from the seaward margin and up the topographic gradient but is also affected by compartmentalization due to internal road embankments and culverts that effectively attenuates tidal input to the upstream compartments. For this reason, the evolution model includes a 2D hydrodynamic module which is able to handle man-made flow controls and spatially varying roughness. It continually simulates tidal inputs into the wetland and computes annual values of hydroperiod and tidal range to update vegetation distribution based on preference to hydrodynamic conditions of the different vegetation types. It also computes soil accretion rates and updates roughness coefficient values according to evolving vegetation types. In order to explore in more detail the magnitude of flow attenuation due to roughness and its effects on the computation of tidal range and hydroperiod, we performed numerical experiments simulating floodplain flow on the side of a tidal creek using different roughness values. Even though the values of roughness that produce appreciable changes in hydroperiod and tidal range are relatively high, they are within the range expected for some of the wetland vegetation. Both applications of the model show that flow attenuation can play a major role in wetland hydrodynamics and that its effects must be considered when predicting wetland evolution under climate change scenarios, particularly in situations where existing infrastructure affects the flow.

Explicit Content Caching at Mobile Edge Networks with Cross-Layer Sensing

PubMed Central

Chen, Lingyu; Su, Youxing; Luo, Wenbin; Hong, Xuemin; Shi, Jianghong

2018-01-01

The deployment density and computational power of small base stations (BSs) are expected to increase significantly in the next generation mobile communication networks. These BSs form the mobile edge network, which is a pervasive and distributed infrastructure that can empower a variety of edge/fog computing applications. This paper proposes a novel edge-computing application called explicit caching, which stores selective contents at BSs and exposes such contents to local users for interactive browsing and download. We formulate the explicit caching problem as a joint content recommendation, caching, and delivery problem, which aims to maximize the expected user quality-of-experience (QoE) with varying degrees of cross-layer sensing capability. Optimal and effective heuristic algorithms are presented to solve the problem. The theoretical performance bounds of the explicit caching system are derived in simplified scenarios. The impacts of cache storage space, BS backhaul capacity, cross-layer information, and user mobility on the system performance are simulated and discussed in realistic scenarios. Results suggest that, compared with conventional implicit caching schemes, explicit caching can better exploit the mobile edge network infrastructure for personalized content dissemination. PMID:29565313

Explicit Content Caching at Mobile Edge Networks with Cross-Layer Sensing.

PubMed

Chen, Lingyu; Su, Youxing; Luo, Wenbin; Hong, Xuemin; Shi, Jianghong

2018-03-22

The deployment density and computational power of small base stations (BSs) are expected to increase significantly in the next generation mobile communication networks. These BSs form the mobile edge network, which is a pervasive and distributed infrastructure that can empower a variety of edge/fog computing applications. This paper proposes a novel edge-computing application called explicit caching, which stores selective contents at BSs and exposes such contents to local users for interactive browsing and download. We formulate the explicit caching problem as a joint content recommendation, caching, and delivery problem, which aims to maximize the expected user quality-of-experience (QoE) with varying degrees of cross-layer sensing capability. Optimal and effective heuristic algorithms are presented to solve the problem. The theoretical performance bounds of the explicit caching system are derived in simplified scenarios. The impacts of cache storage space, BS backhaul capacity, cross-layer information, and user mobility on the system performance are simulated and discussed in realistic scenarios. Results suggest that, compared with conventional implicit caching schemes, explicit caching can better exploit the mobile edge network infrastructure for personalized content dissemination.

Using Multi-modal Sensing for Human Activity Modeling in the Real World

NASA Astrophysics Data System (ADS)

Harrison, Beverly L.; Consolvo, Sunny; Choudhury, Tanzeem

Traditionally smart environments have been understood to represent those (often physical) spaces where computation is embedded into the users' surrounding infrastructure, buildings, homes, and workplaces. Users of this "smartness" move in and out of these spaces. Ambient intelligence assumes that users are automatically and seamlessly provided with context-aware, adaptive information, applications and even sensing - though this remains a significant challenge even when limited to these specialized, instrumented locales. Since not all environments are "smart" the experience is not a pervasive one; rather, users move between these intelligent islands of computationally enhanced space while we still aspire to achieve a more ideal anytime, anywhere experience. Two key technological trends are helping to bridge the gap between these smart environments and make the associated experience more persistent and pervasive. Smaller and more computationally sophisticated mobile devices allow sensing, communication, and services to be more directly and continuously experienced by user. Improved infrastructure and the availability of uninterrupted data streams, for instance location-based data, enable new services and applications to persist across environments.

AstroCloud, a Cyber-Infrastructure for Astronomy Research: Overview

NASA Astrophysics Data System (ADS)

Cui, C.; Yu, C.; Xiao, J.; He, B.; Li, C.; Fan, D.; Wang, C.; Hong, Z.; Li, S.; Mi, L.; Wan, W.; Cao, Z.; Wang, J.; Yin, S.; Fan, Y.; Wang, J.

2015-09-01

AstroCloud is a cyber-Infrastructure for Astronomy Research initiated by Chinese Virtual Observatory (China-VO) under funding support from NDRC (National Development and Reform commission) and CAS (Chinese Academy of Sciences). Tasks such as proposal submission, proposal peer-review, data archiving, data quality control, data release and open access, Cloud based data processing and analyzing, will be all supported on the platform. It will act as a full lifecycle management system for astronomical data and telescopes. Achievements from international Virtual Observatories and Cloud Computing are adopted heavily. In this paper, backgrounds of the project, key features of the system, and latest progresses are introduced.

The computing and data infrastructure to interconnect EEE stations

NASA Astrophysics Data System (ADS)

Noferini, F.; EEE Collaboration

2016-07-01

The Extreme Energy Event (EEE) experiment is devoted to the search of high energy cosmic rays through a network of telescopes installed in about 50 high schools distributed throughout the Italian territory. This project requires a peculiar data management infrastructure to collect data registered in stations very far from each other and to allow a coordinated analysis. Such an infrastructure is realized at INFN-CNAF, which operates a Cloud facility based on the OpenStack opensource Cloud framework and provides Infrastructure as a Service (IaaS) for its users. In 2014 EEE started to use it for collecting, monitoring and reconstructing the data acquired in all the EEE stations. For the synchronization between the stations and the INFN-CNAF infrastructure we used BitTorrent Sync, a free peer-to-peer software designed to optimize data syncronization between distributed nodes. All data folders are syncronized with the central repository in real time to allow an immediate reconstruction of the data and their publication in a monitoring webpage. We present the architecture and the functionalities of this data management system that provides a flexible environment for the specific needs of the EEE project.

Cloud computing applications for biomedical science: A perspective.

PubMed

Navale, Vivek; Bourne, Philip E

2018-06-01

Biomedical research has become a digital data-intensive endeavor, relying on secure and scalable computing, storage, and network infrastructure, which has traditionally been purchased, supported, and maintained locally. For certain types of biomedical applications, cloud computing has emerged as an alternative to locally maintained traditional computing approaches. Cloud computing offers users pay-as-you-go access to services such as hardware infrastructure, platforms, and software for solving common biomedical computational problems. Cloud computing services offer secure on-demand storage and analysis and are differentiated from traditional high-performance computing by their rapid availability and scalability of services. As such, cloud services are engineered to address big data problems and enhance the likelihood of data and analytics sharing, reproducibility, and reuse. Here, we provide an introductory perspective on cloud computing to help the reader determine its value to their own research.

Cloud computing applications for biomedical science: A perspective

PubMed Central

2018-01-01

Biomedical research has become a digital data–intensive endeavor, relying on secure and scalable computing, storage, and network infrastructure, which has traditionally been purchased, supported, and maintained locally. For certain types of biomedical applications, cloud computing has emerged as an alternative to locally maintained traditional computing approaches. Cloud computing offers users pay-as-you-go access to services such as hardware infrastructure, platforms, and software for solving common biomedical computational problems. Cloud computing services offer secure on-demand storage and analysis and are differentiated from traditional high-performance computing by their rapid availability and scalability of services. As such, cloud services are engineered to address big data problems and enhance the likelihood of data and analytics sharing, reproducibility, and reuse. Here, we provide an introductory perspective on cloud computing to help the reader determine its value to their own research. PMID:29902176

Comparison of Computer-based Clinical Decision Support Systems and Content for Diabetes Mellitus.

PubMed

Kantor, M; Wright, A; Burton, M; Fraser, G; Krall, M; Maviglia, S; Mohammed-Rajput, N; Simonaitis, L; Sonnenberg, F; Middleton, B

2011-01-01

Computer-based clinical decision support (CDS) systems have been shown to improve quality of care and workflow efficiency, and health care reform legislation relies on electronic health records and CDS systems to improve the cost and quality of health care in the United States; however, the heterogeneity of CDS content and infrastructure of CDS systems across sites is not well known. We aimed to determine the scope of CDS content in diabetes care at six sites, assess the capabilities of CDS in use at these sites, characterize the scope of CDS infrastructure at these sites, and determine how the sites use CDS beyond individual patient care in order to identify characteristics of CDS systems and content that have been successfully implemented in diabetes care. We compared CDS systems in six collaborating sites of the Clinical Decision Support Consortium. We gathered CDS content on care for patients with diabetes mellitus and surveyed institutions on characteristics of their site, the infrastructure of CDS at these sites, and the capabilities of CDS at these sites. The approach to CDS and the characteristics of CDS content varied among sites. Some commonalities included providing customizability by role or user, applying sophisticated exclusion criteria, and using CDS automatically at the time of decision-making. Many messages were actionable recommendations. Most sites had monitoring rules (e.g. assessing hemoglobin A1c), but few had rules to diagnose diabetes or suggest specific treatments. All sites had numerous prevention rules including reminders for providing eye examinations, influenza vaccines, lipid screenings, nephropathy screenings, and pneumococcal vaccines. Computer-based CDS systems vary widely across sites in content and scope, but both institution-created and purchased systems had many similar features and functionality, such as integration of alerts and reminders into the decision-making workflow of the provider and providing messages that are actionable recommendations.

Health care information infrastructure: what will it be and how will we get there?

NASA Astrophysics Data System (ADS)

Kun, Luis G.

1996-02-01

During the first Health Care Technology Policy [HCTPI conference last year, during Health Care Reform, four major issues were brought up in regards to the underway efforts to develop a Computer Based Patient Record (CBPR)I the National Information Infrastructure (NIl) as part of the High Performance Computers & Communications (HPCC), and the so-called "Patient Card" . More specifically it was explained how a national information system will greatly affect the way health care delivery is provided to the United States public and reduce its costs. These four issues were: Constructing a National Information Infrastructure (NIl); Building a Computer Based Patient Record System; Bringing the collective resources of our National Laboratories to bear in developing and implementing the NIl and CBPR, as well as a security system with which to safeguard the privacy rights of patients and the physician-patient privilege; Utilizing Government (e.g. DOD, DOE) capabilities (technology and human resources) to maximize resource utilization, create new jobs and accelerate technology transfer to address health care issues. During the second HCTP conference, in mid 1 995, a section of this meeting entitled: "Health Care Technology Assets of the Federal Government" addressed benefits of the technology transfer which should occur for maximizing already developed resources. Also a section entitled:"Transfer and Utilization of Government Technology Assets to the Private Sector", looked at both Health Care and non-Health Care related technologies since many areas such as Information Technologies (i.e. imaging, communications, archival I retrieval, systems integration, information display, multimedia, heterogeneous data bases, etc.) already exist and are part of our National Labs and/or other federal agencies, i.e. ARPA. These technologies although they are not labeled under "Health Care" programs they could provide enormous value to address technical needs. An additional issue deals with both the technical (hardware, software) and human expertise that resides within these labs and their possible role in creating cost effective solutions.

National Computational Infrastructure for Lattice Gauge Theory SciDAC-2 Closeout Report Indiana University Component

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gottlieb, Steven Arthur; DeTar, Carleton; Tousaint, Doug

This is the closeout report for the Indiana University portion of the National Computational Infrastructure for Lattice Gauge Theory project supported by the United States Department of Energy under the SciDAC program. It includes information about activities at Indian University, the University of Arizona, and the University of Utah, as those three universities coordinated their activities.

Deploying Crowd-Sourced Formal Verification Systems in a DoD Network

DTIC Science & Technology

2013-09-01

INTENTIONALLY LEFT BLANK 1 I. INTRODUCTION A. INTRODUCTION In 2014 cyber attacks on critical infrastructure are expected to increase...CSFV systems on the Internet‒‒possibly using cloud infrastructure (Dean, 2013). By using Amazon Compute Cloud (EC2) systems, DARPA will use ordinary...through standard access methods. Those clients could be mobile phones, laptops, netbooks, tablet computers or personal digital assistants (PDAs) (Smoot

New Trends in E-Science: Machine Learning and Knowledge Discovery in Databases

NASA Astrophysics Data System (ADS)

Brescia, Massimo

2012-11-01

Data mining, or Knowledge Discovery in Databases (KDD), while being the main methodology to extract the scientific information contained in Massive Data Sets (MDS), needs to tackle crucial problems since it has to orchestrate complex challenges posed by transparent access to different computing environments, scalability of algorithms, reusability of resources. To achieve a leap forward for the progress of e-science in the data avalanche era, the community needs to implement an infrastructure capable of performing data access, processing and mining in a distributed but integrated context. The increasing complexity of modern technologies carried out a huge production of data, whose related warehouse management and the need to optimize analysis and mining procedures lead to a change in concept on modern science. Classical data exploration, based on local user own data storage and limited computing infrastructures, is no more efficient in the case of MDS, worldwide spread over inhomogeneous data centres and requiring teraflop processing power. In this context modern experimental and observational science requires a good understanding of computer science, network infrastructures, Data Mining, etc. i.e. of all those techniques which fall into the domain of the so called e-science (recently assessed also by the Fourth Paradigm of Science). Such understanding is almost completely absent in the older generations of scientists and this reflects in the inadequacy of most academic and research programs. A paradigm shift is needed: statistical pattern recognition, object oriented programming, distributed computing, parallel programming need to become an essential part of scientific background. A possible practical solution is to provide the research community with easy-to understand, easy-to-use tools, based on the Web 2.0 technologies and Machine Learning methodology. Tools where almost all the complexity is hidden to the final user, but which are still flexible and able to produce efficient and reliable scientific results. All these considerations will be described in the detail in the chapter. Moreover, examples of modern applications offering to a wide variety of e-science communities a large spectrum of computational facilities to exploit the wealth of available massive data sets and powerful machine learning and statistical algorithms will be also introduced.

Commissioning the CERN IT Agile Infrastructure with experiment workloads

NASA Astrophysics Data System (ADS)

Medrano Llamas, Ramón; Harald Barreiro Megino, Fernando; Kucharczyk, Katarzyna; Kamil Denis, Marek; Cinquilli, Mattia

2014-06-01

In order to ease the management of their infrastructure, most of the WLCG sites are adopting cloud based strategies. In the case of CERN, the Tier 0 of the WLCG, is completely restructuring the resource and configuration management of their computing center under the codename Agile Infrastructure. Its goal is to manage 15,000 Virtual Machines by means of an OpenStack middleware in order to unify all the resources in CERN's two datacenters: the one placed in Meyrin and the new on in Wigner, Hungary. During the commissioning of this infrastructure, CERN IT is offering an attractive amount of computing resources to the experiments (800 cores for ATLAS and CMS) through a private cloud interface. ATLAS and CMS have joined forces to exploit them by running stress tests and simulation workloads since November 2012. This work will describe the experience of the first deployments of the current experiment workloads on the CERN private cloud testbed. The paper is organized as follows: the first section will explain the integration of the experiment workload management systems (WMS) with the cloud resources. The second section will revisit the performance and stress testing performed with HammerCloud in order to evaluate and compare the suitability for the experiment workloads. The third section will go deeper into the dynamic provisioning techniques, such as the use of the cloud APIs directly by the WMS. The paper finishes with a review of the conclusions and the challenges ahead.

Cloud Computing with iPlant Atmosphere.

PubMed

McKay, Sheldon J; Skidmore, Edwin J; LaRose, Christopher J; Mercer, Andre W; Noutsos, Christos

2013-10-15

Cloud Computing refers to distributed computing platforms that use virtualization software to provide easy access to physical computing infrastructure and data storage, typically administered through a Web interface. Cloud-based computing provides access to powerful servers, with specific software and virtual hardware configurations, while eliminating the initial capital cost of expensive computers and reducing the ongoing operating costs of system administration, maintenance contracts, power consumption, and cooling. This eliminates a significant barrier to entry into bioinformatics and high-performance computing for many researchers. This is especially true of free or modestly priced cloud computing services. The iPlant Collaborative offers a free cloud computing service, Atmosphere, which allows users to easily create and use instances on virtual servers preconfigured for their analytical needs. Atmosphere is a self-service, on-demand platform for scientific computing. This unit demonstrates how to set up, access and use cloud computing in Atmosphere. Copyright © 2013 John Wiley & Sons, Inc.

An u-Service Model Based on a Smart Phone for Urban Computing Environments

NASA Astrophysics Data System (ADS)

Cho, Yongyun; Yoe, Hyun

In urban computing environments, all of services should be based on the interaction between humans and environments around them, which frequently and ordinarily in home and office. This paper propose an u-service model based on a smart phone for urban computing environments. The suggested service model includes a context-aware and personalized service scenario development environment that can instantly describe user's u-service demand or situation information with smart devices. To do this, the architecture of the suggested service model consists of a graphical service editing environment for smart devices, an u-service platform, and an infrastructure with sensors and WSN/USN. The graphic editor expresses contexts as execution conditions of a new service through a context model based on ontology. The service platform deals with the service scenario according to contexts. With the suggested service model, an user in urban computing environments can quickly and easily make u-service or new service using smart devices.

SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology.

PubMed

Adams, Richard; Clark, Allan; Yamaguchi, Azusa; Hanlon, Neil; Tsorman, Nikos; Ali, Shakir; Lebedeva, Galina; Goltsov, Alexey; Sorokin, Anatoly; Akman, Ozgur E; Troein, Carl; Millar, Andrew J; Goryanin, Igor; Gilmore, Stephen

2013-03-01

Complex computational experiments in Systems Biology, such as fitting model parameters to experimental data, can be challenging to perform. Not only do they frequently require a high level of computational power, but the software needed to run the experiment needs to be usable by scientists with varying levels of computational expertise, and modellers need to be able to obtain up-to-date experimental data resources easily. We have developed a software suite, the Systems Biology Software Infrastructure (SBSI), to facilitate the parameter-fitting process. SBSI is a modular software suite composed of three major components: SBSINumerics, a high-performance library containing parallelized algorithms for performing parameter fitting; SBSIDispatcher, a middleware application to track experiments and submit jobs to back-end servers; and SBSIVisual, an extensible client application used to configure optimization experiments and view results. Furthermore, we have created a plugin infrastructure to enable project-specific modules to be easily installed. Plugin developers can take advantage of the existing user-interface and application framework to customize SBSI for their own uses, facilitated by SBSI's use of standard data formats. All SBSI binaries and source-code are freely available from http://sourceforge.net/projects/sbsi under an Apache 2 open-source license. The server-side SBSINumerics runs on any Unix-based operating system; both SBSIVisual and SBSIDispatcher are written in Java and are platform independent, allowing use on Windows, Linux and Mac OS X. The SBSI project website at http://www.sbsi.ed.ac.uk provides documentation and tutorials.

Economic models for management of resources in peer-to-peer and grid computing

NASA Astrophysics Data System (ADS)

Buyya, Rajkumar; Stockinger, Heinz; Giddy, Jonathan; Abramson, David

2001-07-01

The accelerated development in Peer-to-Peer (P2P) and Grid computing has positioned them as promising next generation computing platforms. They enable the creation of Virtual Enterprises (VE) for sharing resources distributed across the world. However, resource management, application development and usage models in these environments is a complex undertaking. This is due to the geographic distribution of resources that are owned by different organizations or peers. The resource owners of each of these resources have different usage or access policies and cost models, and varying loads and availability. In order to address complex resource management issues, we have proposed a computational economy framework for resource allocation and for regulating supply and demand in Grid computing environments. The framework provides mechanisms for optimizing resource provider and consumer objective functions through trading and brokering services. In a real world market, there exist various economic models for setting the price for goods based on supply-and-demand and their value to the user. They include commodity market, posted price, tenders and auctions. In this paper, we discuss the use of these models for interaction between Grid components in deciding resource value and the necessary infrastructure to realize them. In addition to normal services offered by Grid computing systems, we need an infrastructure to support interaction protocols, allocation mechanisms, currency, secure banking, and enforcement services. Furthermore, we demonstrate the usage of some of these economic models in resource brokering through Nimrod/G deadline and cost-based scheduling for two different optimization strategies on the World Wide Grid (WWG) testbed that contains peer-to-peer resources located on five continents: Asia, Australia, Europe, North America, and South America.

Methodologies and systems for heterogeneous concurrent computing

NASA Technical Reports Server (NTRS)

Sunderam, V. S.

1994-01-01

Heterogeneous concurrent computing is gaining increasing acceptance as an alternative or complementary paradigm to multiprocessor-based parallel processing as well as to conventional supercomputing. While algorithmic and programming aspects of heterogeneous concurrent computing are similar to their parallel processing counterparts, system issues, partitioning and scheduling, and performance aspects are significantly different. In this paper, we discuss critical design and implementation issues in heterogeneous concurrent computing, and describe techniques for enhancing its effectiveness. In particular, we highlight the system level infrastructures that are required, aspects of parallel algorithm development that most affect performance, system capabilities and limitations, and tools and methodologies for effective computing in heterogeneous networked environments. We also present recent developments and experiences in the context of the PVM system and comment on ongoing and future work.

Scaling the CERN OpenStack cloud

NASA Astrophysics Data System (ADS)

Bell, T.; Bompastor, B.; Bukowiec, S.; Castro Leon, J.; Denis, M. K.; van Eldik, J.; Fermin Lobo, M.; Fernandez Alvarez, L.; Fernandez Rodriguez, D.; Marino, A.; Moreira, B.; Noel, B.; Oulevey, T.; Takase, W.; Wiebalck, A.; Zilli, S.

2015-12-01

CERN has been running a production OpenStack cloud since July 2013 to support physics computing and infrastructure services for the site. In the past year, CERN Cloud Infrastructure has seen a constant increase in nodes, virtual machines, users and projects. This paper will present what has been done in order to make the CERN cloud infrastructure scale out.

Science of Security Lablet - Scalability and Usability

DTIC Science & Technology

2014-12-16

mobile computing [19]. However, the high-level infrastructure design and our own implementation (both described throughout this paper) can easily...critical and infrastructural systems demands high levels of sophistication in the technical aspects of cybersecurity, software and hardware design...Forget, S. Komanduri, Alessandro Acquisti, Nicolas Christin, Lorrie Cranor, Rahul Telang. "Security Behavior Observatory: Infrastructure for Long-term

The CMS Tier0 goes cloud and grid for LHC Run 2

DOE PAGES

Hufnagel, Dirk

2015-12-23

In 2015, CMS will embark on a new era of collecting LHC collisions at unprecedented rates and complexity. This will put a tremendous stress on our computing systems. Prompt Processing of the raw data by the Tier-0 infrastructure will no longer be constrained to CERN alone due to the significantly increased resource requirements. In LHC Run 2, we will need to operate it as a distributed system utilizing both the CERN Cloud-based Agile Infrastructure and a significant fraction of the CMS Tier-1 Grid resources. In another big change for LHC Run 2, we will process all data using the multi-threadedmore » framework to deal with the increased event complexity and to ensure efficient use of the resources. Furthermore, this contribution will cover the evolution of the Tier-0 infrastructure and present scale testing results and experiences from the first data taking in 2015.« less

The CMS TierO goes Cloud and Grid for LHC Run 2

NASA Astrophysics Data System (ADS)

Hufnagel, Dirk

2015-12-01

In 2015, CMS will embark on a new era of collecting LHC collisions at unprecedented rates and complexity. This will put a tremendous stress on our computing systems. Prompt Processing of the raw data by the Tier-0 infrastructure will no longer be constrained to CERN alone due to the significantly increased resource requirements. In LHC Run 2, we will need to operate it as a distributed system utilizing both the CERN Cloud-based Agile Infrastructure and a significant fraction of the CMS Tier-1 Grid resources. In another big change for LHC Run 2, we will process all data using the multi-threaded framework to deal with the increased event complexity and to ensure efficient use of the resources. This contribution will cover the evolution of the Tier-0 infrastructure and present scale testing results and experiences from the first data taking in 2015.

Role of Computational Fluid Dynamics and Wind Tunnels in Aeronautics R and D

NASA Technical Reports Server (NTRS)

Malik, Murjeeb R.; Bushnell, Dennis M.

2012-01-01

The purpose of this report is to investigate the status and future projections for the question of supplantation of wind tunnels by computation in design and to intuit the potential impact of computation approaches on wind-tunnel utilization all with an eye toward reducing the infrastructure cost at aeronautics R&D centers. Wind tunnels have been closing for myriad reasons, and such closings have reduced infrastructure costs. Further cost reductions are desired, and the work herein attempts to project which wind-tunnel capabilities can be replaced in the future and, if possible, the timing of such. If the possibility exists to project when a facility could be closed, then maintenance and other associated costs could be rescheduled accordingly (i.e., before the fact) to obtain an even greater infrastructure cost reduction.

A Computational framework for telemedicine.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foster, I.; von Laszewski, G.; Thiruvathukal, G. K.

1998-07-01

Emerging telemedicine applications require the ability to exploit diverse and geographically distributed resources. Highspeed networks are used to integrate advanced visualization devices, sophisticated instruments, large databases, archival storage devices, PCs, workstations, and supercomputers. This form of telemedical environment is similar to networked virtual supercomputers, also known as metacomputers. Metacomputers are already being used in many scientific application areas. In this article, we analyze requirements necessary for a telemedical computing infrastructure and compare them with requirements found in a typical metacomputing environment. We will show that metacomputing environments can be used to enable a more powerful and unified computational infrastructure formore » telemedicine. The Globus metacomputing toolkit can provide the necessary low level mechanisms to enable a large scale telemedical infrastructure. The Globus toolkit components are designed in a modular fashion and can be extended to support the specific requirements for telemedicine.« less

Redefining Tactical Operations for MER Using Cloud Computing

NASA Technical Reports Server (NTRS)

Joswig, Joseph C.; Shams, Khawaja S.

2011-01-01

The Mars Exploration Rover Mission (MER) includes the twin rovers, Spirit and Opportunity, which have been performing geological research and surface exploration since early 2004. The rovers' durability well beyond their original prime mission (90 sols or Martian days) has allowed them to be a valuable platform for scientific research for well over 2000 sols, but as a by-product it has produced new challenges in providing efficient and cost-effective tactical operational planning. An early stage process adaptation was the move to distributed operations as mission scientists returned to their places of work in the summer of 2004, but they would still came together via teleconference and connected software to plan rover activities a few times a week. This distributed model has worked well since, but it requires the purchase, operation, and maintenance of a dedicated infrastructure at the Jet Propulsion Laboratory. This server infrastructure is costly to operate and the periodic nature of its usage (typically heavy usage for 8 hours every 2 days) has made moving to a cloud based tactical infrastructure an extremely tempting proposition. In this paper we will review both past and current implementations of the tactical planning application focusing on remote plan saving and discuss the unique challenges present with long-latency, distributed operations. We then detail the motivations behind our move to cloud based computing services and as well as our system design and implementation. We will discuss security and reliability concerns and how they were addressed

Executable research compendia in geoscience research infrastructures

NASA Astrophysics Data System (ADS)

Nüst, Daniel

2017-04-01

From generation through analysis and collaboration to communication, scientific research requires the right tools. Scientists create their own software using third party libraries and platforms. Cloud computing, Open Science, public data infrastructures, and Open Source enable scientists with unprecedented opportunites, nowadays often in a field "Computational X" (e.g. computational seismology) or X-informatics (e.g. geoinformatics) [0]. This increases complexity and generates more innovation, e.g. Environmental Research Infrastructures (environmental RIs [1]). Researchers in Computational X write their software relying on both source code (e.g. from https://github.com) and binary libraries (e.g. from package managers such as APT, https://wiki.debian.org/Apt, or CRAN, https://cran.r-project.org/). They download data from domain specific (cf. https://re3data.org) or generic (e.g. https://zenodo.org) data repositories, and deploy computations remotely (e.g. European Open Science Cloud). The results themselves are archived, given persistent identifiers, connected to other works (e.g. using https://orcid.org/), and listed in metadata catalogues. A single researcher, intentionally or not, interacts with all sub-systems of RIs: data acquisition, data access, data processing, data curation, and community support [3]. To preserve computational research [3] proposes the Executable Research Compendium (ERC), a container format closing the gap of dependency preservation by encapsulating the runtime environment. ERCs and RIs can be integrated for different uses: (i) Coherence: ERC services validate completeness, integrity and results (ii) Metadata: ERCs connect the different parts of a piece of research and faciliate discovery (iii) Exchange and Preservation: ERC as usable building blocks are the shared and archived entity (iv) Self-consistency: ERCs remove dependence on ephemeral sources (v) Execution: ERC services create and execute a packaged analysis but integrate with existing platforms for display and control These integrations are vital for capturing workflows in RIs and connect key stakeholders (scientists, publishers, librarians). They are demonstrated using developments by the DFG-funded project Opening Reproducible Research (http://o2r.info). Semi-automatic creation of ERCs based on research workflows is a core goal of the project. References [0] Tony Hey, Stewart Tansley, Kristin Tolle (eds), 2009. The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research. [1] P. Martin et al., Open Information Linking for Environmental Research Infrastructures, 2015 IEEE 11th International Conference on e-Science, Munich, 2015, pp. 513-520. doi: 10.1109/eScience.2015.66 [2] Y. Chen et al., Analysis of Common Requirements for Environmental Science Research Infrastructures, The International Symposium on Grids and Clouds (ISGC) 2013, Taipei, 2013, http://pos.sissa.it/archive/conferences/179/032/ISGC [3] Opening Reproducible Research, Geophysical Research Abstracts Vol. 18, EGU2016-7396, 2016, http://meetingorganizer.copernicus.org/EGU2016/EGU2016-7396.pdf

Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ondrej Linda; Todd Vollmer; Jason Wright

Resiliency and security in critical infrastructure control systems in the modern world of cyber terrorism constitute a relevant concern. Developing a network security system specifically tailored to the requirements of such critical assets is of a primary importance. This paper proposes a novel learning algorithm for anomaly based network security cyber sensor together with its hardware implementation. The presented learning algorithm constructs a fuzzy logic rule based model of normal network behavior. Individual fuzzy rules are extracted directly from the stream of incoming packets using an online clustering algorithm. This learning algorithm was specifically developed to comply with the constrainedmore » computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental test-bed mimicking the environment of a critical infrastructure control system.« less

Information technology developments within the national biological information infrastructure

USGS Publications Warehouse

Cotter, G.; Frame, M.T.

2000-01-01

Looking out an office window or exploring a community park, one can easily see the tremendous challenges that biological information presents the computer science community. Biological information varies in format and content depending whether or not it is information pertaining to a particular species (i.e. Brown Tree Snake), or a specific ecosystem, which often includes multiple species, land use characteristics, and geospatially referenced information. The complexity and uniqueness of each individual species or ecosystem do not easily lend themselves to today's computer science tools and applications. To address the challenges that the biological enterprise presents the National Biological Information Infrastructure (NBII) (http://www.nbii.gov) was established in 1993. The NBII is designed to address these issues on a National scale within the United States, and through international partnerships abroad. This paper discusses current computer science efforts within the National Biological Information Infrastructure Program and future computer science research endeavors that are needed to address the ever-growing issues related to our Nation's biological concerns.

EGI-EUDAT integration activity - Pair data and high-throughput computing resources together

NASA Astrophysics Data System (ADS)

Scardaci, Diego; Viljoen, Matthew; Vitlacil, Dejan; Fiameni, Giuseppe; Chen, Yin; sipos, Gergely; Ferrari, Tiziana

2016-04-01

EGI (www.egi.eu) is a publicly funded e-infrastructure put together to give scientists access to more than 530,000 logical CPUs, 200 PB of disk capacity and 300 PB of tape storage to drive research and innovation in Europe. The infrastructure provides both high throughput computing and cloud compute/storage capabilities. Resources are provided by about 350 resource centres which are distributed across 56 countries in Europe, the Asia-Pacific region, Canada and Latin America. EUDAT (www.eudat.eu) is a collaborative Pan-European infrastructure providing research data services, training and consultancy for researchers, research communities, research infrastructures and data centres. EUDAT's vision is to enable European researchers and practitioners from any research discipline to preserve, find, access, and process data in a trusted environment, as part of a Collaborative Data Infrastructure (CDI) conceived as a network of collaborating, cooperating centres, combining the richness of numerous community-specific data repositories with the permanence and persistence of some of Europe's largest scientific data centres. EGI and EUDAT, in the context of their flagship projects, EGI-Engage and EUDAT2020, started in March 2015 a collaboration to harmonise the two infrastructures, including technical interoperability, authentication, authorisation and identity management, policy and operations. The main objective of this work is to provide end-users with a seamless access to an integrated infrastructure offering both EGI and EUDAT services and, then, pairing data and high-throughput computing resources together. To define the roadmap of this collaboration, EGI and EUDAT selected a set of relevant user communities, already collaborating with both infrastructures, which could bring requirements and help to assign the right priorities to each of them. In this way, from the beginning, this activity has been really driven by the end users. The identified user communities are relevant European Research infrastructure in the field of Earth Science (EPOS and ICOS), Bioinformatics (BBMRI and ELIXIR) and Space Physics (EISCAT-3D). The first outcome of this activity has been the definition of a generic use case that captures the typical user scenario with respect the integrated use of the EGI and EUDAT infrastructures. This generic use case allows a user to instantiate a set of Virtual Machine images on the EGI Federated Cloud to perform computational jobs that analyse data previously stored on EUDAT long-term storage systems. The results of such analysis can be staged back to EUDAT storages, and if needed, allocated with Permanent identifyers (PIDs) for future use. The implementation of this generic use case requires the following integration activities between EGI and EUDAT: (1) harmonisation of the user authentication and authorisation models, (2) implementing interface connectors between the relevant EGI and EUDAT services, particularly EGI Cloud compute facilities and EUDAT long-term storage and PID systems. In the presentation, the collected user requirements and the implementation status of the universal use case will be showed. Furthermore, how the universal use case is currently applied to satisfy EPOS and ICOS needs will be described.

CLON: Overlay Networks and Gossip Protocols for Cloud Environments

NASA Astrophysics Data System (ADS)

Matos, Miguel; Sousa, António; Pereira, José; Oliveira, Rui; Deliot, Eric; Murray, Paul

Although epidemic or gossip-based multicast is a robust and scalable approach to reliable data dissemination, its inherent redundancy results in high resource consumption on both links and nodes. This problem is aggravated in settings that have costlier or resource constrained links as happens in Cloud Computing infrastructures composed by several interconnected data centers across the globe.

Feasibility of Cloud Computing Implementation for eLearning in Secondary Schools in Tanzania

ERIC Educational Resources Information Center

Mwakisole, Kennedy F.; Kissaka, Mussa M.; Mtebe, Joel S.

2018-01-01

This article assessed the feasibility of implementing eLearning systems in a cloud-based infrastructure for secondary schools in Tanzania. The study adopted questionnaire and document reviews as data collection tools. A total of 820 students successfully returned the questionnaire from seven secondary schools in Tanzania. The study found that 11%…

Advanced Decentralized Water/Energy Network Design for Sustainable Infrastructure presentation at the 2012 National Association of Home Builders (NAHB) International Builders'Show

EPA Science Inventory

A university/industry panel will report on the progress and findings of a fivesteve-year project funded by the US Environmental Protection Agency. The project's end product will be a Web-based, 3D computer-simulated residential environment with a decision support system to assist...

High-throughput neuroimaging-genetics computational infrastructure

PubMed Central

Dinov, Ivo D.; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Hobel, Sam; Vespa, Paul; Woo Moon, Seok; Van Horn, John D.; Franco, Joseph; Toga, Arthur W.

2014-01-01

Many contemporary neuroscientific investigations face significant challenges in terms of data management, computational processing, data mining, and results interpretation. These four pillars define the core infrastructure necessary to plan, organize, orchestrate, validate, and disseminate novel scientific methods, computational resources, and translational healthcare findings. Data management includes protocols for data acquisition, archival, query, transfer, retrieval, and aggregation. Computational processing involves the necessary software, hardware, and networking infrastructure required to handle large amounts of heterogeneous neuroimaging, genetics, clinical, and phenotypic data and meta-data. Data mining refers to the process of automatically extracting data features, characteristics and associations, which are not readily visible by human exploration of the raw dataset. Result interpretation includes scientific visualization, community validation of findings and reproducible findings. In this manuscript we describe the novel high-throughput neuroimaging-genetics computational infrastructure available at the Institute for Neuroimaging and Informatics (INI) and the Laboratory of Neuro Imaging (LONI) at University of Southern California (USC). INI and LONI include ultra-high-field and standard-field MRI brain scanners along with an imaging-genetics database for storing the complete provenance of the raw and derived data and meta-data. In addition, the institute provides a large number of software tools for image and shape analysis, mathematical modeling, genomic sequence processing, and scientific visualization. A unique feature of this architecture is the Pipeline environment, which integrates the data management, processing, transfer, and visualization. Through its client-server architecture, the Pipeline environment provides a graphical user interface for designing, executing, monitoring validating, and disseminating of complex protocols that utilize diverse suites of software tools and web-services. These pipeline workflows are represented as portable XML objects which transfer the execution instructions and user specifications from the client user machine to remote pipeline servers for distributed computing. Using Alzheimer's and Parkinson's data, we provide several examples of translational applications using this infrastructure1. PMID:24795619

Role of the ATLAS Grid Information System (AGIS) in Distributed Data Analysis and Simulation

NASA Astrophysics Data System (ADS)

Anisenkov, A. V.

2018-03-01

In modern high-energy physics experiments, particular attention is paid to the global integration of information and computing resources into a unified system for efficient storage and processing of experimental data. Annually, the ATLAS experiment performed at the Large Hadron Collider at the European Organization for Nuclear Research (CERN) produces tens of petabytes raw data from the recording electronics and several petabytes of data from the simulation system. For processing and storage of such super-large volumes of data, the computing model of the ATLAS experiment is based on heterogeneous geographically distributed computing environment, which includes the worldwide LHC computing grid (WLCG) infrastructure and is able to meet the requirements of the experiment for processing huge data sets and provide a high degree of their accessibility (hundreds of petabytes). The paper considers the ATLAS grid information system (AGIS) used by the ATLAS collaboration to describe the topology and resources of the computing infrastructure, to configure and connect the high-level software systems of computer centers, to describe and store all possible parameters, control, configuration, and other auxiliary information required for the effective operation of the ATLAS distributed computing applications and services. The role of the AGIS system in the development of a unified description of the computing resources provided by grid sites, supercomputer centers, and cloud computing into a consistent information model for the ATLAS experiment is outlined. This approach has allowed the collaboration to extend the computing capabilities of the WLCG project and integrate the supercomputers and cloud computing platforms into the software components of the production and distributed analysis workload management system (PanDA, ATLAS).

Towards an advanced e-Infrastructure for Civil Protection applications: Research Strategies and Innovation Guidelines

NASA Astrophysics Data System (ADS)

Mazzetti, P.; Nativi, S.; Verlato, M.; Angelini, V.

2009-04-01

In the context of the EU co-funded project CYCLOPS (http://www.cyclops-project.eu) the problem of designing an advanced e-Infrastructure for Civil Protection (CP) applications has been addressed. As a preliminary step, some studies about European CP systems and operational applications were performed in order to define their specific system requirements. At a higher level it was verified that CP applications are usually conceived to map CP Business Processes involving different levels of processing including data access, data processing, and output visualization. At their core they usually run one or more Earth Science models for information extraction. The traditional approach based on the development of monolithic applications presents some limitations related to flexibility (e.g. the possibility of running the same models with different input data sources, or different models with the same data sources) and scalability (e.g. launching several runs for different scenarios, or implementing more accurate and computing-demanding models). Flexibility can be addressed adopting a modular design based on a SOA and standard services and models, such as OWS and ISO for geospatial services. Distributed computing and storage solutions could improve scalability. Basing on such considerations an architectural framework has been defined. It is made of a Web Service layer providing advanced services for CP applications (e.g. standard geospatial data sharing and processing services) working on the underlying Grid platform. This framework has been tested through the development of prototypes as proof-of-concept. These theoretical studies and proof-of-concept demonstrated that although Grid and geospatial technologies would be able to provide significant benefits to CP applications in terms of scalability and flexibility, current platforms are designed taking into account requirements different from CP. In particular CP applications have strict requirements in terms of: a) Real-Time capabilities, privileging time-of-response instead of accuracy, b) Security services to support complex data policies and trust relationships, c) Interoperability with existing or planned infrastructures (e.g. e-Government, INSPIRE compliant, etc.). Actually these requirements are the main reason why CP applications differ from Earth Science applications. Therefore further research is required to design and implement an advanced e-Infrastructure satisfying those specific requirements. In particular five themes where further research is required were identified: Grid Infrastructure Enhancement, Advanced Middleware for CP Applications, Security and Data Policies, CP Applications Enablement, and Interoperability. For each theme several research topics were proposed and detailed. They are targeted to solve specific problems for the implementation of an effective operational European e-Infrastructure for CP applications.

Towards a single seismological service infrastructure in Europe

NASA Astrophysics Data System (ADS)

Spinuso, A.; Trani, L.; Frobert, L.; Van Eck, T.

2012-04-01

In the last five year services and data providers, within the seismological community in Europe, focused their efforts in migrating the way of opening their archives towards a Service Oriented Architecture (SOA). This process tries to follow pragmatically the technological trends and available solutions aiming at effectively improving all the data stewardship activities. These advancements are possible thanks to the cooperation and the follow-ups of several EC infrastructural projects that, by looking at general purpose techniques, combine their developments envisioning a multidisciplinary platform for the earth observation as the final common objective (EPOS, Earth Plate Observation System) One of the first results of this effort is the Earthquake Data Portal (http://www.seismicportal.eu), which provides a collection of tools to discover, visualize and access a variety of seismological data sets like seismic waveform, accelerometric data, earthquake catalogs and parameters. The Portal offers a cohesive distributed search environment, linking data search and access across multiple data providers through interactive web-services, map-based tools and diverse command-line clients. Our work continues under other EU FP7 projects. Here we will address initiatives in two of those projects. The NERA, (Network of European Research Infrastructures for Earthquake Risk Assessment and Mitigation) project will implement a Common Services Architecture based on OGC services APIs, in order to provide Resource-Oriented common interfaces across the data access and processing services. This will improve interoperability between tools and across projects, enabling the development of higher-level applications that can uniformly access the data and processing services of all participants. This effort will be conducted jointly with the VERCE project (Virtual Earthquake and Seismology Research Community for Europe). VERCE aims to enable seismologists to exploit the wealth of seismic data within a data-intensive computation framework, which will be tailored to the specific needs of the community. It will provide a new interoperable infrastructure, as the computational backbone laying behind the publicly available interfaces. VERCE will have to face the challenges of implementing a service oriented architecture providing an efficient layer between the Data and the Grid infrastructures, coupling HPC data analysis and HPC data modeling applications through the execution of workflows and data sharing mechanism. Online registries of interoperable worklflow components, storage of intermediate results and data provenance are those aspects that are currently under investigations to make the VERCE facilities usable from a large scale of users, data and service providers. For such purposes the adoption of a Digital Object Architecture, to create online catalogs referencing and describing semantically all these distributed resources, such as datasets, computational processes and derivative products, is seen as one of the viable solution to monitor and steer the usage of the infrastructure, increasing its efficiency and the cooperation among the community.

32 CFR 240.4 - Policy.

Code of Federal Regulations, 2012 CFR

2012-07-01

... enterprise information infrastructure requirements. (c) The academic disciplines, with concentrations in IA..., computer systems analysis, cyber operations, cybersecurity, database administration, data management... infrastructure development and academic research to support the DoD IA/IT critical areas of interest. ...

32 CFR 240.4 - Policy.

Code of Federal Regulations, 2013 CFR

2013-07-01

... enterprise information infrastructure requirements. (c) The academic disciplines, with concentrations in IA..., computer systems analysis, cyber operations, cybersecurity, database administration, data management... infrastructure development and academic research to support the DoD IA/IT critical areas of interest. ...

32 CFR 240.4 - Policy.

Code of Federal Regulations, 2014 CFR

2014-07-01

... enterprise information infrastructure requirements. (c) The academic disciplines, with concentrations in IA..., computer systems analysis, cyber operations, cybersecurity, database administration, data management... infrastructure development and academic research to support the DoD IA/IT critical areas of interest. ...

Knowledge-Based Environmental Context Modeling

NASA Astrophysics Data System (ADS)

Pukite, P. R.; Challou, D. J.

2017-12-01

As we move from the oil-age to an energy infrastructure based on renewables, the need arises for new educational tools to support the analysis of geophysical phenomena and their behavior and properties. Our objective is to present models of these phenomena to make them amenable for incorporation into more comprehensive analysis contexts. Starting at the level of a college-level computer science course, the intent is to keep the models tractable and therefore practical for student use. Based on research performed via an open-source investigation managed by DARPA and funded by the Department of Interior [1], we have adapted a variety of physics-based environmental models for a computer-science curriculum. The original research described a semantic web architecture based on patterns and logical archetypal building-blocks (see figure) well suited for a comprehensive environmental modeling framework. The patterns span a range of features that cover specific land, atmospheric and aquatic domains intended for engineering modeling within a virtual environment. The modeling engine contained within the server relied on knowledge-based inferencing capable of supporting formal terminology (through NASA JPL's Semantic Web for Earth and Environmental Technology (SWEET) ontology and a domain-specific language) and levels of abstraction via integrated reasoning modules. One of the key goals of the research was to simplify models that were ordinarily computationally intensive to keep them lightweight enough for interactive or virtual environment contexts. The breadth of the elements incorporated is well-suited for learning as the trend toward ontologies and applying semantic information is vital for advancing an open knowledge infrastructure. As examples of modeling, we have covered such geophysics topics as fossil-fuel depletion, wind statistics, tidal analysis, and terrain modeling, among others. Techniques from the world of computer science will be necessary to promote efficient use of our renewable natural resources. [1] C2M2L (Component, Context, and Manufacturing Model Library) Final Report, https://doi.org/10.13140/RG.2.1.4956.3604

RecceMan: an interactive recognition assistance for image-based reconnaissance: synergistic effects of human perception and computational methods for object recognition, identification, and infrastructure analysis

NASA Astrophysics Data System (ADS)

El Bekri, Nadia; Angele, Susanne; Ruckhäberle, Martin; Peinsipp-Byma, Elisabeth; Haelke, Bruno

2015-10-01

This paper introduces an interactive recognition assistance system for imaging reconnaissance. This system supports aerial image analysts on missions during two main tasks: Object recognition and infrastructure analysis. Object recognition concentrates on the classification of one single object. Infrastructure analysis deals with the description of the components of an infrastructure and the recognition of the infrastructure type (e.g. military airfield). Based on satellite or aerial images, aerial image analysts are able to extract single object features and thereby recognize different object types. It is one of the most challenging tasks in the imaging reconnaissance. Currently, there are no high potential ATR (automatic target recognition) applications available, as consequence the human observer cannot be replaced entirely. State-of-the-art ATR applications cannot assume in equal measure human perception and interpretation. Why is this still such a critical issue? First, cluttered and noisy images make it difficult to automatically extract, classify and identify object types. Second, due to the changed warfare and the rise of asymmetric threats it is nearly impossible to create an underlying data set containing all features, objects or infrastructure types. Many other reasons like environmental parameters or aspect angles compound the application of ATR supplementary. Due to the lack of suitable ATR procedures, the human factor is still important and so far irreplaceable. In order to use the potential benefits of the human perception and computational methods in a synergistic way, both are unified in an interactive assistance system. RecceMan® (Reconnaissance Manual) offers two different modes for aerial image analysts on missions: the object recognition mode and the infrastructure analysis mode. The aim of the object recognition mode is to recognize a certain object type based on the object features that originated from the image signatures. The infrastructure analysis mode pursues the goal to analyze the function of the infrastructure. The image analyst extracts visually certain target object signatures, assigns them to corresponding object features and is finally able to recognize the object type. The system offers him the possibility to assign the image signatures to features given by sample images. The underlying data set contains a wide range of objects features and object types for different domains like ships or land vehicles. Each domain has its own feature tree developed by aerial image analyst experts. By selecting the corresponding features, the possible solution set of objects is automatically reduced and matches only the objects that contain the selected features. Moreover, we give an outlook of current research in the field of ground target analysis in which we deal with partly automated methods to extract image signatures and assign them to the corresponding features. This research includes methods for automatically determining the orientation of an object and geometric features like width and length of the object. This step enables to reduce automatically the possible object types offered to the image analyst by the interactive recognition assistance system.

Architecture Design of Healthcare Software-as-a-Service Platform for Cloud-Based Clinical Decision Support Service

PubMed Central

Oh, Sungyoung; Cha, Jieun; Ji, Myungkyu; Kang, Hyekyung; Kim, Seok; Heo, Eunyoung; Han, Jong Soo; Kang, Hyunggoo; Chae, Hoseok; Hwang, Hee

2015-01-01

Objectives To design a cloud computing-based Healthcare Software-as-a-Service (SaaS) Platform (HSP) for delivering healthcare information services with low cost, high clinical value, and high usability. Methods We analyzed the architecture requirements of an HSP, including the interface, business services, cloud SaaS, quality attributes, privacy and security, and multi-lingual capacity. For cloud-based SaaS services, we focused on Clinical Decision Service (CDS) content services, basic functional services, and mobile services. Microsoft's Azure cloud computing for Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) was used. Results The functional and software views of an HSP were designed in a layered architecture. External systems can be interfaced with the HSP using SOAP and REST/JSON. The multi-tenancy model of the HSP was designed as a shared database, with a separate schema for each tenant through a single application, although healthcare data can be physically located on a cloud or in a hospital, depending on regulations. The CDS services were categorized into rule-based services for medications, alert registration services, and knowledge services. Conclusions We expect that cloud-based HSPs will allow small and mid-sized hospitals, in addition to large-sized hospitals, to adopt information infrastructures and health information technology with low system operation and maintenance costs. PMID:25995962

Computational Materials Science and Chemistry: Accelerating Discovery and Innovation through Simulation-Based Engineering and Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crabtree, George; Glotzer, Sharon; McCurdy, Bill

This report is based on a SC Workshop on Computational Materials Science and Chemistry for Innovation on July 26-27, 2010, to assess the potential of state-of-the-art computer simulations to accelerate understanding and discovery in materials science and chemistry, with a focus on potential impacts in energy technologies and innovation. The urgent demand for new energy technologies has greatly exceeded the capabilities of today's materials and chemical processes. To convert sunlight to fuel, efficiently store energy, or enable a new generation of energy production and utilization technologies requires the development of new materials and processes of unprecedented functionality and performance. Newmore » materials and processes are critical pacing elements for progress in advanced energy systems and virtually all industrial technologies. Over the past two decades, the United States has developed and deployed the world's most powerful collection of tools for the synthesis, processing, characterization, and simulation and modeling of materials and chemical systems at the nanoscale, dimensions of a few atoms to a few hundred atoms across. These tools, which include world-leading x-ray and neutron sources, nanoscale science facilities, and high-performance computers, provide an unprecedented view of the atomic-scale structure and dynamics of materials and the molecular-scale basis of chemical processes. For the first time in history, we are able to synthesize, characterize, and model materials and chemical behavior at the length scale where this behavior is controlled. This ability is transformational for the discovery process and, as a result, confers a significant competitive advantage. Perhaps the most spectacular increase in capability has been demonstrated in high performance computing. Over the past decade, computational power has increased by a factor of a million due to advances in hardware and software. This rate of improvement, which shows no sign of abating, has enabled the development of computer simulations and models of unprecedented fidelity. We are at the threshold of a new era where the integrated synthesis, characterization, and modeling of complex materials and chemical processes will transform our ability to understand and design new materials and chemistries with predictive power. In turn, this predictive capability will transform technological innovation by accelerating the development and deployment of new materials and processes in products and manufacturing. Harnessing the potential of computational science and engineering for the discovery and development of materials and chemical processes is essential to maintaining leadership in these foundational fields that underpin energy technologies and industrial competitiveness. Capitalizing on the opportunities presented by simulation-based engineering and science in materials and chemistry will require an integration of experimental capabilities with theoretical and computational modeling; the development of a robust and sustainable infrastructure to support the development and deployment of advanced computational models; and the assembly of a community of scientists and engineers to implement this integration and infrastructure. This community must extend to industry, where incorporating predictive materials science and chemistry into design tools can accelerate the product development cycle and drive economic competitiveness. The confluence of new theories, new materials synthesis capabilities, and new computer platforms has created an unprecedented opportunity to implement a "materials-by-design" paradigm with wide-ranging benefits in technological innovation and scientific discovery. The Workshop on Computational Materials Science and Chemistry for Innovation was convened in Bethesda, Maryland, on July 26-27, 2010. Sponsored by the Department of Energy (DOE) Offices of Advanced Scientific Computing Research and Basic Energy Sciences, the workshop brought together 160 experts in materials science, chemistry, and computational science representing more than 65 universities, laboratories, and industries, and four agencies. The workshop examined seven foundational challenge areas in materials science and chemistry: materials for extreme conditions, self-assembly, light harvesting, chemical reactions, designer fluids, thin films and interfaces, and electronic structure. Each of these challenge areas is critical to the development of advanced energy systems, and each can be accelerated by the integrated application of predictive capability with theory and experiment. The workshop concluded that emerging capabilities in predictive modeling and simulation have the potential to revolutionize the development of new materials and chemical processes. Coupled with world-leading materials characterization and nanoscale science facilities, this predictive capability provides the foundation for an innovation ecosystem that can accelerate the discovery, development, and deployment of new technologies, including advanced energy systems. Delivering on the promise of this innovation ecosystem requires the following: Integration of synthesis, processing, characterization, theory, and simulation and modeling. Many of the newly established Energy Frontier Research Centers and Energy Hubs are exploiting this integration. Achieving/strengthening predictive capability in foundational challenge areas. Predictive capability in the seven foundational challenge areas described in this report is critical to the development of advanced energy technologies. Developing validated computational approaches that span vast differences in time and length scales. This fundamental computational challenge crosscuts all of the foundational challenge areas. Similarly challenging is coupling of analytical data from multiple instruments and techniques that are required to link these length and time scales. Experimental validation and quantification of uncertainty in simulation and modeling. Uncertainty quantification becomes increasingly challenging as simulations become more complex. Robust and sustainable computational infrastructure, including software and applications. For modeling and simulation, software equals infrastructure. To validate the computational tools, software is critical infrastructure that effectively translates huge arrays of experimental data into useful scientific understanding. An integrated approach for managing this infrastructure is essential. Efficient transfer and incorporation of simulation-based engineering and science in industry. Strategies for bridging the gap between research and industrial applications and for widespread industry adoption of integrated computational materials engineering are needed.« less

Probability Distributome: A Web Computational Infrastructure for Exploring the Properties, Interrelations, and Applications of Probability Distributions.

PubMed

Dinov, Ivo D; Siegrist, Kyle; Pearl, Dennis K; Kalinin, Alexandr; Christou, Nicolas

2016-06-01

Probability distributions are useful for modeling, simulation, analysis, and inference on varieties of natural processes and physical phenomena. There are uncountably many probability distributions. However, a few dozen families of distributions are commonly defined and are frequently used in practice for problem solving, experimental applications, and theoretical studies. In this paper, we present a new computational and graphical infrastructure, the Distributome , which facilitates the discovery, exploration and application of diverse spectra of probability distributions. The extensible Distributome infrastructure provides interfaces for (human and machine) traversal, search, and navigation of all common probability distributions. It also enables distribution modeling, applications, investigation of inter-distribution relations, as well as their analytical representations and computational utilization. The entire Distributome framework is designed and implemented as an open-source, community-built, and Internet-accessible infrastructure. It is portable, extensible and compatible with HTML5 and Web2.0 standards (http://Distributome.org). We demonstrate two types of applications of the probability Distributome resources: computational research and science education. The Distributome tools may be employed to address five complementary computational modeling applications (simulation, data-analysis and inference, model-fitting, examination of the analytical, mathematical and computational properties of specific probability distributions, and exploration of the inter-distributional relations). Many high school and college science, technology, engineering and mathematics (STEM) courses may be enriched by the use of modern pedagogical approaches and technology-enhanced methods. The Distributome resources provide enhancements for blended STEM education by improving student motivation, augmenting the classical curriculum with interactive webapps, and overhauling the learning assessment protocols.

Probability Distributome: A Web Computational Infrastructure for Exploring the Properties, Interrelations, and Applications of Probability Distributions

PubMed Central

Dinov, Ivo D.; Siegrist, Kyle; Pearl, Dennis K.; Kalinin, Alexandr; Christou, Nicolas

2015-01-01

Probability distributions are useful for modeling, simulation, analysis, and inference on varieties of natural processes and physical phenomena. There are uncountably many probability distributions. However, a few dozen families of distributions are commonly defined and are frequently used in practice for problem solving, experimental applications, and theoretical studies. In this paper, we present a new computational and graphical infrastructure, the Distributome, which facilitates the discovery, exploration and application of diverse spectra of probability distributions. The extensible Distributome infrastructure provides interfaces for (human and machine) traversal, search, and navigation of all common probability distributions. It also enables distribution modeling, applications, investigation of inter-distribution relations, as well as their analytical representations and computational utilization. The entire Distributome framework is designed and implemented as an open-source, community-built, and Internet-accessible infrastructure. It is portable, extensible and compatible with HTML5 and Web2.0 standards (http://Distributome.org). We demonstrate two types of applications of the probability Distributome resources: computational research and science education. The Distributome tools may be employed to address five complementary computational modeling applications (simulation, data-analysis and inference, model-fitting, examination of the analytical, mathematical and computational properties of specific probability distributions, and exploration of the inter-distributional relations). Many high school and college science, technology, engineering and mathematics (STEM) courses may be enriched by the use of modern pedagogical approaches and technology-enhanced methods. The Distributome resources provide enhancements for blended STEM education by improving student motivation, augmenting the classical curriculum with interactive webapps, and overhauling the learning assessment protocols. PMID:27158191

Spatial data analytics on heterogeneous multi- and many-core parallel architectures using python

USGS Publications Warehouse

Laura, Jason R.; Rey, Sergio J.

2017-01-01

Parallel vector spatial analysis concerns the application of parallel computational methods to facilitate vector-based spatial analysis. The history of parallel computation in spatial analysis is reviewed, and this work is placed into the broader context of high-performance computing (HPC) and parallelization research. The rise of cyber infrastructure and its manifestation in spatial analysis as CyberGIScience is seen as a main driver of renewed interest in parallel computation in the spatial sciences. Key problems in spatial analysis that have been the focus of parallel computing are covered. Chief among these are spatial optimization problems, computational geometric problems including polygonization and spatial contiguity detection, the use of Monte Carlo Markov chain simulation in spatial statistics, and parallel implementations of spatial econometric methods. Future directions for research on parallelization in computational spatial analysis are outlined.

A Comprehensive and Cost-Effective Computer Infrastructure for K-12 Schools

NASA Technical Reports Server (NTRS)

Warren, G. P.; Seaton, J. M.

1996-01-01

Since 1993, NASA Langley Research Center has been developing and implementing a low-cost Internet connection model, including system architecture, training, and support, to provide Internet access for an entire network of computers. This infrastructure allows local area networks which exceed 50 machines per school to independently access the complete functionality of the Internet by connecting to a central site, using state-of-the-art commercial modem technology, through a single standard telephone line. By locating high-cost resources at this central site and sharing these resources and their costs among the school districts throughout a region, a practical, efficient, and affordable infrastructure for providing scale-able Internet connectivity has been developed. As the demand for faster Internet access grows, the model has a simple expansion path that eliminates the need to replace major system components and re-train personnel. Observations of optical Internet usage within an environment, particularly school classrooms, have shown that after an initial period of 'surfing,' the Internet traffic becomes repetitive. By automatically storing requested Internet information on a high-capacity networked disk drive at the local site (network based disk caching), then updating this information only when it changes, well over 80 percent of the Internet traffic that leaves a location can be eliminated by retrieving the information from the local disk cache.

Subtlenoise: sonification of distributed computing operations

NASA Astrophysics Data System (ADS)

Love, P. A.

2015-12-01

The operation of distributed computing systems requires comprehensive monitoring to ensure reliability and robustness. There are two components found in most monitoring systems: one being visually rich time-series graphs and another being notification systems for alerting operators under certain pre-defined conditions. In this paper the sonification of monitoring messages is explored using an architecture that fits easily within existing infrastructures based on mature opensource technologies such as ZeroMQ, Logstash, and Supercollider (a synth engine). Message attributes are mapped onto audio attributes based on broad classification of the message (continuous or discrete metrics) but keeping the audio stream subtle in nature. The benefits of audio rendering are described in the context of distributed computing operations and may provide a less intrusive way to understand the operational health of these systems.

Advanced Artificial Science. The development of an artificial science and engineering research infrastructure to facilitate innovative computational modeling, analysis, and application to interdisciplinary areas of scientific investigation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saffer, Shelley

2014-12-01

This is a final report of the DOE award DE-SC0001132, Advanced Artificial Science. The development of an artificial science and engineering research infrastructure to facilitate innovative computational modeling, analysis, and application to interdisciplinary areas of scientific investigation. This document describes the achievements of the goals, and resulting research made possible by this award.

GSDC: A Unique Data Center in Korea for HEP research

NASA Astrophysics Data System (ADS)

Ahn, Sang-Un

2017-04-01

Global Science experimental Data hub Center (GSDC) at Korea Institute of Science and Technology Information (KISTI) is a unique data center in South Korea established for promoting the fundamental research fields by supporting them with the expertise on Information and Communication Technology (ICT) and the infrastructure for High Performance Computing (HPC), High Throughput Computing (HTC) and Networking. GSDC has supported various research fields in South Korea dealing with the large scale of data, e.g. RENO experiment for neutrino research, LIGO experiment for gravitational wave detection, Genome sequencing project for bio-medical, and HEP experiments such as CDF at FNAL, Belle at KEK, and STAR at BNL. In particular, GSDC has run a Tier-1 center for ALICE experiment using the LHC at CERN since 2013. In this talk, we present the overview on computing infrastructure that GSDC runs for the research fields and we discuss on the data center infrastructure management system deployed at GSDC.

First results from a combined analysis of CERN computing infrastructure metrics

NASA Astrophysics Data System (ADS)

Duellmann, Dirk; Nieke, Christian

2017-10-01

The IT Analysis Working Group (AWG) has been formed at CERN across individual computing units and the experiments to attempt a cross cutting analysis of computing infrastructure and application metrics. In this presentation we will describe the first results obtained using medium/long term data (1 months — 1 year) correlating box level metrics, job level metrics from LSF and HTCondor, IO metrics from the physics analysis disk pools (EOS) and networking and application level metrics from the experiment dashboards. We will cover in particular the measurement of hardware performance and prediction of job duration, the latency sensitivity of different job types and a search for bottlenecks with the production job mix in the current infrastructure. The presentation will conclude with the proposal of a small set of metrics to simplify drawing conclusions also in the more constrained environment of public cloud deployments.

VERCE, Virtual Earthquake and Seismology Research Community in Europe, a new ESFRI initiative integrating data infrastructure, Grid and HPC infrastructures for data integration, data analysis and data modeling in seismology

NASA Astrophysics Data System (ADS)

van Hemert, Jano; Vilotte, Jean-Pierre

2010-05-01

Research in earthquake and seismology addresses fundamental problems in understanding Earth's internal wave sources and structures, and augment applications to societal concerns about natural hazards, energy resources and environmental change. This community is central to the European Plate Observing System (EPOS)—the ESFRI initiative in solid Earth Sciences. Global and regional seismology monitoring systems are continuously operated and are transmitting a growing wealth of data from Europe and from around the world. These tremendous volumes of seismograms, i.e., records of ground motions as a function of time, have a definite multi-use attribute, which puts a great premium on open-access data infrastructures that are integrated globally. In Europe, the earthquake and seismology community is part of the European Integrated Data Archives (EIDA) infrastructure and is structured as "horizontal" data services. On top of this distributed data archive system, the community has developed recently within the EC project NERIES advanced SOA-based web services and a unified portal system. Enabling advanced analysis of these data by utilising a data-aware distributed computing environment is instrumental to fully exploit the cornucopia of data and to guarantee optimal operation of the high-cost monitoring facilities. The strategy of VERCE is driven by the needs of data-intensive applications in data mining and modelling and will be illustrated through a set of applications. It aims to provide a comprehensive architecture and framework adapted to the scale and the diversity of these applications, and to integrate the community data infrastructure with Grid and HPC infrastructures. A first novel aspect is a service-oriented architecture that provides well-equipped integrated workbenches, with an efficient communication layer between data and Grid infrastructures, augmented with bridges to the HPC facilities. A second novel aspect is the coupling between Grid data analysis and HPC data modelling applications through workflow and data sharing mechanisms. VERCE will develop important interactions with the European infrastructure initiatives in Grid and HPC computing. The VERCE team: CNRS-France (IPG Paris, LGIT Grenoble), UEDIN (UK), KNMI-ORFEUS (Holland), EMSC, INGV (Italy), LMU (Germany), ULIV (UK), BADW-LRZ (Germany), SCAI (Germany), CINECA (Italy)

NAS infrastructure management system build 1.5 computer-human interface

DOT National Transportation Integrated Search

2001-01-01

Human factors engineers from the National Airspace System (NAS) Human Factors Branch (ACT-530) of the Federal Aviation Administration William J. Hughes Technical Center conducted an evaluation of the NAS Infrastructure Management System (NIMS) Build ...

Do regions of ALICE matter? Social relationships and data exchanges in the Grid

NASA Astrophysics Data System (ADS)

Widmer, E. D.; Carminati, F.; Grigoras, C.; Viry, G.; Galli Carminati, G.

2012-06-01

Following a previous publication [1], this study aims at investigating the impact of regional affiliations of centres on the organisation of collaboration within the Distributed Computing ALICE infrastructure, based on social networks methods. A self-administered questionnaire was sent to all centre managers about support, email interactions and wished collaborations in the infrastructure. Several additional measures, stemming from technical observations were produced, such as bandwidth, data transfers and Internet Round Trip Time (RTT) were also included. Information for 50 centres were considered (60% response rate). Empirical analysis shows that despite the centralisation on CERN, the network is highly organised by regions. The results are discussed in the light of policy and efficiency issues.

Do regions matter in ALICE?. Social relationships and data exchanges in the Grid

NASA Astrophysics Data System (ADS)

Widmer, E. D.; Viry, G.; Carminati, F.; Galli-Carminati, G.

2012-02-01

This study aims at investigating the impact of regional affiliations of centres on the organisation of collaborations within the Distributed Computing ALICE infrastructure, based on social networks methods. A self-administered questionnaire was sent to all centre managers about support, email interactions and wished collaborations in the infrastructure. Several additional measures, stemming from technical observations were collected, such as bandwidth, data transfers and Internet Round Trip Time (RTT) were also included. Information for 50 centres were considered (about 70% response rate). Empirical analysis shows that despite the centralisation on CERN, the network is highly organised by regions. The results are discussed in the light of policy and efficiency issues.

Automatically generated code for relativistic inhomogeneous cosmologies

NASA Astrophysics Data System (ADS)

Bentivegna, Eloisa

2017-02-01

The applications of numerical relativity to cosmology are on the rise, contributing insight into such cosmological problems as structure formation, primordial phase transitions, gravitational-wave generation, and inflation. In this paper, I present the infrastructure for the computation of inhomogeneous dust cosmologies which was used recently to measure the effect of nonlinear inhomogeneity on the cosmic expansion rate. I illustrate the code's architecture, provide evidence for its correctness in a number of familiar cosmological settings, and evaluate its parallel performance for grids of up to several billion points. The code, which is available as free software, is based on the Einstein Toolkit infrastructure, and in particular leverages the automated code generation capabilities provided by its component Kranc.

Development of a cloud-based Bioinformatics Training Platform.

PubMed

Revote, Jerico; Watson-Haigh, Nathan S; Quenette, Steve; Bethwaite, Blair; McGrath, Annette; Shang, Catherine A

2017-05-01

The Bioinformatics Training Platform (BTP) has been developed to provide access to the computational infrastructure required to deliver sophisticated hands-on bioinformatics training courses. The BTP is a cloud-based solution that is in active use for delivering next-generation sequencing training to Australian researchers at geographically dispersed locations. The BTP was built to provide an easy, accessible, consistent and cost-effective approach to delivering workshops at host universities and organizations with a high demand for bioinformatics training but lacking the dedicated bioinformatics training suites required. To support broad uptake of the BTP, the platform has been made compatible with multiple cloud infrastructures. The BTP is an open-source and open-access resource. To date, 20 training workshops have been delivered to over 700 trainees at over 10 venues across Australia using the BTP. © The Author 2016. Published by Oxford University Press.

Development of a cloud-based Bioinformatics Training Platform

PubMed Central

Revote, Jerico; Watson-Haigh, Nathan S.; Quenette, Steve; Bethwaite, Blair; McGrath, Annette

2017-01-01

Abstract The Bioinformatics Training Platform (BTP) has been developed to provide access to the computational infrastructure required to deliver sophisticated hands-on bioinformatics training courses. The BTP is a cloud-based solution that is in active use for delivering next-generation sequencing training to Australian researchers at geographically dispersed locations. The BTP was built to provide an easy, accessible, consistent and cost-effective approach to delivering workshops at host universities and organizations with a high demand for bioinformatics training but lacking the dedicated bioinformatics training suites required. To support broad uptake of the BTP, the platform has been made compatible with multiple cloud infrastructures. The BTP is an open-source and open-access resource. To date, 20 training workshops have been delivered to over 700 trainees at over 10 venues across Australia using the BTP. PMID:27084333

Sustainable Cooperative Robotic Technologies for Human and Robotic Outpost Infrastructure Construction and Maintenance

NASA Technical Reports Server (NTRS)

Stroupe, Ashley W.; Okon, Avi; Robinson, Matthew; Huntsberger, Terry; Aghazarian, Hrand; Baumgartner, Eric

2004-01-01

Robotic Construction Crew (RCC) is a heterogeneous multi-robot system for autonomous acquisition, transport, and precision mating of components in construction tasks. RCC minimizes resources constrained in a space environment such as computation, power, communication and, sensing. A behavior-based architecture provides adaptability and robustness despite low computational requirements. RCC successfully performs several construction related tasks in an emulated outdoor environment despite high levels of uncertainty in motions and sensing. Quantitative results are provided for formation keeping in component transport, precision instrument placement, and construction tasks.

Design and Development of a Run-Time Monitor for Multi-Core Architectures in Cloud Computing

PubMed Central

Kang, Mikyung; Kang, Dong-In; Crago, Stephen P.; Park, Gyung-Leen; Lee, Junghoon

2011-01-01

Cloud computing is a new information technology trend that moves computing and data away from desktops and portable PCs into large data centers. The basic principle of cloud computing is to deliver applications as services over the Internet as well as infrastructure. A cloud is a type of parallel and distributed system consisting of a collection of inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resources. The large-scale distributed applications on a cloud require adaptive service-based software, which has the capability of monitoring system status changes, analyzing the monitored information, and adapting its service configuration while considering tradeoffs among multiple QoS features simultaneously. In this paper, we design and develop a Run-Time Monitor (RTM) which is a system software to monitor the application behavior at run-time, analyze the collected information, and optimize cloud computing resources for multi-core architectures. RTM monitors application software through library instrumentation as well as underlying hardware through a performance counter optimizing its computing configuration based on the analyzed data. PMID:22163811

Design and development of a run-time monitor for multi-core architectures in cloud computing.

PubMed

Kang, Mikyung; Kang, Dong-In; Crago, Stephen P; Park, Gyung-Leen; Lee, Junghoon

2011-01-01

Cloud computing is a new information technology trend that moves computing and data away from desktops and portable PCs into large data centers. The basic principle of cloud computing is to deliver applications as services over the Internet as well as infrastructure. A cloud is a type of parallel and distributed system consisting of a collection of inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resources. The large-scale distributed applications on a cloud require adaptive service-based software, which has the capability of monitoring system status changes, analyzing the monitored information, and adapting its service configuration while considering tradeoffs among multiple QoS features simultaneously. In this paper, we design and develop a Run-Time Monitor (RTM) which is a system software to monitor the application behavior at run-time, analyze the collected information, and optimize cloud computing resources for multi-core architectures. RTM monitors application software through library instrumentation as well as underlying hardware through a performance counter optimizing its computing configuration based on the analyzed data.

About Distributed Simulation-based Optimization of Forming Processes using a Grid Architecture

NASA Astrophysics Data System (ADS)

Grauer, Manfred; Barth, Thomas

2004-06-01

Permanently increasing complexity of products and their manufacturing processes combined with a shorter "time-to-market" leads to more and more use of simulation and optimization software systems for product design. Finding a "good" design of a product implies the solution of computationally expensive optimization problems based on the results of simulation. Due to the computational load caused by the solution of these problems, the requirements on the Information&Telecommunication (IT) infrastructure of an enterprise or research facility are shifting from stand-alone resources towards the integration of software and hardware resources in a distributed environment for high-performance computing. Resources can either comprise software systems, hardware systems, or communication networks. An appropriate IT-infrastructure must provide the means to integrate all these resources and enable their use even across a network to cope with requirements from geographically distributed scenarios, e.g. in computational engineering and/or collaborative engineering. Integrating expert's knowledge into the optimization process is inevitable in order to reduce the complexity caused by the number of design variables and the high dimensionality of the design space. Hence, utilization of knowledge-based systems must be supported by providing data management facilities as a basis for knowledge extraction from product data. In this paper, the focus is put on a distributed problem solving environment (PSE) capable of providing access to a variety of necessary resources and services. A distributed approach integrating simulation and optimization on a network of workstations and cluster systems is presented. For geometry generation the CAD-system CATIA is used which is coupled with the FEM-simulation system INDEED for simulation of sheet-metal forming processes and the problem solving environment OpTiX for distributed optimization.

A prototype Infrastructure for Cloud-based distributed services in High Availability over WAN

NASA Astrophysics Data System (ADS)

Bulfon, C.; Carlino, G.; De Salvo, A.; Doria, A.; Graziosi, C.; Pardi, S.; Sanchez, A.; Carboni, M.; Bolletta, P.; Puccio, L.; Capone, V.; Merola, L.

2015-12-01

In this work we present the architectural and performance studies concerning a prototype of a distributed Tier2 infrastructure for HEP, instantiated between the two Italian sites of INFN-Romal and INFN-Napoli. The network infrastructure is based on a Layer-2 geographical link, provided by the Italian NREN (GARR), directly connecting the two remote LANs of the named sites. By exploiting the possibilities offered by the new distributed file systems, a shared storage area with synchronous copy has been set up. The computing infrastructure, based on an OpenStack facility, is using a set of distributed Hypervisors installed in both sites. The main parameter to be taken into account when managing two remote sites with a single framework is the effect of the latency, due to the distance and the end-to-end service overhead. In order to understand the capabilities and limits of our setup, the impact of latency has been investigated by means of a set of stress tests, including data I/O throughput, metadata access performance evaluation and network occupancy, during the life cycle of a Virtual Machine. A set of resilience tests has also been performed, in order to verify the stability of the system on the event of hardware or software faults. The results of this work show that the reliability and robustness of the chosen architecture are effective enough to build a production system and to provide common services. This prototype can also be extended to multiple sites with small changes of the network topology, thus creating a National Network of Cloud-based distributed services, in HA over WAN.

Infrastructure sensing.

PubMed

Soga, Kenichi; Schooling, Jennifer

2016-08-06

Design, construction, maintenance and upgrading of civil engineering infrastructure requires fresh thinking to minimize use of materials, energy and labour. This can only be achieved by understanding the performance of the infrastructure, both during its construction and throughout its design life, through innovative monitoring. Advances in sensor systems offer intriguing possibilities to radically alter methods of condition assessment and monitoring of infrastructure. In this paper, it is hypothesized that the future of infrastructure relies on smarter information; the rich information obtained from embedded sensors within infrastructure will act as a catalyst for new design, construction, operation and maintenance processes for integrated infrastructure systems linked directly with user behaviour patterns. Some examples of emerging sensor technologies for infrastructure sensing are given. They include distributed fibre-optics sensors, computer vision, wireless sensor networks, low-power micro-electromechanical systems, energy harvesting and citizens as sensors.

Infrastructure sensing

PubMed Central

Soga, Kenichi; Schooling, Jennifer

2016-01-01

Design, construction, maintenance and upgrading of civil engineering infrastructure requires fresh thinking to minimize use of materials, energy and labour. This can only be achieved by understanding the performance of the infrastructure, both during its construction and throughout its design life, through innovative monitoring. Advances in sensor systems offer intriguing possibilities to radically alter methods of condition assessment and monitoring of infrastructure. In this paper, it is hypothesized that the future of infrastructure relies on smarter information; the rich information obtained from embedded sensors within infrastructure will act as a catalyst for new design, construction, operation and maintenance processes for integrated infrastructure systems linked directly with user behaviour patterns. Some examples of emerging sensor technologies for infrastructure sensing are given. They include distributed fibre-optics sensors, computer vision, wireless sensor networks, low-power micro-electromechanical systems, energy harvesting and citizens as sensors. PMID:27499845

On the convergence of nanotechnology and Big Data analysis for computer-aided diagnosis.

PubMed

Rodrigues, Jose F; Paulovich, Fernando V; de Oliveira, Maria Cf; de Oliveira, Osvaldo N

2016-04-01

An overview is provided of the challenges involved in building computer-aided diagnosis systems capable of precise medical diagnostics based on integration and interpretation of data from different sources and formats. The availability of massive amounts of data and computational methods associated with the Big Data paradigm has brought hope that such systems may soon be available in routine clinical practices, which is not the case today. We focus on visual and machine learning analysis of medical data acquired with varied nanotech-based techniques and on methods for Big Data infrastructure. Because diagnosis is essentially a classification task, we address the machine learning techniques with supervised and unsupervised classification, making a critical assessment of the progress already made in the medical field and the prospects for the near future. We also advocate that successful computer-aided diagnosis requires a merge of methods and concepts from nanotechnology and Big Data analysis.

Cloudbursting - Solving the 3-body problem

NASA Astrophysics Data System (ADS)

Chang, G.; Heistand, S.; Vakhnin, A.; Huang, T.; Zimdars, P.; Hua, H.; Hood, R.; Koenig, J.; Mehrotra, P.; Little, M. M.; Law, E.

2014-12-01

Many science projects in the future will be accomplished through collaboration among 2 or more NASA centers along with, potentially, external scientists. Science teams will be composed of more geographically dispersed individuals and groups. However, the current computing environment does not make this easy and seamless. By being able to share computing resources among members of a multi-center team working on a science/ engineering project, limited pre-competition funds could be more efficiently applied and technical work could be conducted more effectively with less time spent moving data or waiting for computing resources to free up. Based on the work from an NASA CIO IT Labs task, this presentation will highlight our prototype work in identifying the feasibility and identify the obstacles, both technical and management, to perform "Cloudbursting" among private clouds located at three different centers. We will demonstrate the use of private cloud computing infrastructure at the Jet Propulsion Laboratory, Langley Research Center, and Ames Research Center to provide elastic computation to each other to perform parallel Earth Science data imaging. We leverage elastic load balancing and auto-scaling features at each data center so that each location can independently define how many resources to allocate to a particular job that was "bursted" from another data center and demonstrate that compute capacity scales up and down with the job. We will also discuss future work in the area, which could include the use of cloud infrastructure from different cloud framework providers as well as other cloud service providers.

Human Pacman: A Mobile Augmented Reality Entertainment System Based on Physical, Social, and Ubiquitous Computing

NASA Astrophysics Data System (ADS)

Cheok, Adrian David

This chapter details the Human Pacman system to illuminate entertainment computing which ventures to embed the natural physical world seamlessly with a fantasy virtual playground by capitalizing on infrastructure provided by mobile computing, wireless LAN, and ubiquitous computing. With Human Pacman, we have a physical role-playing computer fantasy together with real human-social and mobile-gaming that emphasizes on collaboration and competition between players in a wide outdoor physical area that allows natural wide-area human-physical movements. Pacmen and Ghosts are now real human players in the real world experiencing mixed computer graphics fantasy-reality provided by using the wearable computers on them. Virtual cookies and actual tangible physical objects are incorporated into the game play to provide novel experiences of seamless transitions between the real and virtual worlds. This is an example of a new form of gaming that anchors on physicality, mobility, social interaction, and ubiquitous computing.

The optimal design of service level agreement in IAAS based on BDIM

NASA Astrophysics Data System (ADS)

Liu, Xiaochen; Zhan, Zhiqiang

2013-03-01

Cloud Computing has become more and more prevalent over the past few years, and we have seen the importance of Infrastructure-as-a-service (IaaS). This kind of service enables scaling of bandwidth, memory, computing power and storage. But the SLA in IaaS also faces complexity and variety. Users also consider the business of the service. To meet the most users requirements, a methodology for designing optimal SLA in IaaS from the business perspectives is proposed. This method is different from the conventional SLA design method, It not only focuses on service provider perspective, also from the customer to carry on the design. This methodology better captures the linkage between service provider and service client by considering minimizing the business loss originated from performance degradation and IT infrastructure failures and maximizing profits for service provider and clients. An optimal design in an IaaS model is provided and an example are analyzed to show this approach obtain higher profit.

Grid computing technology for hydrological applications

NASA Astrophysics Data System (ADS)

Lecca, G.; Petitdidier, M.; Hluchy, L.; Ivanovic, M.; Kussul, N.; Ray, N.; Thieron, V.

2011-06-01

SummaryAdvances in e-Infrastructure promise to revolutionize sensing systems and the way in which data are collected and assimilated, and complex water systems are simulated and visualized. According to the EU Infrastructure 2010 work-programme, data and compute infrastructures and their underlying technologies, either oriented to tackle scientific challenges or complex problem solving in engineering, are expected to converge together into the so-called knowledge infrastructures, leading to a more effective research, education and innovation in the next decade and beyond. Grid technology is recognized as a fundamental component of e-Infrastructures. Nevertheless, this emerging paradigm highlights several topics, including data management, algorithm optimization, security, performance (speed, throughput, bandwidth, etc.), and scientific cooperation and collaboration issues that require further examination to fully exploit it and to better inform future research policies. The paper illustrates the results of six different surface and subsurface hydrology applications that have been deployed on the Grid. All the applications aim to answer to strong requirements from the Civil Society at large, relatively to natural and anthropogenic risks. Grid technology has been successfully tested to improve flood prediction, groundwater resources management and Black Sea hydrological survey, by providing large computing resources. It is also shown that Grid technology facilitates e-cooperation among partners by means of services for authentication and authorization, seamless access to distributed data sources, data protection and access right, and standardization.

Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing

NASA Technical Reports Server (NTRS)

Brown, Richard B.; Smoot, James C.; Underwood, Lauren; Armstrong, C. Duane

2012-01-01

Geospatial resource assessments frequently require timely geospatial data processing that involves large multivariate remote sensing data sets. In particular, for disasters, response requires rapid access to large data volumes, substantial storage space and high performance processing capability. The processing and distribution of this data into usable information products requires a processing pipeline that can efficiently manage the required storage, computing utilities, and data handling requirements. In recent years, with the availability of cloud computing technology, cloud processing platforms have made available a powerful new computing infrastructure resource that can meet this need. To assess the utility of this resource, this project investigates cloud computing platforms for bulk, automated geoprocessing capabilities with respect to data handling and application development requirements. This presentation is of work being conducted by Applied Sciences Program Office at NASA-Stennis Space Center. A prototypical set of image manipulation and transformation processes that incorporate sample Unmanned Airborne System data were developed to create value-added products and tested for implementation on the "cloud". This project outlines the steps involved in creating and testing of open source software developed process code on a local prototype platform, and then transitioning this code with associated environment requirements into an analogous, but memory and processor enhanced cloud platform. A data processing cloud was used to store both standard digital camera panchromatic and multi-band image data, which were subsequently subjected to standard image processing functions such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), band stacking, reprojection, and other similar type data processes. Cloud infrastructure service providers were evaluated by taking these locally tested processing functions, and then applying them to a given cloud-enabled infrastructure to assesses and compare environment setup options and enabled technologies. This project reviews findings that were observed when cloud platforms were evaluated for bulk geoprocessing capabilities based on data handling and application development requirements.

Streaming support for data intensive cloud-based sequence analysis.

PubMed

Issa, Shadi A; Kienzler, Romeo; El-Kalioby, Mohamed; Tonellato, Peter J; Wall, Dennis; Bruggmann, Rémy; Abouelhoda, Mohamed

2013-01-01

Cloud computing provides a promising solution to the genomics data deluge problem resulting from the advent of next-generation sequencing (NGS) technology. Based on the concepts of "resources-on-demand" and "pay-as-you-go", scientists with no or limited infrastructure can have access to scalable and cost-effective computational resources. However, the large size of NGS data causes a significant data transfer latency from the client's site to the cloud, which presents a bottleneck for using cloud computing services. In this paper, we provide a streaming-based scheme to overcome this problem, where the NGS data is processed while being transferred to the cloud. Our scheme targets the wide class of NGS data analysis tasks, where the NGS sequences can be processed independently from one another. We also provide the elastream package that supports the use of this scheme with individual analysis programs or with workflow systems. Experiments presented in this paper show that our solution mitigates the effect of data transfer latency and saves both time and cost of computation.

European environmental research infrastructures are going for common 30 years strategy

NASA Astrophysics Data System (ADS)

Asmi, Ari; Konjin, Jacco; Pursula, Antti

2014-05-01

Environmental Research infrastructures are facilities, resources, systems and related services that are used by research communities to conduct top-level research. Environmental research is addressing processes at very different time scales, and supporting research infrastructures must be designed as long-term facilities in order to meet the requirements of continuous environmental observation, measurement and analysis. This longevity makes the environmental research infrastructures ideal structures to support the long-term development in environmental sciences. ENVRI project is a collaborative action of the major European (ESFRI) Environmental Research Infrastructures working towards increased co-operation and interoperability between the infrastructures. One of the key products of the ENVRI project is to combine the long-term plans of the individual infrastructures towards a common strategy, describing the vision and planned actions. The envisaged vision for environmental research infrastructures toward 2030 is to support the holistic understanding of our planet and it's behavior. The development of a 'Standard Model of the Planet' is a common ambition, a challenge to define an environmental standard model; a framework of all interactions within the Earth System, from solid earth to near space. Indeed scientists feel challenged to contribute to a 'Standard Model of the Planet' with data, models, algorithms and discoveries. Understanding the Earth System as an interlinked system requires a systems approach. The Environmental Sciences are rapidly moving to become a one system-level science. Mainly since modern science, engineering and society are increasingly facing complex problems that can only be understood in the context of the full overall system. The strategy of the supporting collaborating research infrastructures is based on developing three key factors for the Environmental Sciences: the technological, the cultural and the human capital. The technological capital development concentrates on improving the capacities to measure, observe, preserve and compute. This requires staff, technologies, sensors, satellites, floats, software to integrate and to do analysis and modeling, including data storage, computing platforms and networks. The cultural capital development addresses issues such as open access to data, rules, licenses, citation agreements, IPR agreements, technologies for machine-machine interaction, workflows, metadata, and RI community on the policy level. Human capital actions are based on anticipated need of specialists, including data scientists and 'generalists' that oversee more than just their own discipline. Developing these, as interrelated services, should help the scientific community to enter innovative and large projects contributing to a 'Standard Model of the Planet'. To achieve the overall goal, ENVRI will publish a set of action items that contains intermediate aims, bigger and smaller steps to work towards the development of the 'Standard Model of the Planet' approach. This timeline of actions can used as reference and 'common denominator' in defining new projects and research programs. Either within the various environmental scientific disciplines or when cooperating among these disciplines or even when outreaching towards other disciplines like social sciences, physics/chemistry, medical/life sciences etc.

The Virtual Geophysics Laboratory (VGL): Scientific Workflows Operating Across Organizations and Across Infrastructures

NASA Astrophysics Data System (ADS)

Cox, S. J.; Wyborn, L. A.; Fraser, R.; Rankine, T.; Woodcock, R.; Vote, J.; Evans, B.

2012-12-01

The Virtual Geophysics Laboratory (VGL) is web portal that provides geoscientists with an integrated online environment that: seamlessly accesses geophysical and geoscience data services from the AuScope national geoscience information infrastructure; loosely couples these data to a variety of gesocience software tools; and provides large scale processing facilities via cloud computing. VGL is a collaboration between CSIRO, Geoscience Australia, National Computational Infrastructure, Monash University, Australian National University and the University of Queensland. The VGL provides a distributed system whereby a user can enter an online virtual laboratory to seamlessly connect to OGC web services for geoscience data. The data is supplied in open standards formats using international standards like GeoSciML. A VGL user uses a web mapping interface to discover and filter the data sources using spatial and attribute filters to define a subset. Once the data is selected the user is not required to download the data. VGL collates the service query information for later in the processing workflow where it will be staged directly to the computing facilities. The combination of deferring data download and access to Cloud computing enables VGL users to access their data at higher resolutions and to undertake larger scale inversions, more complex models and simulations than their own local computing facilities might allow. Inside the Virtual Geophysics Laboratory, the user has access to a library of existing models, complete with exemplar workflows for specific scientific problems based on those models. For example, the user can load a geological model published by Geoscience Australia, apply a basic deformation workflow provided by a CSIRO scientist, and have it run in a scientific code from Monash. Finally the user can publish these results to share with a colleague or cite in a paper. This opens new opportunities for access and collaboration as all the resources (models, code, data, processing) are shared in the one virtual laboratory. VGL provides end users with access to an intuitive, user-centered interface that leverages cloud storage and cloud and cluster processing from both the research communities and commercial suppliers (e.g. Amazon). As the underlying data and information services are agnostic of the scientific domain, they can support many other data types. This fundamental characteristic results in a highly reusable virtual laboratory infrastructure that could also be used for example natural hazards, satellite processing, soil geochemistry, climate modeling, agriculture crop modeling.

Parameters Free Computational Characterization of Defects in Transition Metal Oxides with Diffusion Quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Santana, Juan A.; Krogel, Jaron T.; Kent, Paul R.; Reboredo, Fernando

Materials based on transition metal oxides (TMO's) are among the most challenging systems for computational characterization. Reliable and practical computations are possible by directly solving the many-body problem for TMO's with quantum Monte Carlo (QMC) methods. These methods are very computationally intensive, but recent developments in algorithms and computational infrastructures have enabled their application to real materials. We will show our efforts on the application of the diffusion quantum Monte Carlo (DMC) method to study the formation of defects in binary and ternary TMO and heterostructures of TMO. We will also outline current limitations in hardware and algorithms. This work is supported by the Materials Sciences & Engineering Division of the Office of Basic Energy Sciences, U.S. Department of Energy (DOE).

Microcomputers and the future of epidemiology.

PubMed Central

Dean, A G

1994-01-01

The Workshop on Microcomputers and the Future of Epidemiology was held March 8-9, 1993, at the Turner Conference Center, Atlanta, GA, with 130 public health professionals participating. The purpose of the workshop was to define microcomputer needs in epidemiology and to propose future initiatives. Thirteen groups representing public health disciplines defined their needs for better and more useful data, development of computer technology appropriate to epidemiology, user support and human infrastructure development, and global communication and planning. Initiatives proposed were demonstration of health surveillance systems, new software and hardware, computer-based training, projects to establish or improve data bases and community access to data bases, improved international communication, conferences on microcomputer use in particular disciplines, a suggestion to encourage competition in the production of public-domain software, and longrange global planning for epidemiologic computing and data management. Other interested groups are urged to study, modify, and implement those ideas. PMID:7910692

EduCloud: PaaS versus IaaS Cloud Usage for an Advanced Computer Science Course

ERIC Educational Resources Information Center

Vaquero, L. M.

2011-01-01

The cloud has become a widely used term in academia and the industry. Education has not remained unaware of this trend, and several educational solutions based on cloud technologies are already in place, especially for software as a service cloud. However, an evaluation of the educational potential of infrastructure and platform clouds has not…

Transportation Infrastructure Design and Construction \\0x16 Virtual Training Tools

DOT National Transportation Integrated Search

2003-09-01

This project will develop 3D interactive computer-training environments for a major element of transportation infrastructure : hot mix asphalt paving. These tools will include elements of hot mix design (including laboratory equipment) and constructi...

Putting the Information Infrastructure to Work. Report of the Information Infrastructure Task Force Committee on Applications and Technology. NIST Special Publication 857.

ERIC Educational Resources Information Center

National Inst. of Standards and Technology, Gaithersburg, MD.

An interconnection of computer networks, telecommunications services, and applications, the National Information Infrastructure (NII) can open up new vistas and profoundly change much of American life. This report explores some of the opportunities and obstacles to the use of the NII by people and organizations. The goal is to express how…

Integrating Network Management for Cloud Computing Services

DTIC Science & Technology

2015-06-01

abstraction and system design. In this dissertation, we make three major contributions. We rst propose to consolidate the tra c and infrastructure management...abstraction and system design. In this dissertation, we make three major contributions. We first propose to consolidate the traffic and infrastructure ...1.3.1 Safe Datacenter Traffic/ Infrastructure Management . . . . . . 9 1.3.2 End-host/Network Cooperative Traffic Management . . . . . . 10 1.3.3 Direct

Long-term real-time structural health monitoring using wireless smart sensor

NASA Astrophysics Data System (ADS)

Jang, Shinae; Mensah-Bonsu, Priscilla O.; Li, Jingcheng; Dahal, Sushil

2013-04-01

Improving the safety and security of civil infrastructure has become a critical issue for decades since it plays a central role in the economics and politics of a modern society. Structural health monitoring of civil infrastructure using wireless smart sensor network has emerged as a promising solution recently to increase structural reliability, enhance inspection quality, and reduce maintenance costs. Though hardware and software framework are well prepared for wireless smart sensors, the long-term real-time health monitoring strategy are still not available due to the lack of systematic interface. In this paper, the Imote2 smart sensor platform is employed, and a graphical user interface for the long-term real-time structural health monitoring has been developed based on Matlab for the Imote2 platform. This computer-aided engineering platform enables the control, visualization of measured data as well as safety alarm feature based on modal property fluctuation. A new decision making strategy to check the safety is also developed and integrated in this software. Laboratory validation of the computer aided engineering platform for the Imote2 on a truss bridge and a building structure has shown the potential of the interface for long-term real-time structural health monitoring.

The semantics of Chemical Markup Language (CML) for computational chemistry : CompChem.

PubMed

Phadungsukanan, Weerapong; Kraft, Markus; Townsend, Joe A; Murray-Rust, Peter

2012-08-07

: This paper introduces a subdomain chemistry format for storing computational chemistry data called CompChem. It has been developed based on the design, concepts and methodologies of Chemical Markup Language (CML) by adding computational chemistry semantics on top of the CML Schema. The format allows a wide range of ab initio quantum chemistry calculations of individual molecules to be stored. These calculations include, for example, single point energy calculation, molecular geometry optimization, and vibrational frequency analysis. The paper also describes the supporting infrastructure, such as processing software, dictionaries, validation tools and database repositories. In addition, some of the challenges and difficulties in developing common computational chemistry dictionaries are discussed. The uses of CompChem are illustrated by two practical applications.

The semantics of Chemical Markup Language (CML) for computational chemistry : CompChem

PubMed Central

2012-01-01

This paper introduces a subdomain chemistry format for storing computational chemistry data called CompChem. It has been developed based on the design, concepts and methodologies of Chemical Markup Language (CML) by adding computational chemistry semantics on top of the CML Schema. The format allows a wide range of ab initio quantum chemistry calculations of individual molecules to be stored. These calculations include, for example, single point energy calculation, molecular geometry optimization, and vibrational frequency analysis. The paper also describes the supporting infrastructure, such as processing software, dictionaries, validation tools and database repositories. In addition, some of the challenges and difficulties in developing common computational chemistry dictionaries are discussed. The uses of CompChem are illustrated by two practical applications. PMID:22870956

Using IKAROS as a data transfer and management utility within the KM3NeT computing model

NASA Astrophysics Data System (ADS)

Filippidis, Christos; Cotronis, Yiannis; Markou, Christos

2016-04-01

KM3NeT is a future European deep-sea research infrastructure hosting a new generation neutrino detectors that - located at the bottom of the Mediterranean Sea - will open a new window on the universe and answer fundamental questions both in particle physics and astrophysics. IKAROS is a framework that enables creating scalable storage formations on-demand and helps addressing several limitations that the current file systems face when dealing with very large scale infrastructures. It enables creating ad-hoc nearby storage formations and can use a huge number of I/O nodes in order to increase the available bandwidth (I/O and network). IKAROS unifies remote and local access in the overall data flow, by permitting direct access to each I/O node. In this way we can handle the overall data flow at the network layer, limiting the interaction with the operating system. This approach allows virtually connecting, at the users level, the several different computing facilities used (Grids, Clouds, HPCs, Data Centers, Local computing Clusters and personal storage devices), on-demand, based on the needs, by using well known standards and protocols, like HTTP.

Future opportunities and trends for e-infrastructures and life sciences: going beyond the grid to enable life science data analysis

PubMed Central

Duarte, Afonso M. S.; Psomopoulos, Fotis E.; Blanchet, Christophe; Bonvin, Alexandre M. J. J.; Corpas, Manuel; Franc, Alain; Jimenez, Rafael C.; de Lucas, Jesus M.; Nyrönen, Tommi; Sipos, Gergely; Suhr, Stephanie B.

2015-01-01

With the increasingly rapid growth of data in life sciences we are witnessing a major transition in the way research is conducted, from hypothesis-driven studies to data-driven simulations of whole systems. Such approaches necessitate the use of large-scale computational resources and e-infrastructures, such as the European Grid Infrastructure (EGI). EGI, one of key the enablers of the digital European Research Area, is a federation of resource providers set up to deliver sustainable, integrated and secure computing services to European researchers and their international partners. Here we aim to provide the state of the art of Grid/Cloud computing in EU research as viewed from within the field of life sciences, focusing on key infrastructures and projects within the life sciences community. Rather than focusing purely on the technical aspects underlying the currently provided solutions, we outline the design aspects and key characteristics that can be identified across major research approaches. Overall, we aim to provide significant insights into the road ahead by establishing ever-strengthening connections between EGI as a whole and the life sciences community. PMID:26157454

Future opportunities and trends for e-infrastructures and life sciences: going beyond the grid to enable life science data analysis.

PubMed

Duarte, Afonso M S; Psomopoulos, Fotis E; Blanchet, Christophe; Bonvin, Alexandre M J J; Corpas, Manuel; Franc, Alain; Jimenez, Rafael C; de Lucas, Jesus M; Nyrönen, Tommi; Sipos, Gergely; Suhr, Stephanie B

2015-01-01

With the increasingly rapid growth of data in life sciences we are witnessing a major transition in the way research is conducted, from hypothesis-driven studies to data-driven simulations of whole systems. Such approaches necessitate the use of large-scale computational resources and e-infrastructures, such as the European Grid Infrastructure (EGI). EGI, one of key the enablers of the digital European Research Area, is a federation of resource providers set up to deliver sustainable, integrated and secure computing services to European researchers and their international partners. Here we aim to provide the state of the art of Grid/Cloud computing in EU research as viewed from within the field of life sciences, focusing on key infrastructures and projects within the life sciences community. Rather than focusing purely on the technical aspects underlying the currently provided solutions, we outline the design aspects and key characteristics that can be identified across major research approaches. Overall, we aim to provide significant insights into the road ahead by establishing ever-strengthening connections between EGI as a whole and the life sciences community.

Biomedical image analysis and processing in clouds

NASA Astrophysics Data System (ADS)

Bednarz, Tomasz; Szul, Piotr; Arzhaeva, Yulia; Wang, Dadong; Burdett, Neil; Khassapov, Alex; Chen, Shiping; Vallotton, Pascal; Lagerstrom, Ryan; Gureyev, Tim; Taylor, John

2013-10-01

Cloud-based Image Analysis and Processing Toolbox project runs on the Australian National eResearch Collaboration Tools and Resources (NeCTAR) cloud infrastructure and allows access to biomedical image processing and analysis services to researchers via remotely accessible user interfaces. By providing user-friendly access to cloud computing resources and new workflow-based interfaces, our solution enables researchers to carry out various challenging image analysis and reconstruction tasks. Several case studies will be presented during the conference.

PRACE - The European HPC Infrastructure

NASA Astrophysics Data System (ADS)

Stadelmeyer, Peter

2014-05-01

The mission of PRACE (Partnership for Advanced Computing in Europe) is to enable high impact scientific discovery and engineering research and development across all disciplines to enhance European competitiveness for the benefit of society. PRACE seeks to realize this mission by offering world class computing and data management resources and services through a peer review process. This talk gives a general overview about PRACE and the PRACE research infrastructure (RI). PRACE is established as an international not-for-profit association and the PRACE RI is a pan-European supercomputing infrastructure which offers access to computing and data management resources at partner sites distributed throughout Europe. Besides a short summary about the organization, history, and activities of PRACE, it is explained how scientists and researchers from academia and industry from around the world can access PRACE systems and which education and training activities are offered by PRACE. The overview also contains a selection of PRACE contributions to societal challenges and ongoing activities. Examples of the latter are beside others petascaling, application benchmark suite, best practice guides for efficient use of key architectures, application enabling / scaling, new programming models, and industrial applications. The Partnership for Advanced Computing in Europe (PRACE) is an international non-profit association with its seat in Brussels. The PRACE Research Infrastructure provides a persistent world-class high performance computing service for scientists and researchers from academia and industry in Europe. The computer systems and their operations accessible through PRACE are provided by 4 PRACE members (BSC representing Spain, CINECA representing Italy, GCS representing Germany and GENCI representing France). The Implementation Phase of PRACE receives funding from the EU's Seventh Framework Programme (FP7/2007-2013) under grant agreements RI-261557, RI-283493 and RI-312763. For more information, see www.prace-ri.eu

High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis

PubMed Central

Simonyan, Vahan; Chumakov, Konstantin; Dingerdissen, Hayley; Faison, William; Goldweber, Scott; Golikov, Anton; Gulzar, Naila; Karagiannis, Konstantinos; Vinh Nguyen Lam, Phuc; Maudru, Thomas; Muravitskaja, Olesja; Osipova, Ekaterina; Pan, Yang; Pschenichnov, Alexey; Rostovtsev, Alexandre; Santana-Quintero, Luis; Smith, Krista; Thompson, Elaine E.; Tkachenko, Valery; Torcivia-Rodriguez, John; Wan, Quan; Wang, Jing; Wu, Tsung-Jung; Wilson, Carolyn; Mazumder, Raja

2016-01-01

The High-performance Integrated Virtual Environment (HIVE) is a distributed storage and compute environment designed primarily to handle next-generation sequencing (NGS) data. This multicomponent cloud infrastructure provides secure web access for authorized users to deposit, retrieve, annotate and compute on NGS data, and to analyse the outcomes using web interface visual environments appropriately built in collaboration with research and regulatory scientists and other end users. Unlike many massively parallel computing environments, HIVE uses a cloud control server which virtualizes services, not processes. It is both very robust and flexible due to the abstraction layer introduced between computational requests and operating system processes. The novel paradigm of moving computations to the data, instead of moving data to computational nodes, has proven to be significantly less taxing for both hardware and network infrastructure. The honeycomb data model developed for HIVE integrates metadata into an object-oriented model. Its distinction from other object-oriented databases is in the additional implementation of a unified application program interface to search, view and manipulate data of all types. This model simplifies the introduction of new data types, thereby minimizing the need for database restructuring and streamlining the development of new integrated information systems. The honeycomb model employs a highly secure hierarchical access control and permission system, allowing determination of data access privileges in a finely granular manner without flooding the security subsystem with a multiplicity of rules. HIVE infrastructure will allow engineers and scientists to perform NGS analysis in a manner that is both efficient and secure. HIVE is actively supported in public and private domains, and project collaborations are welcomed. Database URL: https://hive.biochemistry.gwu.edu PMID:26989153

High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis.

PubMed

Simonyan, Vahan; Chumakov, Konstantin; Dingerdissen, Hayley; Faison, William; Goldweber, Scott; Golikov, Anton; Gulzar, Naila; Karagiannis, Konstantinos; Vinh Nguyen Lam, Phuc; Maudru, Thomas; Muravitskaja, Olesja; Osipova, Ekaterina; Pan, Yang; Pschenichnov, Alexey; Rostovtsev, Alexandre; Santana-Quintero, Luis; Smith, Krista; Thompson, Elaine E; Tkachenko, Valery; Torcivia-Rodriguez, John; Voskanian, Alin; Wan, Quan; Wang, Jing; Wu, Tsung-Jung; Wilson, Carolyn; Mazumder, Raja

2016-01-01

The High-performance Integrated Virtual Environment (HIVE) is a distributed storage and compute environment designed primarily to handle next-generation sequencing (NGS) data. This multicomponent cloud infrastructure provides secure web access for authorized users to deposit, retrieve, annotate and compute on NGS data, and to analyse the outcomes using web interface visual environments appropriately built in collaboration with research and regulatory scientists and other end users. Unlike many massively parallel computing environments, HIVE uses a cloud control server which virtualizes services, not processes. It is both very robust and flexible due to the abstraction layer introduced between computational requests and operating system processes. The novel paradigm of moving computations to the data, instead of moving data to computational nodes, has proven to be significantly less taxing for both hardware and network infrastructure.The honeycomb data model developed for HIVE integrates metadata into an object-oriented model. Its distinction from other object-oriented databases is in the additional implementation of a unified application program interface to search, view and manipulate data of all types. This model simplifies the introduction of new data types, thereby minimizing the need for database restructuring and streamlining the development of new integrated information systems. The honeycomb model employs a highly secure hierarchical access control and permission system, allowing determination of data access privileges in a finely granular manner without flooding the security subsystem with a multiplicity of rules. HIVE infrastructure will allow engineers and scientists to perform NGS analysis in a manner that is both efficient and secure. HIVE is actively supported in public and private domains, and project collaborations are welcomed. Database URL: https://hive.biochemistry.gwu.edu. © The Author(s) 2016. Published by Oxford University Press.

Cooperative high-performance storage in the accelerated strategic computing initiative

NASA Technical Reports Server (NTRS)

Gary, Mark; Howard, Barry; Louis, Steve; Minuzzo, Kim; Seager, Mark

1996-01-01

The use and acceptance of new high-performance, parallel computing platforms will be impeded by the absence of an infrastructure capable of supporting orders-of-magnitude improvement in hierarchical storage and high-speed I/O (Input/Output). The distribution of these high-performance platforms and supporting infrastructures across a wide-area network further compounds this problem. We describe an architectural design and phased implementation plan for a distributed, Cooperative Storage Environment (CSE) to achieve the necessary performance, user transparency, site autonomy, communication, and security features needed to support the Accelerated Strategic Computing Initiative (ASCI). ASCI is a Department of Energy (DOE) program attempting to apply terascale platforms and Problem-Solving Environments (PSEs) toward real-world computational modeling and simulation problems. The ASCI mission must be carried out through a unified, multilaboratory effort, and will require highly secure, efficient access to vast amounts of data. The CSE provides a logically simple, geographically distributed, storage infrastructure of semi-autonomous cooperating sites to meet the strategic ASCI PSE goal of highperformance data storage and access at the user desktop.

A Semantic Grid Oriented to E-Tourism

NASA Astrophysics Data System (ADS)

Zhang, Xiao Ming

With increasing complexity of tourism business models and tasks, there is a clear need of the next generation e-Tourism infrastructure to support flexible automation, integration, computation, storage, and collaboration. Currently several enabling technologies such as semantic Web, Web service, agent and grid computing have been applied in the different e-Tourism applications, however there is no a unified framework to be able to integrate all of them. So this paper presents a promising e-Tourism framework based on emerging semantic grid, in which a number of key design issues are discussed including architecture, ontologies structure, semantic reconciliation, service and resource discovery, role based authorization and intelligent agent. The paper finally provides the implementation of the framework.

Privacy and the National Information Infrastructure.

ERIC Educational Resources Information Center

Rotenberg, Marc

1994-01-01

Explains the work of Computer Professionals for Social Responsibility regarding privacy issues in the use of electronic networks; recommends principles that should be adopted for a National Information Infrastructure privacy code; discusses the need for public education; and suggests pertinent legislative proposals. (LRW)

Effecting IT infrastructure culture change: management by processes and metrics

NASA Technical Reports Server (NTRS)

Miller, R. L.

2001-01-01

This talk describes the processes and metrics used by Jet Propulsion Laboratory to bring about the required IT infrastructure culture change to update and certify, as Y2K compliant, thousands of computers and millions of lines of code.

IEEE TRANSACTIONS ON CYBERNETICS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Craig R. RIeger; David H. Scheidt; William D. Smart

2014-11-01

MODERN societies depend on complex and critical infrastructures for energy, transportation, sustenance, medical care, emergency response, communications security. As computers, automation, and information technology (IT) have advanced, these technologies have been exploited to enhance the efficiency of operating the processes that make up these infrastructures

Grid-based HPC astrophysical applications at INAF Catania.

NASA Astrophysics Data System (ADS)

Costa, A.; Calanducci, A.; Becciani, U.; Capuzzo Dolcetta, R.

The research activity on grid area at INAF Catania has been devoted to two main goals: the integration of a multiprocessor supercomputer (IBM SP4) within INFN-GRID middleware and the developing of a web-portal, Astrocomp-G, for the submission of astrophysical jobs into the grid infrastructure. Most of the actual grid implementation infrastructure is based on common hardware, i.e. i386 architecture machines (Intel Celeron, Pentium III, IV, Amd Duron, Athlon) using Linux RedHat OS. We were the first institute to integrate a totally different machine, an IBM SP with RISC architecture and AIX OS, as a powerful Worker Node inside a grid infrastructure. We identified and ported to AIX OS the grid components dealing with job monitoring and execution and properly tuned the Computing Element to delivery jobs into this special Worker Node. For testing purpose we used MARA, an astrophysical application for the analysis of light curve sequences. Astrocomp-G is a user-friendly front end to our grid site. Users who want to submit the astrophysical applications already available in the portal need to own a valid personal X509 certificate in addiction to a username and password released by the grid portal web master. The personal X509 certificate is a prerequisite for the creation of a short or long-term proxy certificate that allows the grid infrastructure services to identify clearly whether the owner of the job has the permissions to use resources and data. X509 and proxy certificates are part of GSI (Grid Security Infrastructure), a standard security tool adopted by all major grid sites around the world.

A Big Data Platform for Storing, Accessing, Mining and Learning Geospatial Data

NASA Astrophysics Data System (ADS)

Yang, C. P.; Bambacus, M.; Duffy, D.; Little, M. M.

2017-12-01

Big Data is becoming a norm in geoscience domains. A platform that is capable to effiently manage, access, analyze, mine, and learn the big data for new information and knowledge is desired. This paper introduces our latest effort on developing such a platform based on our past years' experiences on cloud and high performance computing, analyzing big data, comparing big data containers, and mining big geospatial data for new information. The platform includes four layers: a) the bottom layer includes a computing infrastructure with proper network, computer, and storage systems; b) the 2nd layer is a cloud computing layer based on virtualization to provide on demand computing services for upper layers; c) the 3rd layer is big data containers that are customized for dealing with different types of data and functionalities; d) the 4th layer is a big data presentation layer that supports the effient management, access, analyses, mining and learning of big geospatial data.

Toward a web-based real-time radiation treatment planning system in a cloud computing environment.

PubMed

Na, Yong Hum; Suh, Tae-Suk; Kapp, Daniel S; Xing, Lei

2013-09-21

To exploit the potential dosimetric advantages of intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT), an in-depth approach is required to provide efficient computing methods. This needs to incorporate clinically related organ specific constraints, Monte Carlo (MC) dose calculations, and large-scale plan optimization. This paper describes our first steps toward a web-based real-time radiation treatment planning system in a cloud computing environment (CCE). The Amazon Elastic Compute Cloud (EC2) with a master node (named m2.xlarge containing 17.1 GB of memory, two virtual cores with 3.25 EC2 Compute Units each, 420 GB of instance storage, 64-bit platform) is used as the backbone of cloud computing for dose calculation and plan optimization. The master node is able to scale the workers on an 'on-demand' basis. MC dose calculation is employed to generate accurate beamlet dose kernels by parallel tasks. The intensity modulation optimization uses total-variation regularization (TVR) and generates piecewise constant fluence maps for each initial beam direction in a distributed manner over the CCE. The optimized fluence maps are segmented into deliverable apertures. The shape of each aperture is iteratively rectified to be a sequence of arcs using the manufacture's constraints. The output plan file from the EC2 is sent to the simple storage service. Three de-identified clinical cancer treatment plans have been studied for evaluating the performance of the new planning platform with 6 MV flattening filter free beams (40 × 40 cm(2)) from the Varian TrueBeam(TM) STx linear accelerator. A CCE leads to speed-ups of up to 14-fold for both dose kernel calculations and plan optimizations in the head and neck, lung, and prostate cancer cases considered in this study. The proposed system relies on a CCE that is able to provide an infrastructure for parallel and distributed computing. The resultant plans from the cloud computing are identical to PC-based IMRT and VMAT plans, confirming the reliability of the cloud computing platform. This cloud computing infrastructure has been established for a radiation treatment planning. It substantially improves the speed of inverse planning and makes future on-treatment adaptive re-planning possible.

Toward a web-based real-time radiation treatment planning system in a cloud computing environment

NASA Astrophysics Data System (ADS)

Hum Na, Yong; Suh, Tae-Suk; Kapp, Daniel S.; Xing, Lei

2013-09-01

To exploit the potential dosimetric advantages of intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT), an in-depth approach is required to provide efficient computing methods. This needs to incorporate clinically related organ specific constraints, Monte Carlo (MC) dose calculations, and large-scale plan optimization. This paper describes our first steps toward a web-based real-time radiation treatment planning system in a cloud computing environment (CCE). The Amazon Elastic Compute Cloud (EC2) with a master node (named m2.xlarge containing 17.1 GB of memory, two virtual cores with 3.25 EC2 Compute Units each, 420 GB of instance storage, 64-bit platform) is used as the backbone of cloud computing for dose calculation and plan optimization. The master node is able to scale the workers on an ‘on-demand’ basis. MC dose calculation is employed to generate accurate beamlet dose kernels by parallel tasks. The intensity modulation optimization uses total-variation regularization (TVR) and generates piecewise constant fluence maps for each initial beam direction in a distributed manner over the CCE. The optimized fluence maps are segmented into deliverable apertures. The shape of each aperture is iteratively rectified to be a sequence of arcs using the manufacture’s constraints. The output plan file from the EC2 is sent to the simple storage service. Three de-identified clinical cancer treatment plans have been studied for evaluating the performance of the new planning platform with 6 MV flattening filter free beams (40 × 40 cm2) from the Varian TrueBeamTM STx linear accelerator. A CCE leads to speed-ups of up to 14-fold for both dose kernel calculations and plan optimizations in the head and neck, lung, and prostate cancer cases considered in this study. The proposed system relies on a CCE that is able to provide an infrastructure for parallel and distributed computing. The resultant plans from the cloud computing are identical to PC-based IMRT and VMAT plans, confirming the reliability of the cloud computing platform. This cloud computing infrastructure has been established for a radiation treatment planning. It substantially improves the speed of inverse planning and makes future on-treatment adaptive re-planning possible.

The GENIUS Grid Portal and robot certificates: a new tool for e-Science

PubMed Central

Barbera, Roberto; Donvito, Giacinto; Falzone, Alberto; La Rocca, Giuseppe; Milanesi, Luciano; Maggi, Giorgio Pietro; Vicario, Saverio

2009-01-01

Background Grid technology is the computing model which allows users to share a wide pletora of distributed computational resources regardless of their geographical location. Up to now, the high security policy requested in order to access distributed computing resources has been a rather big limiting factor when trying to broaden the usage of Grids into a wide community of users. Grid security is indeed based on the Public Key Infrastructure (PKI) of X.509 certificates and the procedure to get and manage those certificates is unfortunately not straightforward. A first step to make Grids more appealing for new users has recently been achieved with the adoption of robot certificates. Methods Robot certificates have recently been introduced to perform automated tasks on Grids on behalf of users. They are extremely useful for instance to automate grid service monitoring, data processing production, distributed data collection systems. Basically these certificates can be used to identify a person responsible for an unattended service or process acting as client and/or server. Robot certificates can be installed on a smart card and used behind a portal by everyone interested in running the related applications in a Grid environment using a user-friendly graphic interface. In this work, the GENIUS Grid Portal, powered by EnginFrame, has been extended in order to support the new authentication based on the adoption of these robot certificates. Results The work carried out and reported in this manuscript is particularly relevant for all users who are not familiar with personal digital certificates and the technical aspects of the Grid Security Infrastructure (GSI). The valuable benefits introduced by robot certificates in e-Science can so be extended to users belonging to several scientific domains, providing an asset in raising Grid awareness to a wide number of potential users. Conclusion The adoption of Grid portals extended with robot certificates, can really contribute to creating transparent access to computational resources of Grid Infrastructures, enhancing the spread of this new paradigm in researchers' working life to address new global scientific challenges. The evaluated solution can of course be extended to other portals, applications and scientific communities. PMID:19534747

The GENIUS Grid Portal and robot certificates: a new tool for e-Science.

PubMed

Barbera, Roberto; Donvito, Giacinto; Falzone, Alberto; La Rocca, Giuseppe; Milanesi, Luciano; Maggi, Giorgio Pietro; Vicario, Saverio

2009-06-16

Grid technology is the computing model which allows users to share a wide pletora of distributed computational resources regardless of their geographical location. Up to now, the high security policy requested in order to access distributed computing resources has been a rather big limiting factor when trying to broaden the usage of Grids into a wide community of users. Grid security is indeed based on the Public Key Infrastructure (PKI) of X.509 certificates and the procedure to get and manage those certificates is unfortunately not straightforward. A first step to make Grids more appealing for new users has recently been achieved with the adoption of robot certificates. Robot certificates have recently been introduced to perform automated tasks on Grids on behalf of users. They are extremely useful for instance to automate grid service monitoring, data processing production, distributed data collection systems. Basically these certificates can be used to identify a person responsible for an unattended service or process acting as client and/or server. Robot certificates can be installed on a smart card and used behind a portal by everyone interested in running the related applications in a Grid environment using a user-friendly graphic interface. In this work, the GENIUS Grid Portal, powered by EnginFrame, has been extended in order to support the new authentication based on the adoption of these robot certificates. The work carried out and reported in this manuscript is particularly relevant for all users who are not familiar with personal digital certificates and the technical aspects of the Grid Security Infrastructure (GSI). The valuable benefits introduced by robot certificates in e-Science can so be extended to users belonging to several scientific domains, providing an asset in raising Grid awareness to a wide number of potential users. The adoption of Grid portals extended with robot certificates, can really contribute to creating transparent access to computational resources of Grid Infrastructures, enhancing the spread of this new paradigm in researchers' working life to address new global scientific challenges. The evaluated solution can of course be extended to other portals, applications and scientific communities.

In-Use and Emerging Disruptive Technology Trends

DTIC Science & Technology

2015-03-31

blog/establishing-zero-trust- infrastructure / (accessed No- vember 7, 2014) Mobile Thin Client End Points In the early days of computing, the...companies are using their network infrastructure to break into the mobile broadband market. For example, Ca- blevision recently began providing a Wi-Fi...smartphones and mobile devic- es will be used within the Pentagon. A building-wide cellular infrastructure is not the an- swer to retrieving and sending

Services and the National Information Infrastructure. Report of the Information Infrastructure Task Force Committee on Applications and Technology, Technology Policy Working Group. Draft for Public Comment.

ERIC Educational Resources Information Center

Office of Science and Technology Policy, Washington, DC.

In this report, the National Information Infrastructure (NII) services issue is addressed, and activities to advance the development of NII services are recommended. The NII is envisioned to grow into a seamless web of communications networks, computers, databases, and consumer electronics that will put vast amounts of information at users'…

Enhancing the Resilience of Interdependent Critical Infrastructure Systems Using a Common Computational Framework

NASA Astrophysics Data System (ADS)

Little, J. C.; Filz, G. M.

2016-12-01

As modern societies become more complex, critical interdependent infrastructure systems become more likely to fail under stress unless they are designed and implemented to be resilient. Hurricane Katrina clearly demonstrated the catastrophic and as yet unpredictable consequences of such failures. Resilient infrastructure systems maintain the flow of goods and services in the face of a broad range of natural and manmade hazards. In this presentation, we illustrate a generic computational framework to facilitate high-level decision-making about how to invest scarce resources most effectively to enhance resilience in coastal protection, transportation, and the economy of a region. Coastal Louisiana, our study area, has experienced the catastrophic effects of several land-falling hurricanes in recent years. In this project, we implement and further refine three process models (a coastal protection model, a transportation model, and an economic model) for the coastal Louisiana region. We upscale essential mechanistic features of the three detailed process models to the systems level and integrate the three reduced-order systems models in a modular fashion. We also evaluate the proposed approach in annual workshops with input from stakeholders. Based on stakeholder inputs, we derive a suite of goals, targets, and indicators for evaluating resilience at the systems level, and assess and enhance resilience using several deterministic scenarios. The unifying framework will be able to accommodate the different spatial and temporal scales that are appropriate for each model. We combine our generic computational framework, which encompasses the entire system of systems, with the targets, and indicators needed to systematically meet our chosen resilience goals. We will start with targets that focus on technical and economic systems, but future work will ensure that targets and indicators are extended to other dimensions of resilience including those in the environmental and social systems. The overall model can be used to optimize decision making in a probabilistic risk-based framework.

Standardized cardiovascular data for clinical research, registries, and patient care: a report from the Data Standards Workgroup of the National Cardiovascular Research Infrastructure project.

PubMed

Anderson, H Vernon; Weintraub, William S; Radford, Martha J; Kremers, Mark S; Roe, Matthew T; Shaw, Richard E; Pinchotti, Dana M; Tcheng, James E

2013-05-07

Relatively little attention has been focused on standardization of data exchange in clinical research studies and patient care activities. Both are usually managed locally using separate and generally incompatible data systems at individual hospitals or clinics. In the past decade there have been nascent efforts to create data standards for clinical research and patient care data, and to some extent these are helpful in providing a degree of uniformity. Nonetheless, these data standards generally have not been converted into accepted computer-based language structures that could permit reliable data exchange across computer networks. The National Cardiovascular Research Infrastructure (NCRI) project was initiated with a major objective of creating a model framework for standard data exchange in all clinical research, clinical registry, and patient care environments, including all electronic health records. The goal is complete syntactic and semantic interoperability. A Data Standards Workgroup was established to create or identify and then harmonize clinical definitions for a base set of standardized cardiovascular data elements that could be used in this network infrastructure. Recognizing the need for continuity with prior efforts, the Workgroup examined existing data standards sources. A basic set of 353 elements was selected. The NCRI staff then collaborated with the 2 major technical standards organizations in health care, the Clinical Data Interchange Standards Consortium and Health Level Seven International, as well as with staff from the National Cancer Institute Enterprise Vocabulary Services. Modeling and mapping were performed to represent (instantiate) the data elements in appropriate technical computer language structures for endorsement as an accepted data standard for public access and use. Fully implemented, these elements will facilitate clinical research, registry reporting, administrative reporting and regulatory compliance, and patient care. Copyright © 2013 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

The International Symposium on Grids and Clouds

NASA Astrophysics Data System (ADS)

The International Symposium on Grids and Clouds (ISGC) 2012 will be held at Academia Sinica in Taipei from 26 February to 2 March 2012, with co-located events and workshops. The conference is hosted by the Academia Sinica Grid Computing Centre (ASGC). 2012 is the decennium anniversary of the ISGC which over the last decade has tracked the convergence, collaboration and innovation of individual researchers across the Asia Pacific region to a coherent community. With the continuous support and dedication from the delegates, ISGC has provided the primary international distributed computing platform where distinguished researchers and collaboration partners from around the world share their knowledge and experiences. The last decade has seen the wide-scale emergence of e-Infrastructure as a critical asset for the modern e-Scientist. The emergence of large-scale research infrastructures and instruments that has produced a torrent of electronic data is forcing a generational change in the scientific process and the mechanisms used to analyse the resulting data deluge. No longer can the processing of these vast amounts of data and production of relevant scientific results be undertaken by a single scientist. Virtual Research Communities that span organisations around the world, through an integrated digital infrastructure that connects the trust and administrative domains of multiple resource providers, have become critical in supporting these analyses. Topics covered in ISGC 2012 include: High Energy Physics, Biomedicine & Life Sciences, Earth Science, Environmental Changes and Natural Disaster Mitigation, Humanities & Social Sciences, Operations & Management, Middleware & Interoperability, Security and Networking, Infrastructure Clouds & Virtualisation, Business Models & Sustainability, Data Management, Distributed Volunteer & Desktop Grid Computing, High Throughput Computing, and High Performance, Manycore & GPU Computing.

Testing of SWMM Model’s LID Modules

EPA Science Inventory

EPA’s Storm Water Management Model (SWMM) is a computational code heavily relied upon by industry for the simulation of wastewater and stormwater infrastructure performance to . design and build multi-billion-dollar, multi-decade infrastructure upgrades. Since the 1970’s, EPA a...

Extensible Infrastructure for Browsing and Searching Abstracted Spacecraft Data

NASA Technical Reports Server (NTRS)

Wallick, Michael N.; Crockett, Thomas M.; Joswig, Joseph C.; Torres, Recaredo J.; Norris, Jeffrey S.; Fox, Jason M.; Powell, Mark W.; Mittman, David S.; Abramyan, Lucy; Shams, Khawaja S.;

The Path to Convergence: Design, Coordination and Social Issues in the Implementation of a Middleware Data Broker.

NASA Astrophysics Data System (ADS)

Slota, S.; Khalsa, S. J. S.

2015-12-01

Infrastructures are the result of systems, networks, and inter-networks that accrete, overlay and segment one another over time. As a result, working infrastructures represent a broad heterogeneity of elements - data types, computational resources, material substrates (computing hardware, physical infrastructure, labs, physical information resources, etc.) as well as organizational and social functions which result in divergent outputs and goals. Cyber infrastructure's engineering often defaults to a separation of the social from the technical that results in the engineering succeeding in limited ways, or the exposure of unanticipated points of failure within the system. Studying the development of middleware intended to mediate interactions among systems within an earth systems science infrastructure exposes organizational, technical and standards-focused negotiations endemic to a fundamental trait of infrastructure: its characteristic invisibility in use. Intended to perform a core function within the EarthCube cyberinfrastructure, the development, governance and maintenance of an automated brokering system is a microcosm of large-scale infrastructural efforts. Points of potential system failure, regardless of the extent to which they are more social or more technical in nature, can be considered in terms of the reverse salient: a point of social and material configuration that momentarily lags behind the progress of an emerging or maturing infrastructure. The implementation of the BCube data broker has exposed reverse salients in regards to the overall EarthCube infrastructure (and the role of middleware brokering) in the form of organizational factors such as infrastructural alignment, maintenance and resilience; differing and incompatible practices of data discovery and evaluation among users and stakeholders; and a preponderance of local variations in the implementation of standards and authentication in data access. These issues are characterized by their role in increasing tension or friction among components that are on the path to convergence and may help to predict otherwise-occluded endogenous points of failure or non-adoption in the infrastructure.

An atom is known by the company it keeps: Content, representation and pedagogy within the epistemic revolution of the complexity sciences

NASA Astrophysics Data System (ADS)

Blikstein, Paulo

The goal of this dissertation is to explore relations between content, representation, and pedagogy, so as to understand the impact of the nascent field of complexity sciences on science, technology, engineering and mathematics (STEM) learning. Wilensky & Papert coined the term "structurations" to express the relationship between knowledge and its representational infrastructure. A change from one representational infrastructure to another they call a "restructuration." The complexity sciences have introduced a novel and powerful structuration: agent-based modeling. In contradistinction to traditional mathematical modeling, which relies on equational descriptions of macroscopic properties of systems, agent-based modeling focuses on a few archetypical micro-behaviors of "agents" to explain emergent macro-behaviors of the agent collective. Specifically, this dissertation is about a series of studies of undergraduate students' learning of materials science, in which two structurations are compared (equational and agent-based), consisting of both design research and empirical evaluation. I have designed MaterialSim, a constructionist suite of computer models, supporting materials and learning activities designed within the approach of agent-based modeling, and over four years conducted an empirical inves3 tigation of an undergraduate materials science course. The dissertation is comprised of three studies: Study 1 - diagnosis . I investigate current representational and pedagogical practices in engineering classrooms. Study 2 - laboratory studies. I investigate the cognition of students engaging in scientific inquiry through programming their own scientific models. Study 3 - classroom implementation. I investigate the characteristics, advantages, and trajectories of scientific content knowledge that is articulated in epistemic forms and representational infrastructures unique to complexity sciences, as well as the feasibility of the integration of constructionist, agent-based learning environments in engineering classrooms. Data sources include classroom observations, interviews, videotaped sessions of model-building, questionnaires, analysis of computer-generated logfiles, and quantitative and qualitative analysis of artifacts. Results shows that (1) current representational and pedagogical practices in engineering classrooms were not up to the challenge of the complex content being taught, (2) by building their own scientific models, students developed a deeper understanding of core scientific concepts, and learned how to better identify unifying principles and behaviors in materials science, and (3) programming computer models was feasible within a regular engineering classroom.

Earthquake prediction in California using regression algorithms and cloud-based big data infrastructure

NASA Astrophysics Data System (ADS)

Asencio-Cortés, G.; Morales-Esteban, A.; Shang, X.; Martínez-Álvarez, F.

2018-06-01

Earthquake magnitude prediction is a challenging problem that has been widely studied during the last decades. Statistical, geophysical and machine learning approaches can be found in literature, with no particularly satisfactory results. In recent years, powerful computational techniques to analyze big data have emerged, making possible the analysis of massive datasets. These new methods make use of physical resources like cloud based architectures. California is known for being one of the regions with highest seismic activity in the world and many data are available. In this work, the use of several regression algorithms combined with ensemble learning is explored in the context of big data (1 GB catalog is used), in order to predict earthquakes magnitude within the next seven days. Apache Spark framework, H2 O library in R language and Amazon cloud infrastructure were been used, reporting very promising results.

XML Based Scientific Data Management Facility

NASA Technical Reports Server (NTRS)

Mehrotra, Piyush; Zubair, M.; Ziebartt, John (Technical Monitor)

2001-01-01

The World Wide Web consortium has developed an Extensible Markup Language (XML) to support the building of better information management infrastructures. The scientific computing community realizing the benefits of HTML has designed markup languages for scientific data. In this paper, we propose a XML based scientific data management facility, XDMF. The project is motivated by the fact that even though a lot of scientific data is being generated, it is not being shared because of lack of standards and infrastructure support for discovering and transforming the data. The proposed data management facility can be used to discover the scientific data itself, the transformation functions, and also for applying the required transformations. We have built a prototype system of the proposed data management facility that can work on different platforms. We have implemented the system using Java, and Apache XSLT engine Xalan. To support remote data and transformation functions, we had to extend the XSLT specification and the Xalan package.

XML Based Scientific Data Management Facility

NASA Technical Reports Server (NTRS)

Mehrotra, P.; Zubair, M.; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

The World Wide Web consortium has developed an Extensible Markup Language (XML) to support the building of better information management infrastructures. The scientific computing community realizing the benefits of XML has designed markup languages for scientific data. In this paper, we propose a XML based scientific data management ,facility, XDMF. The project is motivated by the fact that even though a lot of scientific data is being generated, it is not being shared because of lack of standards and infrastructure support for discovering and transforming the data. The proposed data management facility can be used to discover the scientific data itself, the transformation functions, and also for applying the required transformations. We have built a prototype system of the proposed data management facility that can work on different platforms. We have implemented the system using Java, and Apache XSLT engine Xalan. To support remote data and transformation functions, we had to extend the XSLT specification and the Xalan package.

National Laboratory for Advanced Scientific Visualization at UNAM - Mexico

NASA Astrophysics Data System (ADS)

Manea, Marina; Constantin Manea, Vlad; Varela, Alfredo

2016-04-01

In 2015, the National Autonomous University of Mexico (UNAM) joined the family of Universities and Research Centers where advanced visualization and computing plays a key role to promote and advance missions in research, education, community outreach, as well as business-oriented consulting. This initiative provides access to a great variety of advanced hardware and software resources and offers a range of consulting services that spans a variety of areas related to scientific visualization, among which are: neuroanatomy, embryonic development, genome related studies, geosciences, geography, physics and mathematics related disciplines. The National Laboratory for Advanced Scientific Visualization delivers services through three main infrastructure environments: the 3D fully immersive display system Cave, the high resolution parallel visualization system Powerwall, the high resolution spherical displays Earth Simulator. The entire visualization infrastructure is interconnected to a high-performance-computing-cluster (HPCC) called ADA in honor to Ada Lovelace, considered to be the first computer programmer. The Cave is an extra large 3.6m wide room with projected images on the front, left and right, as well as floor walls. Specialized crystal eyes LCD-shutter glasses provide a strong stereo depth perception, and a variety of tracking devices allow software to track the position of a user's hand, head and wand. The Powerwall is designed to bring large amounts of complex data together through parallel computing for team interaction and collaboration. This system is composed by 24 (6x4) high-resolution ultra-thin (2 mm) bezel monitors connected to a high-performance GPU cluster. The Earth Simulator is a large (60") high-resolution spherical display used for global-scale data visualization like geophysical, meteorological, climate and ecology data. The HPCC-ADA, is a 1000+ computing core system, which offers parallel computing resources to applications that requires large quantity of memory as well as large and fast parallel storage systems. The entire system temperature is controlled by an energy and space efficient cooling solution, based on large rear door liquid cooled heat exchangers. This state-of-the-art infrastructure will boost research activities in the region, offer a powerful scientific tool for teaching at undergraduate and graduate levels, and enhance association and cooperation with business-oriented organizations.

Do Clouds Compute? A Framework for Estimating the Value of Cloud Computing

NASA Astrophysics Data System (ADS)

Klems, Markus; Nimis, Jens; Tai, Stefan

On-demand provisioning of scalable and reliable compute services, along with a cost model that charges consumers based on actual service usage, has been an objective in distributed computing research and industry for a while. Cloud Computing promises to deliver on this objective: consumers are able to rent infrastructure in the Cloud as needed, deploy applications and store data, and access them via Web protocols on a pay-per-use basis. The acceptance of Cloud Computing, however, depends on the ability for Cloud Computing providers and consumers to implement a model for business value co-creation. Therefore, a systematic approach to measure costs and benefits of Cloud Computing is needed. In this paper, we discuss the need for valuation of Cloud Computing, identify key components, and structure these components in a framework. The framework assists decision makers in estimating Cloud Computing costs and to compare these costs to conventional IT solutions. We demonstrate by means of representative use cases how our framework can be applied to real world scenarios.

Parallel, distributed and GPU computing technologies in single-particle electron microscopy

PubMed Central

Schmeisser, Martin; Heisen, Burkhard C.; Luettich, Mario; Busche, Boris; Hauer, Florian; Koske, Tobias; Knauber, Karl-Heinz; Stark, Holger

2009-01-01

Most known methods for the determination of the structure of macromolecular complexes are limited or at least restricted at some point by their computational demands. Recent developments in information technology such as multicore, parallel and GPU processing can be used to overcome these limitations. In particular, graphics processing units (GPUs), which were originally developed for rendering real-time effects in computer games, are now ubiquitous and provide unprecedented computational power for scientific applications. Each parallel-processing paradigm alone can improve overall performance; the increased computational performance obtained by combining all paradigms, unleashing the full power of today’s technology, makes certain applications feasible that were previously virtually impossible. In this article, state-of-the-art paradigms are introduced, the tools and infrastructure needed to apply these paradigms are presented and a state-of-the-art infrastructure and solution strategy for moving scientific applications to the next generation of computer hardware is outlined. PMID:19564686

Parallel, distributed and GPU computing technologies in single-particle electron microscopy.

PubMed

Schmeisser, Martin; Heisen, Burkhard C; Luettich, Mario; Busche, Boris; Hauer, Florian; Koske, Tobias; Knauber, Karl-Heinz; Stark, Holger

2009-07-01

Most known methods for the determination of the structure of macromolecular complexes are limited or at least restricted at some point by their computational demands. Recent developments in information technology such as multicore, parallel and GPU processing can be used to overcome these limitations. In particular, graphics processing units (GPUs), which were originally developed for rendering real-time effects in computer games, are now ubiquitous and provide unprecedented computational power for scientific applications. Each parallel-processing paradigm alone can improve overall performance; the increased computational performance obtained by combining all paradigms, unleashing the full power of today's technology, makes certain applications feasible that were previously virtually impossible. In this article, state-of-the-art paradigms are introduced, the tools and infrastructure needed to apply these paradigms are presented and a state-of-the-art infrastructure and solution strategy for moving scientific applications to the next generation of computer hardware is outlined.

Cloud based intelligent system for delivering health care as a service.

PubMed

Kaur, Pankaj Deep; Chana, Inderveer

2014-01-01

The promising potential of cloud computing and its convergence with technologies such as mobile computing, wireless networks, sensor technologies allows for creation and delivery of newer type of cloud services. In this paper, we advocate the use of cloud computing for the creation and management of cloud based health care services. As a representative case study, we design a Cloud Based Intelligent Health Care Service (CBIHCS) that performs real time monitoring of user health data for diagnosis of chronic illness such as diabetes. Advance body sensor components are utilized to gather user specific health data and store in cloud based storage repositories for subsequent analysis and classification. In addition, infrastructure level mechanisms are proposed to provide dynamic resource elasticity for CBIHCS. Experimental results demonstrate that classification accuracy of 92.59% is achieved with our prototype system and the predicted patterns of CPU usage offer better opportunities for adaptive resource elasticity. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

KeyWare: an open wireless distributed computing environment

NASA Astrophysics Data System (ADS)

Shpantzer, Isaac; Schoenfeld, Larry; Grindahl, Merv; Kelman, Vladimir

1995-12-01

Deployment of distributed applications in the wireless domain lack equivalent tools, methodologies, architectures, and network management that exist in LAN based applications. A wireless distributed computing environment (KeyWareTM) based on intelligent agents within a multiple client multiple server scheme was developed to resolve this problem. KeyWare renders concurrent application services to wireline and wireless client nodes encapsulated in multiple paradigms such as message delivery, database access, e-mail, and file transfer. These services and paradigms are optimized to cope with temporal and spatial radio coverage, high latency, limited throughput and transmission costs. A unified network management paradigm for both wireless and wireline facilitates seamless extensions of LAN- based management tools to include wireless nodes. A set of object oriented tools and methodologies enables direct asynchronous invocation of agent-based services supplemented by tool-sets matched to supported KeyWare paradigms. The open architecture embodiment of KeyWare enables a wide selection of client node computing platforms, operating systems, transport protocols, radio modems and infrastructures while maintaining application portability.

The future of metabolomics in ELIXIR

PubMed Central

van Rijswijk, Merlijn; Beirnaert, Charlie; Caron, Christophe; Cascante, Marta; Dominguez, Victoria; Dunn, Warwick B.; Ebbels, Timothy M. D.; Giacomoni, Franck; Gonzalez-Beltran, Alejandra; Hankemeier, Thomas; Haug, Kenneth; Izquierdo-Garcia, Jose L.; Jimenez, Rafael C.; Jourdan, Fabien; Kale, Namrata; Klapa, Maria I.; Kohlbacher, Oliver; Koort, Kairi; Kultima, Kim; Le Corguillé, Gildas; Moreno, Pablo; Moschonas, Nicholas K.; Neumann, Steffen; O’Donovan, Claire; Reczko, Martin; Rocca-Serra, Philippe; Rosato, Antonio; Salek, Reza M.; Sansone, Susanna-Assunta; Satagopam, Venkata; Schober, Daniel; Shimmo, Ruth; Spicer, Rachel A.; Spjuth, Ola; Thévenot, Etienne A.; Viant, Mark R.; Weber, Ralf J. M.; Willighagen, Egon L.; Zanetti, Gianluigi; Steinbeck, Christoph

2017-01-01

Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the “Future of metabolomics in ELIXIR” was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases. PMID:29043062

The future of metabolomics in ELIXIR.

PubMed

van Rijswijk, Merlijn; Beirnaert, Charlie; Caron, Christophe; Cascante, Marta; Dominguez, Victoria; Dunn, Warwick B; Ebbels, Timothy M D; Giacomoni, Franck; Gonzalez-Beltran, Alejandra; Hankemeier, Thomas; Haug, Kenneth; Izquierdo-Garcia, Jose L; Jimenez, Rafael C; Jourdan, Fabien; Kale, Namrata; Klapa, Maria I; Kohlbacher, Oliver; Koort, Kairi; Kultima, Kim; Le Corguillé, Gildas; Moreno, Pablo; Moschonas, Nicholas K; Neumann, Steffen; O'Donovan, Claire; Reczko, Martin; Rocca-Serra, Philippe; Rosato, Antonio; Salek, Reza M; Sansone, Susanna-Assunta; Satagopam, Venkata; Schober, Daniel; Shimmo, Ruth; Spicer, Rachel A; Spjuth, Ola; Thévenot, Etienne A; Viant, Mark R; Weber, Ralf J M; Willighagen, Egon L; Zanetti, Gianluigi; Steinbeck, Christoph

2017-01-01

Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.

SEQADAPT: an adaptable system for the tracking, storage and analysis of high throughput sequencing experiments.

PubMed

Burdick, David B; Cavnor, Chris C; Handcock, Jeremy; Killcoyne, Sarah; Lin, Jake; Marzolf, Bruz; Ramsey, Stephen A; Rovira, Hector; Bressler, Ryan; Shmulevich, Ilya; Boyle, John

2010-07-14

High throughput sequencing has become an increasingly important tool for biological research. However, the existing software systems for managing and processing these data have not provided the flexible infrastructure that research requires. Existing software solutions provide static and well-established algorithms in a restrictive package. However as high throughput sequencing is a rapidly evolving field, such static approaches lack the ability to readily adopt the latest advances and techniques which are often required by researchers. We have used a loosely coupled, service-oriented infrastructure to develop SeqAdapt. This system streamlines data management and allows for rapid integration of novel algorithms. Our approach also allows computational biologists to focus on developing and applying new methods instead of writing boilerplate infrastructure code. The system is based around the Addama service architecture and is available at our website as a demonstration web application, an installable single download and as a collection of individual customizable services.

SEQADAPT: an adaptable system for the tracking, storage and analysis of high throughput sequencing experiments

PubMed Central

2010-01-01

Background High throughput sequencing has become an increasingly important tool for biological research. However, the existing software systems for managing and processing these data have not provided the flexible infrastructure that research requires. Results Existing software solutions provide static and well-established algorithms in a restrictive package. However as high throughput sequencing is a rapidly evolving field, such static approaches lack the ability to readily adopt the latest advances and techniques which are often required by researchers. We have used a loosely coupled, service-oriented infrastructure to develop SeqAdapt. This system streamlines data management and allows for rapid integration of novel algorithms. Our approach also allows computational biologists to focus on developing and applying new methods instead of writing boilerplate infrastructure code. Conclusion The system is based around the Addama service architecture and is available at our website as a demonstration web application, an installable single download and as a collection of individual customizable services. PMID:20630057

Internet of things for an age-friendly healthcare.

PubMed

Konstantinidis, Evdokimos I; Bamparopoulos, Giorgos; Billis, Antonis; Bamidis, Panagiotis D

2015-01-01

In healthcare applications a large cohort of recent implementations utilises IoT-oriented infrastructures (XMPP) as well as smart mobile devices as communication gateways. IoT characteristi Communication/Connectivity, Pervasive Computing and Ambient Intelligence, are all highly related to Active and Healthy Aging environments. This paper presents a new idea, that of IoT enabled devices which are directly connected to the IoT (a glucose meter is used as an example herein), complying with the XMPP messaging protocol and the incorporation of a recently released Controller Application Communication (CAC) framework for distributed, cross-platform communication. A web based exergaming platform and a disease management tool, provide the vehicles for the demonstration of the feasibility and the successful implementation and integration of the aforementioned infrastructure.

Tool Integration Framework for Bio-Informatics

DTIC Science & Technology

2007-04-01

Java NetBeans [11] based Integrated Development Environment (IDE) for developing modules and packaging computational tools. The framework is extremely...integrate an Eclipse front-end for Desktop Integration. Eclipse was chosen over Netbeans owing to a higher acceptance, better infrastructure...5.0. This version of Dashboard ran with NetBeans IDE 3.6 requiring Java Runtime 1.4 on a machine with Windows XP. The toolchain is executed by

The AAL project: automated monitoring and intelligent analysis for the ATLAS data taking infrastructure

NASA Astrophysics Data System (ADS)

Kazarov, A.; Lehmann Miotto, G.; Magnoni, L.

2012-06-01

The Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment at CERN is the infrastructure responsible for collecting and transferring ATLAS experimental data from detectors to the mass storage system. It relies on a large, distributed computing environment, including thousands of computing nodes with thousands of application running concurrently. In such a complex environment, information analysis is fundamental for controlling applications behavior, error reporting and operational monitoring. During data taking runs, streams of messages sent by applications via the message reporting system together with data published from applications via information services are the main sources of knowledge about correctness of running operations. The flow of data produced (with an average rate of O(1-10KHz)) is constantly monitored by experts to detect problem or misbehavior. This requires strong competence and experience in understanding and discovering problems and root causes, and often the meaningful information is not in the single message or update, but in the aggregated behavior in a certain time-line. The AAL project is meant at reducing the man power needs and at assuring a constant high quality of problem detection by automating most of the monitoring tasks and providing real-time correlation of data-taking and system metrics. This project combines technologies coming from different disciplines, in particular it leverages on an Event Driven Architecture to unify the flow of data from the ATLAS infrastructure, on a Complex Event Processing (CEP) engine for correlation of events and on a message oriented architecture for components integration. The project is composed of 2 main components: a core processing engine, responsible for correlation of events through expert-defined queries and a web based front-end to present real-time information and interact with the system. All components works in a loose-coupled event based architecture, with a message broker to centralize all communication between modules. The result is an intelligent system able to extract and compute relevant information from the flow of operational data to provide real-time feedback to human experts who can promptly react when needed. The paper presents the design and implementation of the AAL project, together with the results of its usage as automated monitoring assistant for the ATLAS data taking infrastructure.

The EPOS ICT Architecture

NASA Astrophysics Data System (ADS)

Jeffery, Keith; Harrison, Matt; Bailo, Daniele

2016-04-01

The EPOS-PP Project 2010-2014 proposed an architecture and demonstrated feasibility with a prototype. Requirements based on use cases were collected and an inventory of assets (e.g. datasets, software, users, computing resources, equipment/detectors, laboratory services) (RIDE) was developed. The architecture evolved through three stages of refinement with much consultation both with the EPOS community representing EPOS users and participants in geoscience and with the overall ICT community especially those working on research such as the RDA (Research Data Alliance) community. The architecture consists of a central ICS (Integrated Core Services) consisting of a portal and catalog, the latter providing to end-users a 'map' of all EPOS resources (datasets, software, users, computing, equipment/detectors etc.). ICS is extended to ICS-d (distributed ICS) for certain services (such as visualisation software services or Cloud computing resources) and CES (Computational Earth Science) for specific simulation or analytical processing. ICS also communicates with TCS (Thematic Core Services) which represent European-wide portals to national and local assets, resources and services in the various specific domains (e.g. seismology, volcanology, geodesy) of EPOS. The EPOS-IP project 2015-2019 started October 2015. Two work-packages cover the ICT aspects; WP6 involves interaction with the TCS while WP7 concentrates on ICS including interoperation with ICS-d and CES offerings: in short the ICT architecture. Based on the experience and results of EPOS-PP the ICT team held a pre-meeting in July 2015 and set out a project plan. The first major activity involved requirements (re-)collection with use cases and also updating the inventory of assets held by the various TCS in EPOS. The RIDE database of assets is currently being converted to CERIF (Common European Research Information Format - an EU Recommendation to Member States) to provide the basis for the EPOS-IP ICS Catalog. In parallel the ICT team is tracking developments in ICT for relevance to EPOS-IP. In particular, the potential utilisation of e-Is (e-Infrastructures) such as GEANT(network), AARC (security), EGI (GRID computing), EUDAT (data curation), PRACE (High Performance Computing), HELIX-Nebula / Open Science Cloud (Cloud computing) are being assessed. Similarly relationships to other e-RIs (e-Research Infrastructures) such as ENVRI+, EXCELERATE and other ESFRI (European Strategic Forum for Research Infrastructures) projects are developed to share experience and technology and to promote interoperability. EPOS ICT team members are also involved in VRE4EIC, a project developing a reference architecture and component software services for a Virtual Research Environment to be superimposed on EPOS-ICS. The challenge which is being tackled now is therefore to keep consistency and interoperability among the different modules, initiatives and actors which participate to the process of running the EPOS platform. It implies both a continuous update about IT aspects of mentioned initiatives and a refinement of the e-architecture designed so far. One major aspect of EPOS-IP is the ICT support for legalistic, financial and governance aspects of the EPOS ERIC to be initiated during EPOS-IP. This implies a sophisticated AAAI (Authentication, authorization, accounting infrastructure) with consistency throughout the software, communications and data stack.

OpenSoC Fabric

DOE Office of Scientific and Technical Information (OSTI.GOV)

2014-08-21

Recent advancements in technology scaling have shown a trend towards greater integration with large-scale chips containing thousands of processors connected to memories and other I/O devices using non-trivial network topologies. Software simulation proves insufficient to study the tradeoffs in such complex systems due to slow execution time, whereas hardware RTL development is too time-consuming. We present OpenSoC Fabric, an on-chip network generation infrastructure which aims to provide a parameterizable and powerful on-chip network generator for evaluating future high performance computing architectures based on SoC technology. OpenSoC Fabric leverages a new hardware DSL, Chisel, which contains powerful abstractions provided by itsmore » base language, Scala, and generates both software (C++) and hardware (Verilog) models from a single code base. The OpenSoC Fabric2 infrastructure is modeled after existing state-of-the-art simulators, offers large and powerful collections of configuration options, and follows object-oriented design and functional programming to make functionality extension as easy as possible.« less

A Cloud-Based Global Flood Disaster Community Cyber-Infrastructure: Development and Demonstration

NASA Technical Reports Server (NTRS)

Wan, Zhanming; Hong, Yang; Khan, Sadiq; Gourley, Jonathan; Flamig, Zachary; Kirschbaum, Dalia; Tang, Guoqiang

2014-01-01

Flood disasters have significant impacts on the development of communities globally. This study describes a public cloud-based flood cyber-infrastructure (CyberFlood) that collects, organizes, visualizes, and manages several global flood databases for authorities and the public in real-time, providing location-based eventful visualization as well as statistical analysis and graphing capabilities. In order to expand and update the existing flood inventory, a crowdsourcing data collection methodology is employed for the public with smartphones or Internet to report new flood events, which is also intended to engage citizen-scientists so that they may become motivated and educated about the latest developments in satellite remote sensing and hydrologic modeling technologies. Our shared vision is to better serve the global water community with comprehensive flood information, aided by the state-of-the- art cloud computing and crowdsourcing technology. The CyberFlood presents an opportunity to eventually modernize the existing paradigm used to collect, manage, analyze, and visualize water-related disasters.

A Serviced-based Approach to Connect Seismological Infrastructures: Current Efforts at the IRIS DMC

NASA Astrophysics Data System (ADS)

Ahern, Tim; Trabant, Chad

2014-05-01

As part of the COOPEUS initiative to build infrastructure that connects European and US research infrastructures, IRIS has advocated for the development of Federated services based upon internationally recognized standards using web services. By deploying International Federation of Digital Seismograph Networks (FDSN) endorsed web services at multiple data centers in the US and Europe, we have shown that integration within seismological domain can be realized. By deploying identical methods to invoke the web services at multiple centers this approach can significantly ease the methods through which a scientist can access seismic data (time series, metadata, and earthquake catalogs) from distributed federated centers. IRIS has developed an IRIS federator that helps a user identify where seismic data from global seismic networks can be accessed. The web services based federator can build the appropriate URLs and return them to client software running on the scientists own computer. These URLs are then used to directly pull data from the distributed center in a very peer-based fashion. IRIS is also involved in deploying web services across horizontal domains. As part of the US National Science Foundation's (NSF) EarthCube effort, an IRIS led EarthCube Building Block's project is underway. When completed this project will aid in the discovery, access, and usability of data across multiple geoscienece domains. This presentation will summarize current IRIS efforts in building vertical integration infrastructure within seismology working closely with 5 centers in Europe and 2 centers in the US, as well as how we are taking first steps toward horizontal integration of data from 14 different domains in the US, in Europe, and around the world.

The diverse use of clouds by CMS

DOE PAGES

Andronis, Anastasios; Bauer, Daniela; Chaze, Olivier; ...

2015-12-23

The resources CMS is using are increasingly being offered as clouds. In Run 2 of the LHC the majority of CMS CERN resources, both in Meyrin and at the Wigner Computing Centre, will be presented as cloud resources on which CMS will have to build its own infrastructure. This infrastructure will need to run all of the CMS workflows including: Tier 0, production and user analysis. In addition, the CMS High Level Trigger will provide a compute resource comparable in scale to the total offered by the CMS Tier 1 sites, when it is not running as part of themore » trigger system. During these periods a cloud infrastructure will be overlaid on this resource, making it accessible for general CMS use. Finally, CMS is starting to utilise cloud resources being offered by individual institutes and is gaining experience to facilitate the use of opportunistically available cloud resources. Lastly, we present a snap shot of this infrastructure and its operation at the time of the CHEP2015 conference.« less

Open source system OpenVPN in a function of Virtual Private Network

NASA Astrophysics Data System (ADS)

Skendzic, A.; Kovacic, B.

2017-05-01

Using of Virtual Private Networks (VPN) can establish high security level in network communication. VPN technology enables high security networking using distributed or public network infrastructure. VPN uses different security and managing rules inside networks. It can be set up using different communication channels like Internet or separate ISP communication infrastructure. VPN private network makes security communication channel over public network between two endpoints (computers). OpenVPN is an open source software product under GNU General Public License (GPL) that can be used to establish VPN communication between two computers inside business local network over public communication infrastructure. It uses special security protocols and 256-bit Encryption and it is capable of traversing network address translators (NATs) and firewalls. It allows computers to authenticate each other using a pre-shared secret key, certificates or username and password. This work gives review of VPN technology with a special accent on OpenVPN. This paper will also give comparison and financial benefits of using open source VPN software in business environment.

Cloudweaver: Adaptive and Data-Driven Workload Manager for Generic Clouds

NASA Astrophysics Data System (ADS)

Li, Rui; Chen, Lei; Li, Wen-Syan

Cloud computing denotes the latest trend in application development for parallel computing on massive data volumes. It relies on clouds of servers to handle tasks that used to be managed by an individual server. With cloud computing, software vendors can provide business intelligence and data analytic services for internet scale data sets. Many open source projects, such as Hadoop, offer various software components that are essential for building a cloud infrastructure. Current Hadoop (and many others) requires users to configure cloud infrastructures via programs and APIs and such configuration is fixed during the runtime. In this chapter, we propose a workload manager (WLM), called CloudWeaver, which provides automated configuration of a cloud infrastructure for runtime execution. The workload management is data-driven and can adapt to dynamic nature of operator throughput during different execution phases. CloudWeaver works for a single job and a workload consisting of multiple jobs running concurrently, which aims at maximum throughput using a minimum set of processors.

Assessing the uptake of persistent identifiers by research infrastructure users

PubMed Central

Maull, Keith E.

2017-01-01

Significant progress has been made in the past few years in the development of recommendations, policies, and procedures for creating and promoting citations to data sets, software, and other research infrastructures like computing facilities. Open questions remain, however, about the extent to which referencing practices of authors of scholarly publications are changing in ways desired by these initiatives. This paper uses four focused case studies to evaluate whether research infrastructures are being increasingly identified and referenced in the research literature via persistent citable identifiers. The findings of the case studies show that references to such resources are increasing, but that the patterns of these increases are variable. In addition, the study suggests that citation practices for data sets may change more slowly than citation practices for software and research facilities, due to the inertia of existing practices for referencing the use of data. Similarly, existing practices for acknowledging computing support may slow the adoption of formal citations for computing resources. PMID:28394907

Big-BOE: Fusing Spanish Official Gazette with Big Data Technology.

PubMed

Basanta-Val, Pablo; Sánchez-Fernández, Luis

2018-06-01

The proliferation of new data sources, stemmed from the adoption of open-data schemes, in combination with an increasing computing capacity causes the inception of new type of analytics that process Internet of things with low-cost engines to speed up data processing using parallel computing. In this context, the article presents an initiative, called BIG-Boletín Oficial del Estado (BOE), designed to process the Spanish official government gazette (BOE) with state-of-the-art processing engines, to reduce computation time and to offer additional speed up for big data analysts. The goal of including a big data infrastructure is to be able to process different BOE documents in parallel with specific analytics, to search for several issues in different documents. The application infrastructure processing engine is described from an architectural perspective and from performance, showing evidence on how this type of infrastructure improves the performance of different types of simple analytics as several machines cooperate.

NASA's Participation in the National Computational Grid

NASA Technical Reports Server (NTRS)

Feiereisen, William J.; Zornetzer, Steve F. (Technical Monitor)

1998-01-01

Over the last several years it has become evident that the character of NASA's supercomputing needs has changed. One of the major missions of the agency is to support the design and manufacture of aero- and space-vehicles with technologies that will significantly reduce their cost. It is becoming clear that improvements in the process of aerospace design and manufacturing will require a high performance information infrastructure that allows geographically dispersed teams to draw upon resources that are broader than traditional supercomputing. A computational grid draws together our information resources into one system. We can foresee the time when a Grid will allow engineers and scientists to use the tools of supercomputers, databases and on line experimental devices in a virtual environment to collaborate with distant colleagues. The concept of a computational grid has been spoken of for many years, but several events in recent times are conspiring to allow us to actually build one. In late 1997 the National Science Foundation initiated the Partnerships for Advanced Computational Infrastructure (PACI) which is built around the idea of distributed high performance computing. The Alliance lead, by the National Computational Science Alliance (NCSA), and the National Partnership for Advanced Computational Infrastructure (NPACI), lead by the San Diego Supercomputing Center, have been instrumental in drawing together the "Grid Community" to identify the technology bottlenecks and propose a research agenda to address them. During the same period NASA has begun to reformulate parts of two major high performance computing research programs to concentrate on distributed high performance computing and has banded together with the PACI centers to address the research agenda in common.

A Primer on High-Throughput Computing for Genomic Selection

PubMed Central

Wu, Xiao-Lin; Beissinger, Timothy M.; Bauck, Stewart; Woodward, Brent; Rosa, Guilherme J. M.; Weigel, Kent A.; Gatti, Natalia de Leon; Gianola, Daniel

2011-01-01

High-throughput computing (HTC) uses computer clusters to solve advanced computational problems, with the goal of accomplishing high-throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long, and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl, and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general-purpose computation on a graphics processing unit provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin–Madison, which can be leveraged for genomic selection, in terms of central processing unit capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general-purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of marker panels to realized genetic gain). Eventually, HTC may change our view of data analysis as well as decision-making in the post-genomic era of selection programs in animals and plants, or in the study of complex diseases in humans. PMID:22303303

The StratusLab cloud distribution: Use-cases and support for scientific applications

NASA Astrophysics Data System (ADS)

Floros, E.

2012-04-01

The StratusLab project is integrating an open cloud software distribution that enables organizations to setup and provide their own private or public IaaS (Infrastructure as a Service) computing clouds. StratusLab distribution capitalizes on popular infrastructure virtualization solutions like KVM, the OpenNebula virtual machine manager, Claudia service manager and SlipStream deployment platform, which are further enhanced and expanded with additional components developed within the project. The StratusLab distribution covers the core aspects of a cloud IaaS architecture, namely Computing (life-cycle management of virtual machines), Storage, Appliance management and Networking. The resulting software stack provides a packaged turn-key solution for deploying cloud computing services. The cloud computing infrastructures deployed using StratusLab can support a wide range of scientific and business use cases. Grid computing has been the primary use case pursued by the project and for this reason the initial priority has been the support for the deployment and operation of fully virtualized production-level grid sites; a goal that has already been achieved by operating such a site as part of EGI's (European Grid Initiative) pan-european grid infrastructure. In this area the project is currently working to provide non-trivial capabilities like elastic and autonomic management of grid site resources. Although grid computing has been the motivating paradigm, StratusLab's cloud distribution can support a wider range of use cases. Towards this direction, we have developed and currently provide support for setting up general purpose computing solutions like Hadoop, MPI and Torque clusters. For what concerns scientific applications the project is collaborating closely with the Bioinformatics community in order to prepare VM appliances and deploy optimized services for bioinformatics applications. In a similar manner additional scientific disciplines like Earth Science can take advantage of StratusLab cloud solutions. Interested users are welcomed to join StratusLab's user community by getting access to the reference cloud services deployed by the project and offered to the public.

Infrastructure for Training and Partnershipes: California Water and Coastal Ocean Resources

NASA Technical Reports Server (NTRS)

Siegel, David A.; Dozier, Jeffrey; Gautier, Catherine; Davis, Frank; Dickey, Tommy; Dunne, Thomas; Frew, James; Keller, Arturo; MacIntyre, Sally; Melack, John

2000-01-01

The purpose of this project was to advance the existing ICESS/Bren School computing infrastructure to allow scientists, students, and research trainees the opportunity to interact with environmental data and simulations in near-real time. Improvements made with the funding from this project have helped to strengthen the research efforts within both units, fostered graduate research training, and helped fortify partnerships with government and industry. With this funding, we were able to expand our computational environment in which computer resources, software, and data sets are shared by ICESS/Bren School faculty researchers in all areas of Earth system science. All of the graduate and undergraduate students associated with the Donald Bren School of Environmental Science and Management and the Institute for Computational Earth System Science have benefited from the infrastructure upgrades accomplished by this project. Additionally, the upgrades fostered a significant number of research projects (attached is a list of the projects that benefited from the upgrades). As originally proposed, funding for this project provided the following infrastructure upgrades: 1) a modem file management system capable of interoperating UNIX and NT file systems that can scale to 6.7 TB, 2) a Qualstar 40-slot tape library with two AIT tape drives and Legato Networker backup/archive software, 3) previously unavailable import/export capability for data sets on Zip, Jaz, DAT, 8mm, CD, and DLT media in addition to a 622Mb/s Internet 2 connection, 4) network switches capable of 100 Mbps to 128 desktop workstations, 5) Portable Batch System (PBS) computational task scheduler, and vi) two Compaq/Digital Alpha XP1000 compute servers each with 1.5 GB of RAM along with an SGI Origin 2000 (purchased partially using funds from this project along with funding from various other sources) to be used for very large computations, as required for simulation of mesoscale meteorology or climate.

Parallel Infrastructure Modeling and Inversion Module for E4D

DOE Office of Scientific and Technical Information (OSTI.GOV)

2014-10-09

Electrical resistivity tomography ERT is a method of imaging the electrical conductivity of the subsurface. Electrical conductivity is a useful metric for understanding the subsurface because it is governed by geomechanical and geochemical properties that drive subsurface systems. ERT works by injecting current into the subsurface across a pair of electrodes, and measuring the corresponding electrical potential response across another pair of electrodes. Many such measurements are strategically taken across an array of electrodes to produce an ERT data set. These data are then processed through a computationally demanding process known as inversion to produce an image of the subsurfacemore » conductivity structure that gave rise to the measurements. Data can be inverted to provide 2D images, 3D images, or in the case of time-lapse 3D imaging, 4D images. ERT is generally not well suited for environments with buried electrically conductive infrastructure such as pipes, tanks, or well casings, because these features tend to dominate and degrade ERT images. This reduces or eliminates the utility of ERT imaging where it would otherwise be highly useful for, for example, imaging fluid migration from leaking pipes, imaging soil contamination beneath leaking subusurface tanks, and monitoring contaminant migration in locations with dense network of metal cased monitoring wells. The location and dimension of buried metallic infrastructure is often known. If so, then the effects of the infrastructure can be explicitly modeled within the ERT imaging algorithm, and thereby removed from the corresponding ERT image. However,there are a number of obstacles limiting this application. 1) Metallic infrastructure cannot be accurately modeled with standard codes because of the large contrast in conductivity between the metal and host material. 2) Modeling infrastructure in true dimension requires the computational mesh to be highly refined near the metal inclusions, which increases computational demands. 3) The ERT imaging algorithm requires specialized modifications to accomodate high conductivty inclusions within the computational mesh. The solution to each of these challenges was implemented within E4D (formerly FERM3D), which is a parallel ERT imaging code developed at PNNL (IPID #30249). The infrastructure modeling module implement in E4D uses a method of decoupling the model at the metallic interface(s) boundaries, into several well posed sub-problems (one for each distinct metallicinclusion) that are subsequently solved and recombined to form the global solution. The approach is based on the immersed interface method, with has been applied for similar problems in other fields (e.g. semiconductor industry). Comparisons to analytic solutions have shown the results to be very accurate, addressing item 1 above. The solution is implemented about an unstructured mesh, which enables arbitrary shapes to be efficiently modelled, thereby addressing item 2 above. In addition, the algorithm is written in parallel and shows excellent scalability, which also addresses equation 2 above. Finally, because only the boundaries of metallic inclusions are modeled, there are no high conductivity cells within the modeling mesh, and the problem described by item 3 above is no longer applicable.« less

Constructing a Foundational Platform Driven by Japan's K Supercomputer for Next-Generation Drug Design.

PubMed

Brown, J B; Nakatsui, Masahiko; Okuno, Yasushi

2014-12-01

The cost of pharmaceutical R&D has risen enormously, both worldwide and in Japan. However, Japan faces a particularly difficult situation in that its population is aging rapidly, and the cost of pharmaceutical R&D affects not only the industry but the entire medical system as well. To attempt to reduce costs, the newly launched K supercomputer is available for big data drug discovery and structural simulation-based drug discovery. We have implemented both primary (direct) and secondary (infrastructure, data processing) methods for the two types of drug discovery, custom tailored to maximally use the 88 128 compute nodes/CPUs of K, and evaluated the implementations. We present two types of results. In the first, we executed the virtual screening of nearly 19 billion compound-protein interactions, and calculated the accuracy of predictions against publicly available experimental data. In the second investigation, we implemented a very computationally intensive binding free energy algorithm, and found that comparison of our binding free energies was considerably accurate when validated against another type of publicly available experimental data. The common feature of both result types is the scale at which computations were executed. The frameworks presented in this article provide prospectives and applications that, while tuned to the computing resources available in Japan, are equally applicable to any equivalent large-scale infrastructure provided elsewhere. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automating ATLAS Computing Operations using the Site Status Board

NASA Astrophysics Data System (ADS)

J, Andreeva; Iglesias C, Borrego; S, Campana; Girolamo A, Di; I, Dzhunov; Curull X, Espinal; S, Gayazov; E, Magradze; M, Nowotka M.; L, Rinaldi; P, Saiz; J, Schovancova; A, Stewart G.; M, Wright

2012-12-01

The automation of operations is essential to reduce manpower costs and improve the reliability of the system. The Site Status Board (SSB) is a framework which allows Virtual Organizations to monitor their computing activities at distributed sites and to evaluate site performance. The ATLAS experiment intensively uses the SSB for the distributed computing shifts, for estimating data processing and data transfer efficiencies at a particular site, and for implementing automatic exclusion of sites from computing activities, in case of potential problems. The ATLAS SSB provides a real-time aggregated monitoring view and keeps the history of the monitoring metrics. Based on this history, usability of a site from the perspective of ATLAS is calculated. The paper will describe how the SSB is integrated in the ATLAS operations and computing infrastructure and will cover implementation details of the ATLAS SSB sensors and alarm system, based on the information in the SSB. It will demonstrate the positive impact of the use of the SSB on the overall performance of ATLAS computing activities and will overview future plans.

Research infrastructure support to address ecosystem dynamics

NASA Astrophysics Data System (ADS)

Los, Wouter

2014-05-01

Predicting the evolution of ecosystems to climate change or human pressures is a challenge. Even understanding past or current processes is complicated as a result of the many interactions and feedbacks that occur within and between components of the system. This talk will present an example of current research on changes in landscape evolution, hydrology, soil biogeochemical processes, zoological food webs, and plant community succession, and how these affect feedbacks to components of the systems, including the climate system. Multiple observations, experiments, and simulations provide a wealth of data, but not necessarily understanding. Model development on the coupled processes on different spatial and temporal scales is sensitive for variations in data and of parameter change. Fast high performance computing may help to visualize the effect of these changes and the potential stability (and reliability) of the models. This may than allow for iteration between data production and models towards stable models reducing uncertainty and improving the prediction of change. The role of research infrastructures becomes crucial is overcoming barriers for such research. Environmental infrastructures are covering physical site facilities, dedicated instrumentation and e-infrastructure. The LifeWatch infrastructure for biodiversity and ecosystem research will provide services for data integration, analysis and modeling. But it has to cooperate intensively with the other kinds of infrastructures in order to support the iteration between data production and model computation. The cooperation in the ENVRI project (Common operations of environmental research infrastructures) is one of the initiatives to foster such multidisciplinary research.

Physicists Get INSPIREd: INSPIRE Project and Grid Applications

NASA Astrophysics Data System (ADS)

Klem, Jukka; Iwaszkiewicz, Jan

2011-12-01

INSPIRE is the new high-energy physics scientific information system developed by CERN, DESY, Fermilab and SLAC. INSPIRE combines the curated and trusted contents of SPIRES database with Invenio digital library technology. INSPIRE contains the entire HEP literature with about one million records and in addition to becoming the reference HEP scientific information platform, it aims to provide new kinds of data mining services and metrics to assess the impact of articles and authors. Grid and cloud computing provide new opportunities to offer better services in areas that require large CPU and storage resources including document Optical Character Recognition (OCR) processing, full-text indexing of articles and improved metrics. D4Science-II is a European project that develops and operates an e-Infrastructure supporting Virtual Research Environments (VREs). It develops an enabling technology (gCube) which implements a mechanism for facilitating the interoperation of its e-Infrastructure with other autonomously running data e-Infrastructures. As a result, this creates the core of an e-Infrastructure ecosystem. INSPIRE is one of the e-Infrastructures participating in D4Science-II project. In the context of the D4Science-II project, the INSPIRE e-Infrastructure makes available some of its resources and services to other members of the resulting ecosystem. Moreover, it benefits from the ecosystem via a dedicated Virtual Organization giving access to an array of resources ranging from computing and storage resources of grid infrastructures to data and services.

Wide-area, real-time monitoring and visualization system

DOEpatents

Budhraja, Vikram S.; Dyer, James D.; Martinez Morales, Carlos A.

2013-03-19

A real-time performance monitoring system for monitoring an electric power grid. The electric power grid has a plurality of grid portions, each grid portion corresponding to one of a plurality of control areas. The real-time performance monitoring system includes a monitor computer for monitoring at least one of reliability metrics, generation metrics, transmission metrics, suppliers metrics, grid infrastructure security metrics, and markets metrics for the electric power grid. The data for metrics being monitored by the monitor computer are stored in a data base, and a visualization of the metrics is displayed on at least one display computer having a monitor. The at least one display computer in one said control area enables an operator to monitor the grid portion corresponding to a different said control area.

Wide-area, real-time monitoring and visualization system

DOEpatents

Budhraja, Vikram S [Los Angeles, CA; Dyer, James D [La Mirada, CA; Martinez Morales, Carlos A [Upland, CA

2011-11-15

A real-time performance monitoring system for monitoring an electric power grid. The electric power grid has a plurality of grid portions, each grid portion corresponding to one of a plurality of control areas. The real-time performance monitoring system includes a monitor computer for monitoring at least one of reliability metrics, generation metrics, transmission metrics, suppliers metrics, grid infrastructure security metrics, and markets metrics for the electric power grid. The data for metrics being monitored by the monitor computer are stored in a data base, and a visualization of the metrics is displayed on at least one display computer having a monitor. The at least one display computer in one said control area enables an operator to monitor the grid portion corresponding to a different said control area.

Real-time performance monitoring and management system

DOEpatents

Budhraja, Vikram S [Los Angeles, CA; Dyer, James D [La Mirada, CA; Martinez Morales, Carlos A [Upland, CA

2007-06-19

A real-time performance monitoring system for monitoring an electric power grid. The electric power grid has a plurality of grid portions, each grid portion corresponding to one of a plurality of control areas. The real-time performance monitoring system includes a monitor computer for monitoring at least one of reliability metrics, generation metrics, transmission metrics, suppliers metrics, grid infrastructure security metrics, and markets metrics for the electric power grid. The data for metrics being monitored by the monitor computer are stored in a data base, and a visualization of the metrics is displayed on at least one display computer having a monitor. The at least one display computer in one said control area enables an operator to monitor the grid portion corresponding to a different said control area.

SEED: A Suite of Instructional Laboratories for Computer Security Education

ERIC Educational Resources Information Center

Du, Wenliang; Wang, Ronghua

2008-01-01

The security and assurance of our computing infrastructure has become a national priority. To address this priority, higher education has gradually incorporated the principles of computer and information security into the mainstream undergraduate and graduate computer science curricula. To achieve effective education, learning security principles…

Storing and using health data in a virtual private cloud.

PubMed

Regola, Nathan; Chawla, Nitesh V

2013-03-13

Electronic health records are being adopted at a rapid rate due to increased funding from the US federal government. Health data provide the opportunity to identify possible improvements in health care delivery by applying data mining and statistical methods to the data and will also enable a wide variety of new applications that will be meaningful to patients and medical professionals. Researchers are often granted access to health care data to assist in the data mining process, but HIPAA regulations mandate comprehensive safeguards to protect the data. Often universities (and presumably other research organizations) have an enterprise information technology infrastructure and a research infrastructure. Unfortunately, both of these infrastructures are generally not appropriate for sensitive research data such as HIPAA, as they require special accommodations on the part of the enterprise information technology (or increased security on the part of the research computing environment). Cloud computing, which is a concept that allows organizations to build complex infrastructures on leased resources, is rapidly evolving to the point that it is possible to build sophisticated network architectures with advanced security capabilities. We present a prototype infrastructure in Amazon's Virtual Private Cloud to allow researchers and practitioners to utilize the data in a HIPAA-compliant environment.

Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duque, Earl P.N.; Whitlock, Brad J.

High performance computers have for many years been on a trajectory that gives them extraordinary compute power with the addition of more and more compute cores. At the same time, other system parameters such as the amount of memory per core and bandwidth to storage have remained constant or have barely increased. This creates an imbalance in the computer, giving it the ability to compute a lot of data that it cannot reasonably save out due to time and storage constraints. While technologies have been invented to mitigate this problem (burst buffers, etc.), software has been adapting to employ inmore » situ libraries which perform data analysis and visualization on simulation data while it is still resident in memory. This avoids the need to ever have to pay the costs of writing many terabytes of data files. Instead, in situ enables the creation of more concentrated data products such as statistics, plots, and data extracts, which are all far smaller than the full-sized volume data. With the increasing popularity of in situ, multiple in situ infrastructures have been created, each with its own mechanism for integrating with a simulation. To make it easier to instrument a simulation with multiple in situ infrastructures and include custom analysis algorithms, this project created the SENSEI framework.« less

An EMSO data case study within the INDIGO-DC project

NASA Astrophysics Data System (ADS)

Monna, Stephen; Marcucci, Nicola M.; Marinaro, Giuditta; Fiore, Sandro; D'Anca, Alessandro; Antonacci, Marica; Beranzoli, Laura; Favali, Paolo

2017-04-01

We present our experience based on a case study within the INDIGO-DataCloud (INtegrating Distributed data Infrastructures for Global ExplOitation) project (www.indigo-datacloud.eu). The aim of INDIGO-DC is to develop a data and computing platform targeting scientific communities. Our case study is an example of activities performed by INGV using data from seafloor observatories that are nodes of the infrastructure EMSO (European Multidisciplinary Seafloor and water column Observatory)-ERIC (www.emso-eu.org). EMSO is composed of several deep-seafloor and water column observatories, deployed at key sites in the European waters, thus forming a widely distributed pan-European infrastructure. In our case study we consider data collected by the NEMO-SN1 observatory, one of the EMSO nodes used for geohazard monitoring, located in the Western Ionian Sea in proximity of Etna volcano. Starting from the case study, through an agile approach, we defined some requirements for INDIGO developers, and tested some of the proposed INDIGO solutions that are of interest for our research community. Given that EMSO is a distributed infrastructure, we are interested in INDIGO solutions that allow access to distributed data storage. Access should be both user-oriented and machine-oriented, and with the use of a common identity and access system. For this purpose, we have been testing: - ONEDATA (https://onedata.org), as global data management system. - INDIGO-IAM as Identity and Access Management system. Another aspect we are interested in is the efficient data processing, and we have focused on two types of INDIGO products: - Ophidia (http://ophidia.cmcc.it), a big data analytics framework for eScience for the analysis of multidimensional data. - A collection of INDIGO Services to run processes for scientific computing through the INDIGO Orchestrator.

Exploratory Application of Augmented Reality/Mixed Reality Devices for Acute Care Procedure Training.

PubMed

Kobayashi, Leo; Zhang, Xiao Chi; Collins, Scott A; Karim, Naz; Merck, Derek L

2018-01-01

Augmented reality (AR), mixed reality (MR), and virtual reality devices are enabling technologies that may facilitate effective communication in healthcare between those with information and knowledge (clinician/specialist; expert; educator) and those seeking understanding and insight (patient/family; non-expert; learner). Investigators initiated an exploratory program to enable the study of AR/MR use-cases in acute care clinical and instructional settings. Academic clinician educators, computer scientists, and diagnostic imaging specialists conducted a proof-of-concept project to 1) implement a core holoimaging pipeline infrastructure and open-access repository at the study institution, and 2) use novel AR/MR techniques on off-the-shelf devices with holoimages generated by the infrastructure to demonstrate their potential role in the instructive communication of complex medical information. The study team successfully developed a medical holoimaging infrastructure methodology to identify, retrieve, and manipulate real patients' de-identified computed tomography and magnetic resonance imagesets for rendering, packaging, transfer, and display of modular holoimages onto AR/MR headset devices and connected displays. Holoimages containing key segmentations of cervical and thoracic anatomic structures and pathology were overlaid and registered onto physical task trainers for simulation-based "blind insertion" invasive procedural training. During the session, learners experienced and used task-relevant anatomic holoimages for central venous catheter and tube thoracostomy insertion training with enhanced visual cues and haptic feedback. Direct instructor access into the learner's AR/MR headset view of the task trainer was achieved for visual-axis interactive instructional guidance. Investigators implemented a core holoimaging pipeline infrastructure and modular open-access repository to generate and enable access to modular holoimages during exploratory pilot stage applications for invasive procedure training that featured innovative AR/MR techniques on off-the-shelf headset devices.

Exploratory Application of Augmented Reality/Mixed Reality Devices for Acute Care Procedure Training

PubMed Central

Kobayashi, Leo; Zhang, Xiao Chi; Collins, Scott A.; Karim, Naz; Merck, Derek L.

2018-01-01

Introduction Augmented reality (AR), mixed reality (MR), and virtual reality devices are enabling technologies that may facilitate effective communication in healthcare between those with information and knowledge (clinician/specialist; expert; educator) and those seeking understanding and insight (patient/family; non-expert; learner). Investigators initiated an exploratory program to enable the study of AR/MR use-cases in acute care clinical and instructional settings. Methods Academic clinician educators, computer scientists, and diagnostic imaging specialists conducted a proof-of-concept project to 1) implement a core holoimaging pipeline infrastructure and open-access repository at the study institution, and 2) use novel AR/MR techniques on off-the-shelf devices with holoimages generated by the infrastructure to demonstrate their potential role in the instructive communication of complex medical information. Results The study team successfully developed a medical holoimaging infrastructure methodology to identify, retrieve, and manipulate real patients’ de-identified computed tomography and magnetic resonance imagesets for rendering, packaging, transfer, and display of modular holoimages onto AR/MR headset devices and connected displays. Holoimages containing key segmentations of cervical and thoracic anatomic structures and pathology were overlaid and registered onto physical task trainers for simulation-based “blind insertion” invasive procedural training. During the session, learners experienced and used task-relevant anatomic holoimages for central venous catheter and tube thoracostomy insertion training with enhanced visual cues and haptic feedback. Direct instructor access into the learner’s AR/MR headset view of the task trainer was achieved for visual-axis interactive instructional guidance. Conclusion Investigators implemented a core holoimaging pipeline infrastructure and modular open-access repository to generate and enable access to modular holoimages during exploratory pilot stage applications for invasive procedure training that featured innovative AR/MR techniques on off-the-shelf headset devices. PMID:29383074

Design and implementation of a remote UAV-based mobile health monitoring system

NASA Astrophysics Data System (ADS)

Li, Songwei; Wan, Yan; Fu, Shengli; Liu, Mushuang; Wu, H. Felix

2017-04-01

Unmanned aerial vehicles (UAVs) play increasing roles in structure health monitoring. With growing mobility in modern Internet-of-Things (IoT) applications, the health monitoring of mobile structures becomes an emerging application. In this paper, we develop a UAV-carried vision-based monitoring system that allows a UAV to continuously track and monitor a mobile infrastructure and transmit back the monitoring information in real- time from a remote location. The monitoring system uses a simple UAV-mounted camera and requires only a single feature located on the mobile infrastructure for target detection and tracking. The computation-effective vision-based tracking solution based on a single feature is an improvement over existing vision-based lead-follower tracking systems that either have poor tracking performance due to the use of a single feature, or have improved tracking performance at a cost of the usage of multiple features. In addition, a UAV-carried aerial networking infrastructure using directional antennas is used to enable robust real-time transmission of monitoring video streams over a long distance. Automatic heading control is used to self-align headings of directional antennas to enable robust communication in mobility. Compared to existing omni-communication systems, the directional communication solution significantly increases the operation range of remote monitoring systems. In this paper, we develop the integrated modeling framework of camera and mobile platforms, design the tracking algorithm, develop a testbed of UAVs and mobile platforms, and evaluate system performance through both simulation studies and field tests.

Exploring Cloud Computing for Large-scale Scientific Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Guang; Han, Binh; Yin, Jian

This paper explores cloud computing for large-scale data-intensive scientific applications. Cloud computing is attractive because it provides hardware and software resources on-demand, which relieves the burden of acquiring and maintaining a huge amount of resources that may be used only once by a scientific application. However, unlike typical commercial applications that often just requires a moderate amount of ordinary resources, large-scale scientific applications often need to process enormous amount of data in the terabyte or even petabyte range and require special high performance hardware with low latency connections to complete computation in a reasonable amount of time. To address thesemore » challenges, we build an infrastructure that can dynamically select high performance computing hardware across institutions and dynamically adapt the computation to the selected resources to achieve high performance. We have also demonstrated the effectiveness of our infrastructure by building a system biology application and an uncertainty quantification application for carbon sequestration, which can efficiently utilize data and computation resources across several institutions.« less

NGScloud: RNA-seq analysis of non-model species using cloud computing.

PubMed

Mora-Márquez, Fernando; Vázquez-Poletti, José Luis; López de Heredia, Unai

2018-05-03

RNA-seq analysis usually requires large computing infrastructures. NGScloud is a bioinformatic system developed to analyze RNA-seq data using the cloud computing services of Amazon that permit the access to ad hoc computing infrastructure scaled according to the complexity of the experiment, so its costs and times can be optimized. The application provides a user-friendly front-end to operate Amazon's hardware resources, and to control a workflow of RNA-seq analysis oriented to non-model species, incorporating the cluster concept, which allows parallel runs of common RNA-seq analysis programs in several virtual machines for faster analysis. NGScloud is freely available at https://github.com/GGFHF/NGScloud/. A manual detailing installation and how-to-use instructions is available with the distribution. unai.lopezdeheredia@upm.es.

Securing the Data Storage and Processing in Cloud Computing Environment

ERIC Educational Resources Information Center

Owens, Rodney

2013-01-01

Organizations increasingly utilize cloud computing architectures to reduce costs and energy consumption both in the data warehouse and on mobile devices by better utilizing the computing resources available. However, the security and privacy issues with publicly available cloud computing infrastructures have not been studied to a sufficient depth…

Building Efficient Wireless Infrastructures for Pervasive Computing Environments

ERIC Educational Resources Information Center

Sheng, Bo

2010-01-01

Pervasive computing is an emerging concept that thoroughly brings computing devices and the consequent technology into people's daily life and activities. Most of these computing devices are very small, sometimes even "invisible", and often embedded into the objects surrounding people. In addition, these devices usually are not isolated, but…

CTserver: A Computational Thermodynamics Server for the Geoscience Community

NASA Astrophysics Data System (ADS)

Kress, V. C.; Ghiorso, M. S.

2006-12-01

The CTserver platform is an Internet-based computational resource that provides on-demand services in Computational Thermodynamics (CT) to a diverse geoscience user base. This NSF-supported resource can be accessed at ctserver.ofm-research.org. The CTserver infrastructure leverages a high-quality and rigorously tested software library of routines for computing equilibrium phase assemblages and for evaluating internally consistent thermodynamic properties of materials, e.g. mineral solid solutions and a variety of geological fluids, including magmas. Thermodynamic models are currently available for 167 phases. Recent additions include Duan, Møller and Weare's model for supercritical C-O-H-S, extended to include SO2 and S2 species, and an entirely new associated solution model for O-S-Fe-Ni sulfide liquids. This software library is accessed via the CORBA Internet protocol for client-server communication. CORBA provides a standardized, object-oriented, language and platform independent, fast, low-bandwidth interface to phase property modules running on the server cluster. Network transport, language translation and resource allocation are handled by the CORBA interface. Users access server functionality in two principal ways. Clients written as browser- based Java applets may be downloaded which provide specific functionality such as retrieval of thermodynamic properties of phases, computation of phase equilibria for systems of specified composition, or modeling the evolution of these systems along some particular reaction path. This level of user interaction requires minimal programming effort and is ideal for classroom use. A more universal and flexible mode of CTserver access involves making remote procedure calls from user programs directly to the server public interface. The CTserver infrastructure relieves the user of the burden of implementing and testing the often complex thermodynamic models of real liquids and solids. A pilot application of this distributed architecture involves CFD computation of magma convection at Volcan Villarrica with magma properties and phase proportions calculated at each spatial node and at each time step via distributed function calls to MELTS-objects executing on the CTserver. Documentation and programming examples are provided at http://ctserver.ofm- research.org.

DICOMGrid: a middleware to integrate PACS and EELA-2 grid infrastructure

NASA Astrophysics Data System (ADS)

Moreno, Ramon A.; de Sá Rebelo, Marina; Gutierrez, Marco A.

2010-03-01

Medical images provide lots of information for physicians, but the huge amount of data produced by medical image equipments in a modern Health Institution is not completely explored in its full potential yet. Nowadays medical images are used in hospitals mostly as part of routine activities while its intrinsic value for research is underestimated. Medical images can be used for the development of new visualization techniques, new algorithms for patient care and new image processing techniques. These research areas usually require the use of huge volumes of data to obtain significant results, along with enormous computing capabilities. Such qualities are characteristics of grid computing systems such as EELA-2 infrastructure. The grid technologies allow the sharing of data in large scale in a safe and integrated environment and offer high computing capabilities. In this paper we describe the DicomGrid to store and retrieve medical images, properly anonymized, that can be used by researchers to test new processing techniques, using the computational power offered by grid technology. A prototype of the DicomGrid is under evaluation and permits the submission of jobs into the EELA-2 grid infrastructure while offering a simple interface that requires minimal understanding of the grid operation.

SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology

PubMed Central

Adams, Richard; Clark, Allan; Yamaguchi, Azusa; Hanlon, Neil; Tsorman, Nikos; Ali, Shakir; Lebedeva, Galina; Goltsov, Alexey; Sorokin, Anatoly; Akman, Ozgur E.; Troein, Carl; Millar, Andrew J.; Goryanin, Igor; Gilmore, Stephen

2013-01-01

Summary: Complex computational experiments in Systems Biology, such as fitting model parameters to experimental data, can be challenging to perform. Not only do they frequently require a high level of computational power, but the software needed to run the experiment needs to be usable by scientists with varying levels of computational expertise, and modellers need to be able to obtain up-to-date experimental data resources easily. We have developed a software suite, the Systems Biology Software Infrastructure (SBSI), to facilitate the parameter-fitting process. SBSI is a modular software suite composed of three major components: SBSINumerics, a high-performance library containing parallelized algorithms for performing parameter fitting; SBSIDispatcher, a middleware application to track experiments and submit jobs to back-end servers; and SBSIVisual, an extensible client application used to configure optimization experiments and view results. Furthermore, we have created a plugin infrastructure to enable project-specific modules to be easily installed. Plugin developers can take advantage of the existing user-interface and application framework to customize SBSI for their own uses, facilitated by SBSI’s use of standard data formats. Availability and implementation: All SBSI binaries and source-code are freely available from http://sourceforge.net/projects/sbsi under an Apache 2 open-source license. The server-side SBSINumerics runs on any Unix-based operating system; both SBSIVisual and SBSIDispatcher are written in Java and are platform independent, allowing use on Windows, Linux and Mac OS X. The SBSI project website at http://www.sbsi.ed.ac.uk provides documentation and tutorials. Contact: stg@inf.ed.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23329415

Open Source Dataturbine (OSDT) Android Sensorpod in Environmental Observing Systems

NASA Astrophysics Data System (ADS)

Fountain, T. R.; Shin, P.; Tilak, S.; Trinh, T.; Smith, J.; Kram, S.

2014-12-01

The OSDT Android SensorPod is a custom-designed mobile computing platform for assembling wireless sensor networks for environmental monitoring applications. Funded by an award from the Gordon and Betty Moore Foundation, the OSDT SensorPod represents a significant technological advance in the application of mobile and cloud computing technologies to near-real-time applications in environmental science, natural resources management, and disaster response and recovery. It provides a modular architecture based on open standards and open-source software that allows system developers to align their projects with industry best practices and technology trends, while avoiding commercial vendor lock-in to expensive proprietary software and hardware systems. The integration of mobile and cloud-computing infrastructure represents a disruptive technology in the field of environmental science, since basic assumptions about technology requirements are now open to revision, e.g., the roles of special purpose data loggers and dedicated site infrastructure. The OSDT Android SensorPod was designed with these considerations in mind, and the resulting system exhibits the following characteristics - it is flexible, efficient and robust. The system was developed and tested in the three science applications: 1) a fresh water limnology deployment in Wisconsin, 2) a near coastal marine science deployment at the UCSD Scripps Pier, and 3) a terrestrial ecological deployment in the mountains of Taiwan. As part of a public education and outreach effort, a Facebook page with daily ocean pH measurements from the UCSD Scripps pier was developed. Wireless sensor networks and the virtualization of data and network services is the future of environmental science infrastructure. The OSDT Android SensorPod was designed and developed to harness these new technology developments for environmental monitoring applications.

Doing Your Science While You're in Orbit

NASA Astrophysics Data System (ADS)

Green, Mark L.; Miller, Stephen D.; Vazhkudai, Sudharshan S.; Trater, James R.

2010-11-01

Large-scale neutron facilities such as the Spallation Neutron Source (SNS) located at Oak Ridge National Laboratory need easy-to-use access to Department of Energy Leadership Computing Facilities and experiment repository data. The Orbiter thick- and thin-client and its supporting Service Oriented Architecture (SOA) based services (available at https://orbiter.sns.gov) consist of standards-based components that are reusable and extensible for accessing high performance computing, data and computational grid infrastructure, and cluster-based resources easily from a user configurable interface. The primary Orbiter system goals consist of (1) developing infrastructure for the creation and automation of virtual instrumentation experiment optimization, (2) developing user interfaces for thin- and thick-client access, (3) provide a prototype incorporating major instrument simulation packages, and (4) facilitate neutron science community access and collaboration. The secure Orbiter SOA authentication and authorization is achieved through the developed Virtual File System (VFS) services, which use Role-Based Access Control (RBAC) for data repository file access, thin-and thick-client functionality and application access, and computational job workflow management. The VFS Relational Database Management System (RDMS) consists of approximately 45 database tables describing 498 user accounts with 495 groups over 432,000 directories with 904,077 repository files. Over 59 million NeXus file metadata records are associated to the 12,800 unique NeXus file field/class names generated from the 52,824 repository NeXus files. Services that enable (a) summary dashboards of data repository status with Quality of Service (QoS) metrics, (b) data repository NeXus file field/class name full text search capabilities within a Google like interface, (c) fully functional RBAC browser for the read-only data repository and shared areas, (d) user/group defined and shared metadata for data repository files, (e) user, group, repository, and web 2.0 based global positioning with additional service capabilities are currently available. The SNS based Orbiter SOA integration progress with the Distributed Data Analysis for Neutron Scattering Experiments (DANSE) software development project is summarized with an emphasis on DANSE Central Services and the Virtual Neutron Facility (VNF). Additionally, the DANSE utilization of the Orbiter SOA authentication, authorization, and data transfer services best practice implementations are presented.

Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community.

PubMed

Krampis, Konstantinos; Booth, Tim; Chapman, Brad; Tiwari, Bela; Bicak, Mesude; Field, Dawn; Nelson, Karen E

2012-03-19

A steep drop in the cost of next-generation sequencing during recent years has made the technology affordable to the majority of researchers, but downstream bioinformatic analysis still poses a resource bottleneck for smaller laboratories and institutes that do not have access to substantial computational resources. Sequencing instruments are typically bundled with only the minimal processing and storage capacity required for data capture during sequencing runs. Given the scale of sequence datasets, scientific value cannot be obtained from acquiring a sequencer unless it is accompanied by an equal investment in informatics infrastructure. Cloud BioLinux is a publicly accessible Virtual Machine (VM) that enables scientists to quickly provision on-demand infrastructures for high-performance bioinformatics computing using cloud platforms. Users have instant access to a range of pre-configured command line and graphical software applications, including a full-featured desktop interface, documentation and over 135 bioinformatics packages for applications including sequence alignment, clustering, assembly, display, editing, and phylogeny. Each tool's functionality is fully described in the documentation directly accessible from the graphical interface of the VM. Besides the Amazon EC2 cloud, we have started instances of Cloud BioLinux on a private Eucalyptus cloud installed at the J. Craig Venter Institute, and demonstrated access to the bioinformatic tools interface through a remote connection to EC2 instances from a local desktop computer. Documentation for using Cloud BioLinux on EC2 is available from our project website, while a Eucalyptus cloud image and VirtualBox Appliance is also publicly available for download and use by researchers with access to private clouds. Cloud BioLinux provides a platform for developing bioinformatics infrastructures on the cloud. An automated and configurable process builds Virtual Machines, allowing the development of highly customized versions from a shared code base. This shared community toolkit enables application specific analysis platforms on the cloud by minimizing the effort required to prepare and maintain them.

Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community

PubMed Central

2012-01-01

Background A steep drop in the cost of next-generation sequencing during recent years has made the technology affordable to the majority of researchers, but downstream bioinformatic analysis still poses a resource bottleneck for smaller laboratories and institutes that do not have access to substantial computational resources. Sequencing instruments are typically bundled with only the minimal processing and storage capacity required for data capture during sequencing runs. Given the scale of sequence datasets, scientific value cannot be obtained from acquiring a sequencer unless it is accompanied by an equal investment in informatics infrastructure. Results Cloud BioLinux is a publicly accessible Virtual Machine (VM) that enables scientists to quickly provision on-demand infrastructures for high-performance bioinformatics computing using cloud platforms. Users have instant access to a range of pre-configured command line and graphical software applications, including a full-featured desktop interface, documentation and over 135 bioinformatics packages for applications including sequence alignment, clustering, assembly, display, editing, and phylogeny. Each tool's functionality is fully described in the documentation directly accessible from the graphical interface of the VM. Besides the Amazon EC2 cloud, we have started instances of Cloud BioLinux on a private Eucalyptus cloud installed at the J. Craig Venter Institute, and demonstrated access to the bioinformatic tools interface through a remote connection to EC2 instances from a local desktop computer. Documentation for using Cloud BioLinux on EC2 is available from our project website, while a Eucalyptus cloud image and VirtualBox Appliance is also publicly available for download and use by researchers with access to private clouds. Conclusions Cloud BioLinux provides a platform for developing bioinformatics infrastructures on the cloud. An automated and configurable process builds Virtual Machines, allowing the development of highly customized versions from a shared code base. This shared community toolkit enables application specific analysis platforms on the cloud by minimizing the effort required to prepare and maintain them. PMID:22429538

The Integration of CloudStack and OCCI/OpenNebula with DIRAC

NASA Astrophysics Data System (ADS)

Méndez Muñoz, Víctor; Fernández Albor, Víctor; Graciani Diaz, Ricardo; Casajús Ramo, Adriàn; Fernández Pena, Tomás; Merino Arévalo, Gonzalo; José Saborido Silva, Juan

2012-12-01

The increasing availability of Cloud resources is arising as a realistic alternative to the Grid as a paradigm for enabling scientific communities to access large distributed computing resources. The DIRAC framework for distributed computing is an easy way to efficiently access to resources from both systems. This paper explains the integration of DIRAC with two open-source Cloud Managers: OpenNebula (taking advantage of the OCCI standard) and CloudStack. These are computing tools to manage the complexity and heterogeneity of distributed data center infrastructures, allowing to create virtual clusters on demand, including public, private and hybrid clouds. This approach has required to develop an extension to the previous DIRAC Virtual Machine engine, which was developed for Amazon EC2, allowing the connection with these new cloud managers. In the OpenNebula case, the development has been based on the CernVM Virtual Software Appliance with appropriate contextualization, while in the case of CloudStack, the infrastructure has been kept more general, which permits other Virtual Machine sources and operating systems being used. In both cases, CernVM File System has been used to facilitate software distribution to the computing nodes. With the resulting infrastructure, the cloud resources are transparent to the users through a friendly interface, like the DIRAC Web Portal. The main purpose of this integration is to get a system that can manage cloud and grid resources at the same time. This particular feature pushes DIRAC to a new conceptual denomination as interware, integrating different middleware. Users from different communities do not need to care about the installation of the standard software that is available at the nodes, nor the operating system of the host machine which is transparent to the user. This paper presents an analysis of the overhead of the virtual layer, doing some tests to compare the proposed approach with the existing Grid solution. License Notice: Published under licence in Journal of Physics: Conference Series by IOP Publishing Ltd.

Streaming Support for Data Intensive Cloud-Based Sequence Analysis

PubMed Central

Issa, Shadi A.; Kienzler, Romeo; El-Kalioby, Mohamed; Tonellato, Peter J.; Wall, Dennis; Bruggmann, Rémy; Abouelhoda, Mohamed

2013-01-01

Cloud computing provides a promising solution to the genomics data deluge problem resulting from the advent of next-generation sequencing (NGS) technology. Based on the concepts of “resources-on-demand” and “pay-as-you-go”, scientists with no or limited infrastructure can have access to scalable and cost-effective computational resources. However, the large size of NGS data causes a significant data transfer latency from the client's site to the cloud, which presents a bottleneck for using cloud computing services. In this paper, we provide a streaming-based scheme to overcome this problem, where the NGS data is processed while being transferred to the cloud. Our scheme targets the wide class of NGS data analysis tasks, where the NGS sequences can be processed independently from one another. We also provide the elastream package that supports the use of this scheme with individual analysis programs or with workflow systems. Experiments presented in this paper show that our solution mitigates the effect of data transfer latency and saves both time and cost of computation. PMID:23710461

Fast Risk Assessment Software For Natural Hazard Phenomena Using Georeference Population And Infrastructure Data Bases

NASA Astrophysics Data System (ADS)

Marrero, J. M.; Pastor Paz, J. E.; Erazo, C.; Marrero, M.; Aguilar, J.; Yepes, H. A.; Estrella, C. M.; Mothes, P. A.

2015-12-01

Disaster Risk Reduction (DRR) requires an integrated multi-hazard assessment approach towards natural hazard mitigation. In the case of volcanic risk, long term hazard maps are generally developed on a basis of the most probable scenarios (likelihood of occurrence) or worst cases. However, in the short-term, expected scenarios may vary substantially depending on the monitoring data or new knowledge. In this context, the time required to obtain and process data is critical for optimum decision making. Availability of up-to-date volcanic scenarios is as crucial as it is to have this data accompanied by efficient estimations of their impact among populations and infrastructure. To address this impact estimation during volcanic crises, or other natural hazards, a web interface has been developed to execute an ANSI C application. This application allows one to compute - in a matter of seconds - the demographic and infrastructure impact that any natural hazard may cause employing an overlay-layer approach. The web interface is tailored to users involved in the volcanic crises management of Cotopaxi volcano (Ecuador). The population data base and the cartographic basis used are of public domain, published by the National Office of Statistics of Ecuador (INEC, by its Spanish acronym). To run the application and obtain results the user is expected to upload a raster file containing information related to the volcanic hazard or any other natural hazard, and determine categories to group population or infrastructure potentially affected. The results are displayed in a user-friendly report.

Integration of XRootD into the cloud infrastructure for ALICE data analysis

NASA Astrophysics Data System (ADS)

Kompaniets, Mikhail; Shadura, Oksana; Svirin, Pavlo; Yurchenko, Volodymyr; Zarochentsev, Andrey

2015-12-01

Cloud technologies allow easy load balancing between different tasks and projects. From the viewpoint of the data analysis in the ALICE experiment, cloud allows to deploy software using Cern Virtual Machine (CernVM) and CernVM File System (CVMFS), to run different (including outdated) versions of software for long term data preservation and to dynamically allocate resources for different computing activities, e.g. grid site, ALICE Analysis Facility (AAF) and possible usage for local projects or other LHC experiments. We present a cloud solution for Tier-3 sites based on OpenStack and Ceph distributed storage with an integrated XRootD based storage element (SE). One of the key features of the solution is based on idea that Ceph has been used as a backend for Cinder Block Storage service for OpenStack, and in the same time as a storage backend for XRootD, with redundancy and availability of data preserved by Ceph settings. For faster and easier OpenStack deployment was applied the Packstack solution, which is based on the Puppet configuration management system. Ceph installation and configuration operations are structured and converted to Puppet manifests describing node configurations and integrated into Packstack. This solution can be easily deployed, maintained and used even in small groups with limited computing resources and small organizations, which usually have lack of IT support. The proposed infrastructure has been tested on two different clouds (SPbSU & BITP) and integrates successfully with the ALICE data analysis model.

Integrating Reconfigurable Hardware-Based Grid for High Performance Computing

PubMed Central

Dondo Gazzano, Julio; Sanchez Molina, Francisco; Rincon, Fernando; López, Juan Carlos

2015-01-01

FPGAs have shown several characteristics that make them very attractive for high performance computing (HPC). The impressive speed-up factors that they are able to achieve, the reduced power consumption, and the easiness and flexibility of the design process with fast iterations between consecutive versions are examples of benefits obtained with their use. However, there are still some difficulties when using reconfigurable platforms as accelerator that need to be addressed: the need of an in-depth application study to identify potential acceleration, the lack of tools for the deployment of computational problems in distributed hardware platforms, and the low portability of components, among others. This work proposes a complete grid infrastructure for distributed high performance computing based on dynamically reconfigurable FPGAs. Besides, a set of services designed to facilitate the application deployment is described. An example application and a comparison with other hardware and software implementations are shown. Experimental results show that the proposed architecture offers encouraging advantages for deployment of high performance distributed applications simplifying development process. PMID:25874241

New project to support scientific collaboration electronically

NASA Astrophysics Data System (ADS)

Clauer, C. R.; Rasmussen, C. E.; Niciejewski, R. J.; Killeen, T. L.; Kelly, J. D.; Zambre, Y.; Rosenberg, T. J.; Stauning, P.; Friis-Christensen, E.; Mende, S. B.; Weymouth, T. E.; Prakash, A.; McDaniel, S. E.; Olson, G. M.; Finholt, T. A.; Atkins, D. E.

A new multidisciplinary effort is linking research in the upper atmospheric and space, computer, and behavioral sciences to develop a prototype electronic environment for conducting team science worldwide. A real-world electronic collaboration testbed has been established to support scientific work centered around the experimental operations being conducted with instruments from the Sondrestrom Upper Atmospheric Research Facility in Kangerlussuaq, Greenland. Such group computing environments will become an important component of the National Information Infrastructure initiative, which is envisioned as the high-performance communications infrastructure to support national scientific research.

Restricted Authentication and Encryption for Cyber-physical Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kirkpatrick, Michael S; Bertino, Elisa; Sheldon, Frederick T

2009-01-01

Cyber-physical systems (CPS) are characterized by the close linkage of computational resources and physical devices. These systems can be deployed in a number of critical infrastructure settings. As a result, the security requirements of CPS are different than traditional computing architectures. For example, critical functions must be identified and isolated from interference by other functions. Similarly, lightweight schemes may be required, as CPS can include devices with limited computing power. One approach that offers promise for CPS security is the use of lightweight, hardware-based authentication. Specifically, we consider the use of Physically Unclonable Functions (PUFs) to bind an access requestmore » to specific hardware with device-specific keys. PUFs are implemented in hardware, such as SRAM, and can be used to uniquely identify the device. This technology could be used in CPS to ensure location-based access control and encryption, both of which would be desirable for CPS implementations.« less

Towards agile large-scale predictive modelling in drug discovery with flow-based programming design principles.

PubMed

Lampa, Samuel; Alvarsson, Jonathan; Spjuth, Ola

2016-01-01

Predictive modelling in drug discovery is challenging to automate as it often contains multiple analysis steps and might involve cross-validation and parameter tuning that create complex dependencies between tasks. With large-scale data or when using computationally demanding modelling methods, e-infrastructures such as high-performance or cloud computing are required, adding to the existing challenges of fault-tolerant automation. Workflow management systems can aid in many of these challenges, but the currently available systems are lacking in the functionality needed to enable agile and flexible predictive modelling. We here present an approach inspired by elements of the flow-based programming paradigm, implemented as an extension of the Luigi system which we name SciLuigi. We also discuss the experiences from using the approach when modelling a large set of biochemical interactions using a shared computer cluster.Graphical abstract.

ENFIN--A European network for integrative systems biology.

PubMed

Kahlem, Pascal; Clegg, Andrew; Reisinger, Florian; Xenarios, Ioannis; Hermjakob, Henning; Orengo, Christine; Birney, Ewan

2009-11-01

Integration of biological data of various types and the development of adapted bioinformatics tools represent critical objectives to enable research at the systems level. The European Network of Excellence ENFIN is engaged in developing an adapted infrastructure to connect databases, and platforms to enable both the generation of new bioinformatics tools and the experimental validation of computational predictions. With the aim of bridging the gap existing between standard wet laboratories and bioinformatics, the ENFIN Network runs integrative research projects to bring the latest computational techniques to bear directly on questions dedicated to systems biology in the wet laboratory environment. The Network maintains internally close collaboration between experimental and computational research, enabling a permanent cycling of experimental validation and improvement of computational prediction methods. The computational work includes the development of a database infrastructure (EnCORE), bioinformatics analysis methods and a novel platform for protein function analysis FuncNet.

Knowledge-based decision support for Space Station assembly sequence planning

NASA Astrophysics Data System (ADS)

1991-04-01

A complete Personal Analysis Assistant (PAA) for Space Station Freedom (SSF) assembly sequence planning consists of three software components: the system infrastructure, intra-flight value added, and inter-flight value added. The system infrastructure is the substrate on which software elements providing inter-flight and intra-flight value-added functionality are built. It provides the capability for building representations of assembly sequence plans and specification of constraints and analysis options. Intra-flight value-added provides functionality that will, given the manifest for each flight, define cargo elements, place them in the National Space Transportation System (NSTS) cargo bay, compute performance measure values, and identify violated constraints. Inter-flight value-added provides functionality that will, given major milestone dates and capability requirements, determine the number and dates of required flights and develop a manifest for each flight. The current project is Phase 1 of a projected two phase program and delivers the system infrastructure. Intra- and inter-flight value-added were to be developed in Phase 2, which has not been funded. Based on experience derived from hundreds of projects conducted over the past seven years, ISX developed an Intelligent Systems Engineering (ISE) methodology that combines the methods of systems engineering and knowledge engineering to meet the special systems development requirements posed by intelligent systems, systems that blend artificial intelligence and other advanced technologies with more conventional computing technologies. The ISE methodology defines a phased program process that begins with an application assessment designed to provide a preliminary determination of the relative technical risks and payoffs associated with a potential application, and then moves through requirements analysis, system design, and development.

Knowledge-based decision support for Space Station assembly sequence planning

NASA Technical Reports Server (NTRS)

1991-01-01

A complete Personal Analysis Assistant (PAA) for Space Station Freedom (SSF) assembly sequence planning consists of three software components: the system infrastructure, intra-flight value added, and inter-flight value added. The system infrastructure is the substrate on which software elements providing inter-flight and intra-flight value-added functionality are built. It provides the capability for building representations of assembly sequence plans and specification of constraints and analysis options. Intra-flight value-added provides functionality that will, given the manifest for each flight, define cargo elements, place them in the National Space Transportation System (NSTS) cargo bay, compute performance measure values, and identify violated constraints. Inter-flight value-added provides functionality that will, given major milestone dates and capability requirements, determine the number and dates of required flights and develop a manifest for each flight. The current project is Phase 1 of a projected two phase program and delivers the system infrastructure. Intra- and inter-flight value-added were to be developed in Phase 2, which has not been funded. Based on experience derived from hundreds of projects conducted over the past seven years, ISX developed an Intelligent Systems Engineering (ISE) methodology that combines the methods of systems engineering and knowledge engineering to meet the special systems development requirements posed by intelligent systems, systems that blend artificial intelligence and other advanced technologies with more conventional computing technologies. The ISE methodology defines a phased program process that begins with an application assessment designed to provide a preliminary determination of the relative technical risks and payoffs associated with a potential application, and then moves through requirements analysis, system design, and development.

Implementation Issues of Virtual Desktop Infrastructure and Its Case Study for a Physician's Round at Seoul National University Bundang Hospital.

PubMed

Yoo, Sooyoung; Kim, Seok; Kim, Taegi; Kim, Jon Soo; Baek, Rong-Min; Suh, Chang Suk; Chung, Chin Youb; Hwang, Hee

2012-12-01

The cloud computing-based virtual desktop infrastructure (VDI) allows access to computing environments with no limitations in terms of time or place such that it can permit the rapid establishment of a mobile hospital environment. The objective of this study was to investigate the empirical issues to be considered when establishing a virtual mobile environment using VDI technology in a hospital setting and to examine the utility of the technology with an Apple iPad during a physician's rounds as a case study. Empirical implementation issues were derived from a 910-bed tertiary national university hospital that recently launched a VDI system. During the physicians' rounds, we surveyed patient satisfaction levels with the VDI-based mobile consultation service with the iPad and the relationship between these levels of satisfaction and hospital revisits, hospital recommendations, and the hospital brand image. Thirty-five inpatients (including their next-of-kin) and seven physicians participated in the survey. Implementation issues pertaining to the VDI system arose with regard to the highly availability system architecture, wireless network infrastructure, and screen resolution of the system. Other issues were related to privacy and security, mobile device management, and user education. When the system was used in rounds, patients and their next-of-kin expressed high satisfaction levels, and a positive relationship was noted as regards patients' decisions to revisit the hospital and whether the use of the VDI system improved the brand image of the hospital. Mobile hospital environments have the potential to benefit both physicians and patients. The issues related to the implementation of VDI system discussed here should be examined in advance for its successful adoption and implementation.

Implementation Issues of Virtual Desktop Infrastructure and Its Case Study for a Physician's Round at Seoul National University Bundang Hospital

PubMed Central

Yoo, Sooyoung; Kim, Seok; Kim, Taegi; Kim, Jon Soo; Baek, Rong-Min; Suh, Chang Suk; Chung, Chin Youb

2012-01-01

Objectives The cloud computing-based virtual desktop infrastructure (VDI) allows access to computing environments with no limitations in terms of time or place such that it can permit the rapid establishment of a mobile hospital environment. The objective of this study was to investigate the empirical issues to be considered when establishing a virtual mobile environment using VDI technology in a hospital setting and to examine the utility of the technology with an Apple iPad during a physician's rounds as a case study. Methods Empirical implementation issues were derived from a 910-bed tertiary national university hospital that recently launched a VDI system. During the physicians' rounds, we surveyed patient satisfaction levels with the VDI-based mobile consultation service with the iPad and the relationship between these levels of satisfaction and hospital revisits, hospital recommendations, and the hospital brand image. Thirty-five inpatients (including their next-of-kin) and seven physicians participated in the survey. Results Implementation issues pertaining to the VDI system arose with regard to the highly availability system architecture, wireless network infrastructure, and screen resolution of the system. Other issues were related to privacy and security, mobile device management, and user education. When the system was used in rounds, patients and their next-of-kin expressed high satisfaction levels, and a positive relationship was noted as regards patients' decisions to revisit the hospital and whether the use of the VDI system improved the brand image of the hospital. Conclusions Mobile hospital environments have the potential to benefit both physicians and patients. The issues related to the implementation of VDI system discussed here should be examined in advance for its successful adoption and implementation. PMID:23346476

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis.

PubMed

Simonyan, Vahan; Mazumder, Raja

2014-09-30

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis.

A Reliable TTP-Based Infrastructure with Low Sensor Resource Consumption for the Smart Home Multi-Platform

PubMed Central

Kang, Jungho; Kim, Mansik; Park, Jong Hyuk

2016-01-01

With the ICT technology making great progress in the smart home environment, the ubiquitous environment is rapidly emerging all over the world, but problems are also increasing proportionally to the rapid growth of the smart home market such as multiplatform heterogeneity and new security threats. In addition, the smart home sensors have so low computing resources that they cannot process complicated computation tasks, which is required to create a proper security environment. A service provider also faces overhead in processing data from a rapidly increasing number of sensors. This paper aimed to propose a scheme to build infrastructure in which communication entities can securely authenticate and design security channel with physically unclonable PUFs and the TTP that smart home communication entities can rely on. In addition, we analyze and evaluate the proposed scheme for security and performance and prove that it can build secure channels with low resources. Finally, we expect that the proposed scheme can be helpful for secure communication with low resources in future smart home multiplatforms. PMID:27399699

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis

PubMed Central

Simonyan, Vahan; Mazumder, Raja

2014-01-01

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis. PMID:25271953

A Reliable TTP-Based Infrastructure with Low Sensor Resource Consumption for the Smart Home Multi-Platform.

PubMed

Kang, Jungho; Kim, Mansik; Park, Jong Hyuk

2016-07-05

With the ICT technology making great progress in the smart home environment, the ubiquitous environment is rapidly emerging all over the world, but problems are also increasing proportionally to the rapid growth of the smart home market such as multiplatform heterogeneity and new security threats. In addition, the smart home sensors have so low computing resources that they cannot process complicated computation tasks, which is required to create a proper security environment. A service provider also faces overhead in processing data from a rapidly increasing number of sensors. This paper aimed to propose a scheme to build infrastructure in which communication entities can securely authenticate and design security channel with physically unclonable PUFs and the TTP that smart home communication entities can rely on. In addition, we analyze and evaluate the proposed scheme for security and performance and prove that it can build secure channels with low resources. Finally, we expect that the proposed scheme can be helpful for secure communication with low resources in future smart home multiplatforms.

Self-service for software development projects and HPC activities

NASA Astrophysics Data System (ADS)

Husejko, M.; Høimyr, N.; Gonzalez, A.; Koloventzos, G.; Asbury, D.; Trzcinska, A.; Agtzidis, I.; Botrel, G.; Otto, J.

2014-05-01

This contribution describes how CERN has implemented several essential tools for agile software development processes, ranging from version control (Git) to issue tracking (Jira) and documentation (Wikis). Running such services in a large organisation like CERN requires many administrative actions both by users and service providers, such as creating software projects, managing access rights, users and groups, and performing tool-specific customisation. Dealing with these requests manually would be a time-consuming task. Another area of our CERN computing services that has required dedicated manual support has been clusters for specific user communities with special needs. Our aim is to move all our services to a layered approach, with server infrastructure running on the internal cloud computing infrastructure at CERN. This contribution illustrates how we plan to optimise the management of our of services by means of an end-user facing platform acting as a portal into all the related services for software projects, inspired by popular portals for open-source developments such as Sourceforge, GitHub and others. Furthermore, the contribution will discuss recent activities with tests and evaluations of High Performance Computing (HPC) applications on different hardware and software stacks, and plans to offer a dynamically scalable HPC service at CERN, based on affordable hardware.

Role of information systems in controlling costs: the electronic medical record (EMR) and the high-performance computing and communications (HPCC) efforts

NASA Astrophysics Data System (ADS)

Kun, Luis G.

1994-12-01

On October 18, 1991, the IEEE-USA produced an entity statement which endorsed the vital importance of the High Performance Computer and Communications Act of 1991 (HPCC) and called for the rapid implementation of all its elements. Efforts are now underway to develop a Computer Based Patient Record (CBPR), the National Information Infrastructure (NII) as part of the HPCC, and the so-called `Patient Card'. Multiple legislative initiatives which address these and related information technology issues are pending in Congress. Clearly, a national information system will greatly affect the way health care delivery is provided to the United States public. Timely and reliable information represents a critical element in any initiative to reform the health care system as well as to protect and improve the health of every person. Appropriately used, information technologies offer a vital means of improving the quality of patient care, increasing access to universal care and lowering overall costs within a national health care program. Health care reform legislation should reflect increased budgetary support and a legal mandate for the creation of a national health care information system by: (1) constructing a National Information Infrastructure; (2) building a Computer Based Patient Record System; (3) bringing the collective resources of our National Laboratories to bear in developing and implementing the NII and CBPR, as well as a security system with which to safeguard the privacy rights of patients and the physician-patient privilege; and (4) utilizing Government (e.g. DOD, DOE) capabilities (technology and human resources) to maximize resource utilization, create new jobs and accelerate technology transfer to address health care issues.

CloudNeo: a cloud pipeline for identifying patient-specific tumor neoantigens.

PubMed

Bais, Preeti; Namburi, Sandeep; Gatti, Daniel M; Zhang, Xinyu; Chuang, Jeffrey H

2017-10-01

We present CloudNeo, a cloud-based computational workflow for identifying patient-specific tumor neoantigens from next generation sequencing data. Tumor-specific mutant peptides can be detected by the immune system through their interactions with the human leukocyte antigen complex, and neoantigen presence has recently been shown to correlate with anti T-cell immunity and efficacy of checkpoint inhibitor therapy. However computing capabilities to identify neoantigens from genomic sequencing data are a limiting factor for understanding their role. This challenge has grown as cancer datasets become increasingly abundant, making them cumbersome to store and analyze on local servers. Our cloud-based pipeline provides scalable computation capabilities for neoantigen identification while eliminating the need to invest in local infrastructure for data transfer, storage or compute. The pipeline is a Common Workflow Language (CWL) implementation of human leukocyte antigen (HLA) typing using Polysolver or HLAminer combined with custom scripts for mutant peptide identification and NetMHCpan for neoantigen prediction. We have demonstrated the efficacy of these pipelines on Amazon cloud instances through the Seven Bridges Genomics implementation of the NCI Cancer Genomics Cloud, which provides graphical interfaces for running and editing, infrastructure for workflow sharing and version tracking, and access to TCGA data. The CWL implementation is at: https://github.com/TheJacksonLaboratory/CloudNeo. For users who have obtained licenses for all internal software, integrated versions in CWL and on the Seven Bridges Cancer Genomics Cloud platform (https://cgc.sbgenomics.com/, recommended version) can be obtained by contacting the authors. jeff.chuang@jax.org. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Web-Based Integrated Research Environment for Aerodynamic Analyses and Design

NASA Astrophysics Data System (ADS)

Ahn, Jae Wan; Kim, Jin-Ho; Kim, Chongam; Cho, Jung-Hyun; Hur, Cinyoung; Kim, Yoonhee; Kang, Sang-Hyun; Kim, Byungsoo; Moon, Jong Bae; Cho, Kum Won

e-AIRS[1,2], an abbreviation of ‘e-Science Aerospace Integrated Research System,' is a virtual organization designed to support aerodynamic flow analyses in aerospace engineering using the e-Science environment. As the first step toward a virtual aerospace engineering organization, e-AIRS intends to give a full support of aerodynamic research process. Currently, e-AIRS can handle both the computational and experimental aerodynamic research on the e-Science infrastructure. In detail, users can conduct a full CFD (Computational Fluid Dynamics) research process, request wind tunnel experiment, perform comparative analysis between computational prediction and experimental measurement, and finally, collaborate with other researchers using the web portal. The present paper describes those services and the internal architecture of the e-AIRS system.

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

Service-Oriented Architecture for NVO and TeraGrid Computing

NASA Technical Reports Server (NTRS)

Jacob, Joseph; Miller, Craig; Williams, Roy; Steenberg, Conrad; Graham, Matthew

2008-01-01

The National Virtual Observatory (NVO) Extensible Secure Scalable Service Infrastructure (NESSSI) is a Web service architecture and software framework that enables Web-based astronomical data publishing and processing on grid computers such as the National Science Foundation's TeraGrid. Characteristics of this architecture include the following: (1) Services are created, managed, and upgraded by their developers, who are trusted users of computing platforms on which the services are deployed. (2) Service jobs can be initiated by means of Java or Python client programs run on a command line or with Web portals. (3) Access is granted within a graduated security scheme in which the size of a job that can be initiated depends on the level of authentication of the user.

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

DOE PAGES

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek; ...

2017-04-24

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

Reconciliation of the cloud computing model with US federal electronic health record regulations

PubMed Central

2011-01-01

Cloud computing refers to subscription-based, fee-for-service utilization of computer hardware and software over the Internet. The model is gaining acceptance for business information technology (IT) applications because it allows capacity and functionality to increase on the fly without major investment in infrastructure, personnel or licensing fees. Large IT investments can be converted to a series of smaller operating expenses. Cloud architectures could potentially be superior to traditional electronic health record (EHR) designs in terms of economy, efficiency and utility. A central issue for EHR developers in the US is that these systems are constrained by federal regulatory legislation and oversight. These laws focus on security and privacy, which are well-recognized challenges for cloud computing systems in general. EHRs built with the cloud computing model can achieve acceptable privacy and security through business associate contracts with cloud providers that specify compliance requirements, performance metrics and liability sharing. PMID:21727204

Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment.

PubMed

Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Abdulhamid, Shafi'i Muhammad; Usman, Mohammed Joda

2017-01-01

Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing.

Snore related signals processing in a private cloud computing system.

PubMed

Qian, Kun; Guo, Jian; Xu, Huijie; Zhu, Zhaomeng; Zhang, Gongxuan

2014-09-01

Snore related signals (SRS) have been demonstrated to carry important information about the obstruction site and degree in the upper airway of Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) patients in recent years. To make this acoustic signal analysis method more accurate and robust, big SRS data processing is inevitable. As an emerging concept and technology, cloud computing has motivated numerous researchers and engineers to exploit applications both in academic and industry field, which could have an ability to implement a huge blue print in biomedical engineering. Considering the security and transferring requirement of biomedical data, we designed a system based on private cloud computing to process SRS. Then we set the comparable experiments of processing a 5-hour audio recording of an OSAHS patient by a personal computer, a server and a private cloud computing system to demonstrate the efficiency of the infrastructure we proposed.

Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment

PubMed Central

Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Usman, Mohammed Joda

2017-01-01

Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing. PMID:28467505

Processing of the WLCG monitoring data using NoSQL

NASA Astrophysics Data System (ADS)

Andreeva, J.; Beche, A.; Belov, S.; Dzhunov, I.; Kadochnikov, I.; Karavakis, E.; Saiz, P.; Schovancova, J.; Tuckett, D.

2014-06-01

The Worldwide LHC Computing Grid (WLCG) today includes more than 150 computing centres where more than 2 million jobs are being executed daily and petabytes of data are transferred between sites. Monitoring the computing activities of the LHC experiments, over such a huge heterogeneous infrastructure, is extremely demanding in terms of computation, performance and reliability. Furthermore, the generated monitoring flow is constantly increasing, which represents another challenge for the monitoring systems. While existing solutions are traditionally based on Oracle for data storage and processing, recent developments evaluate NoSQL for processing large-scale monitoring datasets. NoSQL databases are getting increasingly popular for processing datasets at the terabyte and petabyte scale using commodity hardware. In this contribution, the integration of NoSQL data processing in the Experiment Dashboard framework is described along with first experiences of using this technology for monitoring the LHC computing activities.

LHC@Home: a BOINC-based volunteer computing infrastructure for physics studies at CERN

NASA Astrophysics Data System (ADS)

Barranco, Javier; Cai, Yunhai; Cameron, David; Crouch, Matthew; Maria, Riccardo De; Field, Laurence; Giovannozzi, Massimo; Hermes, Pascal; Høimyr, Nils; Kaltchev, Dobrin; Karastathis, Nikos; Luzzi, Cinzia; Maclean, Ewen; McIntosh, Eric; Mereghetti, Alessio; Molson, James; Nosochkov, Yuri; Pieloni, Tatiana; Reid, Ivan D.; Rivkin, Lenny; Segal, Ben; Sjobak, Kyrre; Skands, Peter; Tambasco, Claudia; Veken, Frederik Van der; Zacharov, Igor

2017-12-01

The LHC@Home BOINC project has provided computing capacity for numerical simulations to researchers at CERN since 2004, and has since 2011 been expanded with a wider range of applications. The traditional CERN accelerator physics simulation code SixTrack enjoys continuing volunteers support, and thanks to virtualisation a number of applications from the LHC experiment collaborations and particle theory groups have joined the consolidated LHC@Home BOINC project. This paper addresses the challenges related to traditional and virtualized applications in the BOINC environment, and how volunteer computing has been integrated into the overall computing strategy of the laboratory through the consolidated LHC@Home service. Thanks to the computing power provided by volunteers joining LHC@Home, numerous accelerator beam physics studies have been carried out, yielding an improved understanding of charged particle dynamics in the CERN Large Hadron Collider (LHC) and its future upgrades. The main results are highlighted in this paper.

Research on the application in disaster reduction for using cloud computing technology

NASA Astrophysics Data System (ADS)

Tao, Liang; Fan, Yida; Wang, Xingling

Cloud Computing technology has been rapidly applied in different domains recently, promotes the progress of the domain's informatization. Based on the analysis of the state of application requirement in disaster reduction and combining the characteristics of Cloud Computing technology, we present the research on the application of Cloud Computing technology in disaster reduction. First of all, we give the architecture of disaster reduction cloud, which consists of disaster reduction infrastructure as a service (IAAS), disaster reduction cloud application platform as a service (PAAS) and disaster reduction software as a service (SAAS). Secondly, we talk about the standard system of disaster reduction in five aspects. Thirdly, we indicate the security system of disaster reduction cloud. Finally, we draw a conclusion the use of cloud computing technology will help us to solve the problems for disaster reduction and promote the development of disaster reduction.

Reconciliation of the cloud computing model with US federal electronic health record regulations.

PubMed

Schweitzer, Eugene J

2012-01-01

Cloud computing refers to subscription-based, fee-for-service utilization of computer hardware and software over the Internet. The model is gaining acceptance for business information technology (IT) applications because it allows capacity and functionality to increase on the fly without major investment in infrastructure, personnel or licensing fees. Large IT investments can be converted to a series of smaller operating expenses. Cloud architectures could potentially be superior to traditional electronic health record (EHR) designs in terms of economy, efficiency and utility. A central issue for EHR developers in the US is that these systems are constrained by federal regulatory legislation and oversight. These laws focus on security and privacy, which are well-recognized challenges for cloud computing systems in general. EHRs built with the cloud computing model can achieve acceptable privacy and security through business associate contracts with cloud providers that specify compliance requirements, performance metrics and liability sharing.

National research and education network

NASA Technical Reports Server (NTRS)

Villasenor, Tony

1991-01-01

Some goals of this network are as follows: Extend U.S. technological leadership in high performance computing and computer communications; Provide wide dissemination and application of the technologies both to the speed and the pace of innovation and to serve the national economy, national security, education, and the global environment; and Spur gains in the U.S. productivity and industrial competitiveness by making high performance computing and networking technologies an integral part of the design and production process. Strategies for achieving these goals are as follows: Support solutions to important scientific and technical challenges through a vigorous R and D effort; Reduce the uncertainties to industry for R and D and use of this technology through increased cooperation between government, industry, and universities and by the continued use of government and government funded facilities as a prototype user for early commercial HPCC products; and Support underlying research, network, and computational infrastructures on which U.S. high performance computing technology is based.

Artificial intelligence and signal processing for infrastructure assessment

NASA Astrophysics Data System (ADS)

Assaleh, Khaled; Shanableh, Tamer; Yehia, Sherif

2015-04-01

The Ground Penetrating Radar (GPR) is being recognized as an effective nondestructive evaluation technique to improve the inspection process. However, data interpretation and complexity of the results impose some limitations on the practicality of using this technique. This is mainly due to the need of a trained experienced person to interpret images obtained by the GPR system. In this paper, an algorithm to classify and assess the condition of infrastructures utilizing image processing and pattern recognition techniques is discussed. Features extracted form a dataset of images of defected and healthy slabs are used to train a computer vision based system while another dataset is used to evaluate the proposed algorithm. Initial results show that the proposed algorithm is able to detect the existence of defects with about 77% success rate.

Flexible Description and Adaptive Processing of Earth Observation Data through the BigEarth Platform

NASA Astrophysics Data System (ADS)

Gorgan, Dorian; Bacu, Victor; Stefanut, Teodor; Nandra, Cosmin; Mihon, Danut

2016-04-01

The Earth Observation data repositories extending periodically by several terabytes become a critical issue for organizations. The management of the storage capacity of such big datasets, accessing policy, data protection, searching, and complex processing require high costs that impose efficient solutions to balance the cost and value of data. Data can create value only when it is used, and the data protection has to be oriented toward allowing innovation that sometimes depends on creative people, which achieve unexpected valuable results through a flexible and adaptive manner. The users need to describe and experiment themselves different complex algorithms through analytics in order to valorize data. The analytics uses descriptive and predictive models to gain valuable knowledge and information from data analysis. Possible solutions for advanced processing of big Earth Observation data are given by the HPC platforms such as cloud. With platforms becoming more complex and heterogeneous, the developing of applications is even harder and the efficient mapping of these applications to a suitable and optimum platform, working on huge distributed data repositories, is challenging and complex as well, even by using specialized software services. From the user point of view, an optimum environment gives acceptable execution times, offers a high level of usability by hiding the complexity of computing infrastructure, and supports an open accessibility and control to application entities and functionality. The BigEarth platform [1] supports the entire flow of flexible description of processing by basic operators and adaptive execution over cloud infrastructure [2]. The basic modules of the pipeline such as the KEOPS [3] set of basic operators, the WorDeL language [4], the Planner for sequential and parallel processing, and the Executor through virtual machines, are detailed as the main components of the BigEarth platform [5]. The presentation exemplifies the development of some Earth Observation oriented applications based on flexible description of processing, and adaptive and portable execution over Cloud infrastructure. Main references for further information: [1] BigEarth project, http://cgis.utcluj.ro/projects/bigearth [2] Gorgan, D., "Flexible and Adaptive Processing of Earth Observation Data over High Performance Computation Architectures", International Conference and Exhibition Satellite 2015, August 17-19, Houston, Texas, USA. [3] Mihon, D., Bacu, V., Colceriu, V., Gorgan, D., "Modeling of Earth Observation Use Cases through the KEOPS System", Proceedings of the Intelligent Computer Communication and Processing (ICCP), IEEE-Press, pp. 455-460, (2015). [4] Nandra, C., Gorgan, D., "Workflow Description Language for Defining Big Earth Data Processing Tasks", Proceedings of the Intelligent Computer Communication and Processing (ICCP), IEEE-Press, pp. 461-468, (2015). [5] Bacu, V., Stefan, T., Gorgan, D., "Adaptive Processing of Earth Observation Data on Cloud Infrastructures Based on Workflow Description", Proceedings of the Intelligent Computer Communication and Processing (ICCP), IEEE-Press, pp.444-454, (2015).

INDIGO-DataCloud solutions for Earth Sciences

NASA Astrophysics Data System (ADS)

Aguilar Gómez, Fernando; de Lucas, Jesús Marco; Fiore, Sandro; Monna, Stephen; Chen, Yin

2017-04-01

INDIGO-DataCloud (https://www.indigo-datacloud.eu/) is a European Commission funded project aiming to develop a data and computing platform targeting scientific communities, deployable on multiple hardware and provisioned over hybrid (private or public) e-infrastructures. The development of INDIGO solutions covers the different layers in cloud computing (IaaS, PaaS, SaaS), and provides tools to exploit resources like HPC or GPGPUs. INDIGO is oriented to support European Scientific research communities, that are well represented in the project. Twelve different Case Studies have been analyzed in detail from different fields: Biological & Medical sciences, Social sciences & Humanities, Environmental and Earth sciences and Physics & Astrophysics. INDIGO-DataCloud provides solutions to emerging challenges in Earth Science like: -Enabling an easy deployment of community services at different cloud sites. Many Earth Science research infrastructures often involve distributed observation stations across countries, and also have distributed data centers to support the corresponding data acquisition and curation. There is a need to easily deploy new data center services while the research infrastructure continuous spans. As an example: LifeWatch (ESFRI, Ecosystems and Biodiversity) uses INDIGO solutions to manage the deployment of services to perform complex hydrodynamics and water quality modelling over a Cloud Computing environment, predicting algae blooms, using the Docker technology: TOSCA requirement description, Docker repository, Orchestrator for deployment, AAI (AuthN, AuthZ) and OneData (Distributed Storage System). -Supporting Big Data Analysis. Nowadays, many Earth Science research communities produce large amounts of data and and are challenged by the difficulties of processing and analysing it. A climate models intercomparison data analysis case study for the European Network for Earth System Modelling (ENES) community has been setup, based on the Ophidia big data analysis framework and the Kepler workflow management system. Such services normally involve a large and distributed set of data and computing resources. In this regard, this case study exploits the INDIGO PaaS for a flexible and dynamic allocation of the resources at the infrastructural level. -Providing Distributed Data Storage Solutions. In order to allow scientific communities to perform heavy computation on huge datasets, INDIGO provides global data access solutions allowing researchers to access data in a distributed environment like fashion regardless of its location, and also to publish and share their research results with public or close communities. INDIGO solutions that support the access to distributed data storage (OneData) are being tested on EMSO infrastructure (Ocean Sciences and Geohazards) data. Another aspect of interest for the EMSO community is in efficient data processing by exploiting INDIGO services like PaaS Orchestrator. Further, for HPC exploitation, a new solution named Udocker has been implemented, enabling users to execute docker containers in supercomputers, without requiring administration privileges. This presentation will overview INDIGO solutions that are interesting and useful for Earth science communities and will show how they can be applied to other Case Studies.

X-ray-induced acoustic computed tomography of concrete infrastructure

NASA Astrophysics Data System (ADS)

Tang, Shanshan; Ramseyer, Chris; Samant, Pratik; Xiang, Liangzhong

2018-02-01

X-ray-induced Acoustic Computed Tomography (XACT) takes advantage of both X-ray absorption contrast and high ultrasonic resolution in a single imaging modality by making use of the thermoacoustic effect. In XACT, X-ray absorption by defects and other structures in concrete create thermally induced pressure jumps that launch ultrasonic waves, which are then received by acoustic detectors to form images. In this research, XACT imaging was used to non-destructively test and identify defects in concrete. For concrete structures, we conclude that XACT imaging allows multiscale imaging at depths ranging from centimeters to meters, with spatial resolutions from sub-millimeter to centimeters. XACT imaging also holds promise for single-side testing of concrete infrastructure and provides an optimal solution for nondestructive inspection of existing bridges, pavement, nuclear power plants, and other concrete infrastructure.

Proactive health computing.

PubMed

Timpka, T

2001-08-01

In an analysis departing from the global health situation, the foundation for a change of paradigm in health informatics based on socially embedded information infrastructures and technologies is identified and discussed. It is shown how an increasing computing and data transmitting capacity can be employed for proactive health computing. As a foundation for ubiquitous health promotion and prevention of disease and injury, proactive health systems use data from multiple sources to supply individuals and communities evidence-based information on means to improve their state of health and avoid health risks. The systems are characterised by: (1) being profusely connected to the world around them, using perceptual interfaces, sensors and actuators; (2) responding to external stimuli at faster than human speeds; (3) networked feedback loops; and (4) humans remaining in control, while being left outside the primary computing loop. The extended scientific mission of this new partnership between computer science, electrical engineering and social medicine is suggested to be the investigation of how the dissemination of information and communication technology on democratic grounds can be made even more important for global health than sanitation and urban planning became a century ago.

Implementing a web-based oncology protocol system in Australia: evaluation of the first 3 years of operation.

PubMed

Hains, I M; Ward, R L; Pearson, S-A

2012-01-01

EviQ is a web-based oncology protocol system launched across Australia in 2005 (http://www.eviq.org.au). We evaluated eviQ use at the point-of-care and determined the factors impacting on its uptake and routine use in the first three years of operation. We conducted a suite of qualitative and quantitative studies with over 200 Australian oncology physicians, nurses and pharmacists working at treatment centres in diverse geographical locations. EviQ was part of routine care at many hospitals; however, the way in which it was used at the point-of-care varies according to clinician roles and hospital location. We identified a range of factors impacting on eviQ uptake and routine use. Infrastructure, such as availability of point-of-care computers, and formal policies endorsing eviQ are fundamental to increasing uptake. Furthermore, the level of clinical and computer experience of end-users, the attitudes and behaviour of clinicians, endorsement and promotion strategies, and level and type of eviQ education all need to be considered and managed to ensure that the system is being used to its full potential. Our findings show that the dissemination of web-based treatment protocols does not guarantee widespread use. Organisational, environmental and clinician-specific factors play a role in uptake and utilisation. The deployment of sufficient computer infrastructure, implementation of targeted training programmes and hospital policies and investment in marketing approaches are fundamental to uptake and continued use. This study highlights the value of ongoing monitoring and evaluation to ensure systems like eviQ achieve their primary purpose - reducing treatment variation and improving quality of care. © 2010 The Authors. Internal Medicine Journal © 2010 Royal Australasian College of Physicians.

Emergency navigation without an infrastructure.

PubMed

Gelenbe, Erol; Bi, Huibo

2014-08-18

Emergency navigation systems for buildings and other built environments, such as sport arenas or shopping centres, typically rely on simple sensor networks to detect emergencies and, then, provide automatic signs to direct the evacuees. The major drawbacks of such static wireless sensor network (WSN)-based emergency navigation systems are the very limited computing capacity, which makes adaptivity very difficult, and the restricted battery power, due to the low cost of sensor nodes for unattended operation. If static wireless sensor networks and cloud-computing can be integrated, then intensive computations that are needed to determine optimal evacuation routes in the presence of time-varying hazards can be offloaded to the cloud, but the disadvantages of limited battery life-time at the client side, as well as the high likelihood of system malfunction during an emergency still remain. By making use of the powerful sensing ability of smart phones, which are increasingly ubiquitous, this paper presents a cloud-enabled indoor emergency navigation framework to direct evacuees in a coordinated fashion and to improve the reliability and resilience for both communication and localization. By combining social potential fields (SPF) and a cognitive packet network (CPN)-based algorithm, evacuees are guided to exits in dynamic loose clusters. Rather than relying on a conventional telecommunications infrastructure, we suggest an ad hoc cognitive packet network (AHCPN)-based protocol to adaptively search optimal communication routes between portable devices and the network egress nodes that provide access to cloud servers, in a manner that spares the remaining battery power of smart phones and minimizes the time latency. Experimental results through detailed simulations indicate that smart human motion and smart network management can increase the survival rate of evacuees and reduce the number of drained smart phones in an evacuation process.

Emergency Navigation without an Infrastructure

PubMed Central

Gelenbe, Erol; Bi, Huibo

2014-01-01

Emergency navigation systems for buildings and other built environments, such as sport arenas or shopping centres, typically rely on simple sensor networks to detect emergencies and, then, provide automatic signs to direct the evacuees. The major drawbacks of such static wireless sensor network (WSN)-based emergency navigation systems are the very limited computing capacity, which makes adaptivity very difficult, and the restricted battery power, due to the low cost of sensor nodes for unattended operation. If static wireless sensor networks and cloud-computing can be integrated, then intensive computations that are needed to determine optimal evacuation routes in the presence of time-varying hazards can be offloaded to the cloud, but the disadvantages of limited battery life-time at the client side, as well as the high likelihood of system malfunction during an emergency still remain. By making use of the powerful sensing ability of smart phones, which are increasingly ubiquitous, this paper presents a cloud-enabled indoor emergency navigation framework to direct evacuees in a coordinated fashion and to improve the reliability and resilience for both communication and localization. By combining social potential fields (SPF) and a cognitive packet network (CPN)-based algorithm, evacuees are guided to exits in dynamic loose clusters. Rather than relying on a conventional telecommunications infrastructure, we suggest an ad hoc cognitive packet network (AHCPN)-based protocol to adaptively search optimal communication routes between portable devices and the network egress nodes that provide access to cloud servers, in a manner that spares the remaining battery power of smart phones and minimizes the time latency. Experimental results through detailed simulations indicate that smart human motion and smart network management can increase the survival rate of evacuees and reduce the number of drained smart phones in an evacuation process. PMID:25196014

Big data computing: Building a vision for ARS information management

USDA-ARS?s Scientific Manuscript database

Improvements are needed within the ARS to increase scientific capacity and keep pace with new developments in computer technologies that support data acquisition and analysis. Enhancements in computing power and IT infrastructure are needed to provide scientists better access to high performance com...

DREAMS and IMAGE: A Model and Computer Implementation for Concurrent, Life-Cycle Design of Complex Systems

NASA Technical Reports Server (NTRS)

Hale, Mark A.; Craig, James I.; Mistree, Farrokh; Schrage, Daniel P.

1995-01-01

Computing architectures are being assembled that extend concurrent engineering practices by providing more efficient execution and collaboration on distributed, heterogeneous computing networks. Built on the successes of initial architectures, requirements for a next-generation design computing infrastructure can be developed. These requirements concentrate on those needed by a designer in decision-making processes from product conception to recycling and can be categorized in two areas: design process and design information management. A designer both designs and executes design processes throughout design time to achieve better product and process capabilities while expanding fewer resources. In order to accomplish this, information, or more appropriately design knowledge, needs to be adequately managed during product and process decomposition as well as recomposition. A foundation has been laid that captures these requirements in a design architecture called DREAMS (Developing Robust Engineering Analysis Models and Specifications). In addition, a computing infrastructure, called IMAGE (Intelligent Multidisciplinary Aircraft Generation Environment), is being developed that satisfies design requirements defined in DREAMS and incorporates enabling computational technologies.

Integration of a neuroimaging processing pipeline into a pan-canadian computing grid

NASA Astrophysics Data System (ADS)

Lavoie-Courchesne, S.; Rioux, P.; Chouinard-Decorte, F.; Sherif, T.; Rousseau, M.-E.; Das, S.; Adalat, R.; Doyon, J.; Craddock, C.; Margulies, D.; Chu, C.; Lyttelton, O.; Evans, A. C.; Bellec, P.

2012-02-01

The ethos of the neuroimaging field is quickly moving towards the open sharing of resources, including both imaging databases and processing tools. As a neuroimaging database represents a large volume of datasets and as neuroimaging processing pipelines are composed of heterogeneous, computationally intensive tools, such open sharing raises specific computational challenges. This motivates the design of novel dedicated computing infrastructures. This paper describes an interface between PSOM, a code-oriented pipeline development framework, and CBRAIN, a web-oriented platform for grid computing. This interface was used to integrate a PSOM-compliant pipeline for preprocessing of structural and functional magnetic resonance imaging into CBRAIN. We further tested the capacity of our infrastructure to handle a real large-scale project. A neuroimaging database including close to 1000 subjects was preprocessed using our interface and publicly released to help the participants of the ADHD-200 international competition. This successful experiment demonstrated that our integrated grid-computing platform is a powerful solution for high-throughput pipeline analysis in the field of neuroimaging.

Parallel high-performance grid computing: capabilities and opportunities of a novel demanding service and business class allowing highest resource efficiency.

PubMed

Kepper, Nick; Ettig, Ramona; Dickmann, Frank; Stehr, Rene; Grosveld, Frank G; Wedemann, Gero; Knoch, Tobias A

2010-01-01

Especially in the life-science and the health-care sectors the huge IT requirements are imminent due to the large and complex systems to be analysed and simulated. Grid infrastructures play here a rapidly increasing role for research, diagnostics, and treatment, since they provide the necessary large-scale resources efficiently. Whereas grids were first used for huge number crunching of trivially parallelizable problems, increasingly parallel high-performance computing is required. Here, we show for the prime example of molecular dynamic simulations how the presence of large grid clusters including very fast network interconnects within grid infrastructures allows now parallel high-performance grid computing efficiently and thus combines the benefits of dedicated super-computing centres and grid infrastructures. The demands for this service class are the highest since the user group has very heterogeneous requirements: i) two to many thousands of CPUs, ii) different memory architectures, iii) huge storage capabilities, and iv) fast communication via network interconnects, are all needed in different combinations and must be considered in a highly dedicated manner to reach highest performance efficiency. Beyond, advanced and dedicated i) interaction with users, ii) the management of jobs, iii) accounting, and iv) billing, not only combines classic with parallel high-performance grid usage, but more importantly is also able to increase the efficiency of IT resource providers. Consequently, the mere "yes-we-can" becomes a huge opportunity like e.g. the life-science and health-care sectors as well as grid infrastructures by reaching higher level of resource efficiency.

Software Infrastructure for Computer-aided Drug Discovery and Development, a Practical Example with Guidelines.

PubMed

Moretti, Loris; Sartori, Luca

2016-09-01

In the field of Computer-Aided Drug Discovery and Development (CADDD) the proper software infrastructure is essential for everyday investigations. The creation of such an environment should be carefully planned and implemented with certain features in order to be productive and efficient. Here we describe a solution to integrate standard computational services into a functional unit that empowers modelling applications for drug discovery. This system allows users with various level of expertise to run in silico experiments automatically and without the burden of file formatting for different software, managing the actual computation, keeping track of the activities and graphical rendering of the structural outcomes. To showcase the potential of this approach, performances of five different docking programs on an Hiv-1 protease test set are presented. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Maintaining Traceability in an Evolving Distributed Computing Environment

NASA Astrophysics Data System (ADS)

Collier, I.; Wartel, R.

2015-12-01

The management of risk is fundamental to the operation of any distributed computing infrastructure. Identifying the cause of incidents is essential to prevent them from re-occurring. In addition, it is a goal to contain the impact of an incident while keeping services operational. For response to incidents to be acceptable this needs to be commensurate with the scale of the problem. The minimum level of traceability for distributed computing infrastructure usage is to be able to identify the source of all actions (executables, file transfers, pilot jobs, portal jobs, etc.) and the individual who initiated them. In addition, sufficiently fine-grained controls, such as blocking the originating user and monitoring to detect abnormal behaviour, are necessary for keeping services operational. It is essential to be able to understand the cause and to fix any problems before re-enabling access for the user. The aim is to be able to answer the basic questions who, what, where, and when concerning any incident. This requires retaining all relevant information, including timestamps and the digital identity of the user, sufficient to identify, for each service instance, and for every security event including at least the following: connect, authenticate, authorize (including identity changes) and disconnect. In traditional grid infrastructures (WLCG, EGI, OSG etc.) best practices and procedures for gathering and maintaining the information required to maintain traceability are well established. In particular, sites collect and store information required to ensure traceability of events at their sites. With the increased use of virtualisation and private and public clouds for HEP workloads established procedures, which are unable to see 'inside' running virtual machines no longer capture all the information required. Maintaining traceability will at least involve a shift of responsibility from sites to Virtual Organisations (VOs) bringing with it new requirements for their logging infrastructures. VOs indeed need to fulfil a new operational role and become fully active participants in the incident response process. We present an analysis of the changing requirements to maintain traceability for virtualised and cloud based workflows with particular reference to the work of the WLCG Traceability Working Group.

Collaboratively Architecting a Scalable and Adaptable Petascale Infrastructure to Support Transdisciplinary Scientific Research for the Australian Earth and Environmental Sciences

NASA Astrophysics Data System (ADS)

Wyborn, L. A.; Evans, B. J. K.; Pugh, T.; Lescinsky, D. T.; Foster, C.; Uhlherr, A.

2014-12-01

The National Computational Infrastructure (NCI) at the Australian National University (ANU) is a partnership between CSIRO, ANU, Bureau of Meteorology (BoM) and Geoscience Australia. Recent investments in a 1.2 PFlop Supercomputer (Raijin), ~ 20 PB data storage using Lustre filesystems and a 3000 core high performance cloud have created a hybrid platform for higher performance computing and data-intensive science to enable large scale earth and climate systems modelling and analysis. There are > 3000 users actively logging in and > 600 projects on the NCI system. Efficiently scaling and adapting data and software systems to petascale infrastructures requires the collaborative development of an architecture that is designed, programmed and operated to enable users to interactively invoke different forms of in-situ computation over complex and large scale data collections. NCI makes available major and long tail data collections from both the government and research sectors based on six themes: 1) weather, climate and earth system science model simulations, 2) marine and earth observations, 3) geosciences, 4) terrestrial ecosystems, 5) water and hydrology and 6) astronomy, bio and social. Collectively they span the lithosphere, crust, biosphere, hydrosphere, troposphere, and stratosphere. Collections are the operational form for data management and access. Similar data types from individual custodians are managed cohesively. Use of international standards for discovery and interoperability allow complex interactions within and between the collections. This design facilitates a transdisciplinary approach to research and enables a shift from small scale, 'stove-piped' science efforts to large scale, collaborative systems science. This new and complex infrastructure requires a move to shared, globally trusted software frameworks that can be maintained and updated. Workflow engines become essential and need to integrate provenance, versioning, traceability, repeatability and publication. There are also human resource challenges as highly skilled HPC/HPD specialists, specialist programmers, and data scientists are required whose skills can support scaling to the new paradigm of effective and efficient data-intensive earth science analytics on petascale, and soon to be exascale systems.

Unidata's Vision for Transforming Geoscience by Moving Data Services and Software to the Cloud

NASA Astrophysics Data System (ADS)

Ramamurthy, M. K.; Fisher, W.; Yoksas, T.

2014-12-01

Universities are facing many challenges: shrinking budgets, rapidly evolving information technologies, exploding data volumes, multidisciplinary science requirements, and high student expectations. These changes are upending traditional approaches to accessing and using data and software. It is clear that Unidata's products and services must evolve to support new approaches to research and education. After years of hype and ambiguity, cloud computing is maturing in usability in many areas of science and education, bringing the benefits of virtualized and elastic remote services to infrastructure, software, computation, and data. Cloud environments reduce the amount of time and money spent to procure, install, and maintain new hardware and software, and reduce costs through resource pooling and shared infrastructure. Cloud services aimed at providing any resource, at any time, from any place, using any device are increasingly being embraced by all types of organizations. Given this trend and the enormous potential of cloud-based services, Unidata is taking moving to augment its products, services, data delivery mechanisms and applications to align with the cloud-computing paradigm. Specifically, Unidata is working toward establishing a community-based development environment that supports the creation and use of software services to build end-to-end data workflows. The design encourages the creation of services that can be broken into small, independent chunks that provide simple capabilities. Chunks could be used individually to perform a task, or chained into simple or elaborate workflows. The services will also be portable, allowing their use in researchers' own cloud-based computing environments. In this talk, we present a vision for Unidata's future in a cloud-enabled data services and discuss our initial efforts to deploy a subset of Unidata data services and tools in the Amazon EC2 and Microsoft Azure cloud environments, including the transfer of real-time meteorological data into its cloud instances, product generation using those data, and the deployment of TDS, McIDAS ADDE and AWIPS II data servers and the Integrated Data Server visualization tool.

e-Science on Earthquake Disaster Mitigation by EUAsiaGrid

NASA Astrophysics Data System (ADS)

Yen, Eric; Lin, Simon; Chen, Hsin-Yen; Chao, Li; Huang, Bor-Shoh; Liang, Wen-Tzong

2010-05-01

Although earthquake is not predictable at this moment, with the aid of accurate seismic wave propagation analysis, we could simulate the potential hazards at all distances from possible fault sources by understanding the source rupture process during large earthquakes. With the integration of strong ground-motion sensor network, earthquake data center and seismic wave propagation analysis over gLite e-Science Infrastructure, we could explore much better knowledge on the impact and vulnerability of potential earthquake hazards. On the other hand, this application also demonstrated the e-Science way to investigate unknown earth structure. Regional integration of earthquake sensor networks could aid in fast event reporting and accurate event data collection. Federation of earthquake data center entails consolidation and sharing of seismology and geology knowledge. Capability building of seismic wave propagation analysis implies the predictability of potential hazard impacts. With gLite infrastructure and EUAsiaGrid collaboration framework, earth scientists from Taiwan, Vietnam, Philippine, Thailand are working together to alleviate potential seismic threats by making use of Grid technologies and also to support seismology researches by e-Science. A cross continental e-infrastructure, based on EGEE and EUAsiaGrid, is established for seismic wave forward simulation and risk estimation. Both the computing challenge on seismic wave analysis among 5 European and Asian partners, and the data challenge for data center federation had been exercised and verified. Seismogram-on-Demand service is also developed for the automatic generation of seismogram on any sensor point to a specific epicenter. To ease the access to all the services based on users workflow and retain the maximal flexibility, a Seismology Science Gateway integating data, computation, workflow, services and user communities would be implemented based on typical use cases. In the future, extension of the earthquake wave propagation to tsunami mitigation would be feasible once the user community support is in place.

Branch Campus Librarianship with Minimal Infrastructure: Rewards and Challenges

ERIC Educational Resources Information Center

Knickman, Elena; Walton, Kerry

2014-01-01

Delaware County Community College provides library services to its branch campus community members by stationing a librarian at a campus 5 to 20 hours each week, without any more library infrastructure than an Internet-enabled computer on the school network. Faculty and students have reacted favorably to the increased presence of librarians.…

VERA 3.6 Release Notes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williamson, Richard L.; Kochunas, Brendan; Adams, Brian M.

The Virtual Environment for Reactor Applications components included in this distribution include selected computational tools and supporting infrastructure that solve neutronics, thermal-hydraulics, fuel performance, and coupled neutronics-thermal hydraulics problems. The infrastructure components provide a simplified common user input capability and provide for the physics integration with data transfer and coupled-physics iterative solution algorithms.

Quantifying Security Threats and Their Impact

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aissa, Anis Ben; Abercrombie, Robert K; Sheldon, Frederick T

In earlier works, we present a computational infrastructure that allows an analyst to estimate the security of a system in terms of the loss that each stakeholder stands to sustain as a result of security breakdowns. In this paper we illustrate this infrastructure by means of a sample example involving an e-commerce application.

Quantifying Security Threats and Their Potential Impacts: A Case Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aissa, Anis Ben; Abercrombie, Robert K; Sheldon, Frederick T

In earlier works, we present a computational infrastructure that allows an analyst to estimate the security of a system in terms of the loss that each stakeholder stands to sustain as a result of security breakdowns. In this paper, we illustrate this infrastructure by means of an e-commerce application.

WLCG scale testing during CMS data challenges

NASA Astrophysics Data System (ADS)

Gutsche, O.; Hajdu, C.

2008-07-01

The CMS computing model to process and analyze LHC collision data follows a data-location driven approach and is using the WLCG infrastructure to provide access to GRID resources. As a preparation for data taking, CMS tests its computing model during dedicated data challenges. An important part of the challenges is the test of the user analysis which poses a special challenge for the infrastructure with its random distributed access patterns. The CMS Remote Analysis Builder (CRAB) handles all interactions with the WLCG infrastructure transparently for the user. During the 2006 challenge, CMS set its goal to test the infrastructure at a scale of 50,000 user jobs per day using CRAB. Both direct submissions by individual users and automated submissions by robots were used to achieve this goal. A report will be given about the outcome of the user analysis part of the challenge using both the EGEE and OSG parts of the WLCG. In particular, the difference in submission between both GRID middlewares (resource broker vs. direct submission) will be discussed. In the end, an outlook for the 2007 data challenge is given.

AstroGrid-D: Grid technology for astronomical science

NASA Astrophysics Data System (ADS)

Enke, Harry; Steinmetz, Matthias; Adorf, Hans-Martin; Beck-Ratzka, Alexander; Breitling, Frank; Brüsemeister, Thomas; Carlson, Arthur; Ensslin, Torsten; Högqvist, Mikael; Nickelt, Iliya; Radke, Thomas; Reinefeld, Alexander; Reiser, Angelika; Scholl, Tobias; Spurzem, Rainer; Steinacker, Jürgen; Voges, Wolfgang; Wambsganß, Joachim; White, Steve

2011-02-01

We present status and results of AstroGrid-D, a joint effort of astrophysicists and computer scientists to employ grid technology for scientific applications. AstroGrid-D provides access to a network of distributed machines with a set of commands as well as software interfaces. It allows simple use of computer and storage facilities and to schedule or monitor compute tasks and data management. It is based on the Globus Toolkit middleware (GT4). Chapter 1 describes the context which led to the demand for advanced software solutions in Astrophysics, and we state the goals of the project. We then present characteristic astrophysical applications that have been implemented on AstroGrid-D in chapter 2. We describe simulations of different complexity, compute-intensive calculations running on multiple sites (Section 2.1), and advanced applications for specific scientific purposes (Section 2.2), such as a connection to robotic telescopes (Section 2.2.3). We can show from these examples how grid execution improves e.g. the scientific workflow. Chapter 3 explains the software tools and services that we adapted or newly developed. Section 3.1 is focused on the administrative aspects of the infrastructure, to manage users and monitor activity. Section 3.2 characterises the central components of our architecture: The AstroGrid-D information service to collect and store metadata, a file management system, the data management system, and a job manager for automatic submission of compute tasks. We summarise the successfully established infrastructure in chapter 4, concluding with our future plans to establish AstroGrid-D as a platform of modern e-Astronomy.

Defense strategies for cloud computing multi-site server infrastructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rao, Nageswara S.; Ma, Chris Y. T.; He, Fei

We consider cloud computing server infrastructures for big data applications, which consist of multiple server sites connected over a wide-area network. The sites house a number of servers, network elements and local-area connections, and the wide-area network plays a critical, asymmetric role of providing vital connectivity between them. We model this infrastructure as a system of systems, wherein the sites and wide-area network are represented by their cyber and physical components. These components can be disabled by cyber and physical attacks, and also can be protected against them using component reinforcements. The effects of attacks propagate within the systems, andmore » also beyond them via the wide-area network.We characterize these effects using correlations at two levels using: (a) aggregate failure correlation function that specifies the infrastructure failure probability given the failure of an individual site or network, and (b) first-order differential conditions on system survival probabilities that characterize the component-level correlations within individual systems. We formulate a game between an attacker and a provider using utility functions composed of survival probability and cost terms. At Nash Equilibrium, we derive expressions for the expected capacity of the infrastructure given by the number of operational servers connected to the network for sum-form, product-form and composite utility functions.« less

Storing and Using Health Data in a Virtual Private Cloud

PubMed Central

Regola, Nathan

2013-01-01

Electronic health records are being adopted at a rapid rate due to increased funding from the US federal government. Health data provide the opportunity to identify possible improvements in health care delivery by applying data mining and statistical methods to the data and will also enable a wide variety of new applications that will be meaningful to patients and medical professionals. Researchers are often granted access to health care data to assist in the data mining process, but HIPAA regulations mandate comprehensive safeguards to protect the data. Often universities (and presumably other research organizations) have an enterprise information technology infrastructure and a research infrastructure. Unfortunately, both of these infrastructures are generally not appropriate for sensitive research data such as HIPAA, as they require special accommodations on the part of the enterprise information technology (or increased security on the part of the research computing environment). Cloud computing, which is a concept that allows organizations to build complex infrastructures on leased resources, is rapidly evolving to the point that it is possible to build sophisticated network architectures with advanced security capabilities. We present a prototype infrastructure in Amazon’s Virtual Private Cloud to allow researchers and practitioners to utilize the data in a HIPAA-compliant environment. PMID:23485880

Telescience workstation

NASA Technical Reports Server (NTRS)

Brown, Robert L.; Doyle, Dee; Haines, Richard F.; Slocum, Michael

1989-01-01

As part of the Telescience Testbed Pilot Program, the Universities Space Research Association/ Research Institute for Advanced Computer Science (USRA/RIACS) proposed to support remote communication by providing a network of human/machine interfaces, computer resources, and experimental equipment which allows: remote science, collaboration, technical exchange, and multimedia communication. The telescience workstation is intended to provide a local computing environment for telescience. The purpose of the program are as follows: (1) to provide a suitable environment to integrate existing and new software for a telescience workstation; (2) to provide a suitable environment to develop new software in support of telescience activities; (3) to provide an interoperable environment so that a wide variety of workstations may be used in the telescience program; (4) to provide a supportive infrastructure and a common software base; and (5) to advance, apply, and evaluate the telescience technolgy base. A prototype telescience computing environment designed to bring practicing scientists in domains other than their computer science into a modern style of doing their computing was created and deployed. This environment, the Telescience Windowing Environment, Phase 1 (TeleWEn-1), met some, but not all of the goals stated above. The TeleWEn-1 provided a window-based workstation environment and a set of tools for text editing, document preparation, electronic mail, multimedia mail, raster manipulation, and system management.

Security Analysis of Smart Grid Cyber Physical Infrastructures Using Modeling and Game Theoretic Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abercrombie, Robert K; Sheldon, Frederick T.

Cyber physical computing infrastructures typically consist of a number of sites are interconnected. Its operation critically depends both on cyber components and physical components. Both types of components are subject to attacks of different kinds and frequencies, which must be accounted for the initial provisioning and subsequent operation of the infrastructure via information security analysis. Information security analysis can be performed using game theory implemented in dynamic Agent Based Game Theoretic (ABGT) simulations. Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, andmore » information assets. We concentrated our analysis on the electric sector failure scenarios and impact analyses by the NESCOR Working Group Study, From the Section 5 electric sector representative failure scenarios; we extracted the four generic failure scenarios and grouped them into three specific threat categories (confidentiality, integrity, and availability) to the system. These specific failure scenarios serve as a demonstration of our simulation. The analysis using our ABGT simulation demonstrates how to model the electric sector functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the cyber physical infrastructure network with respect to CIA.« less

Computer literacy and attitudes towards e-learning among first year medical students

PubMed Central

Link, Thomas Michael; Marz, Richard

2006-01-01

Background At the Medical University of Vienna, most information for students is available only online. In 2005, an e-learning project was initiated and there are plans to introduce a learning management system. In this study, we estimate the level of students' computer skills, the number of students having difficulty with e-learning, and the number of students opposed to e-learning. Methods The study was conducted in an introductory course on computer-based and web-based training (CBT/WBT). Students were asked to fill out a questionnaire online that covered a wide range of relevant attitudes and experiences. Results While the great majority of students possess sufficient computer skills and acknowledge the advantages of interactive and multimedia-enhanced learning material, a small percentage lacks basic computer skills and/or is very skeptical about e-learning. There is also a consistently significant albeit weak gender difference in available computer infrastructure and Internet access. As for student attitudes toward e-learning, we found that age, computer use, and previous exposure to computers are more important than gender. A sizable number of students, 12% of the total, make little or no use of existing e-learning offerings. Conclusion Many students would benefit from a basic introduction to computers and to the relevant computer-based resources of the university. Given to the wide range of computer skills among students, a single computer course for all students would not be useful nor would it be accepted. Special measures should be taken to prevent students who lack computer skills from being disadvantaged or from developing computer-hostile attitudes. PMID:16784524

Computer literacy and attitudes towards e-learning among first year medical students.

PubMed

Link, Thomas Michael; Marz, Richard

2006-06-19

At the Medical University of Vienna, most information for students is available only online. In 2005, an e-learning project was initiated and there are plans to introduce a learning management system. In this study, we estimate the level of students' computer skills, the number of students having difficulty with e-learning, and the number of students opposed to e-learning. The study was conducted in an introductory course on computer-based and web-based training (CBT/WBT). Students were asked to fill out a questionnaire online that covered a wide range of relevant attitudes and experiences. While the great majority of students possess sufficient computer skills and acknowledge the advantages of interactive and multimedia-enhanced learning material, a small percentage lacks basic computer skills and/or is very skeptical about e-learning. There is also a consistently significant albeit weak gender difference in available computer infrastructure and Internet access. As for student attitudes toward e-learning, we found that age, computer use, and previous exposure to computers are more important than gender. A sizable number of students, 12% of the total, make little or no use of existing e-learning offerings. Many students would benefit from a basic introduction to computers and to the relevant computer-based resources of the university. Given to the wide range of computer skills among students, a single computer course for all students would not be useful nor would it be accepted. Special measures should be taken to prevent students who lack computer skills from being disadvantaged or from developing computer-hostile attitudes.

Evolution of Autonomous Self-Righting Behaviors for Articulated Nanorovers

NASA Technical Reports Server (NTRS)

Tunstel, Edward

1999-01-01

Miniature rovers with articulated mobility mechanisms are being developed for planetary surface exploration on Mars and small solar system bodies. These vehicles are designed to be capable of autonomous recovery from overturning during surface operations. This paper describes a computational means of developing motion behaviors that achieve the autonomous recovery function. It proposes a control software design approach aimed at reducing the effort involved in developing self-righting behaviors. The approach is based on the integration of evolutionary computing with a dynamics simulation environment for evolving and evaluating motion behaviors. The automated behavior design approach is outlined and its underlying genetic programming infrastructure is described.

Impact of configuration management system of computer center on support of scientific projects throughout their lifecycle

NASA Astrophysics Data System (ADS)

Bogdanov, A. V.; Iuzhanin, N. V.; Zolotarev, V. I.; Ezhakova, T. R.

2017-12-01

In this article the problem of scientific projects support throughout their lifecycle in the computer center is considered in every aspect of support. Configuration Management system plays a connecting role in processes related to the provision and support of services of a computer center. In view of strong integration of IT infrastructure components with the use of virtualization, control of infrastructure becomes even more critical to the support of research projects, which means higher requirements for the Configuration Management system. For every aspect of research projects support, the influence of the Configuration Management system is being reviewed and development of the corresponding elements of the system is being described in the present paper.

Towards sustainable infrastructure management: knowledge-based service-oriented computing framework for visual analytics

NASA Astrophysics Data System (ADS)

Vatcha, Rashna; Lee, Seok-Won; Murty, Ajeet; Tolone, William; Wang, Xiaoyu; Dou, Wenwen; Chang, Remco; Ribarsky, William; Liu, Wanqiu; Chen, Shen-en; Hauser, Edd

2009-05-01

Infrastructure management (and its associated processes) is complex to understand, perform and thus, hard to make efficient and effective informed decisions. The management involves a multi-faceted operation that requires the most robust data fusion, visualization and decision making. In order to protect and build sustainable critical assets, we present our on-going multi-disciplinary large-scale project that establishes the Integrated Remote Sensing and Visualization (IRSV) system with a focus on supporting bridge structure inspection and management. This project involves specific expertise from civil engineers, computer scientists, geographers, and real-world practitioners from industry, local and federal government agencies. IRSV is being designed to accommodate the essential needs from the following aspects: 1) Better understanding and enforcement of complex inspection process that can bridge the gap between evidence gathering and decision making through the implementation of ontological knowledge engineering system; 2) Aggregation, representation and fusion of complex multi-layered heterogeneous data (i.e. infrared imaging, aerial photos and ground-mounted LIDAR etc.) with domain application knowledge to support machine understandable recommendation system; 3) Robust visualization techniques with large-scale analytical and interactive visualizations that support users' decision making; and 4) Integration of these needs through the flexible Service-oriented Architecture (SOA) framework to compose and provide services on-demand. IRSV is expected to serve as a management and data visualization tool for construction deliverable assurance and infrastructure monitoring both periodically (annually, monthly, even daily if needed) as well as after extreme events.

An Approach to Dynamic Service Management in Pervasive Computing Systems

DTIC Science & Technology

2005-01-01

standard interface to them that is easily accessible by any user. This paper outlines the design of Centaurus , an infrastructure for presenting...based on Extensi- ble Markup Language (XML) for communication, giving the system a uniform and easily adaptable interface. Centaurus defines a...easy and automatic usage. This is the vision that guides our re- search on the Centaurus system. We define a SmartSpace as a dynamic environment that

Engaging the Nation’s Critical Infrastructure Sector to Deter Cyber Threats

DTIC Science & Technology

2013-03-01

is the component of CyberOps that extends cyber power beyond the defensive boundaries of the GIG to detect, deter, deny, and defeat adversaries... economy .16 DDOS attacks are based on multiple, malware infected personal computers, organized into networks called botnets, and are directed by...not condemn the actions of those involved. Of the two attacks on Estonia and Georgia, it was Estonia that had the greatest damage to its economy

Reproducible Large-Scale Neuroimaging Studies with the OpenMOLE Workflow Management System.

PubMed

Passerat-Palmbach, Jonathan; Reuillon, Romain; Leclaire, Mathieu; Makropoulos, Antonios; Robinson, Emma C; Parisot, Sarah; Rueckert, Daniel

2017-01-01

OpenMOLE is a scientific workflow engine with a strong emphasis on workload distribution. Workflows are designed using a high level Domain Specific Language (DSL) built on top of Scala. It exposes natural parallelism constructs to easily delegate the workload resulting from a workflow to a wide range of distributed computing environments. OpenMOLE hides the complexity of designing complex experiments thanks to its DSL. Users can embed their own applications and scale their pipelines from a small prototype running on their desktop computer to a large-scale study harnessing distributed computing infrastructures, simply by changing a single line in the pipeline definition. The construction of the pipeline itself is decoupled from the execution context. The high-level DSL abstracts the underlying execution environment, contrary to classic shell-script based pipelines. These two aspects allow pipelines to be shared and studies to be replicated across different computing environments. Workflows can be run as traditional batch pipelines or coupled with OpenMOLE's advanced exploration methods in order to study the behavior of an application, or perform automatic parameter tuning. In this work, we briefly present the strong assets of OpenMOLE and detail recent improvements targeting re-executability of workflows across various Linux platforms. We have tightly coupled OpenMOLE with CARE, a standalone containerization solution that allows re-executing on a Linux host any application that has been packaged on another Linux host previously. The solution is evaluated against a Python-based pipeline involving packages such as scikit-learn as well as binary dependencies. All were packaged and re-executed successfully on various HPC environments, with identical numerical results (here prediction scores) obtained on each environment. Our results show that the pair formed by OpenMOLE and CARE is a reliable solution to generate reproducible results and re-executable pipelines. A demonstration of the flexibility of our solution showcases three neuroimaging pipelines harnessing distributed computing environments as heterogeneous as local clusters or the European Grid Infrastructure (EGI).

Reproducible Large-Scale Neuroimaging Studies with the OpenMOLE Workflow Management System

PubMed Central

Passerat-Palmbach, Jonathan; Reuillon, Romain; Leclaire, Mathieu; Makropoulos, Antonios; Robinson, Emma C.; Parisot, Sarah; Rueckert, Daniel

2017-01-01

OpenMOLE is a scientific workflow engine with a strong emphasis on workload distribution. Workflows are designed using a high level Domain Specific Language (DSL) built on top of Scala. It exposes natural parallelism constructs to easily delegate the workload resulting from a workflow to a wide range of distributed computing environments. OpenMOLE hides the complexity of designing complex experiments thanks to its DSL. Users can embed their own applications and scale their pipelines from a small prototype running on their desktop computer to a large-scale study harnessing distributed computing infrastructures, simply by changing a single line in the pipeline definition. The construction of the pipeline itself is decoupled from the execution context. The high-level DSL abstracts the underlying execution environment, contrary to classic shell-script based pipelines. These two aspects allow pipelines to be shared and studies to be replicated across different computing environments. Workflows can be run as traditional batch pipelines or coupled with OpenMOLE's advanced exploration methods in order to study the behavior of an application, or perform automatic parameter tuning. In this work, we briefly present the strong assets of OpenMOLE and detail recent improvements targeting re-executability of workflows across various Linux platforms. We have tightly coupled OpenMOLE with CARE, a standalone containerization solution that allows re-executing on a Linux host any application that has been packaged on another Linux host previously. The solution is evaluated against a Python-based pipeline involving packages such as scikit-learn as well as binary dependencies. All were packaged and re-executed successfully on various HPC environments, with identical numerical results (here prediction scores) obtained on each environment. Our results show that the pair formed by OpenMOLE and CARE is a reliable solution to generate reproducible results and re-executable pipelines. A demonstration of the flexibility of our solution showcases three neuroimaging pipelines harnessing distributed computing environments as heterogeneous as local clusters or the European Grid Infrastructure (EGI). PMID:28381997

The inventions technology on water resources to support environmental engineering based infrastructure

NASA Astrophysics Data System (ADS)

Sunjoto, S.

2017-03-01

Since the Stockholm Declaration, declared on the United Nation Conference on the Human Environment in Sweden on 5-16 June 1972 and attended the 113 country delegations, all the infrastructure construction should comply the sustainable development. As a consequence, almost research and studies were directing to the environmental aspect of construction including on water resources engineering. This paper will present the inventions which are very useful for the design of infrastructure, especially on the Groundwater engineering. This field has been rapidly developed since the publication of the well known law of flow through porous materials by Henri Darcy in 1856 on his book "Les fontaine publiques de la ville de Dijon". This law states that the discharge through porous media is proportional to the product of the hydraulic gradient, the cross-sectional area normal to the flow and the coefficient of permeability of the material. Forchheimer in 1930 developed a breakthrough formula by simplifying solution in a steady state flow condition especially in the case of radial flow to compute the permeability coefficient of casing hole or tube test with zero inflow discharge. The outflow discharge on the holes is equal to shape factor of tip of casing (F) multiplied by coefficient of permeability of soils (K) and multiplied by hydraulic head (H). In 1988, Sunjoto derived an equation in unsteady state flow condition based on this formula. In 2002, Sunjoto developed several formulas of shape factor as the parameters of the equation. In the beginning this formula is implemented to compute for the dimension of recharge well as the best method of water conservation for the urban area. After a long research this formula can be implemented to compute the drawdown on pumping or coefficient of permeability of soil by pumping test. This method can substitute the former methods like Theis (1935), Cooper-Jacob (1946), Chow (1952), Glover (1966), Papadopulos-Cooper (1967), Todd (1980), Singh (2000) etc. The advantages of Sunjoto's equation compared to the former methods that it is simpler in equation, easier to compute, doesn't need graphical support, is accurate in result and doesn't need observation well in pumping test, due to its need on drawdown on well function duration of pumping data only.

Integrating Data Distribution and Data Assimilation Between the OOI CI and the NOAA DIF

NASA Astrophysics Data System (ADS)

Meisinger, M.; Arrott, M.; Clemesha, A.; Farcas, C.; Farcas, E.; Im, T.; Schofield, O.; Krueger, I.; Klacansky, I.; Orcutt, J.; Peach, C.; Chave, A.; Raymer, D.; Vernon, F.

2008-12-01

The Ocean Observatories Initiative (OOI) is an NSF funded program to establish the ocean observing infrastructure of the 21st century benefiting research and education. It is currently approaching final design and promises to deliver cyber and physical observatory infrastructure components as well as substantial core instrumentation to study environmental processes of the ocean at various scales, from coastal shelf-slope exchange processes to the deep ocean. The OOI's data distribution network lies at the heart of its cyber- infrastructure, which enables a multitude of science and education applications, ranging from data analysis, to processing, visualization and ontology supported query and mediation. In addition, it fundamentally supports a class of applications exploiting the knowledge gained from analyzing observational data for objective-driven ocean observing applications, such as automatically triggered response to episodic environmental events and interactive instrument tasking and control. The U.S. Department of Commerce through NOAA operates the Integrated Ocean Observing System (IOOS) providing continuous data in various formats, rates and scales on open oceans and coastal waters to scientists, managers, businesses, governments, and the public to support research and inform decision-making. The NOAA IOOS program initiated development of the Data Integration Framework (DIF) to improve management and delivery of an initial subset of ocean observations with the expectation of achieving improvements in a select set of NOAA's decision-support tools. Both OOI and NOAA through DIF collaborate on an effort to integrate the data distribution, access and analysis needs of both programs. We present details and early findings from this collaboration; one part of it is the development of a demonstrator combining web-based user access to oceanographic data through ERDDAP, efficient science data distribution, and scalable, self-healing deployment in a cloud computing environment. ERDDAP is a web-based front-end application integrating oceanographic data sources of various formats, for instance CDF data files as aggregated through NcML or presented using a THREDDS server. The OOI-designed data distribution network provides global traffic management and computational load balancing for observatory resources; it makes use of the OpenDAP Data Access Protocol (DAP) for efficient canonical science data distribution over the network. A cloud computing strategy is the basis for scalable, self-healing organization of an observatory's computing and storage resources, independent of the physical location and technical implementation of these resources.

Building analytical platform with Big Data solutions for log files of PanDA infrastructure

NASA Astrophysics Data System (ADS)

Alekseev, A. A.; Barreiro Megino, F. G.; Klimentov, A. A.; Korchuganova, T. A.; Maendo, T.; Padolski, S. V.

2018-05-01

The paper describes the implementation of a high-performance system for the processing and analysis of log files for the PanDA infrastructure of the ATLAS experiment at the Large Hadron Collider (LHC), responsible for the workload management of order of 2M daily jobs across the Worldwide LHC Computing Grid. The solution is based on the ELK technology stack, which includes several components: Filebeat, Logstash, ElasticSearch (ES), and Kibana. Filebeat is used to collect data from logs. Logstash processes data and export to Elasticsearch. ES are responsible for centralized data storage. Accumulated data in ES can be viewed using a special software Kibana. These components were integrated with the PanDA infrastructure and replaced previous log processing systems for increased scalability and usability. The authors will describe all the components and their configuration tuning for the current tasks, the scale of the actual system and give several real-life examples of how this centralized log processing and storage service is used to showcase the advantages for daily operations.

A national-scale authentication infrastructure.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Butler, R.; Engert, D.; Foster, I.

2000-12-01

Today, individuals and institutions in science and industry are increasingly forming virtual organizations to pool resources and tackle a common goal. Participants in virtual organizations commonly need to share resources such as data archives, computer cycles, and networks - resources usually available only with restrictions based on the requested resource's nature and the user's identity. Thus, any sharing mechanism must have the ability to authenticate the user's identity and determine if the user is authorized to request the resource. Virtual organizations tend to be fluid, however, so authentication mechanisms must be flexible and lightweight, allowing administrators to quickly establish andmore » change resource-sharing arrangements. However, because virtual organizations complement rather than replace existing institutions, sharing mechanisms cannot change local policies and must allow individual institutions to maintain control over their own resources. Our group has created and deployed an authentication and authorization infrastructure that meets these requirements: the Grid Security Infrastructure. GSI offers secure single sign-ons and preserves site control over access policies and local security. It provides its own versions of common applications, such as FTP and remote login, and a programming interface for creating secure applications.« less

A hybrid computational strategy to address WGS variant analysis in >5000 samples.

PubMed

Huang, Zhuoyi; Rustagi, Navin; Veeraraghavan, Narayanan; Carroll, Andrew; Gibbs, Richard; Boerwinkle, Eric; Venkata, Manjunath Gorentla; Yu, Fuli

2016-09-10

The decreasing costs of sequencing are driving the need for cost effective and real time variant calling of whole genome sequencing data. The scale of these projects are far beyond the capacity of typical computing resources available with most research labs. Other infrastructures like the cloud AWS environment and supercomputers also have limitations due to which large scale joint variant calling becomes infeasible, and infrastructure specific variant calling strategies either fail to scale up to large datasets or abandon joint calling strategies. We present a high throughput framework including multiple variant callers for single nucleotide variant (SNV) calling, which leverages hybrid computing infrastructure consisting of cloud AWS, supercomputers and local high performance computing infrastructures. We present a novel binning approach for large scale joint variant calling and imputation which can scale up to over 10,000 samples while producing SNV callsets with high sensitivity and specificity. As a proof of principle, we present results of analysis on Cohorts for Heart And Aging Research in Genomic Epidemiology (CHARGE) WGS freeze 3 dataset in which joint calling, imputation and phasing of over 5300 whole genome samples was produced in under 6 weeks using four state-of-the-art callers. The callers used were SNPTools, GATK-HaplotypeCaller, GATK-UnifiedGenotyper and GotCloud. We used Amazon AWS, a 4000-core in-house cluster at Baylor College of Medicine, IBM power PC Blue BioU at Rice and Rhea at Oak Ridge National Laboratory (ORNL) for the computation. AWS was used for joint calling of 180 TB of BAM files, and ORNL and Rice supercomputers were used for the imputation and phasing step. All other steps were carried out on the local compute cluster. The entire operation used 5.2 million core hours and only transferred a total of 6 TB of data across the platforms. Even with increasing sizes of whole genome datasets, ensemble joint calling of SNVs for low coverage data can be accomplished in a scalable, cost effective and fast manner by using heterogeneous computing platforms without compromising on the quality of variants.

The Climate-G Portal: a Grid Enabled Scientifc Gateway for Climate Change

NASA Astrophysics Data System (ADS)

Fiore, Sandro; Negro, Alessandro; Aloisio, Giovanni

2010-05-01

Grid portals are web gateways aiming at concealing the underlying infrastructure through a pervasive, transparent, user-friendly, ubiquitous and seamless access to heterogeneous and geographical spread resources (i.e. storage, computational facilities, services, sensors, network, databases). Definitively they provide an enhanced problem-solving environment able to deal with modern, large scale scientific and engineering problems. Scientific gateways are able to introduce a revolution in the way scientists and researchers organize and carry out their activities. Access to distributed resources, complex workflow capabilities, and community-oriented functionalities are just some of the features that can be provided by such a web-based environment. In the context of the EGEE NA4 Earth Science Cluster, Climate-G is a distributed testbed focusing on climate change research topics. The Euro-Mediterranean Center for Climate Change (CMCC) is actively participating in the testbed providing the scientific gateway (Climate-G Portal) to access to the entire infrastructure. The Climate-G Portal has to face important and critical challenges as well as has to satisfy and address key requirements. In the following, the most relevant ones are presented and discussed. Transparency: the portal has to provide a transparent access to the underlying infrastructure preventing users from dealing with low level details and the complexity of a distributed grid environment. Security: users must be authenticated and authorized on the portal to access and exploit portal functionalities. A wide set of roles is needed to clearly assign the proper one to each user. The access to the computational grid must be completely secured, since the target infrastructure to run jobs is a production grid environment. A security infrastructure (based on X509v3 digital certificates) is strongly needed. Pervasivity and ubiquity: the access to the system must be pervasive and ubiquitous. This is easily true due to the nature of the needed web approach. Usability and simplicity: the portal has to provide simple, high level and user friendly interfaces to ease the access and exploitation of the entire system. Coexistence of general purpose and domain oriented services: along with general purpose services (file transfer, job submission, etc.), the portal has to provide domain based services and functionalities. Subsetting of data, visualization of 2D maps around a virtual globe, delivery of maps through OGC compliant interfaces (i.e. Web Map Service - WMS) are just some examples. Since april 2009, about 70 users (85% coming from the climate change community) got access to the portal. A key challenge of this work is the idea to provide users with an integrated working environment, that is a place where scientists can find huge amount of data, complete metadata support, a wide set of data access services, data visualization and analysis tools, easy access to the underlying grid infrastructure and advanced monitoring interfaces.

The Satellite Data Thematic Core Service within the EPOS Research Infrastructure

NASA Astrophysics Data System (ADS)

Manunta, Michele; Casu, Francesco; Zinno, Ivana; De Luca, Claudio; Buonanno, Sabatino; Zeni, Giovanni; Wright, Tim; Hooper, Andy; Diament, Michel; Ostanciaux, Emilie; Mandea, Mioara; Walter, Thomas; Maccaferri, Francesco; Fernandez, Josè; Stramondo, Salvatore; Bignami, Christian; Bally, Philippe; Pinto, Salvatore; Marin, Alessandro; Cuomo, Antonio

2017-04-01

EPOS, the European Plate Observing System, is a long-term plan to facilitate the integrated use of data, data products, software and services, available from distributed Research Infrastructures (RI), for solid Earth science in Europe. Indeed, EPOS integrates a large number of existing European RIs belonging to several fields of the Earth science, from seismology to geodesy, near fault and volcanic observatories as well as anthropogenic hazards. The EPOS vision is that the integration of the existing national and trans-national research infrastructures will increase access and use of the multidisciplinary data recorded by the solid Earth monitoring networks, acquired in laboratory experiments and/or produced by computational simulations. The establishment of EPOS will foster the interoperability of products and services in the Earth science field to a worldwide community of users. Accordingly, the EPOS aim is to integrate the diverse and advanced European Research Infrastructures for solid Earth science, and build on new e-science opportunities to monitor and understand the dynamic and complex solid-Earth System. One of the EPOS Thematic Core Services (TCS), referred to as Satellite Data, aims at developing, implementing and deploying advanced satellite data products and services, mainly based on Copernicus data (namely Sentinel acquisitions), for the Earth science community. This work intends to present the technological enhancements, fostered by EPOS, to deploy effective satellite services in a harmonized and integrated way. In particular, the Satellite Data TCS will deploy five services, EPOSAR, GDM, COMET, 3D-Def and MOD, which are mainly based on the exploitation of SAR data acquired by the Sentinel-1 constellation and designed to provide information on Earth surface displacements. In particular, the planned services will provide both advanced DInSAR products (deformation maps, velocity maps, deformation time series) and value-added measurements (source model, 3D displacement maps, seismic hazard maps). Moreover, the services will release both on-demand and systematic products. The latter will be generated and made available to the users on a continuous basis, by processing each Sentinel-1 data once acquired, over a defined number of areas of interest; while the former will allow users to select data, areas, and time period to carry out their own analyses via an on-line platform. The satellite components will be integrated within the EPOS infrastructure through a common and harmonized interface that will allow users to search, process and share remote sensing images and results. This gateway to the satellite services will be represented by the ESA- Geohazards Exploitation Platform (GEP), a new cloud-based platform for the satellite Earth Observations designed to support the scientific community in the understanding of high impact natural disasters. Satellite Data TCS will use GEP as the common interface toward the main EPOS portal to provide EPOS users not only with data products but also with relevant processing and visualisation software, thus allowing users to gather and process on a cloud-computing infrastructure large datasets without any need to download them locally.

Sessional, Weekly and Diurnal Patterns of Computer Lab Usage by Students Attending a Regional University in Australia

ERIC Educational Resources Information Center

Spennemann, Dirk H. R.; Atkinson, John; Cornforth, David

2007-01-01

Most universities have invested in extensive infrastructure in the form of computer laboratories and computer kiosks. However, is this investment justified when it is suggested that students work predominantly from home using their own computers? This paper provides an empirical study investigating how students at a regional multi-campus…

Easy, Collaborative and Engaging--The Use of Cloud Computing in the Design of Management Classrooms

ERIC Educational Resources Information Center

Schneckenberg, Dirk

2014-01-01

Background: Cloud computing has recently received interest in information systems research and practice as a new way to organise information with the help of an increasingly ubiquitous computer infrastructure. However, the use of cloud computing in higher education institutions and business schools, as well as its potential to create novel…