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 Quantitative Risk Analysis Framework for Evaluating and Monitoring Operational Reliability of Cloud Computing

ERIC Educational Resources Information Center

Islam, Muhammad Faysal

2013-01-01

Cloud computing offers the advantage of on-demand, reliable and cost efficient computing solutions without the capital investment and management resources to build and maintain in-house data centers and network infrastructures. Scalability of cloud solutions enable consumers to upgrade or downsize their services as needed. In a cloud environment,…

cisPath: an R/Bioconductor package for cloud users for visualization and management of functional protein interaction networks.

PubMed

Wang, Likun; Yang, Luhe; Peng, Zuohan; Lu, Dan; Jin, Yan; McNutt, Michael; Yin, Yuxin

2015-01-01

With the burgeoning development of cloud technology and services, there are an increasing number of users who prefer cloud to run their applications. All software and associated data are hosted on the cloud, allowing users to access them via a web browser from any computer, anywhere. This paper presents cisPath, an R/Bioconductor package deployed on cloud servers for client users to visualize, manage, and share functional protein interaction networks. With this R package, users can easily integrate downloaded protein-protein interaction information from different online databases with private data to construct new and personalized interaction networks. Additional functions allow users to generate specific networks based on private databases. Since the results produced with the use of this package are in the form of web pages, cloud users can easily view and edit the network graphs via the browser, using a mouse or touch screen, without the need to download them to a local computer. This package can also be installed and run on a local desktop computer. Depending on user preference, results can be publicized or shared by uploading to a web server or cloud driver, allowing other users to directly access results via a web browser. This package can be installed and run on a variety of platforms. Since all network views are shown in web pages, such package is particularly useful for cloud users. The easy installation and operation is an attractive quality for R beginners and users with no previous experience with cloud services.

cisPath: an R/Bioconductor package for cloud users for visualization and management of functional protein interaction networks

PubMed Central

2015-01-01

Background With the burgeoning development of cloud technology and services, there are an increasing number of users who prefer cloud to run their applications. All software and associated data are hosted on the cloud, allowing users to access them via a web browser from any computer, anywhere. This paper presents cisPath, an R/Bioconductor package deployed on cloud servers for client users to visualize, manage, and share functional protein interaction networks. Results With this R package, users can easily integrate downloaded protein-protein interaction information from different online databases with private data to construct new and personalized interaction networks. Additional functions allow users to generate specific networks based on private databases. Since the results produced with the use of this package are in the form of web pages, cloud users can easily view and edit the network graphs via the browser, using a mouse or touch screen, without the need to download them to a local computer. This package can also be installed and run on a local desktop computer. Depending on user preference, results can be publicized or shared by uploading to a web server or cloud driver, allowing other users to directly access results via a web browser. Conclusions This package can be installed and run on a variety of platforms. Since all network views are shown in web pages, such package is particularly useful for cloud users. The easy installation and operation is an attractive quality for R beginners and users with no previous experience with cloud services. PMID:25708840

Service Migration from Cloud to Multi-tier Fog Nodes for Multimedia Dissemination with QoE Support

PubMed Central

Camargo, João; Rochol, Juergen; Gerla, Mario

2018-01-01

A wide range of multimedia services is expected to be offered for mobile users via various wireless access networks. Even the integration of Cloud Computing in such networks does not support an adequate Quality of Experience (QoE) in areas with high demands for multimedia contents. Fog computing has been conceptualized to facilitate the deployment of new services that cloud computing cannot provide, particularly those demanding QoE guarantees. These services are provided using fog nodes located at the network edge, which is capable of virtualizing their functions/applications. Service migration from the cloud to fog nodes can be actuated by request patterns and the timing issues. To the best of our knowledge, existing works on fog computing focus on architecture and fog node deployment issues. In this article, we describe the operational impacts and benefits associated with service migration from the cloud to multi-tier fog computing for video distribution with QoE support. Besides that, we perform the evaluation of such service migration of video services. Finally, we present potential research challenges and trends. PMID:29364172

Service Migration from Cloud to Multi-tier Fog Nodes for Multimedia Dissemination with QoE Support.

PubMed

Rosário, Denis; Schimuneck, Matias; Camargo, João; Nobre, Jéferson; Both, Cristiano; Rochol, Juergen; Gerla, Mario

2018-01-24

A wide range of multimedia services is expected to be offered for mobile users via various wireless access networks. Even the integration of Cloud Computing in such networks does not support an adequate Quality of Experience (QoE) in areas with high demands for multimedia contents. Fog computing has been conceptualized to facilitate the deployment of new services that cloud computing cannot provide, particularly those demanding QoE guarantees. These services are provided using fog nodes located at the network edge, which is capable of virtualizing their functions/applications. Service migration from the cloud to fog nodes can be actuated by request patterns and the timing issues. To the best of our knowledge, existing works on fog computing focus on architecture and fog node deployment issues. In this article, we describe the operational impacts and benefits associated with service migration from the cloud to multi-tier fog computing for video distribution with QoE support. Besides that, we perform the evaluation of such service migration of video services. Finally, we present potential research challenges and trends.

Comparative study of internet cloud and cloudlet over wireless mesh networks for real-time applications

NASA Astrophysics Data System (ADS)

Khan, Kashif A.; Wang, Qi; Luo, Chunbo; Wang, Xinheng; Grecos, Christos

2014-05-01

Mobile cloud computing is receiving world-wide momentum for ubiquitous on-demand cloud services for mobile users provided by Amazon, Google etc. with low capital cost. However, Internet-centric clouds introduce wide area network (WAN) delays that are often intolerable for real-time applications such as video streaming. One promising approach to addressing this challenge is to deploy decentralized mini-cloud facility known as cloudlets to enable localized cloud services. When supported by local wireless connectivity, a wireless cloudlet is expected to offer low cost and high performance cloud services for the users. In this work, we implement a realistic framework that comprises both a popular Internet cloud (Amazon Cloud) and a real-world cloudlet (based on Ubuntu Enterprise Cloud (UEC)) for mobile cloud users in a wireless mesh network. We focus on real-time video streaming over the HTTP standard and implement a typical application. We further perform a comprehensive comparative analysis and empirical evaluation of the application's performance when it is delivered over the Internet cloud and the cloudlet respectively. The study quantifies the influence of the two different cloud networking architectures on supporting real-time video streaming. We also enable movement of the users in the wireless mesh network and investigate the effect of user's mobility on mobile cloud computing over the cloudlet and Amazon cloud respectively. Our experimental results demonstrate the advantages of the cloudlet paradigm over its Internet cloud counterpart in supporting the quality of service of real-time applications.

A Comprehensive Review on Adaptability of Network Forensics Frameworks for Mobile Cloud Computing

PubMed Central

Abdul Wahab, Ainuddin Wahid; Han, Qi; Bin Abdul Rahman, Zulkanain

2014-01-01

Network forensics enables investigation and identification of network attacks through the retrieved digital content. The proliferation of smartphones and the cost-effective universal data access through cloud has made Mobile Cloud Computing (MCC) a congenital target for network attacks. However, confines in carrying out forensics in MCC is interrelated with the autonomous cloud hosting companies and their policies for restricted access to the digital content in the back-end cloud platforms. It implies that existing Network Forensic Frameworks (NFFs) have limited impact in the MCC paradigm. To this end, we qualitatively analyze the adaptability of existing NFFs when applied to the MCC. Explicitly, the fundamental mechanisms of NFFs are highlighted and then analyzed using the most relevant parameters. A classification is proposed to help understand the anatomy of existing NFFs. Subsequently, a comparison is given that explores the functional similarities and deviations among NFFs. The paper concludes by discussing research challenges for progressive network forensics in MCC. PMID:25097880

A comprehensive review on adaptability of network forensics frameworks for mobile cloud computing.

PubMed

Khan, Suleman; Shiraz, Muhammad; Wahab, Ainuddin Wahid Abdul; Gani, Abdullah; Han, Qi; Rahman, Zulkanain Bin Abdul

2014-01-01

Network forensics enables investigation and identification of network attacks through the retrieved digital content. The proliferation of smartphones and the cost-effective universal data access through cloud has made Mobile Cloud Computing (MCC) a congenital target for network attacks. However, confines in carrying out forensics in MCC is interrelated with the autonomous cloud hosting companies and their policies for restricted access to the digital content in the back-end cloud platforms. It implies that existing Network Forensic Frameworks (NFFs) have limited impact in the MCC paradigm. To this end, we qualitatively analyze the adaptability of existing NFFs when applied to the MCC. Explicitly, the fundamental mechanisms of NFFs are highlighted and then analyzed using the most relevant parameters. A classification is proposed to help understand the anatomy of existing NFFs. Subsequently, a comparison is given that explores the functional similarities and deviations among NFFs. The paper concludes by discussing research challenges for progressive network forensics in MCC.

Enabling Research Network Connectivity to Clouds with Virtual Router Technology

NASA Astrophysics Data System (ADS)

Seuster, R.; Casteels, K.; Leavett-Brown, CR; Paterson, M.; Sobie, RJ

2017-10-01

The use of opportunistic cloud resources by HEP experiments has significantly increased over the past few years. Clouds that are owned or managed by the HEP community are connected to the LHCONE network or the research network with global access to HEP computing resources. Private clouds, such as those supported by non-HEP research funds are generally connected to the international research network; however, commercial clouds are either not connected to the research network or only connect to research sites within their national boundaries. Since research network connectivity is a requirement for HEP applications, we need to find a solution that provides a high-speed connection. We are studying a solution with a virtual router that will address the use case when a commercial cloud has research network connectivity in a limited region. In this situation, we host a virtual router in our HEP site and require that all traffic from the commercial site transit through the virtual router. Although this may increase the network path and also the load on the HEP site, it is a workable solution that would enable the use of the remote cloud for low I/O applications. We are exploring some simple open-source solutions. In this paper, we present the results of our studies and how it will benefit our use of private and public clouds for HEP computing.

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment.

PubMed

Lee, Wei-Po; Hsiao, Yu-Ting; Hwang, Wei-Che

2014-01-16

To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks.

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment

PubMed Central

2014-01-01

Background To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. Results This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Conclusions Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks. PMID:24428926

Virtual Cloud Computing: Effects and Application of Hastily Formed Networks (HFN) for Humanitarian Assistance/Disaster Relief (HA/DR) Missions

DTIC Science & Technology

2011-09-01

COMPUTING: EFFECTS AND APPLICATION OF HASTILY FORMED NETWORKS (HFN) FOR HUMANITARIAN ASSISTANCE/DISASTER RELIEF (HA/DR) MISSIONS by Mark K. Morris...i REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour...SUBTITLE Virtual Cloud Computing: Effects and Application of Hastily Formed Networks (HFN) for Humanitarian Assistance/Disaster Relief (HA/DR) Missions

Design of Control Plane Architecture Based on Cloud Platform and Experimental Network Demonstration for Multi-domain SDON

NASA Astrophysics Data System (ADS)

Li, Ming; Yin, Hongxi; Xing, Fangyuan; Wang, Jingchao; Wang, Honghuan

2016-02-01

With the features of network virtualization and resource programming, Software Defined Optical Network (SDON) is considered as the future development trend of optical network, provisioning a more flexible, efficient and open network function, supporting intraconnection and interconnection of data centers. Meanwhile cloud platform can provide powerful computing, storage and management capabilities. In this paper, with the coordination of SDON and cloud platform, a multi-domain SDON architecture based on cloud control plane has been proposed, which is composed of data centers with database (DB), path computation element (PCE), SDON controller and orchestrator. In addition, the structure of the multidomain SDON orchestrator and OpenFlow-enabled optical node are proposed to realize the combination of centralized and distributed effective management and control platform. Finally, the functional verification and demonstration are performed through our optical experiment network.

Cloud Computing for Pharmacometrics: Using AWS, NONMEM, PsN, Grid Engine, and Sonic

PubMed Central

Sanduja, S; Jewell, P; Aron, E; Pharai, N

2015-01-01

Cloud computing allows pharmacometricians to access advanced hardware, network, and security resources available to expedite analysis and reporting. Cloud-based computing environments are available at a fraction of the time and effort when compared to traditional local datacenter-based solutions. This tutorial explains how to get started with building your own personal cloud computer cluster using Amazon Web Services (AWS), NONMEM, PsN, Grid Engine, and Sonic. PMID:26451333

Cloud Computing for Pharmacometrics: Using AWS, NONMEM, PsN, Grid Engine, and Sonic.

PubMed

Sanduja, S; Jewell, P; Aron, E; Pharai, N

2015-09-01

Cloud computing allows pharmacometricians to access advanced hardware, network, and security resources available to expedite analysis and reporting. Cloud-based computing environments are available at a fraction of the time and effort when compared to traditional local datacenter-based solutions. This tutorial explains how to get started with building your own personal cloud computer cluster using Amazon Web Services (AWS), NONMEM, PsN, Grid Engine, and Sonic.

A Secure and Verifiable Outsourced Access Control Scheme in Fog-Cloud Computing.

PubMed

Fan, Kai; Wang, Junxiong; Wang, Xin; Li, Hui; Yang, Yintang

2017-07-24

With the rapid development of big data and Internet of things (IOT), the number of networking devices and data volume are increasing dramatically. Fog computing, which extends cloud computing to the edge of the network can effectively solve the bottleneck problems of data transmission and data storage. However, security and privacy challenges are also arising in the fog-cloud computing environment. Ciphertext-policy attribute-based encryption (CP-ABE) can be adopted to realize data access control in fog-cloud computing systems. In this paper, we propose a verifiable outsourced multi-authority access control scheme, named VO-MAACS. In our construction, most encryption and decryption computations are outsourced to fog devices and the computation results can be verified by using our verification method. Meanwhile, to address the revocation issue, we design an efficient user and attribute revocation method for it. Finally, analysis and simulation results show that our scheme is both secure and highly efficient.

Understanding the Performance and Potential of Cloud Computing for Scientific Applications

DOE PAGES

Sadooghi, Iman; Martin, Jesus Hernandez; Li, Tonglin; ...

2015-02-19

In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context tomore » price. We evaluate the raw performance of different services of AWS cloud in terms of the basic resources, such as compute, memory, network and I/O. We also evaluate the performance of the scientific applications running in the cloud. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud running scientific applications. We developed a full set of metrics and conducted a comprehensive performance evlauation over the Amazon cloud. We evaluated EC2, S3, EBS and DynamoDB among the many Amazon AWS services. We evaluated the memory sub-system performance with CacheBench, the network performance with iperf, processor and network performance with the HPL benchmark application, and shared storage with NFS and PVFS in addition to S3. We also evaluated a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.« less

Understanding the Performance and Potential of Cloud Computing for Scientific Applications

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

Sadooghi, Iman; Martin, Jesus Hernandez; Li, Tonglin

In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context tomore » price. We evaluate the raw performance of different services of AWS cloud in terms of the basic resources, such as compute, memory, network and I/O. We also evaluate the performance of the scientific applications running in the cloud. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud running scientific applications. We developed a full set of metrics and conducted a comprehensive performance evlauation over the Amazon cloud. We evaluated EC2, S3, EBS and DynamoDB among the many Amazon AWS services. We evaluated the memory sub-system performance with CacheBench, the network performance with iperf, processor and network performance with the HPL benchmark application, and shared storage with NFS and PVFS in addition to S3. We also evaluated a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.« less

CANFAR+Skytree: A Cloud Computing and Data Mining System for Astronomy

NASA Astrophysics Data System (ADS)

Ball, N. M.

2013-10-01

This is a companion Focus Demonstration article to the CANFAR+Skytree poster (Ball 2013, this volume), demonstrating the usage of the Skytree machine learning software on the Canadian Advanced Network for Astronomical Research (CANFAR) cloud computing system. CANFAR+Skytree is the world's first cloud computing system for data mining in astronomy.

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.

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.

A scoping review of cloud computing in healthcare.

PubMed

Griebel, Lena; Prokosch, Hans-Ulrich; Köpcke, Felix; Toddenroth, Dennis; Christoph, Jan; Leb, Ines; Engel, Igor; Sedlmayr, Martin

2015-03-19

Cloud computing is a recent and fast growing area of development in healthcare. Ubiquitous, on-demand access to virtually endless resources in combination with a pay-per-use model allow for new ways of developing, delivering and using services. Cloud computing is often used in an "OMICS-context", e.g. for computing in genomics, proteomics and molecular medicine, while other field of application still seem to be underrepresented. Thus, the objective of this scoping review was to identify the current state and hot topics in research on cloud computing in healthcare beyond this traditional domain. MEDLINE was searched in July 2013 and in December 2014 for publications containing the terms "cloud computing" and "cloud-based". Each journal and conference article was categorized and summarized independently by two researchers who consolidated their findings. 102 publications have been analyzed and 6 main topics have been found: telemedicine/teleconsultation, medical imaging, public health and patient self-management, hospital management and information systems, therapy, and secondary use of data. Commonly used features are broad network access for sharing and accessing data and rapid elasticity to dynamically adapt to computing demands. Eight articles favor the pay-for-use characteristics of cloud-based services avoiding upfront investments. Nevertheless, while 22 articles present very general potentials of cloud computing in the medical domain and 66 articles describe conceptual or prototypic projects, only 14 articles report from successful implementations. Further, in many articles cloud computing is seen as an analogy to internet-/web-based data sharing and the characteristics of the particular cloud computing approach are unfortunately not really illustrated. Even though cloud computing in healthcare is of growing interest only few successful implementations yet exist and many papers just use the term "cloud" synonymously for "using virtual machines" or "web-based" with no described benefit of the cloud paradigm. The biggest threat to the adoption in the healthcare domain is caused by involving external cloud partners: many issues of data safety and security are still to be solved. Until then, cloud computing is favored more for singular, individual features such as elasticity, pay-per-use and broad network access, rather than as cloud paradigm on its own.

Performance Analysis of Cloud Computing Architectures Using Discrete Event Simulation

NASA Technical Reports Server (NTRS)

Stocker, John C.; Golomb, Andrew M.

2011-01-01

Cloud computing offers the economic benefit of on-demand resource allocation to meet changing enterprise computing needs. However, the flexibility of cloud computing is disadvantaged when compared to traditional hosting in providing predictable application and service performance. Cloud computing relies on resource scheduling in a virtualized network-centric server environment, which makes static performance analysis infeasible. We developed a discrete event simulation model to evaluate the overall effectiveness of organizations in executing their workflow in traditional and cloud computing architectures. The two part model framework characterizes both the demand using a probability distribution for each type of service request as well as enterprise computing resource constraints. Our simulations provide quantitative analysis to design and provision computing architectures that maximize overall mission effectiveness. We share our analysis of key resource constraints in cloud computing architectures and findings on the appropriateness of cloud computing in various applications.

Survey on Security Issues in File Management in Cloud Computing Environment

NASA Astrophysics Data System (ADS)

Gupta, Udit

2015-06-01

Cloud computing has pervaded through every aspect of Information technology in past decade. It has become easier to process plethora of data, generated by various devices in real time, with the advent of cloud networks. The privacy of users data is maintained by data centers around the world and hence it has become feasible to operate on that data from lightweight portable devices. But with ease of processing comes the security aspect of the data. One such security aspect is secure file transfer either internally within cloud or externally from one cloud network to another. File management is central to cloud computing and it is paramount to address the security concerns which arise out of it. This survey paper aims to elucidate the various protocols which can be used for secure file transfer and analyze the ramifications of using each protocol.

Bigdata Driven Cloud Security: A Survey

NASA Astrophysics Data System (ADS)

Raja, K.; Hanifa, Sabibullah Mohamed

2017-08-01

Cloud Computing (CC) is a fast-growing technology to perform massive-scale and complex computing. It eliminates the need to maintain expensive computing hardware, dedicated space, and software. Recently, it has been observed that massive growth in the scale of data or big data generated through cloud computing. CC consists of a front-end, includes the users’ computers and software required to access the cloud network, and back-end consists of various computers, servers and database systems that create the cloud. In SaaS (Software as-a-Service - end users to utilize outsourced software), PaaS (Platform as-a-Service-platform is provided) and IaaS (Infrastructure as-a-Service-physical environment is outsourced), and DaaS (Database as-a-Service-data can be housed within a cloud), where leading / traditional cloud ecosystem delivers the cloud services become a powerful and popular architecture. Many challenges and issues are in security or threats, most vital barrier for cloud computing environment. The main barrier to the adoption of CC in health care relates to Data security. When placing and transmitting data using public networks, cyber attacks in any form are anticipated in CC. Hence, cloud service users need to understand the risk of data breaches and adoption of service delivery model during deployment. This survey deeply covers the CC security issues (covering Data Security in Health care) so as to researchers can develop the robust security application models using Big Data (BD) on CC (can be created / deployed easily). Since, BD evaluation is driven by fast-growing cloud-based applications developed using virtualized technologies. In this purview, MapReduce [12] is a good example of big data processing in a cloud environment, and a model for Cloud providers.

CSNS computing environment Based on OpenStack

NASA Astrophysics Data System (ADS)

Li, Yakang; Qi, Fazhi; Chen, Gang; Wang, Yanming; Hong, Jianshu

2017-10-01

Cloud computing can allow for more flexible configuration of IT resources and optimized hardware utilization, it also can provide computing service according to the real need. We are applying this computing mode to the China Spallation Neutron Source(CSNS) computing environment. So, firstly, CSNS experiment and its computing scenarios and requirements are introduced in this paper. Secondly, the design and practice of cloud computing platform based on OpenStack are mainly demonstrated from the aspects of cloud computing system framework, network, storage and so on. Thirdly, some improvments to openstack we made are discussed further. Finally, current status of CSNS cloud computing environment are summarized in the ending of this paper.

Research on private cloud computing based on analysis on typical opensource platform: a case study with Eucalyptus and Wavemaker

NASA Astrophysics Data System (ADS)

Yu, Xiaoyuan; Yuan, Jian; Chen, Shi

2013-03-01

Cloud computing is one of the most popular topics in the IT industry and is recently being adopted by many companies. It has four development models, as: public cloud, community cloud, hybrid cloud and private cloud. Except others, private cloud can be implemented in a private network, and delivers some benefits of cloud computing without pitfalls. This paper makes a comparison of typical open source platforms through which we can implement a private cloud. After this comparison, we choose Eucalyptus and Wavemaker to do a case study on the private cloud. We also do some performance estimation of cloud platform services and development of prototype software as cloud services.

A Secure and Verifiable Outsourced Access Control Scheme in Fog-Cloud Computing

PubMed Central

Fan, Kai; Wang, Junxiong; Wang, Xin; Li, Hui; Yang, Yintang

2017-01-01

With the rapid development of big data and Internet of things (IOT), the number of networking devices and data volume are increasing dramatically. Fog computing, which extends cloud computing to the edge of the network can effectively solve the bottleneck problems of data transmission and data storage. However, security and privacy challenges are also arising in the fog-cloud computing environment. Ciphertext-policy attribute-based encryption (CP-ABE) can be adopted to realize data access control in fog-cloud computing systems. In this paper, we propose a verifiable outsourced multi-authority access control scheme, named VO-MAACS. In our construction, most encryption and decryption computations are outsourced to fog devices and the computation results can be verified by using our verification method. Meanwhile, to address the revocation issue, we design an efficient user and attribute revocation method for it. Finally, analysis and simulation results show that our scheme is both secure and highly efficient. PMID:28737733

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

Software Defined Networking challenges and future direction: A case study of implementing SDN features on OpenStack private cloud

NASA Astrophysics Data System (ADS)

Shamugam, Veeramani; Murray, I.; Leong, J. A.; Sidhu, Amandeep S.

2016-03-01

Cloud computing provides services on demand instantly, such as access to network infrastructure consisting of computing hardware, operating systems, network storage, database and applications. Network usage and demands are growing at a very fast rate and to meet the current requirements, there is a need for automatic infrastructure scaling. Traditional networks are difficult to automate because of the distributed nature of their decision making process for switching or routing which are collocated on the same device. Managing complex environments using traditional networks is time-consuming and expensive, especially in the case of generating virtual machines, migration and network configuration. To mitigate the challenges, network operations require efficient, flexible, agile and scalable software defined networks (SDN). This paper discuss various issues in SDN and suggests how to mitigate the network management related issues. A private cloud prototype test bed was setup to implement the SDN on the OpenStack platform to test and evaluate the various network performances provided by the various configurations.

Impact of office productivity cloud computing on energy consumption and greenhouse gas emissions.

PubMed

Williams, Daniel R; Tang, Yinshan

2013-05-07

Cloud computing is usually regarded as being energy efficient and thus emitting less greenhouse gases (GHG) than traditional forms of computing. When the energy consumption of Microsoft's cloud computing Office 365 (O365) and traditional Office 2010 (O2010) software suites were tested and modeled, some cloud services were found to consume more energy than the traditional form. The developed model in this research took into consideration the energy consumption at the three main stages of data transmission; data center, network, and end user device. Comparable products from each suite were selected and activities were defined for each product to represent a different computing type. Microsoft provided highly confidential data for the data center stage, while the networking and user device stages were measured directly. A new measurement and software apportionment approach was defined and utilized allowing the power consumption of cloud services to be directly measured for the user device stage. Results indicated that cloud computing is more energy efficient for Excel and Outlook which consumed less energy and emitted less GHG than the standalone counterpart. The power consumption of the cloud based Outlook (8%) and Excel (17%) was lower than their traditional counterparts. However, the power consumption of the cloud version of Word was 17% higher than its traditional equivalent. A third mixed access method was also measured for Word which emitted 5% more GHG than the traditional version. It is evident that cloud computing may not provide a unified way forward to reduce energy consumption and GHG. Direct conversion from the standalone package into the cloud provision platform can now consider energy and GHG emissions at the software development and cloud service design stage using the methods described in this research.

Making Cloud Computing Available For Researchers and Innovators (Invited)

NASA Astrophysics Data System (ADS)

Winsor, R.

2010-12-01

High Performance Computing (HPC) facilities exist in most academic institutions but are almost invariably over-subscribed. Access is allocated based on academic merit, the only practical method of assigning valuable finite compute resources. Cloud computing on the other hand, and particularly commercial clouds, draw flexibly on an almost limitless resource as long as the user has sufficient funds to pay the bill. How can the commercial cloud model be applied to scientific computing? Is there a case to be made for a publicly available research cloud and how would it be structured? This talk will explore these themes and describe how Cybera, a not-for-profit non-governmental organization in Alberta Canada, aims to leverage its high speed research and education network to provide cloud computing facilities for a much wider user base.

Community Cloud Computing

NASA Astrophysics Data System (ADS)

Marinos, Alexandros; Briscoe, Gerard

Cloud Computing is rising fast, with its data centres growing at an unprecedented rate. However, this has come with concerns over privacy, efficiency at the expense of resilience, and environmental sustainability, because of the dependence on Cloud vendors such as Google, Amazon and Microsoft. Our response is an alternative model for the Cloud conceptualisation, providing a paradigm for Clouds in the community, utilising networked personal computers for liberation from the centralised vendor model. Community Cloud Computing (C3) offers an alternative architecture, created by combing the Cloud with paradigms from Grid Computing, principles from Digital Ecosystems, and sustainability from Green Computing, while remaining true to the original vision of the Internet. It is more technically challenging than Cloud Computing, having to deal with distributed computing issues, including heterogeneous nodes, varying quality of service, and additional security constraints. However, these are not insurmountable challenges, and with the need to retain control over our digital lives and the potential environmental consequences, it is a challenge we must pursue.

Real-time video streaming in mobile cloud over heterogeneous wireless networks

NASA Astrophysics Data System (ADS)

Abdallah-Saleh, Saleh; Wang, Qi; Grecos, Christos

2012-06-01

Recently, the concept of Mobile Cloud Computing (MCC) has been proposed to offload the resource requirements in computational capabilities, storage and security from mobile devices into the cloud. Internet video applications such as real-time streaming are expected to be ubiquitously deployed and supported over the cloud for mobile users, who typically encounter a range of wireless networks of diverse radio access technologies during their roaming. However, real-time video streaming for mobile cloud users across heterogeneous wireless networks presents multiple challenges. The network-layer quality of service (QoS) provision to support high-quality mobile video delivery in this demanding scenario remains an open research question, and this in turn affects the application-level visual quality and impedes mobile users' perceived quality of experience (QoE). In this paper, we devise a framework to support real-time video streaming in this new mobile video networking paradigm and evaluate the performance of the proposed framework empirically through a lab-based yet realistic testing platform. One particular issue we focus on is the effect of users' mobility on the QoS of video streaming over the cloud. We design and implement a hybrid platform comprising of a test-bed and an emulator, on which our concept of mobile cloud computing, video streaming and heterogeneous wireless networks are implemented and integrated to allow the testing of our framework. As representative heterogeneous wireless networks, the popular WLAN (Wi-Fi) and MAN (WiMAX) networks are incorporated in order to evaluate effects of handovers between these different radio access technologies. The H.264/AVC (Advanced Video Coding) standard is employed for real-time video streaming from a server to mobile users (client nodes) in the networks. Mobility support is introduced to enable continuous streaming experience for a mobile user across the heterogeneous wireless network. Real-time video stream packets are captured for analytical purposes on the mobile user node. Experimental results are obtained and analysed. Future work is identified towards further improvement of the current design and implementation. With this new mobile video networking concept and paradigm implemented and evaluated, results and observations obtained from this study would form the basis of a more in-depth, comprehensive understanding of various challenges and opportunities in supporting high-quality real-time video streaming in mobile cloud over heterogeneous wireless networks.

On Using Home Networks and Cloud Computing for a Future Internet of Things

NASA Astrophysics Data System (ADS)

Niedermayer, Heiko; Holz, Ralph; Pahl, Marc-Oliver; Carle, Georg

In this position paper we state four requirements for a Future Internet and sketch our initial concept. The requirements: (1) more comfort, (2) integration of home networks, (3) resources like service clouds in the network, and (4) access anywhere on any machine. Future Internet needs future quality and future comfort. There need to be new possiblities for everyone. Our focus is on higher layers and related to the many overlay proposals. We consider them to run on top of a basic Future Internet core. A new user experience means to include all user devices. Home networks and services should be a fundamental part of the Future Internet. Home networks extend access and allow interaction with the environment. Cloud Computing can provide reliable resources beyond local boundaries. For access anywhere, we also need secure storage for data and profiles in the network, in particular for access with non-personal devices (Internet terminal, ticket machine, ...).

'Cloud computing' and clinical trials: report from an ECRIN workshop.

PubMed

Ohmann, Christian; Canham, Steve; Danielyan, Edgar; Robertshaw, Steve; Legré, Yannick; Clivio, Luca; Demotes, Jacques

2015-07-29

Growing use of cloud computing in clinical trials prompted the European Clinical Research Infrastructures Network, a European non-profit organisation established to support multinational clinical research, to organise a one-day workshop on the topic to clarify potential benefits and risks. The issues that arose in that workshop are summarised and include the following: the nature of cloud computing and the cloud computing industry; the risks in using cloud computing services now; the lack of explicit guidance on this subject, both generally and with reference to clinical trials; and some possible ways of reducing risks. There was particular interest in developing and using a European 'community cloud' specifically for academic clinical trial data. It was recognised that the day-long workshop was only the start of an ongoing process. Future discussion needs to include clarification of trial-specific regulatory requirements for cloud computing and involve representatives from the relevant regulatory bodies.

Cloud Computing - A Unified Approach for Surveillance Issues

NASA Astrophysics Data System (ADS)

Rachana, C. R.; Banu, Reshma, Dr.; Ahammed, G. F. Ali, Dr.; Parameshachari, B. D., Dr.

2017-08-01

Cloud computing describes highly scalable resources provided as an external service via the Internet on a basis of pay-per-use. From the economic point of view, the main attractiveness of cloud computing is that users only use what they need, and only pay for what they actually use. Resources are available for access from the cloud at any time, and from any location through networks. Cloud computing is gradually replacing the traditional Information Technology Infrastructure. Securing data is one of the leading concerns and biggest issue for cloud computing. Privacy of information is always a crucial pointespecially when an individual’s personalinformation or sensitive information is beingstored in the organization. It is indeed true that today; cloud authorization systems are notrobust enough. This paper presents a unified approach for analyzing the various security issues and techniques to overcome the challenges in the cloud environment.

Cloud Security: Issues and Research Directions

DTIC Science & Technology

2014-11-18

4. Cloud Computing Security: What Changes with Software - Defined Networking ? Maur´ıcio Tsugawa, Andr´ea Matsunaga, and Jos´e A. B. Fortes 5...machine’s memory from an untrusted or malicious hypervisor. In Chapter 4, Tsugawa et al. discuss the security issues introduced when Software - Defined ... Networking ( SDN ) is deployed within and across clouds. Chapters 5-9 are focused on the protection of data stored in the cloud. In Chapter 5, Wang et

The Potentials of Using Cloud Computing in Schools: A Systematic Literature Review

ERIC Educational Resources Information Center

Hartmann, Simon Birk; Braae, Lotte Qulleq Nygaard; Pedersen, Sine; Khalid, Md. Saifuddin

2017-01-01

Cloud Computing (CC) refers to the physical structure of a communications network, where data is stored in large data centers and can be accessed anywhere, at any time, and from different devices. This systematic literature review identifies and categorizes the potential and barriers of cloud-based teaching in schools from an international…

Considerations for Software Defined Networking (SDN): Approaches and use cases

NASA Astrophysics Data System (ADS)

Bakshi, K.

Software Defined Networking (SDN) is an evolutionary approach to network design and functionality based on the ability to programmatically modify the behavior of network devices. SDN uses user-customizable and configurable software that's independent of hardware to enable networked systems to expand data flow control. SDN is in large part about understanding and managing a network as a unified abstraction. It will make networks more flexible, dynamic, and cost-efficient, while greatly simplifying operational complexity. And this advanced solution provides several benefits including network and service customizability, configurability, improved operations, and increased performance. There are several approaches to SDN and its practical implementation. Among them, two have risen to prominence with differences in pedigree and implementation. This paper's main focus will be to define, review, and evaluate salient approaches and use cases of the OpenFlow and Virtual Network Overlay approaches to SDN. OpenFlow is a communication protocol that gives access to the forwarding plane of a network's switches and routers. The Virtual Network Overlay relies on a completely virtualized network infrastructure and services to abstract the underlying physical network, which allows the overlay to be mobile to other physical networks. This is an important requirement for cloud computing, where applications and associated network services are migrated to cloud service providers and remote data centers on the fly as resource demands dictate. The paper will discuss how and where SDN can be applied and implemented, including research and academia, virtual multitenant data center, and cloud computing applications. Specific attention will be given to the cloud computing use case, where automated provisioning and programmable overlay for scalable multi-tenancy is leveraged via the SDN approach.

On Study of Building Smart Campus under Conditions of Cloud Computing and Internet of Things

NASA Astrophysics Data System (ADS)

Huang, Chao

2017-12-01

two new concepts in the information era are cloud computing and internet of things, although they are defined differently, they share close relationship. It is a new measure to realize leap-forward development of campus by virtue of cloud computing, internet of things and other internet technologies to build smart campus. This paper, centering on the construction of smart campus, analyzes and compares differences between network in traditional campus and that in smart campus, and makes proposals on how to build smart campus finally from the perspectives of cloud computing and internet of things.

Challenges in Securing the Interface Between the Cloud and Pervasive Systems

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

Lagesse, Brent J

2011-01-01

Cloud computing presents an opportunity for pervasive systems to leverage computational and storage resources to accomplish tasks that would not normally be possible on such resource-constrained devices. Cloud computing can enable hardware designers to build lighter systems that last longer and are more mobile. Despite the advantages cloud computing offers to the designers of pervasive systems, there are some limitations of leveraging cloud computing that must be addressed. We take the position that cloud-based pervasive system must be secured holistically and discuss ways this might be accomplished. In this paper, we discuss a pervasive system utilizing cloud computing resources andmore » issues that must be addressed in such a system. In this system, the user's mobile device cannot always have network access to leverage resources from the cloud, so it must make intelligent decisions about what data should be stored locally and what processes should be run locally. As a result of these decisions, the user becomes vulnerable to attacks while interfacing with the pervasive system.« less

A Novel Market-Oriented Dynamic Collaborative Cloud Service Platform

NASA Astrophysics Data System (ADS)

Hassan, Mohammad Mehedi; Huh, Eui-Nam

In today's world the emerging Cloud computing (Weiss, 2007) offer a new computing model where resources such as computing power, storage, online applications and networking infrastructures can be shared as "services" over the internet. Cloud providers (CPs) are incentivized by the profits to be made by charging consumers for accessing these services. Consumers, such as enterprises, are attracted by the opportunity for reducing or eliminating costs associated with "in-house" provision of these services.

Cross stratum resources protection in fog-computing-based radio over fiber networks for 5G services

NASA Astrophysics Data System (ADS)

Guo, Shaoyong; Shao, Sujie; Wang, Yao; Yang, Hui

2017-09-01

In order to meet the requirement of internet of things (IoT) and 5G, the cloud radio access network is a paradigm which converges all base stations computational resources into a cloud baseband unit (BBU) pool, while the distributed radio frequency signals are collected by remote radio head (RRH). A precondition for centralized processing in the BBU pool is an interconnection fronthaul network with high capacity and low delay. However, it has become more complex and frequent in the interaction between RRH and BBU and resource scheduling among BBUs in cloud. Cloud radio over fiber network has been proposed in our previous work already. In order to overcome the complexity and latency, in this paper, we first present a novel cross stratum resources protection (CSRP) architecture in fog-computing-based radio over fiber networks (F-RoFN) for 5G services. Additionally, a cross stratum protection (CSP) scheme considering the network survivability is introduced in the proposed architecture. The CSRP with CSP scheme can effectively pull the remote processing resource locally to implement the cooperative radio resource management, enhance the responsiveness and resilience to the dynamic end-to-end 5G service demands, and globally optimize optical network, wireless and fog resources. The feasibility and efficiency of the proposed architecture with CSP scheme are verified on our software defined networking testbed in terms of service latency, transmission success rate, resource occupation rate and blocking probability.

Dynamic Optical Networks for Future Internet Environments

NASA Astrophysics Data System (ADS)

Matera, Francesco

2014-05-01

This article reports an overview on the evolution of the optical network scenario taking into account the exponential growth of connected devices, big data, and cloud computing that is driving a concrete transformation impacting the information and communication technology world. This hyper-connected scenario is deeply affecting relationships between individuals, enterprises, citizens, and public administrations, fostering innovative use cases in practically any environment and market, and introducing new opportunities and new challenges. The successful realization of this hyper-connected scenario depends on different elements of the ecosystem. In particular, it builds on connectivity and functionalities allowed by converged next-generation networks and their capacity to support and integrate with the Internet of Things, machine-to-machine, and cloud computing. This article aims at providing some hints of this scenario to contribute to analyze impacts on optical system and network issues and requirements. In particular, the role of the software-defined network is investigated by taking into account all scenarios regarding data centers, cloud computing, and machine-to-machine and trying to illustrate all the advantages that could be introduced by advanced optical communications.

A Weibull distribution accrual failure detector for cloud computing.

PubMed

Liu, Jiaxi; Wu, Zhibo; Wu, Jin; Dong, Jian; Zhao, Yao; Wen, Dongxin

2017-01-01

Failure detectors are used to build high availability distributed systems as the fundamental component. To meet the requirement of a complicated large-scale distributed system, accrual failure detectors that can adapt to multiple applications have been studied extensively. However, several implementations of accrual failure detectors do not adapt well to the cloud service environment. To solve this problem, a new accrual failure detector based on Weibull Distribution, called the Weibull Distribution Failure Detector, has been proposed specifically for cloud computing. It can adapt to the dynamic and unexpected network conditions in cloud computing. The performance of the Weibull Distribution Failure Detector is evaluated and compared based on public classical experiment data and cloud computing experiment data. The results show that the Weibull Distribution Failure Detector has better performance in terms of speed and accuracy in unstable scenarios, especially in cloud computing.

Cloud-Based Virtual Laboratory for Network Security Education

ERIC Educational Resources Information Center

Xu, Le; Huang, Dijiang; Tsai, Wei-Tek

2014-01-01

Hands-on experiments are essential for computer network security education. Existing laboratory solutions usually require significant effort to build, configure, and maintain and often do not support reconfigurability, flexibility, and scalability. This paper presents a cloud-based virtual laboratory education platform called V-Lab that provides a…

Security Risks of Cloud Computing and Its Emergence as 5th Utility Service

NASA Astrophysics Data System (ADS)

Ahmad, Mushtaq

Cloud Computing is being projected by the major cloud services provider IT companies such as IBM, Google, Yahoo, Amazon and others as fifth utility where clients will have access for processing those applications and or software projects which need very high processing speed for compute intensive and huge data capacity for scientific, engineering research problems and also e- business and data content network applications. These services for different types of clients are provided under DASM-Direct Access Service Management based on virtualization of hardware, software and very high bandwidth Internet (Web 2.0) communication. The paper reviews these developments for Cloud Computing and Hardware/Software configuration of the cloud paradigm. The paper also examines the vital aspects of security risks projected by IT Industry experts, cloud clients. The paper also highlights the cloud provider's response to cloud security risks.

Cloudbus Toolkit for Market-Oriented Cloud Computing

NASA Astrophysics Data System (ADS)

Buyya, Rajkumar; Pandey, Suraj; Vecchiola, Christian

This keynote paper: (1) presents the 21st century vision of computing and identifies various IT paradigms promising to deliver computing as a utility; (2) defines the architecture for creating market-oriented Clouds and computing atmosphere by leveraging technologies such as virtual machines; (3) provides thoughts on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain SLA-oriented resource allocation; (4) presents the work carried out as part of our new Cloud Computing initiative, called Cloudbus: (i) Aneka, a Platform as a Service software system containing SDK (Software Development Kit) for construction of Cloud applications and deployment on private or public Clouds, in addition to supporting market-oriented resource management; (ii) internetworking of Clouds for dynamic creation of federated computing environments for scaling of elastic applications; (iii) creation of 3rd party Cloud brokering services for building content delivery networks and e-Science applications and their deployment on capabilities of IaaS providers such as Amazon along with Grid mashups; (iv) CloudSim supporting modelling and simulation of Clouds for performance studies; (v) Energy Efficient Resource Allocation Mechanisms and Techniques for creation and management of Green Clouds; and (vi) pathways for future research.

Analysis and Research on Spatial Data Storage Model Based on Cloud Computing Platform

NASA Astrophysics Data System (ADS)

Hu, Yong

2017-12-01

In this paper, the data processing and storage characteristics of cloud computing are analyzed and studied. On this basis, a cloud computing data storage model based on BP neural network is proposed. In this data storage model, it can carry out the choice of server cluster according to the different attributes of the data, so as to complete the spatial data storage model with load balancing function, and have certain feasibility and application advantages.

The Role of Networks in Cloud Computing

NASA Astrophysics Data System (ADS)

Lin, Geng; Devine, Mac

The confluence of technology advancements and business developments in Broadband Internet, Web services, computing systems, and application software over the past decade has created a perfect storm for cloud computing. The "cloud model" of delivering and consuming IT functions as services is poised to fundamentally transform the IT industry and rebalance the inter-relationships among end users, enterprise IT, software companies, and the service providers in the IT ecosystem (Armbrust et al., 2009; Lin, Fu, Zhu, & Dasmalchi, 2009).

A hybrid optical switch architecture to integrate IP into optical networks to provide flexible and intelligent bandwidth on demand for cloud computing

NASA Astrophysics Data System (ADS)

Yang, Wei; Hall, Trevor J.

2013-12-01

The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users. As a consequence, the nature of the Internet traffic has been fundamentally transformed from a pure packet-based pattern to today's predominantly flow-based pattern. Cloud computing has also brought about an unprecedented growth in the Internet traffic. In this paper, a hybrid optical switch architecture is presented to deal with the flow-based Internet traffic, aiming to offer flexible and intelligent bandwidth on demand to improve fiber capacity utilization. The hybrid optical switch is capable of integrating IP into optical networks for cloud-based traffic with predictable performance, for which the delay performance of the electronic module in the hybrid optical switch architecture is evaluated through simulation.

Service-oriented Software Defined Optical Networks for Cloud Computing

NASA Astrophysics Data System (ADS)

Liu, Yuze; Li, Hui; Ji, Yuefeng

2017-10-01

With the development of big data and cloud computing technology, the traditional software-defined network is facing new challenges (e.g., ubiquitous accessibility, higher bandwidth, more flexible management and greater security). This paper proposes a new service-oriented software defined optical network architecture, including a resource layer, a service abstract layer, a control layer and an application layer. We then dwell on the corresponding service providing method. Different service ID is used to identify the service a device can offer. Finally, we experimentally evaluate that proposed service providing method can be applied to transmit different services based on the service ID in the service-oriented software defined optical network.

Estimating surface longwave radiative fluxes from satellites utilizing artificial neural networks

NASA Astrophysics Data System (ADS)

Nussbaumer, Eric A.; Pinker, Rachel T.

2012-04-01

A novel approach for calculating downwelling surface longwave (DSLW) radiation under all sky conditions is presented. The DSLW model (hereafter, DSLW/UMD v2) similarly to its predecessor, DSLW/UMD v1, is driven with a combination of Moderate Resolution Imaging Spectroradiometer (MODIS) level-3 cloud parameters and information from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim model. To compute the clear sky component of DSLW a two layer feed-forward artificial neural network with sigmoid hidden neurons and linear output neurons is implemented; it is trained with simulations derived from runs of the Rapid Radiative Transfer Model (RRTM). When computing the cloud contribution to DSLW, the cloud base temperature is estimated by using an independent artificial neural network approach of similar architecture as previously mentioned, and parameterizations. The cloud base temperature neural network is trained using spatially and temporally co-located MODIS and CloudSat Cloud Profiling Radar (CPR) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations. Daily average estimates of DSLW from 2003 to 2009 are compared against ground measurements from the Baseline Surface Radiation Network (BSRN) giving an overall correlation coefficient of 0.98, root mean square error (rmse) of 15.84 W m-2, and a bias of -0.39 W m-2. This is an improvement over an earlier version of the model (DSLW/UMD v1) which for the same time period has an overall correlation coefficient 0.97 rmse of 17.27 W m-2, and bias of 0.73 W m-2.

Embracing Statistical Challenges in the Information Technology Age

DTIC Science & Technology

2006-01-01

computation and feature selection. Moreover, two research projects on network tomography and arctic cloud detection are used throughout the paper to bring...prominent Network Tomography problem, origin- destination (OD) traffic estimation. It demonstrates well how the two modes of data collection interact...software debugging (Biblit et al, 2005 [2]), and network tomography for computer network management. Computer sys- tem problems exist long before the IT

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.

Education on the Cloud: Researching Student-Centered, Cloud-Based Learning Prospects in the Context of a European Network

ERIC Educational Resources Information Center

Panoutsopoulos, Hercules; Donert, Karl; Papoutsis, Panos; Kotsanis, Ioannis

2015-01-01

During the last few years, ongoing developments in the technological field of Cloud computing have initiated discourse on the potential of the Cloud to be systematically exploited in educational contexts. Research interest has been stimulated by a range of advantages of Cloud technologies (e.g. adaptability, flexibility, scalability,…

Cloud computing.

PubMed

Wink, Diane M

2012-01-01

In this bimonthly series, the author examines how nurse educators can use Internet and Web-based technologies such as search, communication, and collaborative writing tools; social networking and social bookmarking sites; virtual worlds; and Web-based teaching and learning programs. This article describes how cloud computing can be used in nursing education.

A Weibull distribution accrual failure detector for cloud computing

PubMed Central

Wu, Zhibo; Wu, Jin; Zhao, Yao; Wen, Dongxin

2017-01-01

Failure detectors are used to build high availability distributed systems as the fundamental component. To meet the requirement of a complicated large-scale distributed system, accrual failure detectors that can adapt to multiple applications have been studied extensively. However, several implementations of accrual failure detectors do not adapt well to the cloud service environment. To solve this problem, a new accrual failure detector based on Weibull Distribution, called the Weibull Distribution Failure Detector, has been proposed specifically for cloud computing. It can adapt to the dynamic and unexpected network conditions in cloud computing. The performance of the Weibull Distribution Failure Detector is evaluated and compared based on public classical experiment data and cloud computing experiment data. The results show that the Weibull Distribution Failure Detector has better performance in terms of speed and accuracy in unstable scenarios, especially in cloud computing. PMID:28278229

Motion/imagery secure cloud enterprise architecture analysis

NASA Astrophysics Data System (ADS)

DeLay, John L.

2012-06-01

Cloud computing with storage virtualization and new service-oriented architectures brings a new perspective to the aspect of a distributed motion imagery and persistent surveillance enterprise. Our existing research is focused mainly on content management, distributed analytics, WAN distributed cloud networking performance issues of cloud based technologies. The potential of leveraging cloud based technologies for hosting motion imagery, imagery and analytics workflows for DOD and security applications is relatively unexplored. This paper will examine technologies for managing, storing, processing and disseminating motion imagery and imagery within a distributed network environment. Finally, we propose areas for future research in the area of distributed cloud content management enterprises.

A Hierarchical Auction-Based Mechanism for Real-Time Resource Allocation in Cloud Robotic Systems.

PubMed

Wang, Lujia; Liu, Ming; Meng, Max Q-H

2017-02-01

Cloud computing enables users to share computing resources on-demand. The cloud computing framework cannot be directly mapped to cloud robotic systems with ad hoc networks since cloud robotic systems have additional constraints such as limited bandwidth and dynamic structure. However, most multirobotic applications with cooperative control adopt this decentralized approach to avoid a single point of failure. Robots need to continuously update intensive data to execute tasks in a coordinated manner, which implies real-time requirements. Thus, a resource allocation strategy is required, especially in such resource-constrained environments. This paper proposes a hierarchical auction-based mechanism, namely link quality matrix (LQM) auction, which is suitable for ad hoc networks by introducing a link quality indicator. The proposed algorithm produces a fast and robust method that is accurate and scalable. It reduces both global communication and unnecessary repeated computation. The proposed method is designed for firm real-time resource retrieval for physical multirobot systems. A joint surveillance scenario empirically validates the proposed mechanism by assessing several practical metrics. The results show that the proposed LQM auction outperforms state-of-the-art algorithms for resource allocation.

Exploration of cloud computing late start LDRD #149630 : Raincoat. v. 2.1.

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

Echeverria, Victor T.; Metral, Michael David; Leger, Michelle A.

This report contains documentation from an interoperability study conducted under the Late Start LDRD 149630, Exploration of Cloud Computing. A small late-start LDRD from last year resulted in a study (Raincoat) on using Virtual Private Networks (VPNs) to enhance security in a hybrid cloud environment. Raincoat initially explored the use of OpenVPN on IPv4 and demonstrates that it is possible to secure the communication channel between two small 'test' clouds (a few nodes each) at New Mexico Tech and Sandia. We extended the Raincoat study to add IPSec support via Vyatta routers, to interface with a public cloud (Amazon Elasticmore » Compute Cloud (EC2)), and to be significantly more scalable than the previous iteration. The study contributed to our understanding of interoperability in a hybrid cloud.« less

A Brief Analysis of Development Situations and Trend of Cloud Computing

NASA Astrophysics Data System (ADS)

Yang, Wenyan

2017-12-01

in recent years, the rapid development of Internet technology has radically changed people's work, learning and lifestyles. More and more activities are completed by virtue of computers and networks. The amount of information and data generated is bigger day by day, and people rely more on computer, which makes computing power of computer fail to meet demands of accuracy and rapidity from people. The cloud computing technology has experienced fast development, which is widely applied in the computer industry as a result of advantages of high precision, fast computing and easy usage. Moreover, it has become a focus in information research at present. In this paper, the development situations and trend of cloud computing shall be analyzed and researched.

Web N.0, the New Development Trend of Internet

NASA Astrophysics Data System (ADS)

Sun, Zhiguo; Wang, Wensheng

This article analyzes the Internet basic theory, the network foundation environment and the user behavior change and so on, Which analyzes the development tendency of existing partial Internet products in the future Internet environment. The article also hot on the concept of cloud computing, Demonstrates the relation between Cloud Computing and Web 2.0 from the angle of Cloud-based end-user applications, The possibly killing application in the future was discussed.

Developing Online Learning Resources: Big Data, Social Networks, and Cloud Computing to Support Pervasive Knowledge

ERIC Educational Resources Information Center

Anshari, Muhammad; Alas, Yabit; Guan, Lim Sei

2016-01-01

Utilizing online learning resources (OLR) from multi channels in learning activities promise extended benefits from traditional based learning-centred to a collaborative based learning-centred that emphasises pervasive learning anywhere and anytime. While compiling big data, cloud computing, and semantic web into OLR offer a broader spectrum of…

Using a Cloud-Based Computing Environment to Support Teacher Training on Common Core Implementation

ERIC Educational Resources Information Center

Robertson, Cory

2013-01-01

A cloud-based computing environment, Google Apps for Education (GAFE), has provided the Anaheim City School District (ACSD) a comprehensive and collaborative avenue for creating, sharing, and editing documents, calendars, and social networking communities. With this environment, teachers and district staff at ACSD are able to utilize the deep…

PRiFi Networking for Tracking-Resistant Mobile Computing

DTIC Science & Technology

2017-11-01

PRiFi NETWORKING FOR TRACKING-RESISTANT MOBILE COMPUTING YALE UNIVERSITY NOVEMBER 2017 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE...From - To) FEB 2016 – MAY 2017 4. TITLE AND SUBTITLE PRiFi NETWORKING FOR TRACKING-RESISTANT MOBILE COMPUTING 5a. CONTRACT NUMBER FA8750-16-2-0034...3 Figure 2: What We Have: A Cloud of Secret Mass Surveillance Processes .................................. 6 Figure 3: What

Dynamic electronic institutions in agent oriented cloud robotic systems.

PubMed

Nagrath, Vineet; Morel, Olivier; Malik, Aamir; Saad, Naufal; Meriaudeau, Fabrice

2015-01-01

The dot-com bubble bursted in the year 2000 followed by a swift movement towards resource virtualization and cloud computing business model. Cloud computing emerged not as new form of computing or network technology but a mere remoulding of existing technologies to suit a new business model. Cloud robotics is understood as adaptation of cloud computing ideas for robotic applications. Current efforts in cloud robotics stress upon developing robots that utilize computing and service infrastructure of the cloud, without debating on the underlying business model. HTM5 is an OMG's MDA based Meta-model for agent oriented development of cloud robotic systems. The trade-view of HTM5 promotes peer-to-peer trade amongst software agents. HTM5 agents represent various cloud entities and implement their business logic on cloud interactions. Trade in a peer-to-peer cloud robotic system is based on relationships and contracts amongst several agent subsets. Electronic Institutions are associations of heterogeneous intelligent agents which interact with each other following predefined norms. In Dynamic Electronic Institutions, the process of formation, reformation and dissolution of institutions is automated leading to run time adaptations in groups of agents. DEIs in agent oriented cloud robotic ecosystems bring order and group intellect. This article presents DEI implementations through HTM5 methodology.

Reprocessing Multiyear GPS Data from Continuously Operating Reference Stations on Cloud Computing Platform

NASA Astrophysics Data System (ADS)

Yoon, S.

2016-12-01

To define geodetic reference frame using GPS data collected by Continuously Operating Reference Stations (CORS) network, historical GPS data needs to be reprocessed regularly. Reprocessing GPS data collected by upto 2000 CORS sites for the last two decades requires a lot of computational resource. At National Geodetic Survey (NGS), there has been one completed reprocessing in 2011, and currently, the second reprocessing is undergoing. For the first reprocessing effort, in-house computing resource was utilized. In the current second reprocessing effort, outsourced cloud computing platform is being utilized. In this presentation, the outline of data processing strategy at NGS is described as well as the effort to parallelize the data processing procedure in order to maximize the benefit of the cloud computing. The time and cost savings realized by utilizing cloud computing approach will also be discussed.

Arctic Boreal Vulnerability Experiment (ABoVE) Science Cloud

NASA Astrophysics Data System (ADS)

Duffy, D.; Schnase, J. L.; McInerney, M.; Webster, W. P.; Sinno, S.; Thompson, J. H.; Griffith, P. C.; Hoy, E.; Carroll, M.

2014-12-01

The effects of climate change are being revealed at alarming rates in the Arctic and Boreal regions of the planet. NASA's Terrestrial Ecology Program has launched a major field campaign to study these effects over the next 5 to 8 years. The Arctic Boreal Vulnerability Experiment (ABoVE) will challenge scientists to take measurements in the field, study remote observations, and even run models to better understand the impacts of a rapidly changing climate for areas of Alaska and western Canada. The NASA Center for Climate Simulation (NCCS) at the Goddard Space Flight Center (GSFC) has partnered with the Terrestrial Ecology Program to create a science cloud designed for this field campaign - the ABoVE Science Cloud. The cloud combines traditional high performance computing with emerging technologies to create an environment specifically designed for large-scale climate analytics. The ABoVE Science Cloud utilizes (1) virtualized high-speed InfiniBand networks, (2) a combination of high-performance file systems and object storage, and (3) virtual system environments tailored for data intensive, science applications. At the center of the architecture is a large object storage environment, much like a traditional high-performance file system, that supports data proximal processing using technologies like MapReduce on a Hadoop Distributed File System (HDFS). Surrounding the storage is a cloud of high performance compute resources with many processing cores and large memory coupled to the storage through an InfiniBand network. Virtual systems can be tailored to a specific scientist and provisioned on the compute resources with extremely high-speed network connectivity to the storage and to other virtual systems. In this talk, we will present the architectural components of the science cloud and examples of how it is being used to meet the needs of the ABoVE campaign. In our experience, the science cloud approach significantly lowers the barriers and risks to organizations that require high performance computing solutions and provides the NCCS with the agility required to meet our customers' rapidly increasing and evolving requirements.

A Simple Technique for Securing Data at Rest Stored in a Computing Cloud

NASA Astrophysics Data System (ADS)

Sedayao, Jeff; Su, Steven; Ma, Xiaohao; Jiang, Minghao; Miao, Kai

"Cloud Computing" offers many potential benefits, including cost savings, the ability to deploy applications and services quickly, and the ease of scaling those application and services once they are deployed. A key barrier for enterprise adoption is the confidentiality of data stored on Cloud Computing Infrastructure. Our simple technique implemented with Open Source software solves this problem by using public key encryption to render stored data at rest unreadable by unauthorized personnel, including system administrators of the cloud computing service on which the data is stored. We validate our approach on a network measurement system implemented on PlanetLab. We then use it on a service where confidentiality is critical - a scanning application that validates external firewall implementations.

Evaluating the Efficacy of the Cloud for Cluster Computation

NASA Technical Reports Server (NTRS)

Knight, David; Shams, Khawaja; Chang, George; Soderstrom, Tom

2012-01-01

Computing requirements vary by industry, and it follows that NASA and other research organizations have computing demands that fall outside the mainstream. While cloud computing made rapid inroads for tasks such as powering web applications, performance issues on highly distributed tasks hindered early adoption for scientific computation. One venture to address this problem is Nebula, NASA's homegrown cloud project tasked with delivering science-quality cloud computing resources. However, another industry development is Amazon's high-performance computing (HPC) instances on Elastic Cloud Compute (EC2) that promises improved performance for cluster computation. This paper presents results from a series of benchmarks run on Amazon EC2 and discusses the efficacy of current commercial cloud technology for running scientific applications across a cluster. In particular, a 240-core cluster of cloud instances achieved 2 TFLOPS on High-Performance Linpack (HPL) at 70% of theoretical computational performance. The cluster's local network also demonstrated sub-100 ?s inter-process latency with sustained inter-node throughput in excess of 8 Gbps. Beyond HPL, a real-world Hadoop image processing task from NASA's Lunar Mapping and Modeling Project (LMMP) was run on a 29 instance cluster to process lunar and Martian surface images with sizes on the order of tens of gigapixels. These results demonstrate that while not a rival of dedicated supercomputing clusters, commercial cloud technology is now a feasible option for moderately demanding scientific workloads.

Cloud Computing Services for Seismic Networks

NASA Astrophysics Data System (ADS)

Olson, Michael

This thesis describes a compositional framework for developing situation awareness applications: applications that provide ongoing information about a user's changing environment. The thesis describes how the framework is used to develop a situation awareness application for earthquakes. The applications are implemented as Cloud computing services connected to sensors and actuators. The architecture and design of the Cloud services are described and measurements of performance metrics are provided. The thesis includes results of experiments on earthquake monitoring conducted over a year. The applications developed by the framework are (1) the CSN---the Community Seismic Network---which uses relatively low-cost sensors deployed by members of the community, and (2) SAF---the Situation Awareness Framework---which integrates data from multiple sources, including the CSN, CISN---the California Integrated Seismic Network, a network consisting of high-quality seismometers deployed carefully by professionals in the CISN organization and spread across Southern California---and prototypes of multi-sensor platforms that include carbon monoxide, methane, dust and radiation sensors.

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

Combining Cloud Networks and Course Management Systems for Enhanced Analysis in Teaching Laboratories

ERIC Educational Resources Information Center

Abrams, Neal M.

2012-01-01

A cloud network system is combined with standard computing applications and a course management system to provide a robust method for sharing data among students. This system provides a unique method to improve data analysis by easily increasing the amount of sampled data available for analysis. The data can be shared within one course as well as…

Cross layer optimization for cloud-based radio over optical fiber networks

NASA Astrophysics Data System (ADS)

Shao, Sujie; Guo, Shaoyong; Qiu, Xuesong; Yang, Hui; Meng, Luoming

2016-07-01

To adapt the 5G communication, the cloud radio access network is a paradigm introduced by operators which aggregates all base stations computational resources into a cloud BBU pool. The interaction between RRH and BBU or resource schedule among BBUs in cloud have become more frequent and complex with the development of system scale and user requirement. It can promote the networking demand among RRHs and BBUs, and force to form elastic optical fiber switching and networking. In such network, multiple stratum resources of radio, optical and BBU processing unit have interweaved with each other. In this paper, we propose a novel multiple stratum optimization (MSO) architecture for cloud-based radio over optical fiber networks (C-RoFN) with software defined networking. Additionally, a global evaluation strategy (GES) is introduced in the proposed architecture. MSO can enhance the responsiveness to end-to-end user demands and globally optimize radio frequency, optical spectrum and BBU processing resources effectively to maximize radio coverage. The feasibility and efficiency of the proposed architecture with GES strategy are experimentally verified on OpenFlow-enabled testbed in terms of resource occupation and path provisioning latency.

A cloud-based data network approach for translational cancer research.

PubMed

Xing, Wei; Tsoumakos, Dimitrios; Ghanem, Moustafa

2015-01-01

We develop a new model and associated technology for constructing and managing self-organizing data to support translational cancer research studies. We employ a semantic content network approach to address the challenges of managing cancer research data. Such data is heterogeneous, large, decentralized, growing and continually being updated. Moreover, the data originates from different information sources that may be partially overlapping, creating redundancies as well as contradictions and inconsistencies. Building on the advantages of elasticity of cloud computing, we deploy the cancer data networks on top of the CELAR Cloud platform to enable more effective processing and analysis of Big cancer data.

School on Cloud: Towards a Paradigm Shift

ERIC Educational Resources Information Center

Koutsopoulos, Kostis C.; Kotsanis, Yannis C.

2014-01-01

This paper presents the basic concept of the EU Network School on Cloud: Namely, that present conditions require a new teaching and learning paradigm based on the integrated dimension of education, when considering the use of cloud computing. In other words, it is suggested that there is a need for an integrated approach which is simultaneously…

Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems

PubMed Central

Wu, Jun; Su, Zhou; Li, Jianhua

2017-01-01

Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on “friend” relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems. PMID:28758943

Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems.

PubMed

Wu, Jun; Su, Zhou; Wang, Shen; Li, Jianhua

2017-07-30

Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on "friend" relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems.

Application of microarray analysis on computer cluster and cloud platforms.

PubMed

Bernau, C; Boulesteix, A-L; Knaus, J

2013-01-01

Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

Snow Leopard Cloud: A Multi-national Education Training and Experimentation Cloud and Its Security Challenges

NASA Astrophysics Data System (ADS)

Cayirci, Erdal; Rong, Chunming; Huiskamp, Wim; Verkoelen, Cor

Military/civilian education training and experimentation networks (ETEN) are an important application area for the cloud computing concept. However, major security challenges have to be overcome to realize an ETEN. These challenges can be categorized as security challenges typical to any cloud and multi-level security challenges specific to an ETEN environment. The cloud approach for ETEN is introduced and its security challenges are explained in this paper.

Green Cloud on the Horizon

NASA Astrophysics Data System (ADS)

Ali, Mufajjul

This paper proposes a Green Cloud model for mobile Cloud computing. The proposed model leverage on the current trend of IaaS (Infrastructure as a Service), PaaS (Platform as a Service) and SaaS (Software as a Service), and look at new paradigm called "Network as a Service" (NaaS). The Green Cloud model proposes various Telco's revenue generating streams and services with the CaaS (Cloud as a Service) for the near future.

Crowd-Funding: A New Resource Cooperation Mode for Mobile Cloud Computing.

PubMed

Zhang, Nan; Yang, Xiaolong; Zhang, Min; Sun, Yan

2016-01-01

Mobile cloud computing, which integrates the cloud computing techniques into the mobile environment, is regarded as one of the enabler technologies for 5G mobile wireless networks. There are many sporadic spare resources distributed within various devices in the networks, which can be used to support mobile cloud applications. However, these devices, with only a few spare resources, cannot support some resource-intensive mobile applications alone. If some of them cooperate with each other and share their resources, then they can support many applications. In this paper, we propose a resource cooperative provision mode referred to as "Crowd-funding", which is designed to aggregate the distributed devices together as the resource provider of mobile applications. Moreover, to facilitate high-efficiency resource management via dynamic resource allocation, different resource providers should be selected to form a stable resource coalition for different requirements. Thus, considering different requirements, we propose two different resource aggregation models for coalition formation. Finally, we may allocate the revenues based on their attributions according to the concept of the "Shapley value" to enable a more impartial revenue share among the cooperators. It is shown that a dynamic and flexible resource-management method can be developed based on the proposed Crowd-funding model, relying on the spare resources in the network.

Crowd-Funding: A New Resource Cooperation Mode for Mobile Cloud Computing

PubMed Central

Zhang, Min; Sun, Yan

2016-01-01

Mobile cloud computing, which integrates the cloud computing techniques into the mobile environment, is regarded as one of the enabler technologies for 5G mobile wireless networks. There are many sporadic spare resources distributed within various devices in the networks, which can be used to support mobile cloud applications. However, these devices, with only a few spare resources, cannot support some resource-intensive mobile applications alone. If some of them cooperate with each other and share their resources, then they can support many applications. In this paper, we propose a resource cooperative provision mode referred to as "Crowd-funding", which is designed to aggregate the distributed devices together as the resource provider of mobile applications. Moreover, to facilitate high-efficiency resource management via dynamic resource allocation, different resource providers should be selected to form a stable resource coalition for different requirements. Thus, considering different requirements, we propose two different resource aggregation models for coalition formation. Finally, we may allocate the revenues based on their attributions according to the concept of the "Shapley value" to enable a more impartial revenue share among the cooperators. It is shown that a dynamic and flexible resource-management method can be developed based on the proposed Crowd-funding model, relying on the spare resources in the network. PMID:28030553

A Science Cloud: OneSpaceNet

NASA Astrophysics Data System (ADS)

Morikawa, Y.; Murata, K. T.; Watari, S.; Kato, H.; Yamamoto, K.; Inoue, S.; Tsubouchi, K.; Fukazawa, K.; Kimura, E.; Tatebe, O.; Shimojo, S.

2010-12-01

Main methodologies of Solar-Terrestrial Physics (STP) so far are theoretical, experimental and observational, and computer simulation approaches. Recently "informatics" is expected as a new (fourth) approach to the STP studies. Informatics is a methodology to analyze large-scale data (observation data and computer simulation data) to obtain new findings using a variety of data processing techniques. At NICT (National Institute of Information and Communications Technology, Japan) we are now developing a new research environment named "OneSpaceNet". The OneSpaceNet is a cloud-computing environment specialized for science works, which connects many researchers with high-speed network (JGN: Japan Gigabit Network). The JGN is a wide-area back-born network operated by NICT; it provides 10G network and many access points (AP) over Japan. The OneSpaceNet also provides with rich computer resources for research studies, such as super-computers, large-scale data storage area, licensed applications, visualization devices (like tiled display wall: TDW), database/DBMS, cluster computers (4-8 nodes) for data processing and communication devices. What is amazing in use of the science cloud is that a user simply prepares a terminal (low-cost PC). Once connecting the PC to JGN2plus, the user can make full use of the rich resources of the science cloud. Using communication devices, such as video-conference system, streaming and reflector servers, and media-players, the users on the OneSpaceNet can make research communications as if they belong to a same (one) laboratory: they are members of a virtual laboratory. The specification of the computer resources on the OneSpaceNet is as follows: The size of data storage we have developed so far is almost 1PB. The number of the data files managed on the cloud storage is getting larger and now more than 40,000,000. What is notable is that the disks forming the large-scale storage are distributed to 5 data centers over Japan (but the storage system performs as one disk). There are three supercomputers allocated on the cloud, one from Tokyo, one from Osaka and the other from Nagoya. One's simulation job data on any supercomputers are saved on the cloud data storage (same directory); it is a kind of virtual computing environment. The tiled display wall has 36 panels acting as one display; the pixel (resolution) size of it is as large as 18000x4300. This size is enough to preview or analyze the large-scale computer simulation data. It also allows us to take a look of multiple (e.g., 100 pictures) on one screen together with many researchers. In our talk we also present a brief report of the initial results using the OneSpaceNet for Global MHD simulations as an example of successful use of our science cloud; (i) Ultra-high time resolution visualization of Global MHD simulations on the large-scale storage and parallel processing system on the cloud, (ii) Database of real-time Global MHD simulation and statistic analyses of the data, and (iii) 3D Web service of Global MHD simulations.

Environments for online maritime simulators with cloud computing capabilities

NASA Astrophysics Data System (ADS)

Raicu, Gabriel; Raicu, Alexandra

2016-12-01

This paper presents the cloud computing environments, network principles and methods for graphical development in realistic naval simulation, naval robotics and virtual interactions. The aim of this approach is to achieve a good simulation quality in large networked environments using open source solutions designed for educational purposes. Realistic rendering of maritime environments requires near real-time frameworks with enhanced computing capabilities during distance interactions. E-Navigation concepts coupled with the last achievements in virtual and augmented reality will enhance the overall experience leading to new developments and innovations. We have to deal with a multiprocessing situation using advanced technologies and distributed applications using remote ship scenario and automation of ship operations.

Research on the digital education resources of sharing pattern in independent colleges based on cloud computing environment

NASA Astrophysics Data System (ADS)

Xiong, Ting; He, Zhiwen

2017-06-01

Cloud computing was first proposed by Google Company in the United States, which was based on the Internet center, providing a standard and open network sharing service approach. With the rapid development of the higher education in China, the educational resources provided by colleges and universities had greatly gap in the actual needs of teaching resources. therefore, Cloud computing of using the Internet technology to provide shared methods liked the timely rain, which had become an important means of the Digital Education on sharing applications in the current higher education. Based on Cloud computing environment, the paper analyzed the existing problems about the sharing of digital educational resources in Jiangxi Province Independent Colleges. According to the sharing characteristics of mass storage, efficient operation and low input about Cloud computing, the author explored and studied the design of the sharing model about the digital educational resources of higher education in Independent College. Finally, the design of the shared model was put into the practical 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 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.

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

Lost in Cloud

NASA Technical Reports Server (NTRS)

Maluf, David A.; Shetye, Sandeep D.; Chilukuri, Sri; Sturken, Ian

2012-01-01

Cloud computing can reduce cost significantly because businesses can share computing resources. In recent years Small and Medium Businesses (SMB) have used Cloud effectively for cost saving and for sharing IT expenses. With the success of SMBs, many perceive that the larger enterprises ought to move into Cloud environment as well. Government agency s stove-piped environments are being considered as candidates for potential use of Cloud either as an enterprise entity or pockets of small communities. Cloud Computing is the delivery of computing as a service rather than as a product, whereby shared resources, software, and information are provided to computers and other devices as a utility over a network. Underneath the offered services, there exists a modern infrastructure cost of which is often spread across its services or its investors. As NASA is considered as an Enterprise class organization, like other enterprises, a shift has been occurring in perceiving its IT services as candidates for Cloud services. This paper discusses market trends in cloud computing from an enterprise angle and then addresses the topic of Cloud Computing for NASA in two possible forms. First, in the form of a public Cloud to support it as an enterprise, as well as to share it with the commercial and public at large. Second, as a private Cloud wherein the infrastructure is operated solely for NASA, whether managed internally or by a third-party and hosted internally or externally. The paper addresses the strengths and weaknesses of both paradigms of public and private Clouds, in both internally and externally operated settings. The content of the paper is from a NASA perspective but is applicable to any large enterprise with thousands of employees and contractors.

Survey on Security Issues in Cloud Computing and Associated Mitigation Techniques

NASA Astrophysics Data System (ADS)

Bhadauria, Rohit; Sanyal, Sugata

2012-06-01

Cloud Computing holds the potential to eliminate the requirements for setting up of high-cost computing infrastructure for IT-based solutions and services that the industry uses. It promises to provide a flexible IT architecture, accessible through internet for lightweight portable devices. This would allow multi-fold increase in the capacity or capabilities of the existing and new software. In a cloud computing environment, the entire data reside over a set of networked resources, enabling the data to be accessed through virtual machines. Since these data-centers may lie in any corner of the world beyond the reach and control of users, there are multifarious security and privacy challenges that need to be understood and taken care of. Also, one can never deny the possibility of a server breakdown that has been witnessed, rather quite often in the recent times. There are various issues that need to be dealt with respect to security and privacy in a cloud computing scenario. This extensive survey paper aims to elaborate and analyze the numerous unresolved issues threatening the cloud computing adoption and diffusion affecting the various stake-holders linked to it.

Analysis of multiuser mixed RF/FSO relay networks for performance improvements in Cloud Computing-Based Radio Access Networks (CC-RANs)

NASA Astrophysics Data System (ADS)

Alimi, Isiaka A.; Monteiro, Paulo P.; Teixeira, António L.

2017-11-01

The key paths toward the fifth generation (5G) network requirements are towards centralized processing and small-cell densification systems that are implemented on the cloud computing-based radio access networks (CC-RANs). The increasing recognitions of the CC-RANs can be attributed to their valuable features regarding system performance optimization and cost-effectiveness. Nevertheless, realization of the stringent requirements of the fronthaul that connects the network elements is highly demanding. In this paper, considering the small-cell network architectures, we present multiuser mixed radio-frequency/free-space optical (RF/FSO) relay networks as feasible technologies for the alleviation of the stringent requirements in the CC-RANs. In this study, we use the end-to-end (e2e) outage probability, average symbol error probability (ASEP), and ergodic channel capacity as the performance metrics in our analysis. Simulation results show the suitability of deployment of mixed RF/FSO schemes in the real-life scenarios.

Experimental demonstration of multi-dimensional resources integration for service provisioning in cloud radio over fiber network

NASA Astrophysics Data System (ADS)

Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young

2016-07-01

Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes.

Experimental demonstration of multi-dimensional resources integration for service provisioning in cloud radio over fiber network.

PubMed

Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young

2016-07-28

Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes.

Performance evaluation of multi-stratum resources optimization with network functions virtualization for cloud-based radio over optical fiber networks.

PubMed

Yang, Hui; He, Yongqi; Zhang, Jie; Ji, Yuefeng; Bai, Wei; Lee, Young

2016-04-18

Cloud radio access network (C-RAN) has become a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing using cloud BBUs. In our previous work, we implemented cross stratum optimization of optical network and application stratums resources that allows to accommodate the services in optical networks. In view of this, this study extends to consider the multiple dimensional resources optimization of radio, optical and BBU processing in 5G age. We propose a novel multi-stratum resources optimization (MSRO) architecture with network functions virtualization for cloud-based radio over optical fiber networks (C-RoFN) using software defined control. A global evaluation scheme (GES) for MSRO in C-RoFN is introduced based on the proposed architecture. The MSRO can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical and BBU resources effectively to maximize radio coverage. The efficiency and feasibility of the proposed architecture are experimentally demonstrated on OpenFlow-based enhanced SDN testbed. The performance of GES under heavy traffic load scenario is also quantitatively evaluated based on MSRO architecture in terms of resource occupation rate and path provisioning latency, compared with other provisioning scheme.

Experimental demonstration of multi-dimensional resources integration for service provisioning in cloud radio over fiber network

PubMed Central

Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young

2016-01-01

Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes. PMID:27465296

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.

Solar-Terrestrial and Astronomical Research Network (STAR-Network) - A Meaningful Practice of New Cyberinfrastructure on Space Science

NASA Astrophysics Data System (ADS)

Hu, X.; Zou, Z.

2017-12-01

For the next decades, comprehensive big data application environment is the dominant direction of cyberinfrastructure development on space science. To make the concept of such BIG cyberinfrastructure (e.g. Digital Space) a reality, these aspects of capability should be focused on and integrated, which includes science data system, digital space engine, big data application (tools and models) and the IT infrastructure. In the past few years, CAS Chinese Space Science Data Center (CSSDC) has made a helpful attempt in this direction. A cloud-enabled virtual research platform on space science, called Solar-Terrestrial and Astronomical Research Network (STAR-Network), has been developed to serve the full lifecycle of space science missions and research activities. It integrated a wide range of disciplinary and interdisciplinary resources, to provide science-problem-oriented data retrieval and query service, collaborative mission demonstration service, mission operation supporting service, space weather computing and Analysis service and other self-help service. This platform is supported by persistent infrastructure, including cloud storage, cloud computing, supercomputing and so on. Different variety of resource are interconnected: the science data can be displayed on the browser by visualization tools, the data analysis tools and physical models can be drived by the applicable science data, the computing results can be saved on the cloud, for example. So far, STAR-Network has served a series of space science mission in China, involving Strategic Pioneer Program on Space Science (this program has invested some space science satellite as DAMPE, HXMT, QUESS, and more satellite will be launched around 2020) and Meridian Space Weather Monitor Project. Scientists have obtained some new findings by using the science data from these missions with STAR-Network's contribution. We are confident that STAR-Network is an exciting practice of new cyberinfrastructure architecture on space science.

JINR cloud infrastructure evolution

NASA Astrophysics Data System (ADS)

Baranov, A. V.; Balashov, N. A.; Kutovskiy, N. A.; Semenov, R. N.

2016-09-01

To fulfil JINR commitments in different national and international projects related to the use of modern information technologies such as cloud and grid computing as well as to provide a modern tool for JINR users for their scientific research a cloud infrastructure was deployed at Laboratory of Information Technologies of Joint Institute for Nuclear Research. OpenNebula software was chosen as a cloud platform. Initially it was set up in simple configuration with single front-end host and a few cloud nodes. Some custom development was done to tune JINR cloud installation to fit local needs: web form in the cloud web-interface for resources request, a menu item with cloud utilization statistics, user authentication via Kerberos, custom driver for OpenVZ containers. Because of high demand in that cloud service and its resources over-utilization it was re-designed to cover increasing users' needs in capacity, availability and reliability. Recently a new cloud instance has been deployed in high-availability configuration with distributed network file system and additional computing power.

Usage of Thin-Client/Server Architecture in Computer Aided Education

ERIC Educational Resources Information Center

Cimen, Caghan; Kavurucu, Yusuf; Aydin, Halit

2014-01-01

With the advances of technology, thin-client/server architecture has become popular in multi-user/single network environments. Thin-client is a user terminal in which the user can login to a domain and run programs by connecting to a remote server. Recent developments in network and hardware technologies (cloud computing, virtualization, etc.)…

Interoperating Cloud-based Virtual Farms

NASA Astrophysics Data System (ADS)

Bagnasco, S.; Colamaria, F.; Colella, D.; Casula, E.; Elia, D.; Franco, A.; Lusso, S.; Luparello, G.; Masera, M.; Miniello, G.; Mura, D.; Piano, S.; Vallero, S.; Venaruzzo, M.; Vino, G.

2015-12-01

The present work aims at optimizing the use of computing resources available at the grid Italian Tier-2 sites of the ALICE experiment at CERN LHC by making them accessible to interactive distributed analysis, thanks to modern solutions based on cloud computing. The scalability and elasticity of the computing resources via dynamic (“on-demand”) provisioning is essentially limited by the size of the computing site, reaching the theoretical optimum only in the asymptotic case of infinite resources. The main challenge of the project is to overcome this limitation by federating different sites through a distributed cloud facility. Storage capacities of the participating sites are seen as a single federated storage area, preventing the need of mirroring data across them: high data access efficiency is guaranteed by location-aware analysis software and storage interfaces, in a transparent way from an end-user perspective. Moreover, the interactive analysis on the federated cloud reduces the execution time with respect to grid batch jobs. The tests of the investigated solutions for both cloud computing and distributed storage on wide area network will be presented.

The Metadata Cloud: The Last Piece of a Distributed Data System Model

NASA Astrophysics Data System (ADS)

King, T. A.; Cecconi, B.; Hughes, J. S.; Walker, R. J.; Roberts, D.; Thieman, J. R.; Joy, S. P.; Mafi, J. N.; Gangloff, M.

2012-12-01

Distributed data systems have existed ever since systems were networked together. Over the years the model for distributed data systems have evolved from basic file transfer to client-server to multi-tiered to grid and finally to cloud based systems. Initially metadata was tightly coupled to the data either by embedding the metadata in the same file containing the data or by co-locating the metadata in commonly named files. As the sources of data multiplied, data volumes have increased and services have specialized to improve efficiency; a cloud system model has emerged. In a cloud system computing and storage are provided as services with accessibility emphasized over physical location. Computation and data clouds are common implementations. Effectively using the data and computation capabilities requires metadata. When metadata is stored separately from the data; a metadata cloud is formed. With a metadata cloud information and knowledge about data resources can migrate efficiently from system to system, enabling services and allowing the data to remain efficiently stored until used. This is especially important with "Big Data" where movement of the data is limited by bandwidth. We examine how the metadata cloud completes a general distributed data system model, how standards play a role and relate this to the existing types of cloud computing. We also look at the major science data systems in existence and compare each to the generalized cloud system model.

The thinking of Cloud computing in the digital construction of the oil companies

NASA Astrophysics Data System (ADS)

CaoLei, Qizhilin; Dengsheng, Lei

In order to speed up digital construction of the oil companies and enhance productivity and decision-support capabilities while avoiding the disadvantages from the waste of the original process of building digital and duplication of development and input. This paper presents a cloud-based models for the build in the digital construction of the oil companies that National oil companies though the private network will join the cloud data of the oil companies and service center equipment integrated into a whole cloud system, then according to the needs of various departments to prepare their own virtual service center, which can provide a strong service industry and computing power for the Oil companies.

Volunteered Cloud Computing for Disaster Management

NASA Astrophysics Data System (ADS)

Evans, J. D.; Hao, W.; Chettri, S. R.

2014-12-01

Disaster management relies increasingly on interpreting earth observations and running numerical models; which require significant computing capacity - usually on short notice and at irregular intervals. Peak computing demand during event detection, hazard assessment, or incident response may exceed agency budgets; however some of it can be met through volunteered computing, which distributes subtasks to participating computers via the Internet. This approach has enabled large projects in mathematics, basic science, and climate research to harness the slack computing capacity of thousands of desktop computers. This capacity is likely to diminish as desktops give way to battery-powered mobile devices (laptops, smartphones, tablets) in the consumer market; but as cloud computing becomes commonplace, it may offer significant slack capacity -- if its users are given an easy, trustworthy mechanism for participating. Such a "volunteered cloud computing" mechanism would also offer several advantages over traditional volunteered computing: tasks distributed within a cloud have fewer bandwidth limitations; granular billing mechanisms allow small slices of "interstitial" computing at no marginal cost; and virtual storage volumes allow in-depth, reversible machine reconfiguration. Volunteered cloud computing is especially suitable for "embarrassingly parallel" tasks, including ones requiring large data volumes: examples in disaster management include near-real-time image interpretation, pattern / trend detection, or large model ensembles. In the context of a major disaster, we estimate that cloud users (if suitably informed) might volunteer hundreds to thousands of CPU cores across a large provider such as Amazon Web Services. To explore this potential, we are building a volunteered cloud computing platform and targeting it to a disaster management context. Using a lightweight, fault-tolerant network protocol, this platform helps cloud users join parallel computing projects; automates reconfiguration of their virtual machines; ensures accountability for donated computing; and optimizes the use of "interstitial" computing. Initial applications include fire detection from multispectral satellite imagery and flood risk mapping through hydrological simulations.

Context dependent off loading for cloudlet in mobile ad-hoc network

NASA Astrophysics Data System (ADS)

Bhatt, N.; Nadesh, R. K.; ArivuSelvan, K.

2017-11-01

Cloud Computing in Mobile Ad-hoc network is emerging part of research consideration as the demand and competency of mobile devices increased in last few years. To follow out operation within the remote cloud builds the postponement and influences the administration standard. To keep away from this trouble cloudlet is presented. Cloudlet gives identical support of the devices as cloud at low inactivity however at high transfer speed. Be that as it may, choice of a cloudlet for offloading calculation with flat energy is a noteworthy test if multiple cloud let is accessible adjacent. Here I proposed energy and bandwidth (Traffic overload for communication with cloud) aware cloudlet selection strategy based on the context dependency of the device location. It works on the basis of mobile device location and bandwidth availability of cloudlet. The cloudlet offloading and selection process using given solution is simulated in Cloud ~ Simulator.

Research on cloud-based remote measurement and analysis system

NASA Astrophysics Data System (ADS)

Gao, Zhiqiang; He, Lingsong; Su, Wei; Wang, Can; Zhang, Changfan

2015-02-01

The promising potential of cloud computing and its convergence with technologies such as cloud storage, cloud push, mobile computing allows for creation and delivery of newer type of cloud service. Combined with the thought of cloud computing, this paper presents a cloud-based remote measurement and analysis system. This system mainly consists of three parts: signal acquisition client, web server deployed on the cloud service, and remote client. This system is a special website developed using asp.net and Flex RIA technology, which solves the selective contradiction between two monitoring modes, B/S and C/S. This platform supplies customer condition monitoring and data analysis service by Internet, which was deployed on the cloud server. Signal acquisition device is responsible for data (sensor data, audio, video, etc.) collection and pushes the monitoring data to the cloud storage database regularly. Data acquisition equipment in this system is only conditioned with the function of data collection and network function such as smartphone and smart sensor. This system's scale can adjust dynamically according to the amount of applications and users, so it won't cause waste of resources. As a representative case study, we developed a prototype system based on Ali cloud service using the rotor test rig as the research object. Experimental results demonstrate that the proposed system architecture is feasible.

Planning and management of cloud computing networks

NASA Astrophysics Data System (ADS)

Larumbe, Federico

The evolution of the Internet has a great impact on a big part of the population. People use it to communicate, query information, receive news, work, and as entertainment. Its extraordinary usefulness as a communication media made the number of applications and technological resources explode. However, that network expansion comes at the cost of an important power consumption. If the power consumption of telecommunication networks and data centers is considered as the power consumption of a country, it would rank at the 5 th place in the world. Furthermore, the number of servers in the world is expected to grow by a factor of 10 between 2013 and 2020. This context motivates us to study techniques and methods to allocate cloud computing resources in an optimal way with respect to cost, quality of service (QoS), power consumption, and environmental impact. The results we obtained from our test cases show that besides minimizing capital expenditures (CAPEX) and operational expenditures (OPEX), the response time can be reduced up to 6 times, power consumption by 30%, and CO2 emissions by a factor of 60. Cloud computing provides dynamic access to IT resources as a service. In this paradigm, programs are executed in servers connected to the Internet that users access from their computers and mobile devices. The first advantage of this architecture is to reduce the time of application deployment and interoperability, because a new user only needs a web browser and does not need to install software on local computers with specific operating systems. Second, applications and information are available from everywhere and with any device with an Internet access. Also, servers and IT resources can be dynamically allocated depending on the number of users and workload, a feature called elasticity. This thesis studies the resource management of cloud computing networks and is divided in three main stages. We start by analyzing the planning of cloud computing networks to get a comprehensive vision. The first question to be solved is what are the optimal data center locations. We found that the location of each data center has a big impact on cost, QoS, power consumption, and greenhouse gas emissions. An optimization problem with a multi-criteria objective function is proposed to decide jointly the optimal location of data centers and software components, link capacities, and information routing. Once the network planning has been analyzed, the problem of dynamic resource provisioning in real time is addressed. In this context, virtualization is a key technique in cloud computing because each server can be shared by multiple Virtual Machines (VMs) and the total power consumption can be reduced. In the same line of location problems, we propose a Green Cloud Broker that optimizes VM placement across multiple data centers. In fact, when multiple data centers are considered, response time can be reduced by placing VMs close to users, cost can be minimized, power consumption can be optimized by using energy efficient data centers, and CO2 emissions can be decreased by choosing data centers provided with renewable energy sources. The third stage of the analysis is the short-term management of a cloud data center. In particular, a method is proposed to assign VMs to servers by considering communication traffic among VMs. Cloud data centers receive new applications over time and these applications need on-demand resource provisioning. Each application is composed of multiple types of VMs that interact among themselves. A program called scheduler must place each new VM in a server and that impacts the QoS and power consumption. Our method places VMs that communicate among themselves in servers that are close to each other in the network topology, thus reducing communication delay and increasing the throughput available among VMs. Furthermore, the power consumption of each type of server is considered and the most efficient ones are chosen to place the VMs. The number of VMs of each application can be dynamically changed to match the workload and servers not needed in a particular period can be suspended to save energy. The methodology developed is based on Mixed Integer Programming (MIP) models to formalize the problems and use state of the art optimization solvers. Then, heuristics are developed to solve cases with more than 1,000 potential data center locations for the planning problem, 1,000 nodes for the cloud broker, and 128,000 servers for the VM placement problem. Solutions with very short optimality gaps, between 0% and 1.95%, are obtained, and execution time in the order of minutes for the planning problem and less than a second for real time cases. We consider that this thesis on resource provisioning of cloud computing networks includes important contributions on this research area, and innovative commercial applications based on the proposed methods have promising future.

Looking at Clouds from All Sides Now

ERIC Educational Resources Information Center

Katz, Richard N.

2010-01-01

On February 9 and 10, 2010, fifty leaders from colleges, universities, corporations, professional associations, and state networks met in Tempe, Arizona, to discuss cloud computing and the impending shift in the mix of where infrastructure, applications, and services are sourced. This group identified a set of actions that colleges and…

A resource-sharing model based on a repeated game in fog computing.

PubMed

Sun, Yan; Zhang, Nan

2017-03-01

With the rapid development of cloud computing techniques, the number of users is undergoing exponential growth. It is difficult for traditional data centers to perform many tasks in real time because of the limited bandwidth of resources. The concept of fog computing is proposed to support traditional cloud computing and to provide cloud services. In fog computing, the resource pool is composed of sporadic distributed resources that are more flexible and movable than a traditional data center. In this paper, we propose a fog computing structure and present a crowd-funding algorithm to integrate spare resources in the network. Furthermore, to encourage more resource owners to share their resources with the resource pool and to supervise the resource supporters as they actively perform their tasks, we propose an incentive mechanism in our algorithm. Simulation results show that our proposed incentive mechanism can effectively reduce the SLA violation rate and accelerate the completion of tasks.

Exploring Infiniband Hardware Virtualization in OpenNebula towards Efficient High-Performance Computing

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

Pais Pitta de Lacerda Ruivo, Tiago; Bernabeu Altayo, Gerard; Garzoglio, Gabriele

2014-11-11

has been widely accepted that software virtualization has a big negative impact on high-performance computing (HPC) application performance. This work explores the potential use of Infiniband hardware virtualization in an OpenNebula cloud towards the efficient support of MPI-based workloads. We have implemented, deployed, and tested an Infiniband network on the FermiCloud private Infrastructure-as-a-Service (IaaS) cloud. To avoid software virtualization towards minimizing the virtualization overhead, we employed a technique called Single Root Input/Output Virtualization (SRIOV). Our solution spanned modifications to the Linux’s Hypervisor as well as the OpenNebula manager. We evaluated the performance of the hardware virtualization on up to 56more » virtual machines connected by up to 8 DDR Infiniband network links, with micro-benchmarks (latency and bandwidth) as well as w a MPI-intensive application (the HPL Linpack benchmark).« less

Comparing Networks from a Data Analysis Perspective

NASA Astrophysics Data System (ADS)

Li, Wei; Yang, Jing-Yu

To probe network characteristics, two predominant ways of network comparison are global property statistics and subgraph enumeration. However, they suffer from limited information and exhaustible computing. Here, we present an approach to compare networks from the perspective of data analysis. Initially, the approach projects each node of original network as a high-dimensional data point, and the network is seen as clouds of data points. Then the dispersion information of the principal component analysis (PCA) projection of the generated data clouds can be used to distinguish networks. We applied this node projection method to the yeast protein-protein interaction networks and the Internet Autonomous System networks, two types of networks with several similar higher properties. The method can efficiently distinguish one from the other. The identical result of different datasets from independent sources also indicated that the method is a robust and universal framework.

Demonstration of measurement-only blind quantum computing

NASA Astrophysics Data System (ADS)

Greganti, Chiara; Roehsner, Marie-Christine; Barz, Stefanie; Morimae, Tomoyuki; Walther, Philip

2016-01-01

Blind quantum computing allows for secure cloud networks of quasi-classical clients and a fully fledged quantum server. Recently, a new protocol has been proposed, which requires a client to perform only measurements. We demonstrate a proof-of-principle implementation of this measurement-only blind quantum computing, exploiting a photonic setup to generate four-qubit cluster states for computation and verification. Feasible technological requirements for the client and the device-independent blindness make this scheme very applicable for future secure quantum networks.

Retrieval of cloud properties from POLDER-3 data using the neural network approach

NASA Astrophysics Data System (ADS)

Di Noia, A.; Hasekamp, O. P.

2017-12-01

Satellite multi-angle spectroplarimetry is a useful technique for observing the microphysical properties of clouds and aerosols. Most of the algorithms for the retrieval of cloud and aerosol properties from satellite measurements require multiple calls to radiative transfer models, which make the retrieval computationally expensive. A traditional alternative to these schemes is represented by lookup-tables (LUTs), where the retrieval is performed by choosing, within a predefined database of combinations of clouds or aerosol properties, the combination that best fits the measurements. LUT retrievals are quicker than full-physics, iterative retrievals, but their accuracy is limited by the number of entries stored in the LUT. Another retrieval method capable of producing very quick retrievals without a big sacrifice in accuracy is the neural network method. Neural network methods are routinely applied to several types of satellite measurements, but their application to multi-angle spectropolarimetric data is still in its early stage, because of the difficulty of accounting for the angular variability of the measurements in the training process. We have recently developed a neural network scheme for the retrieval of cloud properties from POLDER-3 data. The neural network retrieval is trained using synthetic measurements performed for realistic combinations of cloud properties and measurement angles, and is able to process an entire orbit in about 20 seconds. Comparisons of the retrieved cloud properties with Moderate Resolution Imaging Spectroradiometer (MODIS) gridded products during one year show encouraging retrieval performance for cloud optical thickness and effective radius. A discussion of the setup of the neural network and of the validation results will be the main topic of our presentation.

Thundercloud: Domain specific information security training for the smart grid

NASA Astrophysics Data System (ADS)

Stites, Joseph

In this paper, we describe a cloud-based virtual smart grid test bed: ThunderCloud, which is intended to be used for domain-specific security training applicable to the smart grid environment. The test bed consists of virtual machines connected using a virtual internal network. ThunderCloud is remotely accessible, allowing students to undergo educational exercises online. We also describe a series of practical exercises that we have developed for providing the domain-specific training using ThunderCloud. The training exercises and attacks are designed to be realistic and to reflect known vulnerabilities and attacks reported in the smart grid environment. We were able to use ThunderCloud to offer practical domain-specific security training for smart grid environment to computer science students at little or no cost to the department and no risk to any real networks or systems.

Methods for Cloud Cover Estimation

NASA Technical Reports Server (NTRS)

Glackin, D. L.; Huning, J. R.; Smith, J. H.; Logan, T. L.

1984-01-01

Several methods for cloud cover estimation are described relevant to assessing the performance of a ground-based network of solar observatories. The methods rely on ground and satellite data sources and provide meteorological or climatological information. One means of acquiring long-term observations of solar oscillations is the establishment of a ground-based network of solar observatories. Criteria for station site selection are: gross cloudiness, accurate transparency information, and seeing. Alternative methods for computing this duty cycle are discussed. The cycle, or alternatively a time history of solar visibility from the network, can then be input to a model to determine the effect of duty cycle on derived solar seismology parameters. Cloudiness from space is studied to examine various means by which the duty cycle might be computed. Cloudiness, and to some extent transparency, can potentially be estimated from satellite data.

Applying a cloud computing approach to storage architectures for spacecraft

NASA Astrophysics Data System (ADS)

Baldor, Sue A.; Quiroz, Carlos; Wood, Paul

As sensor technologies, processor speeds, and memory densities increase, spacecraft command, control, processing, and data storage systems have grown in complexity to take advantage of these improvements and expand the possible missions of spacecraft. Spacecraft systems engineers are increasingly looking for novel ways to address this growth in complexity and mitigate associated risks. Looking to conventional computing, many solutions have been executed to solve both the problem of complexity and heterogeneity in systems. In particular, the cloud-based paradigm provides a solution for distributing applications and storage capabilities across multiple platforms. In this paper, we propose utilizing a cloud-like architecture to provide a scalable mechanism for providing mass storage in spacecraft networks that can be reused on multiple spacecraft systems. By presenting a consistent interface to applications and devices that request data to be stored, complex systems designed by multiple organizations may be more readily integrated. Behind the abstraction, the cloud storage capability would manage wear-leveling, power consumption, and other attributes related to the physical memory devices, critical components in any mass storage solution for spacecraft. Our approach employs SpaceWire networks and SpaceWire-capable devices, although the concept could easily be extended to non-heterogeneous networks consisting of multiple spacecraft and potentially the ground segment.

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

A convergent model for distributed processing of Big Sensor Data in urban engineering networks

NASA Astrophysics Data System (ADS)

Parygin, D. S.; Finogeev, A. G.; Kamaev, V. A.; Finogeev, A. A.; Gnedkova, E. P.; Tyukov, A. P.

2017-01-01

The problems of development and research of a convergent model of the grid, cloud, fog and mobile computing for analytical Big Sensor Data processing are reviewed. The model is meant to create monitoring systems of spatially distributed objects of urban engineering networks and processes. The proposed approach is the convergence model of the distributed data processing organization. The fog computing model is used for the processing and aggregation of sensor data at the network nodes and/or industrial controllers. The program agents are loaded to perform computing tasks for the primary processing and data aggregation. The grid and the cloud computing models are used for integral indicators mining and accumulating. A computing cluster has a three-tier architecture, which includes the main server at the first level, a cluster of SCADA system servers at the second level, a lot of GPU video cards with the support for the Compute Unified Device Architecture at the third level. The mobile computing model is applied to visualize the results of intellectual analysis with the elements of augmented reality and geo-information technologies. The integrated indicators are transferred to the data center for accumulation in a multidimensional storage for the purpose of data mining and knowledge gaining.

A Cloud-Based Simulation Architecture for Pandemic Influenza Simulation

PubMed Central

Eriksson, Henrik; Raciti, Massimiliano; Basile, Maurizio; Cunsolo, Alessandro; Fröberg, Anders; Leifler, Ola; Ekberg, Joakim; Timpka, Toomas

2011-01-01

High-fidelity simulations of pandemic outbreaks are resource consuming. Cluster-based solutions have been suggested for executing such complex computations. We present a cloud-based simulation architecture that utilizes computing resources both locally available and dynamically rented online. The approach uses the Condor framework for job distribution and management of the Amazon Elastic Computing Cloud (EC2) as well as local resources. The architecture has a web-based user interface that allows users to monitor and control simulation execution. In a benchmark test, the best cost-adjusted performance was recorded for the EC2 H-CPU Medium instance, while a field trial showed that the job configuration had significant influence on the execution time and that the network capacity of the master node could become a bottleneck. We conclude that it is possible to develop a scalable simulation environment that uses cloud-based solutions, while providing an easy-to-use graphical user interface. PMID:22195089

Application-oriented offloading in heterogeneous networks for mobile cloud computing

NASA Astrophysics Data System (ADS)

Tseng, Fan-Hsun; Cho, Hsin-Hung; Chang, Kai-Di; Li, Jheng-Cong; Shih, Timothy K.

2018-04-01

Nowadays Internet applications have become more complicated that mobile device needs more computing resources for shorter execution time but it is restricted to limited battery capacity. Mobile cloud computing (MCC) is emerged to tackle the finite resource problem of mobile device. MCC offloads the tasks and jobs of mobile devices to cloud and fog environments by using offloading scheme. It is vital to MCC that which task should be offloaded and how to offload efficiently. In the paper, we formulate the offloading problem between mobile device and cloud data center and propose two algorithms based on application-oriented for minimum execution time, i.e. the Minimum Offloading Time for Mobile device (MOTM) algorithm and the Minimum Execution Time for Cloud data center (METC) algorithm. The MOTM algorithm minimizes offloading time by selecting appropriate offloading links based on application categories. The METC algorithm minimizes execution time in cloud data center by selecting virtual and physical machines with corresponding resource requirements of applications. Simulation results show that the proposed mechanism not only minimizes total execution time for mobile devices but also decreases their energy consumption.

Visual Analysis of Cloud Computing Performance Using Behavioral Lines.

PubMed

Muelder, Chris; Zhu, Biao; Chen, Wei; Zhang, Hongxin; Ma, Kwan-Liu

2016-02-29

Cloud computing is an essential technology to Big Data analytics and services. A cloud computing system is often comprised of a large number of parallel computing and storage devices. Monitoring the usage and performance of such a system is important for efficient operations, maintenance, and security. Tracing every application on a large cloud system is untenable due to scale and privacy issues. But profile data can be collected relatively efficiently by regularly sampling the state of the system, including properties such as CPU load, memory usage, network usage, and others, creating a set of multivariate time series for each system. Adequate tools for studying such large-scale, multidimensional data are lacking. In this paper, we present a visual based analysis approach to understanding and analyzing the performance and behavior of cloud computing systems. Our design is based on similarity measures and a layout method to portray the behavior of each compute node over time. When visualizing a large number of behavioral lines together, distinct patterns often appear suggesting particular types of performance bottleneck. The resulting system provides multiple linked views, which allow the user to interactively explore the data by examining the data or a selected subset at different levels of detail. Our case studies, which use datasets collected from two different cloud systems, show that this visual based approach is effective in identifying trends and anomalies of the systems.

Secure and Lightweight Cloud-Assisted Video Reporting Protocol over 5G-Enabled Vehicular Networks

PubMed Central

2017-01-01

In the vehicular networks, the real-time video reporting service is used to send the recorded videos in the vehicle to the cloud. However, when facilitating the real-time video reporting service in the vehicular networks, the usage of the fourth generation (4G) long term evolution (LTE) was proved to suffer from latency while the IEEE 802.11p standard does not offer sufficient scalability for a such congested environment. To overcome those drawbacks, the fifth-generation (5G)-enabled vehicular network is considered as a promising technology for empowering the real-time video reporting service. In this paper, we note that security and privacy related issues should also be carefully addressed to boost the early adoption of 5G-enabled vehicular networks. There exist a few research works for secure video reporting service in 5G-enabled vehicular networks. However, their usage is limited because of public key certificates and expensive pairing operations. Thus, we propose a secure and lightweight protocol for cloud-assisted video reporting service in 5G-enabled vehicular networks. Compared to the conventional public key certificates, the proposed protocol achieves entities’ authorization through anonymous credential. Also, by using lightweight security primitives instead of expensive bilinear pairing operations, the proposed protocol minimizes the computational overhead. From the evaluation results, we show that the proposed protocol takes the smaller computation and communication time for the cryptographic primitives than that of the well-known Eiza-Ni-Shi protocol. PMID:28946633

Secure and Lightweight Cloud-Assisted Video Reporting Protocol over 5G-Enabled Vehicular Networks.

PubMed

Nkenyereye, Lewis; Kwon, Joonho; Choi, Yoon-Ho

2017-09-23

In the vehicular networks, the real-time video reporting service is used to send the recorded videos in the vehicle to the cloud. However, when facilitating the real-time video reporting service in the vehicular networks, the usage of the fourth generation (4G) long term evolution (LTE) was proved to suffer from latency while the IEEE 802.11p standard does not offer sufficient scalability for a such congested environment. To overcome those drawbacks, the fifth-generation (5G)-enabled vehicular network is considered as a promising technology for empowering the real-time video reporting service. In this paper, we note that security and privacy related issues should also be carefully addressed to boost the early adoption of 5G-enabled vehicular networks. There exist a few research works for secure video reporting service in 5G-enabled vehicular networks. However, their usage is limited because of public key certificates and expensive pairing operations. Thus, we propose a secure and lightweight protocol for cloud-assisted video reporting service in 5G-enabled vehicular networks. Compared to the conventional public key certificates, the proposed protocol achieves entities' authorization through anonymous credential. Also, by using lightweight security primitives instead of expensive bilinear pairing operations, the proposed protocol minimizes the computational overhead. From the evaluation results, we show that the proposed protocol takes the smaller computation and communication time for the cryptographic primitives than that of the well-known Eiza-Ni-Shi protocol.

Analysis of the new health management based on health internet of things and cloud computing

NASA Astrophysics Data System (ADS)

Liu, Shaogang

2018-05-01

With the development and application of Internet of things and cloud technology in the medical field, it provides a higher level of exploration space for human health management. By analyzing the Internet of things technology and cloud technology, this paper studies a new form of health management system which conforms to the current social and technical level, and explores its system architecture, system characteristics and application. The new health management platform for networking and cloud can achieve the real-time monitoring and prediction of human health through a variety of sensors and wireless networks based on information and can be transmitted to the monitoring system, and then through the software analysis model, and gives the targeted prevention and treatment measures, to achieve real-time, intelligent health management.

A Location-Based Interactive Model of Internet of Things and Cloud (IoT-Cloud) for Mobile Cloud Computing Applications.

PubMed

Dinh, Thanh; Kim, Younghan; Lee, Hyukjoon

2017-03-01

This paper presents a location-based interactive model of Internet of Things (IoT) and cloud integration (IoT-cloud) for mobile cloud computing applications, in comparison with the periodic sensing model. In the latter, sensing collections are performed without awareness of sensing demands. Sensors are required to report their sensing data periodically regardless of whether or not there are demands for their sensing services. This leads to unnecessary energy loss due to redundant transmission. In the proposed model, IoT-cloud provides sensing services on demand based on interest and location of mobile users. By taking advantages of the cloud as a coordinator, sensing scheduling of sensors is controlled by the cloud, which knows when and where mobile users request for sensing services. Therefore, when there is no demand, sensors are put into an inactive mode to save energy. Through extensive analysis and experimental results, we show that the location-based model achieves a significant improvement in terms of network lifetime compared to the periodic model.

A Location-Based Interactive Model of Internet of Things and Cloud (IoT-Cloud) for Mobile Cloud Computing Applications †

PubMed Central

Dinh, Thanh; Kim, Younghan; Lee, Hyukjoon

2017-01-01

This paper presents a location-based interactive model of Internet of Things (IoT) and cloud integration (IoT-cloud) for mobile cloud computing applications, in comparison with the periodic sensing model. In the latter, sensing collections are performed without awareness of sensing demands. Sensors are required to report their sensing data periodically regardless of whether or not there are demands for their sensing services. This leads to unnecessary energy loss due to redundant transmission. In the proposed model, IoT-cloud provides sensing services on demand based on interest and location of mobile users. By taking advantages of the cloud as a coordinator, sensing scheduling of sensors is controlled by the cloud, which knows when and where mobile users request for sensing services. Therefore, when there is no demand, sensors are put into an inactive mode to save energy. Through extensive analysis and experimental results, we show that the location-based model achieves a significant improvement in terms of network lifetime compared to the periodic model. PMID:28257067

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.

Using deep recurrent neural network for direct beam solar irradiance cloud screening

NASA Astrophysics Data System (ADS)

Chen, Maosi; Davis, John M.; Liu, Chaoshun; Sun, Zhibin; Zempila, Melina Maria; Gao, Wei

2017-09-01

Cloud screening is an essential procedure for in-situ calibration and atmospheric properties retrieval on (UV-)MultiFilter Rotating Shadowband Radiometer [(UV-)MFRSR]. Previous study has explored a cloud screening algorithm for direct-beam (UV-)MFRSR voltage measurements based on the stability assumption on a long time period (typically a half day or a whole day). To design such an algorithm requires in-depth understanding of radiative transfer and delicate data manipulation. Recent rapid developments on deep neural network and computation hardware have opened a window for modeling complicated End-to-End systems with a standardized strategy. In this study, a multi-layer dynamic bidirectional recurrent neural network is built for determining the cloudiness on each time point with a 17-year training dataset and tested with another 1-year dataset. The dataset is the daily 3-minute cosine corrected voltages, airmasses, and the corresponding cloud/clear-sky labels at two stations of the USDA UV-B Monitoring and Research Program. The results show that the optimized neural network model (3-layer, 250 hidden units, and 80 epochs of training) has an overall test accuracy of 97.87% (97.56% for the Oklahoma site and 98.16% for the Hawaii site). Generally, the neural network model grasps the key concept of the original model to use data in the entire day rather than short nearby measurements to perform cloud screening. A scrutiny of the logits layer suggests that the neural network model automatically learns a way to calculate a quantity similar to total optical depth and finds an appropriate threshold for cloud screening.

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.

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.

Fog Computing and Edge Computing Architectures for Processing Data From Diabetes Devices Connected to the Medical Internet of Things.

PubMed

Klonoff, David C

2017-07-01

The Internet of Things (IoT) is generating an immense volume of data. With cloud computing, medical sensor and actuator data can be stored and analyzed remotely by distributed servers. The results can then be delivered via the Internet. The number of devices in IoT includes such wireless diabetes devices as blood glucose monitors, continuous glucose monitors, insulin pens, insulin pumps, and closed-loop systems. The cloud model for data storage and analysis is increasingly unable to process the data avalanche, and processing is being pushed out to the edge of the network closer to where the data-generating devices are. Fog computing and edge computing are two architectures for data handling that can offload data from the cloud, process it nearby the patient, and transmit information machine-to-machine or machine-to-human in milliseconds or seconds. Sensor data can be processed near the sensing and actuating devices with fog computing (with local nodes) and with edge computing (within the sensing devices). Compared to cloud computing, fog computing and edge computing offer five advantages: (1) greater data transmission speed, (2) less dependence on limited bandwidths, (3) greater privacy and security, (4) greater control over data generated in foreign countries where laws may limit use or permit unwanted governmental access, and (5) lower costs because more sensor-derived data are used locally and less data are transmitted remotely. Connected diabetes devices almost all use fog computing or edge computing because diabetes patients require a very rapid response to sensor input and cannot tolerate delays for cloud computing.

The direction of cloud computing for Malaysian education sector in 21st century

NASA Astrophysics Data System (ADS)

Jaafar, Jazurainifariza; Rahman, M. Nordin A.; Kadir, M. Fadzil A.; Shamsudin, Syadiah Nor; Saany, Syarilla Iryani A.

2017-08-01

In 21st century, technology has turned learning environment into a new way of education to make learning systems more effective and systematic. Nowadays, education institutions are faced many challenges to ensure the teaching and learning process is running smoothly and manageable. Some of challenges in the current education management are lack of integrated systems, high cost of maintenance, difficulty of configuration and deployment as well as complexity of storage provision. Digital learning is an instructional practice that use technology to make learning experience more effective, provides education process more systematic and attractive. Digital learning can be considered as one of the prominent application that implemented under cloud computing environment. Cloud computing is a type of network resources that provides on-demands services where the users can access applications inside it at any location and no time border. It also promises for minimizing the cost of maintenance and provides a flexible of data storage capacity. The aim of this article is to review the definition and types of cloud computing for improving digital learning management as required in the 21st century education. The analysis of digital learning context focused on primary school in Malaysia. Types of cloud applications and services in education sector are also discussed in the article. Finally, gap analysis and direction of cloud computing in education sector for facing the 21st century challenges are suggested.

Finding Tropical Cyclones on a Cloud Computing Cluster: Using Parallel Virtualization for Large-Scale Climate Simulation Analysis

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

Hasenkamp, Daren; Sim, Alexander; Wehner, Michael

Extensive computing power has been used to tackle issues such as climate changes, fusion energy, and other pressing scientific challenges. These computations produce a tremendous amount of data; however, many of the data analysis programs currently only run a single processor. In this work, we explore the possibility of using the emerging cloud computing platform to parallelize such sequential data analysis tasks. As a proof of concept, we wrap a program for analyzing trends of tropical cyclones in a set of virtual machines (VMs). This approach allows the user to keep their familiar data analysis environment in the VMs, whilemore » we provide the coordination and data transfer services to ensure the necessary input and output are directed to the desired locations. This work extensively exercises the networking capability of the cloud computing systems and has revealed a number of weaknesses in the current cloud system software. In our tests, we are able to scale the parallel data analysis job to a modest number of VMs and achieve a speedup that is comparable to running the same analysis task using MPI. However, compared to MPI based parallelization, the cloud-based approach has a number of advantages. The cloud-based approach is more flexible because the VMs can capture arbitrary software dependencies without requiring the user to rewrite their programs. The cloud-based approach is also more resilient to failure; as long as a single VM is running, it can make progress while as soon as one MPI node fails the whole analysis job fails. In short, this initial work demonstrates that a cloud computing system is a viable platform for distributed scientific data analyses traditionally conducted on dedicated supercomputing systems.« less

Geo-spatial Service and Application based on National E-government Network Platform and Cloud

NASA Astrophysics Data System (ADS)

Meng, X.; Deng, Y.; Li, H.; Yao, L.; Shi, J.

2014-04-01

With the acceleration of China's informatization process, our party and government take a substantive stride in advancing development and application of digital technology, which promotes the evolution of e-government and its informatization. Meanwhile, as a service mode based on innovative resources, cloud computing may connect huge pools together to provide a variety of IT services, and has become one relatively mature technical pattern with further studies and massive practical applications. Based on cloud computing technology and national e-government network platform, "National Natural Resources and Geospatial Database (NRGD)" project integrated and transformed natural resources and geospatial information dispersed in various sectors and regions, established logically unified and physically dispersed fundamental database and developed national integrated information database system supporting main e-government applications. Cross-sector e-government applications and services are realized to provide long-term, stable and standardized natural resources and geospatial fundamental information products and services for national egovernment and public users.

Adaptive Resource Utilization Prediction System for Infrastructure as a Service Cloud.

PubMed

Zia Ullah, Qazi; Hassan, Shahzad; Khan, Gul Muhammad

2017-01-01

Infrastructure as a Service (IaaS) cloud provides resources as a service from a pool of compute, network, and storage resources. Cloud providers can manage their resource usage by knowing future usage demand from the current and past usage patterns of resources. Resource usage prediction is of great importance for dynamic scaling of cloud resources to achieve efficiency in terms of cost and energy consumption while keeping quality of service. The purpose of this paper is to present a real-time resource usage prediction system. The system takes real-time utilization of resources and feeds utilization values into several buffers based on the type of resources and time span size. Buffers are read by R language based statistical system. These buffers' data are checked to determine whether their data follows Gaussian distribution or not. In case of following Gaussian distribution, Autoregressive Integrated Moving Average (ARIMA) is applied; otherwise Autoregressive Neural Network (AR-NN) is applied. In ARIMA process, a model is selected based on minimum Akaike Information Criterion (AIC) values. Similarly, in AR-NN process, a network with the lowest Network Information Criterion (NIC) value is selected. We have evaluated our system with real traces of CPU utilization of an IaaS cloud of one hundred and twenty servers.

Adaptive Resource Utilization Prediction System for Infrastructure as a Service Cloud

PubMed Central

Hassan, Shahzad; Khan, Gul Muhammad

2017-01-01

Infrastructure as a Service (IaaS) cloud provides resources as a service from a pool of compute, network, and storage resources. Cloud providers can manage their resource usage by knowing future usage demand from the current and past usage patterns of resources. Resource usage prediction is of great importance for dynamic scaling of cloud resources to achieve efficiency in terms of cost and energy consumption while keeping quality of service. The purpose of this paper is to present a real-time resource usage prediction system. The system takes real-time utilization of resources and feeds utilization values into several buffers based on the type of resources and time span size. Buffers are read by R language based statistical system. These buffers' data are checked to determine whether their data follows Gaussian distribution or not. In case of following Gaussian distribution, Autoregressive Integrated Moving Average (ARIMA) is applied; otherwise Autoregressive Neural Network (AR-NN) is applied. In ARIMA process, a model is selected based on minimum Akaike Information Criterion (AIC) values. Similarly, in AR-NN process, a network with the lowest Network Information Criterion (NIC) value is selected. We have evaluated our system with real traces of CPU utilization of an IaaS cloud of one hundred and twenty servers. PMID:28811819

Edge-Based Efficient Search over Encrypted Data Mobile Cloud Storage

PubMed Central

Liu, Fang; Cai, Zhiping; Xiao, Nong; Zhao, Ziming

2018-01-01

Smart sensor-equipped mobile devices sense, collect, and process data generated by the edge network to achieve intelligent control, but such mobile devices usually have limited storage and computing resources. Mobile cloud storage provides a promising solution owing to its rich storage resources, great accessibility, and low cost. But it also brings a risk of information leakage. The encryption of sensitive data is the basic step to resist the risk. However, deploying a high complexity encryption and decryption algorithm on mobile devices will greatly increase the burden of terminal operation and the difficulty to implement the necessary privacy protection algorithm. In this paper, we propose ENSURE (EfficieNt and SecURE), an efficient and secure encrypted search architecture over mobile cloud storage. ENSURE is inspired by edge computing. It allows mobile devices to offload the computation intensive task onto the edge server to achieve a high efficiency. Besides, to protect data security, it reduces the information acquisition of untrusted cloud by hiding the relevance between query keyword and search results from the cloud. Experiments on a real data set show that ENSURE reduces the computation time by 15% to 49% and saves the energy consumption by 38% to 69% per query. PMID:29652810

Edge-Based Efficient Search over Encrypted Data Mobile Cloud Storage.

PubMed

Guo, Yeting; Liu, Fang; Cai, Zhiping; Xiao, Nong; Zhao, Ziming

2018-04-13

Smart sensor-equipped mobile devices sense, collect, and process data generated by the edge network to achieve intelligent control, but such mobile devices usually have limited storage and computing resources. Mobile cloud storage provides a promising solution owing to its rich storage resources, great accessibility, and low cost. But it also brings a risk of information leakage. The encryption of sensitive data is the basic step to resist the risk. However, deploying a high complexity encryption and decryption algorithm on mobile devices will greatly increase the burden of terminal operation and the difficulty to implement the necessary privacy protection algorithm. In this paper, we propose ENSURE (EfficieNt and SecURE), an efficient and secure encrypted search architecture over mobile cloud storage. ENSURE is inspired by edge computing. It allows mobile devices to offload the computation intensive task onto the edge server to achieve a high efficiency. Besides, to protect data security, it reduces the information acquisition of untrusted cloud by hiding the relevance between query keyword and search results from the cloud. Experiments on a real data set show that ENSURE reduces the computation time by 15% to 49% and saves the energy consumption by 38% to 69% per query.

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.

Detecting Distributed SQL Injection Attacks in a Eucalyptus Cloud Environment

NASA Technical Reports Server (NTRS)

Kebert, Alan; Barnejee, Bikramjit; Solano, Juan; Solano, Wanda

2013-01-01

The cloud computing environment offers malicious users the ability to spawn multiple instances of cloud nodes that are similar to virtual machines, except that they can have separate external IP addresses. In this paper we demonstrate how this ability can be exploited by an attacker to distribute his/her attack, in particular SQL injection attacks, in such a way that an intrusion detection system (IDS) could fail to identify this attack. To demonstrate this, we set up a small private cloud, established a vulnerable website in one instance, and placed an IDS within the cloud to monitor the network traffic. We found that an attacker could quite easily defeat the IDS by periodically altering its IP address. To detect such an attacker, we propose to use multi-agent plan recognition, where the multiple source IPs are considered as different agents who are mounting a collaborative attack. We show that such a formulation of this problem yields a more sophisticated approach to detecting SQL injection attacks within a cloud computing environment.

Using virtual machine monitors to overcome the challenges of monitoring and managing virtualized cloud infrastructures

NASA Astrophysics Data System (ADS)

Bamiah, Mervat Adib; Brohi, Sarfraz Nawaz; Chuprat, Suriayati

2012-01-01

Virtualization is one of the hottest research topics nowadays. Several academic researchers and developers from IT industry are designing approaches for solving security and manageability issues of Virtual Machines (VMs) residing on virtualized cloud infrastructures. Moving the application from a physical to a virtual platform increases the efficiency, flexibility and reduces management cost as well as effort. Cloud computing is adopting the paradigm of virtualization, using this technique, memory, CPU and computational power is provided to clients' VMs by utilizing the underlying physical hardware. Beside these advantages there are few challenges faced by adopting virtualization such as management of VMs and network traffic, unexpected additional cost and resource allocation. Virtual Machine Monitor (VMM) or hypervisor is the tool used by cloud providers to manage the VMs on cloud. There are several heterogeneous hypervisors provided by various vendors that include VMware, Hyper-V, Xen and Kernel Virtual Machine (KVM). Considering the challenge of VM management, this paper describes several techniques to monitor and manage virtualized cloud infrastructures.

Community Seismic Network (CSN)

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Heaton, T. H.; Kohler, M. D.; Cheng, M.; Guy, R.; Chandy, M.; Krause, A.; Bunn, J.; Olson, M.; Faulkner, M.; Liu, A.; Strand, L.

2012-12-01

We report on developments in sensor connectivity, architecture, and data fusion algorithms executed in Cloud computing systems in the Community Seismic Network (CSN), a network of low-cost sensors housed in homes and offices by volunteers in the Pasadena, CA area. The network has over 200 sensors continuously reporting anomalies in local acceleration through the Internet to a Cloud computing service (the Google App Engine) that continually fuses sensor data to rapidly detect shaking from earthquakes. The Cloud computing system consists of data centers geographically distributed across the continent and is likely to be resilient even during earthquakes and other local disasters. The region of Southern California is partitioned in a multi-grid style into sets of telescoping cells called geocells. Data streams from sensors within a geocell are fused to detect anomalous shaking across the geocell. Temporal spatial patterns across geocells are used to detect anomalies across regions. The challenge is to detect earthquakes rapidly with an extremely low false positive rate. We report on two data fusion algorithms, one that tessellates the surface so as to fuse data from a large region around Pasadena and the other, which uses a standard tessellation of equal-sized cells. Since September 2011, the network has successfully detected earthquakes of magnitude 2.5 or higher within 40 Km of Pasadena. In addition to the standard USB device, which connects to the host's computer, we have developed a stand-alone sensor that directly connects to the internet via Ethernet or wifi. This bypasses security concerns that some companies have with the USB-connected devices, and allows for 24/7 monitoring at sites that would otherwise shut down their computers after working hours. In buildings we use the sensors to model the behavior of the structures during weak events in order to understand how they will perform during strong events. Visualization models of instrumented buildings ranging between five and 22 stories tall have been constructed using Google SketchUp. Ambient vibration records are used to identify the first set of horizontal vibrational modal frequencies of the buildings. These frequencies are used to compute the response on every floor of the building, given either observed data or scenario ground motion input at the buildings' base.

CloudDOE: a user-friendly tool for deploying Hadoop clouds and analyzing high-throughput sequencing data with MapReduce.

PubMed

Chung, Wei-Chun; Chen, Chien-Chih; Ho, Jan-Ming; Lin, Chung-Yen; Hsu, Wen-Lian; Wang, Yu-Chun; Lee, D T; Lai, Feipei; Huang, Chih-Wei; Chang, Yu-Jung

2014-01-01

Explosive growth of next-generation sequencing data has resulted in ultra-large-scale data sets and ensuing computational problems. Cloud computing provides an on-demand and scalable environment for large-scale data analysis. Using a MapReduce framework, data and workload can be distributed via a network to computers in the cloud to substantially reduce computational latency. Hadoop/MapReduce has been successfully adopted in bioinformatics for genome assembly, mapping reads to genomes, and finding single nucleotide polymorphisms. Major cloud providers offer Hadoop cloud services to their users. However, it remains technically challenging to deploy a Hadoop cloud for those who prefer to run MapReduce programs in a cluster without built-in Hadoop/MapReduce. We present CloudDOE, a platform-independent software package implemented in Java. CloudDOE encapsulates technical details behind a user-friendly graphical interface, thus liberating scientists from having to perform complicated operational procedures. Users are guided through the user interface to deploy a Hadoop cloud within in-house computing environments and to run applications specifically targeted for bioinformatics, including CloudBurst, CloudBrush, and CloudRS. One may also use CloudDOE on top of a public cloud. CloudDOE consists of three wizards, i.e., Deploy, Operate, and Extend wizards. Deploy wizard is designed to aid the system administrator to deploy a Hadoop cloud. It installs Java runtime environment version 1.6 and Hadoop version 0.20.203, and initiates the service automatically. Operate wizard allows the user to run a MapReduce application on the dashboard list. To extend the dashboard list, the administrator may install a new MapReduce application using Extend wizard. CloudDOE is a user-friendly tool for deploying a Hadoop cloud. Its smart wizards substantially reduce the complexity and costs of deployment, execution, enhancement, and management. Interested users may collaborate to improve the source code of CloudDOE to further incorporate more MapReduce bioinformatics tools into CloudDOE and support next-generation big data open source tools, e.g., Hadoop BigTop and Spark. CloudDOE is distributed under Apache License 2.0 and is freely available at http://clouddoe.iis.sinica.edu.tw/.

CloudDOE: A User-Friendly Tool for Deploying Hadoop Clouds and Analyzing High-Throughput Sequencing Data with MapReduce

PubMed Central

Chung, Wei-Chun; Chen, Chien-Chih; Ho, Jan-Ming; Lin, Chung-Yen; Hsu, Wen-Lian; Wang, Yu-Chun; Lee, D. T.; Lai, Feipei; Huang, Chih-Wei; Chang, Yu-Jung

2014-01-01

Background Explosive growth of next-generation sequencing data has resulted in ultra-large-scale data sets and ensuing computational problems. Cloud computing provides an on-demand and scalable environment for large-scale data analysis. Using a MapReduce framework, data and workload can be distributed via a network to computers in the cloud to substantially reduce computational latency. Hadoop/MapReduce has been successfully adopted in bioinformatics for genome assembly, mapping reads to genomes, and finding single nucleotide polymorphisms. Major cloud providers offer Hadoop cloud services to their users. However, it remains technically challenging to deploy a Hadoop cloud for those who prefer to run MapReduce programs in a cluster without built-in Hadoop/MapReduce. Results We present CloudDOE, a platform-independent software package implemented in Java. CloudDOE encapsulates technical details behind a user-friendly graphical interface, thus liberating scientists from having to perform complicated operational procedures. Users are guided through the user interface to deploy a Hadoop cloud within in-house computing environments and to run applications specifically targeted for bioinformatics, including CloudBurst, CloudBrush, and CloudRS. One may also use CloudDOE on top of a public cloud. CloudDOE consists of three wizards, i.e., Deploy, Operate, and Extend wizards. Deploy wizard is designed to aid the system administrator to deploy a Hadoop cloud. It installs Java runtime environment version 1.6 and Hadoop version 0.20.203, and initiates the service automatically. Operate wizard allows the user to run a MapReduce application on the dashboard list. To extend the dashboard list, the administrator may install a new MapReduce application using Extend wizard. Conclusions CloudDOE is a user-friendly tool for deploying a Hadoop cloud. Its smart wizards substantially reduce the complexity and costs of deployment, execution, enhancement, and management. Interested users may collaborate to improve the source code of CloudDOE to further incorporate more MapReduce bioinformatics tools into CloudDOE and support next-generation big data open source tools, e.g., Hadoop BigTop and Spark. Availability: CloudDOE is distributed under Apache License 2.0 and is freely available at http://clouddoe.iis.sinica.edu.tw/. PMID:24897343

An approximate dynamic programming approach to resource management in multi-cloud scenarios

NASA Astrophysics Data System (ADS)

Pietrabissa, Antonio; Priscoli, Francesco Delli; Di Giorgio, Alessandro; Giuseppi, Alessandro; Panfili, Martina; Suraci, Vincenzo

2017-03-01

The programmability and the virtualisation of network resources are crucial to deploy scalable Information and Communications Technology (ICT) services. The increasing demand of cloud services, mainly devoted to the storage and computing, requires a new functional element, the Cloud Management Broker (CMB), aimed at managing multiple cloud resources to meet the customers' requirements and, simultaneously, to optimise their usage. This paper proposes a multi-cloud resource allocation algorithm that manages the resource requests with the aim of maximising the CMB revenue over time. The algorithm is based on Markov decision process modelling and relies on reinforcement learning techniques to find online an approximate solution.

Towards Efficient Scientific Data Management Using Cloud Storage

NASA Technical Reports Server (NTRS)

He, Qiming

2013-01-01

A software prototype allows users to backup and restore data to/from both public and private cloud storage such as Amazon's S3 and NASA's Nebula. Unlike other off-the-shelf tools, this software ensures user data security in the cloud (through encryption), and minimizes users operating costs by using space- and bandwidth-efficient compression and incremental backup. Parallel data processing utilities have also been developed by using massively scalable cloud computing in conjunction with cloud storage. One of the innovations in this software is using modified open source components to work with a private cloud like NASA Nebula. Another innovation is porting the complex backup to- cloud software to embedded Linux, running on the home networking devices, in order to benefit more users.

An Artificial Neural Network-Based Decision-Support System for Integrated Network Security

DTIC Science & Technology

2014-09-01

group that they need to know in order to make team-based decisions in real-time environments, (c) Employ secure cloud computing services to host mobile...THESIS Presented to the Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and Management Air Force...out-of-the-loop syndrome and create complexity creep. As a result, full automation efforts can lead to inappropriate decision-making despite a

Techniques and resources for storm-scale numerical weather prediction

NASA Technical Reports Server (NTRS)

Droegemeier, Kelvin; Grell, Georg; Doyle, James; Soong, Su-Tzai; Skamarock, William; Bacon, David; Staniforth, Andrew; Crook, Andrew; Wilhelmson, Robert

1993-01-01

The topics discussed include the following: multiscale application of the 5th-generation PSU/NCAR mesoscale model, the coupling of nonhydrostatic atmospheric and hydrostatic ocean models for air-sea interaction studies; a numerical simulation of cloud formation over complex topography; adaptive grid simulations of convection; an unstructured grid, nonhydrostatic meso/cloud scale model; efficient mesoscale modeling for multiple scales using variable resolution; initialization of cloud-scale models with Doppler radar data; and making effective use of future computing architectures, networks, and visualization software.

Compression-based aggregation model for medical web services.

PubMed

Al-Shammary, Dhiah; Khalil, Ibrahim

2010-01-01

Many organizations such as hospitals have adopted Cloud Web services in applying their network services to avoid investing heavily computing infrastructure. SOAP (Simple Object Access Protocol) is the basic communication protocol of Cloud Web services that is XML based protocol. Generally,Web services often suffer congestions and bottlenecks as a result of the high network traffic that is caused by the large XML overhead size. At the same time, the massive load on Cloud Web services in terms of the large demand of client requests has resulted in the same problem. In this paper, two XML-aware aggregation techniques that are based on exploiting the compression concepts are proposed in order to aggregate the medical Web messages and achieve higher message size reduction.

Integrated Geo Hazard Management System in Cloud Computing Technology

NASA Astrophysics Data System (ADS)

Hanifah, M. I. M.; Omar, R. C.; Khalid, N. H. N.; Ismail, A.; Mustapha, I. S.; Baharuddin, I. N. Z.; Roslan, R.; Zalam, W. M. Z.

2016-11-01

Geo hazard can result in reducing of environmental health and huge economic losses especially in mountainous area. In order to mitigate geo-hazard effectively, cloud computer technology are introduce for managing geo hazard database. Cloud computing technology and it services capable to provide stakeholder's with geo hazards information in near to real time for an effective environmental management and decision-making. UNITEN Integrated Geo Hazard Management System consist of the network management and operation to monitor geo-hazard disaster especially landslide in our study area at Kelantan River Basin and boundary between Hulu Kelantan and Hulu Terengganu. The system will provide easily manage flexible measuring system with data management operates autonomously and can be controlled by commands to collects and controls remotely by using “cloud” system computing. This paper aims to document the above relationship by identifying the special features and needs associated with effective geohazard database management using “cloud system”. This system later will use as part of the development activities and result in minimizing the frequency of the geo-hazard and risk at that research area.

The Military Applications of Cloud Computing Technologies

DTIC Science & Technology

2013-05-23

tactical networks will potentially cause some unique issues when implementing the JIE. Tactical networks are temporary in nature , and are utilized...connected ABCS clients will receive software updates and security patches as they are published over the network , rather than catching up after an extended...approach from the previous JNN network model, in that it introduces a limited, wireless capability to a unit’s LAN that will enable limited, on-the

A service based adaptive U-learning system using UX.

PubMed

Jeong, Hwa-Young; Yi, Gangman

2014-01-01

In recent years, traditional development techniques for e-learning systems have been changing to become more convenient and efficient. One new technology in the development of application systems includes both cloud and ubiquitous computing. Cloud computing can support learning system processes by using services while ubiquitous computing can provide system operation and management via a high performance technical process and network. In the cloud computing environment, a learning service application can provide a business module or process to the user via the internet. This research focuses on providing the learning material and processes of courses by learning units using the services in a ubiquitous computing environment. And we also investigate functions that support users' tailored materials according to their learning style. That is, we analyzed the user's data and their characteristics in accordance with their user experience. We subsequently applied the learning process to fit on their learning performance and preferences. Finally, we demonstrate how the proposed system outperforms learning effects to learners better than existing techniques.

A Service Based Adaptive U-Learning System Using UX

PubMed Central

Jeong, Hwa-Young

2014-01-01

In recent years, traditional development techniques for e-learning systems have been changing to become more convenient and efficient. One new technology in the development of application systems includes both cloud and ubiquitous computing. Cloud computing can support learning system processes by using services while ubiquitous computing can provide system operation and management via a high performance technical process and network. In the cloud computing environment, a learning service application can provide a business module or process to the user via the internet. This research focuses on providing the learning material and processes of courses by learning units using the services in a ubiquitous computing environment. And we also investigate functions that support users' tailored materials according to their learning style. That is, we analyzed the user's data and their characteristics in accordance with their user experience. We subsequently applied the learning process to fit on their learning performance and preferences. Finally, we demonstrate how the proposed system outperforms learning effects to learners better than existing techniques. PMID:25147832

ATLAS WORLD-cloud and networking in PanDA

NASA Astrophysics Data System (ADS)

Barreiro Megino, F.; De, K.; Di Girolamo, A.; Maeno, T.; Walker, R.; ATLAS Collaboration

2017-10-01

The ATLAS computing model was originally designed as static clouds (usually national or geographical groupings of sites) around the Tier 1 centres, which confined tasks and most of the data traffic. Since those early days, the sites’ network bandwidth has increased at 0(1000) and the difference in functionalities between Tier 1s and Tier 2s has reduced. After years of manual, intermediate solutions, we have now ramped up to full usage of World-cloud, the latest step in the PanDA Workload Management System to increase resource utilization on the ATLAS Grid, for all workflows (MC production, data (re)processing, etc.). We have based the development on two new site concepts. Nuclei sites are the Tier 1s and large Tier 2s, where tasks will be assigned and the output aggregated, and satellites are the sites that will execute the jobs and send the output to their nucleus. PanDA dynamically pairs nuclei and satellite sites for each task based on the input data availability, capability matching, site load and network connectivity. This contribution will introduce the conceptual changes for World-cloud, the development necessary in PanDA, an insight into the network model and the first half-year of operational experience.

Distributed denial of service (DDoS) attack in cloud- assisted wireless body area networks: a systematic literature review.

PubMed

Latif, Rabia; Abbas, Haider; Assar, Saïd

2014-11-01

Wireless Body Area Networks (WBANs) have emerged as a promising technology that has shown enormous potential in improving the quality of healthcare, and has thus found a broad range of medical applications from ubiquitous health monitoring to emergency medical response systems. The huge amount of highly sensitive data collected and generated by WBAN nodes requires an ascendable and secure storage and processing infrastructure. Given the limited resources of WBAN nodes for storage and processing, the integration of WBANs and cloud computing may provide a powerful solution. However, despite the benefits of cloud-assisted WBAN, several security issues and challenges remain. Among these, data availability is the most nagging security issue. The most serious threat to data availability is a distributed denial of service (DDoS) attack that directly affects the all-time availability of a patient's data. The existing solutions for standalone WBANs and sensor networks are not applicable in the cloud. The purpose of this review paper is to identify the most threatening types of DDoS attacks affecting the availability of a cloud-assisted WBAN and review the state-of-the-art detection mechanisms for the identified DDoS attacks.

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.

Biomedical cloud computing with Amazon Web Services.

PubMed

Fusaro, Vincent A; Patil, Prasad; Gafni, Erik; Wall, Dennis P; Tonellato, Peter J

2011-08-01

In this overview to biomedical computing in the cloud, we discussed two primary ways to use the cloud (a single instance or cluster), provided a detailed example using NGS mapping, and highlighted the associated costs. While many users new to the cloud may assume that entry is as straightforward as uploading an application and selecting an instance type and storage options, we illustrated that there is substantial up-front effort required before an application can make full use of the cloud's vast resources. Our intention was to provide a set of best practices and to illustrate how those apply to a typical application pipeline for biomedical informatics, but also general enough for extrapolation to other types of computational problems. Our mapping example was intended to illustrate how to develop a scalable project and not to compare and contrast alignment algorithms for read mapping and genome assembly. Indeed, with a newer aligner such as Bowtie, it is possible to map the entire African genome using one m2.2xlarge instance in 48 hours for a total cost of approximately $48 in computation time. In our example, we were not concerned with data transfer rates, which are heavily influenced by the amount of available bandwidth, connection latency, and network availability. When transferring large amounts of data to the cloud, bandwidth limitations can be a major bottleneck, and in some cases it is more efficient to simply mail a storage device containing the data to AWS (http://aws.amazon.com/importexport/). More information about cloud computing, detailed cost analysis, and security can be found in references.

The GONG Site Survey. [solar oscillations

NASA Technical Reports Server (NTRS)

Hill, Frank; Ambastha, Ashok; Ball, Warren; Duhalde, Oscar; Farris, Don; Fischer, George; Hieda, Les; Zhen, Huang; Ingram, Bob; Jackson, Patty

1988-01-01

The Global Oscillation Network Group (GONG) project is planning to place six observing stations around the world to observe the solar oscillations as continuously as possible. The procedures that are being used to select the six sites are described. Results of measurements of cloud cover obtained by networks of 6 (out of 10) radiometers show a duty cycle of over 93 percent, with the first diurnal sidelobe in the window power spectrum suppressed by a factor of 400. The results are in good agreement with the predictions of a computer model of the expected cloud cover at individual sites.

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

Suborbital Telepresence and Over-the-Horizon Networking

NASA Technical Reports Server (NTRS)

Freudinger, Lawrence C.

2007-01-01

A viewgraph presentation describing the suborbital telepresence project utilizing in-flight network computing is shown. The topics include: 1) Motivation; 2) Suborbital Telepresence and Global Test Range; 3) Tropical Composition, Cloud, and Climate Coupling Experiment (TC4); 4) Data Sets for TC4 Real-time Monitoring; 5) TC-4 Notional Architecture; 6) An Application Integration View; 7) Telepresence: Architectural Framework; and 8) Disruption Tolerant Networks.

Atmospheric cloud physics thermal systems analysis

NASA Technical Reports Server (NTRS)

1977-01-01

Engineering analyses performed on the Atmospheric Cloud Physics (ACPL) Science Simulator expansion chamber and associated thermal control/conditioning system are reported. Analyses were made to develop a verified thermal model and to perform parametric thermal investigations to evaluate systems performance characteristics. Thermal network representations of solid components and the complete fluid conditioning system were solved simultaneously using the Systems Improved Numerical Differencing Analyzer (SINDA) computer program.

HyspIRI Low Latency Concept and Benchmarks

NASA Technical Reports Server (NTRS)

Mandl, Dan

2010-01-01

Topics include HyspIRI low latency data ops concept, HyspIRI data flow, ongoing efforts, experiment with Web Coverage Processing Service (WCPS) approach to injecting new algorithms into SensorWeb, low fidelity HyspIRI IPM testbed, compute cloud testbed, open cloud testbed environment, Global Lambda Integrated Facility (GLIF) and OCC collaboration with Starlight, delay tolerant network (DTN) protocol benchmarking, and EO-1 configuration for preliminary DTN prototype.

Cloud Height Estimation with a Single Digital Camera and Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Carretas, Filipe; Janeiro, Fernando M.

2014-05-01

Clouds influence the local weather, the global climate and are an important parameter in the weather prediction models. Clouds are also an essential component of airplane safety when visual flight rules (VFR) are enforced, such as in most small aerodromes where it is not economically viable to install instruments for assisted flying. Therefore it is important to develop low cost and robust systems that can be easily deployed in the field, enabling large scale acquisition of cloud parameters. Recently, the authors developed a low-cost system for the measurement of cloud base height using stereo-vision and digital photography. However, due to the stereo nature of the system, some challenges were presented. In particular, the relative camera orientation requires calibration and the two cameras need to be synchronized so that the photos from both cameras are acquired simultaneously. In this work we present a new system that estimates the cloud height between 1000 and 5000 meters. This prototype is composed by one digital camera controlled by a Raspberry Pi and is installed at Centro de Geofísica de Évora (CGE) in Évora, Portugal. The camera is periodically triggered to acquire images of the overhead sky and the photos are downloaded to the Raspberry Pi which forwards them to a central computer that processes the images and estimates the cloud height in real time. To estimate the cloud height using just one image requires a computer model that is able to learn from previous experiences and execute pattern recognition. The model proposed in this work is an Artificial Neural Network (ANN) that was previously trained with cloud features at different heights. The chosen Artificial Neural Network is a three-layer network, with six parameters in the input layer, 12 neurons in the hidden intermediate layer, and an output layer with only one output. The six input parameters are the average intensity values and the intensity standard deviation of each RGB channel. The output parameter in the output layer is the cloud height estimated by the ANN. The training procedure was performed, using the back-propagation method, in a set of 260 different clouds with heights in the range [1000, 5000] m. The training of the ANN has resulted in a correlation ratio of 0.74. This trained ANN can therefore be used to estimate the cloud height. The previously described system can also measure the wind speed and direction at cloud height by measuring the displacement, in pixels, of a cloud feature between consecutively acquired photos. Also, the geographical north direction can be estimated using this setup through sequential night images with high exposure times. A further advantage of this single camera system is that no camera calibration or synchronization is needed. This significantly reduces the cost and complexity of field deployment of cloud height measurement systems based on digital photography.

A Secure Cloud-Assisted Wireless Body Area Network in Mobile Emergency Medical Care System.

PubMed

Li, Chun-Ta; Lee, Cheng-Chi; Weng, Chi-Yao

2016-05-01

Recent advances in medical treatment and emergency applications, the need of integrating wireless body area network (WBAN) with cloud computing can be motivated by providing useful and real time information about patients' health state to the doctors and emergency staffs. WBAN is a set of body sensors carried by the patient to collect and transmit numerous health items to medical clouds via wireless and public communication channels. Therefore, a cloud-assisted WBAN facilitates response in case of emergency which can save patients' lives. Since the patient's data is sensitive and private, it is important to provide strong security and protection on the patient's medical data over public and insecure communication channels. In this paper, we address the challenge of participant authentication in mobile emergency medical care systems for patients supervision and propose a secure cloud-assisted architecture for accessing and monitoring health items collected by WBAN. For ensuring a high level of security and providing a mutual authentication property, chaotic maps based authentication and key agreement mechanisms are designed according to the concept of Diffie-Hellman key exchange, which depends on the CMBDLP and CMBDHP problems. Security and performance analyses show how the proposed system guaranteed the patient privacy and the system confidentiality of sensitive medical data while preserving the low computation property in medical treatment and remote medical monitoring.

75 FR 27798 - Notice of Issuance of Final Determination Concerning Certain Commodity-Based Clustered Storage Units

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-18

... device to function as a cloud computing device similar to a network storage RAID array (HDDs strung... contract. This final determination, in HQ H082476, was issued at the request of Scale Computing under... response to your request dated October 15, 2009, made on behalf of Scale Computing (``Scale''). You ask for...

A Comparison Between Heliosat-2 and Artificial Neural Network Methods for Global Horizontal Irradiance Retrievals over Desert Environments

NASA Astrophysics Data System (ADS)

Ghedira, H.; Eissa, Y.

2012-12-01

Global horizontal irradiance (GHI) retrievals at the surface of any given location could be used for preliminary solar resource assessments. More accurately, the direct normal irradiance (DNI) and diffuse horizontal irradiance (DHI) are also required to estimate the global tilt irradiance, mainly used for fixed flat plate collectors. Two different satellite-based models for solar irradiance retrievals have been applied over the desert environment of the United Arab Emirates (UAE). Both models employ channels of the SEVIRI instrument, onboard the geostationary satellite Meteosat Second Generation, as their main inputs. The satellite images used in this study have a temporal resolution of 15-min and a spatial resolution of 3-km. The objective of this study is to compare between the GHI retrieved using the Heliosat-2 method and an artificial neural network (ANN) ensemble method over the UAE. The high-resolution visible channel of SEVIRI is used in the Heliosat-2 method to derive the cloud index. The cloud index is then used to compute the cloud transmission, while the cloud-free GHI is computed from the Linke turbidity factor. The product of the cloud transmission and the cloud-free GHI denotes the estimated GHI. A constant underestimation is observed in the estimated GHI over the dataset available in the UAE. Therefore, the cloud-free DHI equation in the model was recalibrated to fix the bias. After recalibration, results over the UAE show a root mean square error (RMSE) value of 10.1% and a mean bias error (MBE) of -0.5%. As for the ANN approach, six thermal channels of SEVIRI were used to estimate the DHI and the total optical depth of the atmosphere (δ). An ensemble approach is employed to obtain a better generalizability of the results, as opposed to using one single weak network. The DNI is then computed from the estimated δ using the Beer-Bouguer-Lambert law. The GHI is computed from the DNI and DHI estimates. The RMSE for the estimated GHI obtained over an independent dataset over the UAE is 7.2% and the MBE is +1.9%. The results obtained by the two methods have shown that both the recalibrated Heliosat-2 and the ANN ensemble methods estimate the GHI at a 15-min resolution with high accuracy. The advantage of the ANN ensemble approach is that it derives the GHI from accurate DNI and DHI estimates. The DNI and DHI estimates are valuable when computing the global tilt irradiance. Also, accurate DNI estimates are beneficial for preliminary site selection for concentrating solar powered plants.

On Study of Application of Big Data and Cloud Computing Technology in Smart Campus

NASA Astrophysics Data System (ADS)

Tang, Zijiao

2017-12-01

We live in an era of network and information, which means we produce and face a lot of data every day, however it is not easy for database in the traditional meaning to better store, process and analyze the mass data, therefore the big data was born at the right moment. Meanwhile, the development and operation of big data rest with cloud computing which provides sufficient space and resources available to process and analyze data of big data technology. Nowadays, the proposal of smart campus construction aims at improving the process of building information in colleges and universities, therefore it is necessary to consider combining big data technology and cloud computing technology into construction of smart campus to make campus database system and campus management system mutually combined rather than isolated, and to serve smart campus construction through integrating, storing, processing and analyzing mass data.

Federated and Cloud Enabled Resources for Data Management and Utilization

NASA Astrophysics Data System (ADS)

Rankin, R.; Gordon, M.; Potter, R. G.; Satchwill, B.

2011-12-01

The emergence of cloud computing over the past three years has led to a paradigm shift in how data can be managed, processed and made accessible. Building on the federated data management system offered through the Canadian Space Science Data Portal (www.cssdp.ca), we demonstrate how heterogeneous and geographically distributed data sets and modeling tools have been integrated to form a virtual data center and computational modeling platform that has services for data processing and visualization embedded within it. We also discuss positive and negative experiences in utilizing Eucalyptus and OpenStack cloud applications, and job scheduling facilitated by Condor and Star Cluster. We summarize our findings by demonstrating use of these technologies in the Cloud Enabled Space Weather Data Assimilation and Modeling Platform CESWP (www.ceswp.ca), which is funded through Canarie's (canarie.ca) Network Enabled Platforms program in Canada.

A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems

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

Hameed, Abdul; Khoshkbarforoushha, Alireza; Ranjan, Rajiv

In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subjectmore » that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.« less

The design of an m-Health monitoring system based on a cloud computing platform

NASA Astrophysics Data System (ADS)

Xu, Boyi; Xu, Lida; Cai, Hongming; Jiang, Lihong; Luo, Yang; Gu, Yizhi

2017-01-01

Compared to traditional medical services provided within hospitals, m-Health monitoring systems (MHMSs) face more challenges in personalised health data processing. To achieve personalised and high-quality health monitoring by means of new technologies, such as mobile network and cloud computing, in this paper, a framework of an m-Health monitoring system based on a cloud computing platform (Cloud-MHMS) is designed to implement pervasive health monitoring. Furthermore, the modules of the framework, which are Cloud Storage and Multiple Tenants Access Control Layer, Healthcare Data Annotation Layer, and Healthcare Data Analysis Layer, are discussed. In the data storage layer, a multiple tenant access method is designed to protect patient privacy. In the data annotation layer, linked open data are adopted to augment health data interoperability semantically. In the data analysis layer, the process mining algorithm and similarity calculating method are implemented to support personalised treatment plan selection. These three modules cooperate to implement the core functions in the process of health monitoring, which are data storage, data processing, and data analysis. Finally, we study the application of our architecture in the monitoring of antimicrobial drug usage to demonstrate the usability of our method in personal healthcare analysis.

Analysis of cloud-based solutions on EHRs systems in different scenarios.

PubMed

Fernández-Cardeñosa, Gonzalo; de la Torre-Díez, Isabel; López-Coronado, Miguel; Rodrigues, Joel J P C

2012-12-01

Nowadays with the growing of the wireless connections people can access all the resources hosted in the Cloud almost everywhere. In this context, organisms can take advantage of this fact, in terms of e-Health, deploying Cloud-based solutions on e-Health services. In this paper two Cloud-based solutions for different scenarios of Electronic Health Records (EHRs) management system are proposed. We have researched articles published between the years 2005 and 2011 about the implementation of e-Health services based on the Cloud in Medline. In order to analyze the best scenario for the deployment of Cloud Computing two solutions for a large Hospital and a network of Primary Care Health centers have been studied. Economic estimation of the cost of the implementation for both scenarios has been done via the Amazon calculator tool. As a result of this analysis two solutions are suggested depending on the scenario: To deploy a Cloud solution for a large Hospital a typical Cloud solution in which are hired just the needed services has been assumed. On the other hand to work with several Primary Care Centers it's suggested the implementation of a network, which interconnects these centers with just one Cloud environment. Finally it's considered the fact of deploying a hybrid solution: in which EHRs with images will be hosted in the Hospital or Primary Care Centers and the rest of them will be migrated to the Cloud.

Software-defined optical network for metro-scale geographically distributed data centers.

PubMed

Samadi, Payman; Wen, Ke; Xu, Junjie; Bergman, Keren

2016-05-30

The emergence of cloud computing and big data has rapidly increased the deployment of small and mid-sized data centers. Enterprises and cloud providers require an agile network among these data centers to empower application reliability and flexible scalability. We present a software-defined inter data center network to enable on-demand scale out of data centers on a metro-scale optical network. The architecture consists of a combined space/wavelength switching platform and a Software-Defined Networking (SDN) control plane equipped with a wavelength and routing assignment module. It enables establishing transparent and bandwidth-selective connections from L2/L3 switches, on-demand. The architecture is evaluated in a testbed consisting of 3 data centers, 5-25 km apart. We successfully demonstrated end-to-end bulk data transfer and Virtual Machine (VM) migrations across data centers with less than 100 ms connection setup time and close to full link capacity utilization.

Application research of Ganglia in Hadoop monitoring and management

NASA Astrophysics Data System (ADS)

Li, Gang; Ding, Jing; Zhou, Lixia; Yang, Yi; Liu, Lei; Wang, Xiaolei

2017-03-01

There are many applications of Hadoop System in the field of large data, cloud computing. The test bench of storage and application in seismic network at Earthquake Administration of Tianjin use with Hadoop system, which is used the open source software of Ganglia to operate and monitor. This paper reviews the function, installation and configuration process, application effect of operating and monitoring in Hadoop system of the Ganglia system. It briefly introduces the idea and effect of Nagios software monitoring Hadoop system. It is valuable for the industry in the monitoring system of cloud computing platform.

Interactive analysis of geographically distributed population imaging data collections over light-path data networks

NASA Astrophysics Data System (ADS)

van Lew, Baldur; Botha, Charl P.; Milles, Julien R.; Vrooman, Henri A.; van de Giessen, Martijn; Lelieveldt, Boudewijn P. F.

2015-03-01

The cohort size required in epidemiological imaging genetics studies often mandates the pooling of data from multiple hospitals. Patient data, however, is subject to strict privacy protection regimes, and physical data storage may be legally restricted to a hospital network. To enable biomarker discovery, fast data access and interactive data exploration must be combined with high-performance computing resources, while respecting privacy regulations. We present a system using fast and inherently secure light-paths to access distributed data, thereby obviating the need for a central data repository. A secure private cloud computing framework facilitates interactive, computationally intensive exploration of this geographically distributed, privacy sensitive data. As a proof of concept, MRI brain imaging data hosted at two remote sites were processed in response to a user command at a third site. The system was able to automatically start virtual machines, run a selected processing pipeline and write results to a user accessible database, while keeping data locally stored in the hospitals. Individual tasks took approximately 50% longer compared to a locally hosted blade server but the cloud infrastructure reduced the total elapsed time by a factor of 40 using 70 virtual machines in the cloud. We demonstrated that the combination light-path and private cloud is a viable means of building an analysis infrastructure for secure data analysis. The system requires further work in the areas of error handling, load balancing and secure support of multiple users.

QoS-aware health monitoring system using cloud-based WBANs.

PubMed

Almashaqbeh, Ghada; Hayajneh, Thaier; Vasilakos, Athanasios V; Mohd, Bassam J

2014-10-01

Wireless Body Area Networks (WBANs) are amongst the best options for remote health monitoring. However, as standalone systems WBANs have many limitations due to the large amount of processed data, mobility of monitored users, and the network coverage area. Integrating WBANs with cloud computing provides effective solutions to these problems and promotes the performance of WBANs based systems. Accordingly, in this paper we propose a cloud-based real-time remote health monitoring system for tracking the health status of non-hospitalized patients while practicing their daily activities. Compared with existing cloud-based WBAN frameworks, we divide the cloud into local one, that includes the monitored users and local medical staff, and a global one that includes the outer world. The performance of the proposed framework is optimized by reducing congestion, interference, and data delivery delay while supporting users' mobility. Several novel techniques and algorithms are proposed to accomplish our objective. First, the concept of data classification and aggregation is utilized to avoid clogging the network with unnecessary data traffic. Second, a dynamic channel assignment policy is developed to distribute the WBANs associated with the users on the available frequency channels to manage interference. Third, a delay-aware routing metric is proposed to be used by the local cloud in its multi-hop communication to speed up the reporting process of the health-related data. Fourth, the delay-aware metric is further utilized by the association protocols used by the WBANs to connect with the local cloud. Finally, the system with all the proposed techniques and algorithms is evaluated using extensive ns-2 simulations. The simulation results show superior performance of the proposed architecture in optimizing the end-to-end delay, handling the increased interference levels, maximizing the network capacity, and tracking user's mobility.

NASA Update for Unidata Stratcomm

NASA Technical Reports Server (NTRS)

Lynnes, Chris

2017-01-01

The NASA representative to the Unidata Strategic Committee presented a semiannual update on NASAs work with and use of Unidata technologies. The talk updated Unidata on the program of cloud computing prototypes underway for the Earth Observing System Data and Information System (EOSDIS). Also discussed was a trade study on the use of the Open source Project for a Network Data Access Protocol (OPeNDAP) with Web Object Storage in the cloud.

Processing NASA Earth Science Data on Nebula Cloud

NASA Technical Reports Server (NTRS)

Chen, Aijun; Pham, Long; Kempler, Steven

2012-01-01

Three applications were successfully migrated to Nebula, including S4PM, AIRS L1/L2 algorithms, and Giovanni MAPSS. Nebula has some advantages compared with local machines (e.g. performance, cost, scalability, bundling, etc.). Nebula still faces some challenges (e.g. stability, object storage, networking, etc.). Migrating applications to Nebula is feasible but time consuming. Lessons learned from our Nebula experience will benefit future Cloud Computing efforts at GES DISC.

An Application-Based Performance Evaluation of NASAs Nebula Cloud Computing Platform

NASA Technical Reports Server (NTRS)

Saini, Subhash; Heistand, Steve; Jin, Haoqiang; Chang, Johnny; Hood, Robert T.; Mehrotra, Piyush; Biswas, Rupak

2012-01-01

The high performance computing (HPC) community has shown tremendous interest in exploring cloud computing as it promises high potential. In this paper, we examine the feasibility, performance, and scalability of production quality scientific and engineering applications of interest to NASA on NASA's cloud computing platform, called Nebula, hosted at Ames Research Center. This work represents the comprehensive evaluation of Nebula using NUTTCP, HPCC, NPB, I/O, and MPI function benchmarks as well as four applications representative of the NASA HPC workload. Specifically, we compare Nebula performance on some of these benchmarks and applications to that of NASA s Pleiades supercomputer, a traditional HPC system. We also investigate the impact of virtIO and jumbo frames on interconnect performance. Overall results indicate that on Nebula (i) virtIO and jumbo frames improve network bandwidth by a factor of 5x, (ii) there is a significant virtualization layer overhead of about 10% to 25%, (iii) write performance is lower by a factor of 25x, (iv) latency for short MPI messages is very high, and (v) overall performance is 15% to 48% lower than that on Pleiades for NASA HPC applications. We also comment on the usability of the cloud platform.

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.

Cloud Image Data Center for Healthcare Network in Taiwan.

PubMed

Weng, Shao-Jen; Lai, Lai-Shiun; Gotcher, Donald; Wu, Hsin-Hung; Xu, Yeong-Yuh; Yang, Ching-Wen

2016-04-01

This paper investigates how a healthcare network in Taiwan uses a practical cloud image data center (CIDC) to communicate with its constituent hospital branches. A case study approach was used. The study was carried out in the central region of Taiwan, with four hospitals belonging to the Veterans Hospital healthcare network. The CIDC provides synchronous and asynchronous consultation among these branches. It provides storage, platforms, and services on demand to the hospitals. Any branch-client can pull up the patient's medical images from any hospital off this cloud. Patients can be examined at the branches, and the images and reports can be further evaluated by physicians in the main Taichung Veterans General Hospital (TVGH) to enhance the usage and efficiency of equipment in the various branches, thereby shortening the waiting time of patients. The performance of the CIDC over 5 years shows: (1) the total number of cross-hospital images accessed with CDC in the branches was 132,712; and (2) TVGH assisted the branches in keying in image reports using the CIDC 4,424 times; and (3) Implementation of the system has improved management, efficiency, speed and quality of care. Therefore, the results lead to the recommendation of continuing and expanding the cloud computing architecture to improve information sharing among branches in the healthcare network.

Analytical modeling and feasibility study of a multi-GPU cloud-based server (MGCS) framework for non-voxel-based dose calculations.

PubMed

Neylon, J; Min, Y; Kupelian, P; Low, D A; Santhanam, A

2017-04-01

In this paper, a multi-GPU cloud-based server (MGCS) framework is presented for dose calculations, exploring the feasibility of remote computing power for parallelization and acceleration of computationally and time intensive radiotherapy tasks in moving toward online adaptive therapies. An analytical model was developed to estimate theoretical MGCS performance acceleration and intelligently determine workload distribution. Numerical studies were performed with a computing setup of 14 GPUs distributed over 4 servers interconnected by a 1 Gigabits per second (Gbps) network. Inter-process communication methods were optimized to facilitate resource distribution and minimize data transfers over the server interconnect. The analytically predicted computation time predicted matched experimentally observations within 1-5 %. MGCS performance approached a theoretical limit of acceleration proportional to the number of GPUs utilized when computational tasks far outweighed memory operations. The MGCS implementation reproduced ground-truth dose computations with negligible differences, by distributing the work among several processes and implemented optimization strategies. The results showed that a cloud-based computation engine was a feasible solution for enabling clinics to make use of fast dose calculations for advanced treatment planning and adaptive radiotherapy. The cloud-based system was able to exceed the performance of a local machine even for optimized calculations, and provided significant acceleration for computationally intensive tasks. Such a framework can provide access to advanced technology and computational methods to many clinics, providing an avenue for standardization across institutions without the requirements of purchasing, maintaining, and continually updating hardware.

Towards Interactive Medical Content Delivery Between Simulated Body Sensor Networks and Practical Data Center.

PubMed

Shi, Xiaobo; Li, Wei; Song, Jeungeun; Hossain, M Shamim; Mizanur Rahman, Sk Md; Alelaiwi, Abdulhameed

2016-10-01

With the development of IoT (Internet of Thing), big data analysis and cloud computing, traditional medical information system integrates with these new technologies. The establishment of cloud-based smart healthcare application gets more and more attention. In this paper, semi-physical simulation technology is applied to cloud-based smart healthcare system. The Body sensor network (BSN) of system transmit has two ways of data collection and transmission. The one is using practical BSN to collect data and transmitting it to the data center. The other is transmitting real medical data to practical data center by simulating BSN. In order to transmit real medical data to practical data center by simulating BSN under semi-physical simulation environment, this paper designs an OPNET packet structure, defines a gateway node model between simulating BSN and practical data center and builds a custom protocol stack. Moreover, this paper conducts a large amount of simulation on the real data transmission through simulation network connecting with practical network. The simulation result can provides a reference for parameter settings of fully practical network and reduces the cost of devices and personnel involved.

Efficient operating system level virtualization techniques for cloud resources

NASA Astrophysics Data System (ADS)

Ansu, R.; Samiksha; Anju, S.; Singh, K. John

2017-11-01

Cloud computing is an advancing technology which provides the servcies of Infrastructure, Platform and Software. Virtualization and Computer utility are the keys of Cloud computing. The numbers of cloud users are increasing day by day. So it is the need of the hour to make resources available on demand to satisfy user requirements. The technique in which resources namely storage, processing power, memory and network or I/O are abstracted is known as Virtualization. For executing the operating systems various virtualization techniques are available. They are: Full System Virtualization and Para Virtualization. In Full Virtualization, the whole architecture of hardware is duplicated virtually. No modifications are required in Guest OS as the OS deals with the VM hypervisor directly. In Para Virtualization, modifications of OS is required to run in parallel with other OS. For the Guest OS to access the hardware, the host OS must provide a Virtual Machine Interface. OS virtualization has many advantages such as migrating applications transparently, consolidation of server, online maintenance of OS and providing security. This paper briefs both the virtualization techniques and discusses the issues in OS level virtualization.

Cloud-based shaft torque estimation for electric vehicle equipped with integrated motor-transmission system

NASA Astrophysics Data System (ADS)

Zhu, Xiaoyuan; Zhang, Hui; Yang, Bo; Zhang, Guichen

2018-01-01

In order to improve oscillation damping control performance as well as gear shift quality of electric vehicle equipped with integrated motor-transmission system, a cloud-based shaft torque estimation scheme is proposed in this paper by using measurable motor and wheel speed signals transmitted by wireless network. It can help reduce computational burden of onboard controllers and also relief network bandwidth requirement of individual vehicle. Considering possible delays during signal wireless transmission, delay-dependent full-order observer design is proposed to estimate the shaft torque in cloud server. With these random delays modeled by using homogenous Markov chain, robust H∞ performance is adopted to minimize the effect of wireless network-induced delays, signal measurement noise as well as system modeling uncertainties on shaft torque estimation error. Observer parameters are derived by solving linear matrix inequalities, and simulation results using acceleration test and tip-in, tip-out test demonstrate the effectiveness of proposed shaft torque observer design.

Continuous-variable quantum computing on encrypted data.

PubMed

Marshall, Kevin; Jacobsen, Christian S; Schäfermeier, Clemens; Gehring, Tobias; Weedbrook, Christian; Andersen, Ulrik L

2016-12-14

The ability to perform computations on encrypted data is a powerful tool for protecting a client's privacy, especially in today's era of cloud and distributed computing. In terms of privacy, the best solutions that classical techniques can achieve are unfortunately not unconditionally secure in the sense that they are dependent on a hacker's computational power. Here we theoretically investigate, and experimentally demonstrate with Gaussian displacement and squeezing operations, a quantum solution that achieves the security of a user's privacy using the practical technology of continuous variables. We demonstrate losses of up to 10 km both ways between the client and the server and show that security can still be achieved. Our approach offers a number of practical benefits (from a quantum perspective) that could one day allow the potential widespread adoption of this quantum technology in future cloud-based computing networks.

Continuous-variable quantum computing on encrypted data

PubMed Central

Marshall, Kevin; Jacobsen, Christian S.; Schäfermeier, Clemens; Gehring, Tobias; Weedbrook, Christian; Andersen, Ulrik L.

2016-01-01

The ability to perform computations on encrypted data is a powerful tool for protecting a client's privacy, especially in today's era of cloud and distributed computing. In terms of privacy, the best solutions that classical techniques can achieve are unfortunately not unconditionally secure in the sense that they are dependent on a hacker's computational power. Here we theoretically investigate, and experimentally demonstrate with Gaussian displacement and squeezing operations, a quantum solution that achieves the security of a user's privacy using the practical technology of continuous variables. We demonstrate losses of up to 10 km both ways between the client and the server and show that security can still be achieved. Our approach offers a number of practical benefits (from a quantum perspective) that could one day allow the potential widespread adoption of this quantum technology in future cloud-based computing networks. PMID:27966528

Continuous-variable quantum computing on encrypted data

NASA Astrophysics Data System (ADS)

Marshall, Kevin; Jacobsen, Christian S.; Schäfermeier, Clemens; Gehring, Tobias; Weedbrook, Christian; Andersen, Ulrik L.

2016-12-01

The ability to perform computations on encrypted data is a powerful tool for protecting a client's privacy, especially in today's era of cloud and distributed computing. In terms of privacy, the best solutions that classical techniques can achieve are unfortunately not unconditionally secure in the sense that they are dependent on a hacker's computational power. Here we theoretically investigate, and experimentally demonstrate with Gaussian displacement and squeezing operations, a quantum solution that achieves the security of a user's privacy using the practical technology of continuous variables. We demonstrate losses of up to 10 km both ways between the client and the server and show that security can still be achieved. Our approach offers a number of practical benefits (from a quantum perspective) that could one day allow the potential widespread adoption of this quantum technology in future cloud-based computing networks.

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.

A world-wide databridge supported by a commercial cloud provider

NASA Astrophysics Data System (ADS)

Tat Cheung, Kwong; Field, Laurence; Furano, Fabrizio

2017-10-01

Volunteer computing has the potential to provide significant additional computing capacity for the LHC experiments. One of the challenges with exploiting volunteer computing is to support a global community of volunteers that provides heterogeneous resources. However, high energy physics applications require more data input and output than the CPU intensive applications that are typically used by other volunteer computing projects. While the so-called databridge has already been successfully proposed as a method to span the untrusted and trusted domains of volunteer computing and Grid computing respective, globally transferring data between potentially poor-performing residential networks and CERN could be unreliable, leading to wasted resources usage. The expectation is that by placing a storage endpoint that is part of a wider, flexible geographical databridge deployment closer to the volunteers, the transfer success rate and the overall performance can be improved. This contribution investigates the provision of a globally distributed databridge implemented upon a commercial cloud provider.

The structure of the clouds distributed operating system

NASA Technical Reports Server (NTRS)

Dasgupta, Partha; Leblanc, Richard J., Jr.

1989-01-01

A novel system architecture, based on the object model, is the central structuring concept used in the Clouds distributed operating system. This architecture makes Clouds attractive over a wide class of machines and environments. Clouds is a native operating system, designed and implemented at Georgia Tech. and runs on a set of generated purpose computers connected via a local area network. The system architecture of Clouds is composed of a system-wide global set of persistent (long-lived) virtual address spaces, called objects that contain persistent data and code. The object concept is implemented at the operating system level, thus presenting a single level storage view to the user. Lightweight treads carry computational activity through the code stored in the objects. The persistent objects and threads gives rise to a programming environment composed of shared permanent memory, dispensing with the need for hardware-derived concepts such as the file systems and message systems. Though the hardware may be distributed and may have disks and networks, the Clouds provides the applications with a logically centralized system, based on a shared, structured, single level store. The current design of Clouds uses a minimalist philosophy with respect to both the kernel and the operating system. That is, the kernel and the operating system support a bare minimum of functionality. Clouds also adheres to the concept of separation of policy and mechanism. Most low-level operating system services are implemented above the kernel and most high level services are implemented at the user level. From the measured performance of using the kernel mechanisms, we are able to demonstrate that efficient implementations are feasible for the object model on commercially available hardware. Clouds provides a rich environment for conducting research in distributed systems. Some of the topics addressed in this paper include distributed programming environments, consistency of persistent data and fault-tolerance.

An interactive web-based system using cloud for large-scale visual analytics

NASA Astrophysics Data System (ADS)

Kaseb, Ahmed S.; Berry, Everett; Rozolis, Erik; McNulty, Kyle; Bontrager, Seth; Koh, Youngsol; Lu, Yung-Hsiang; Delp, Edward J.

2015-03-01

Network cameras have been growing rapidly in recent years. Thousands of public network cameras provide tremendous amount of visual information about the environment. There is a need to analyze this valuable information for a better understanding of the world around us. This paper presents an interactive web-based system that enables users to execute image analysis and computer vision techniques on a large scale to analyze the data from more than 65,000 worldwide cameras. This paper focuses on how to use both the system's website and Application Programming Interface (API). Given a computer program that analyzes a single frame, the user needs to make only slight changes to the existing program and choose the cameras to analyze. The system handles the heterogeneity of the geographically distributed cameras, e.g. different brands, resolutions. The system allocates and manages Amazon EC2 and Windows Azure cloud resources to meet the analysis requirements.

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.

Machine learning based Intelligent cognitive network using fog computing

NASA Astrophysics Data System (ADS)

Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik

2017-05-01

In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.

MapReduce Algorithms for Inferring Gene Regulatory Networks from Time-Series Microarray Data Using an Information-Theoretic Approach.

PubMed

Abduallah, Yasser; Turki, Turki; Byron, Kevin; Du, Zongxuan; Cervantes-Cervantes, Miguel; Wang, Jason T L

2017-01-01

Gene regulation is a series of processes that control gene expression and its extent. The connections among genes and their regulatory molecules, usually transcription factors, and a descriptive model of such connections are known as gene regulatory networks (GRNs). Elucidating GRNs is crucial to understand the inner workings of the cell and the complexity of gene interactions. To date, numerous algorithms have been developed to infer gene regulatory networks. However, as the number of identified genes increases and the complexity of their interactions is uncovered, networks and their regulatory mechanisms become cumbersome to test. Furthermore, prodding through experimental results requires an enormous amount of computation, resulting in slow data processing. Therefore, new approaches are needed to expeditiously analyze copious amounts of experimental data resulting from cellular GRNs. To meet this need, cloud computing is promising as reported in the literature. Here, we propose new MapReduce algorithms for inferring gene regulatory networks on a Hadoop cluster in a cloud environment. These algorithms employ an information-theoretic approach to infer GRNs using time-series microarray data. Experimental results show that our MapReduce program is much faster than an existing tool while achieving slightly better prediction accuracy than the existing tool.

The Clouds distributed operating system - Functional description, implementation details and related work

NASA Technical Reports Server (NTRS)

Dasgupta, Partha; Leblanc, Richard J., Jr.; Appelbe, William F.

1988-01-01

Clouds is an operating system in a novel class of distributed operating systems providing the integration, reliability, and structure that makes a distributed system usable. Clouds is designed to run on a set of general purpose computers that are connected via a medium-of-high speed local area network. The system structuring paradigm chosen for the Clouds operating system, after substantial research, is an object/thread model. All instances of services, programs and data in Clouds are encapsulated in objects. The concept of persistent objects does away with the need for file systems, and replaces it with a more powerful concept, namely the object system. The facilities in Clouds include integration of resources through location transparency; support for various types of atomic operations, including conventional transactions; advanced support for achieving fault tolerance; and provisions for dynamic reconfiguration.

Measuring and Evaluating TCP Splitting for Cloud Services

NASA Astrophysics Data System (ADS)

Pathak, Abhinav; Wang, Y. Angela; Huang, Cheng; Greenberg, Albert; Hu, Y. Charlie; Kern, Randy; Li, Jin; Ross, Keith W.

In this paper, we examine the benefits of split-TCP proxies, deployed in an operational world-wide network, for accelerating cloud services. We consider a fraction of a network consisting of a large number of satellite datacenters, which host split-TCP proxies, and a smaller number of mega datacenters, which ultimately perform computation or provide storage. Using web search as an exemplary case study, our detailed measurements reveal that a vanilla TCP splitting solution deployed at the satellite DCs reduces the 95 th percentile of latency by as much as 43% when compared to serving queries directly from the mega DCs. Through careful dissection of the measurement results, we characterize how individual components, including proxy stacks, network protocols, packet losses and network load, can impact the latency. Finally, we shed light on further optimizations that can fully realize the potential of the TCP splitting solution.

ATLAS computing on Swiss Cloud SWITCHengines

NASA Astrophysics Data System (ADS)

Haug, S.; Sciacca, F. G.; ATLAS Collaboration

2017-10-01

Consolidation towards more computing at flat budgets beyond what pure chip technology can offer, is a requirement for the full scientific exploitation of the future data from the Large Hadron Collider at CERN in Geneva. One consolidation measure is to exploit cloud infrastructures whenever they are financially competitive. We report on the technical solutions and the performances used and achieved running simulation tasks for the ATLAS experiment on SWITCHengines. SWITCHengines is a new infrastructure as a service offered to Swiss academia by the National Research and Education Network SWITCH. While solutions and performances are general, financial considerations and policies, on which we also report, are country specific.

Extending the farm on external sites: the INFN Tier-1 experience

NASA Astrophysics Data System (ADS)

Boccali, T.; Cavalli, A.; Chiarelli, L.; Chierici, A.; Cesini, D.; Ciaschini, V.; Dal Pra, S.; dell'Agnello, L.; De Girolamo, D.; Falabella, A.; Fattibene, E.; Maron, G.; Prosperini, A.; Sapunenko, V.; Virgilio, S.; Zani, S.

2017-10-01

The Tier-1 at CNAF is the main INFN computing facility offering computing and storage resources to more than 30 different scientific collaborations including the 4 experiments at the LHC. It is also foreseen a huge increase in computing needs in the following years mainly driven by the experiments at the LHC (especially starting with the run 3 from 2021) but also by other upcoming experiments such as CTA[1] While we are considering the upgrade of the infrastructure of our data center, we are also evaluating the possibility of using CPU resources available in other data centres or even leased from commercial cloud providers. Hence, at INFN Tier-1, besides participating to the EU project HNSciCloud, we have also pledged a small amount of computing resources (˜ 2000 cores) located at the Bari ReCaS[2] for the WLCG experiments for 2016 and we are testing the use of resources provided by a commercial cloud provider. While the Bari ReCaS data center is directly connected to the GARR network[3] with the obvious advantage of a low latency and high bandwidth connection, in the case of the commercial provider we rely only on the General Purpose Network. In this paper we describe the set-up phase and the first results of these installations started in the last quarter of 2015, focusing on the issues that we have had to cope with and discussing the measured results in terms of efficiency.

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.

Decadal GPS Time Series and Velocity Fields Spanning the North American Continent and Beyond: New Data Products, Cyberinfrastructure and Case Studies from the EarthScope Plate Boundary Observatory (PBO) and Other Regional Networks

NASA Astrophysics Data System (ADS)

Phillips, D. A.; Herring, T.; Melbourne, T. I.; Murray, M. H.; Szeliga, W. M.; Floyd, M.; Puskas, C. M.; King, R. W.; Boler, F. M.; Meertens, C. M.; Mattioli, G. S.

2017-12-01

The Geodesy Advancing Geosciences and EarthScope (GAGE) Facility, operated by UNAVCO, provides a diverse suite of geodetic data, derived products and cyberinfrastructure services to support community Earth science research and education. GPS data and products including decadal station position time series and velocities are provided for 2000+ continuous GPS stations from the Plate Boundary Observatory (PBO) and other networks distributed throughout the high Arctic, North America, and Caribbean regions. The position time series contain a multitude of signals in addition to the secular motions, including coseismic and postseismic displacements, interseismic strain accumulation, and transient signals associated with hydrologic and other processes. We present our latest velocity field solutions, new time series offset estimate products, and new time series examples associated with various phenomena. Position time series, and the signals they contain, are inherently dependent upon analysis parameters such as network scaling and reference frame realization. The estimation of scale changes for example, a common practice, has large impacts on vertical motion estimates. GAGE/PBO velocities and time series are currently provided in IGS (IGb08) and North America (NAM08, IGb08 rotated to a fixed North America Plate) reference frames. We are reprocessing all data (1996 to present) as part of the transition from IGb08 to IGS14 that began in 2017. New NAM14 and IGS14 data products are discussed. GAGE/PBO GPS data products are currently generated using onsite computing clusters. As part of an NSF funded EarthCube Building Blocks project called "Deploying MultiFacility Cyberinfrastructure in Commercial and Private Cloud-based Systems (GeoSciCloud)", we are investigating performance, cost, and efficiency differences between local computing resources and cloud based resources. Test environments include a commercial cloud provider (Amazon/AWS), NSF cloud-like infrastructures within XSEDE (TACC, the Texas Advanced Computing Center), and in-house cyberinfrastructures. Preliminary findings from this effort are presented. Web services developed by UNAVCO to facilitate the discovery, customization and dissemination of GPS data and products are also presented.

Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis.

PubMed

Pan, Yuchen; Ding, Shuai; Fan, Wenjuan; Li, Jing; Yang, Shanlin

2015-01-01

Cloud computing technology plays a very important role in many areas, such as in the construction and development of the smart city. Meanwhile, numerous cloud services appear on the cloud-based platform. Therefore how to how to select trustworthy cloud services remains a significant problem in such platforms, and extensively investigated owing to the ever-growing needs of users. However, trust relationship in social network has not been taken into account in existing methods of cloud service selection and recommendation. In this paper, we propose a cloud service selection model based on the trust-enhanced similarity. Firstly, the direct, indirect, and hybrid trust degrees are measured based on the interaction frequencies among users. Secondly, we estimate the overall similarity by combining the experience usability measured based on Jaccard's Coefficient and the numerical distance computed by Pearson Correlation Coefficient. Then through using the trust degree to modify the basic similarity, we obtain a trust-enhanced similarity. Finally, we utilize the trust-enhanced similarity to find similar trusted neighbors and predict the missing QoS values as the basis of cloud service selection and recommendation. The experimental results show that our approach is able to obtain optimal results via adjusting parameters and exhibits high effectiveness. The cloud services ranking by our model also have better QoS properties than other methods in the comparison experiments.

Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis

PubMed Central

Pan, Yuchen; Ding, Shuai; Fan, Wenjuan; Li, Jing; Yang, Shanlin

2015-01-01

Cloud computing technology plays a very important role in many areas, such as in the construction and development of the smart city. Meanwhile, numerous cloud services appear on the cloud-based platform. Therefore how to how to select trustworthy cloud services remains a significant problem in such platforms, and extensively investigated owing to the ever-growing needs of users. However, trust relationship in social network has not been taken into account in existing methods of cloud service selection and recommendation. In this paper, we propose a cloud service selection model based on the trust-enhanced similarity. Firstly, the direct, indirect, and hybrid trust degrees are measured based on the interaction frequencies among users. Secondly, we estimate the overall similarity by combining the experience usability measured based on Jaccard’s Coefficient and the numerical distance computed by Pearson Correlation Coefficient. Then through using the trust degree to modify the basic similarity, we obtain a trust-enhanced similarity. Finally, we utilize the trust-enhanced similarity to find similar trusted neighbors and predict the missing QoS values as the basis of cloud service selection and recommendation. The experimental results show that our approach is able to obtain optimal results via adjusting parameters and exhibits high effectiveness. The cloud services ranking by our model also have better QoS properties than other methods in the comparison experiments. PMID:26606388

Dynamic Integration of Mobile JXTA with Cloud Computing for Emergency Rural Public Health Care

PubMed Central

Rajkumar, Rajasekaran; Sriman Narayana Iyengar, Nallani Chackravatula

2013-01-01

Objectives The existing processes of health care systems where data collection requires a great deal of labor with high-end tasks to retrieve and analyze information, are usually slow, tedious, and error prone, which restrains their clinical diagnostic and monitoring capabilities. Research is now focused on integrating cloud services with P2P JXTA to identify systematic dynamic process for emergency health care systems. The proposal is based on the concepts of a community cloud for preventative medicine, to help promote a healthy rural community. We investigate the approaches of patient health monitoring, emergency care, and an ambulance alert alarm (AAA) under mobile cloud-based telecare or community cloud controller systems. Methods Considering permanent mobile users, an efficient health promotion method is proposed. Experiments were conducted to verify the effectiveness of the method. The performance was evaluated from September 2011 to July 2012. A total of 1,856,454 cases were transported and referred to hospital, identified with health problems, and were monitored. We selected all the peer groups and the control server N0 which controls N1, N2, and N3 proxied peer groups. The hospital cloud controller maintains the database of the patients through a JXTA network. Results Among 1,856,454 transported cases with beneficiaries of 1,712,877 cases there were 1,662,834 lives saved and 8,500 cases transported per day with 104,530 transported cases found to be registered in a JXTA network. Conclusion The registered case histories were referred from the Hospital community cloud (HCC). SMS messages were sent from node N0 to the relay peers which connected to the N1, N2, and N3 nodes, controlled by the cloud controller through a JXTA network. PMID:24298441

Dynamic Integration of Mobile JXTA with Cloud Computing for Emergency Rural Public Health Care.

PubMed

Rajkumar, Rajasekaran; Sriman Narayana Iyengar, Nallani Chackravatula

2013-10-01

The existing processes of health care systems where data collection requires a great deal of labor with high-end tasks to retrieve and analyze information, are usually slow, tedious, and error prone, which restrains their clinical diagnostic and monitoring capabilities. Research is now focused on integrating cloud services with P2P JXTA to identify systematic dynamic process for emergency health care systems. The proposal is based on the concepts of a community cloud for preventative medicine, to help promote a healthy rural community. We investigate the approaches of patient health monitoring, emergency care, and an ambulance alert alarm (AAA) under mobile cloud-based telecare or community cloud controller systems. Considering permanent mobile users, an efficient health promotion method is proposed. Experiments were conducted to verify the effectiveness of the method. The performance was evaluated from September 2011 to July 2012. A total of 1,856,454 cases were transported and referred to hospital, identified with health problems, and were monitored. We selected all the peer groups and the control server N0 which controls N1, N2, and N3 proxied peer groups. The hospital cloud controller maintains the database of the patients through a JXTA network. Among 1,856,454 transported cases with beneficiaries of 1,712,877 cases there were 1,662,834 lives saved and 8,500 cases transported per day with 104,530 transported cases found to be registered in a JXTA network. The registered case histories were referred from the Hospital community cloud (HCC). SMS messages were sent from node N0 to the relay peers which connected to the N1, N2, and N3 nodes, controlled by the cloud controller through a JXTA network.

Government Cloud Computing Policies: Potential Opportunities for Advancing Military Biomedical Research.

PubMed

Lebeda, Frank J; Zalatoris, Jeffrey J; Scheerer, Julia B

2018-02-07

This position paper summarizes the development and the present status of Department of Defense (DoD) and other government policies and guidances regarding cloud computing services. Due to the heterogeneous and growing biomedical big datasets, cloud computing services offer an opportunity to mitigate the associated storage and analysis requirements. Having on-demand network access to a shared pool of flexible computing resources creates a consolidated system that should reduce potential duplications of effort in military biomedical research. Interactive, online literature searches were performed with Google, at the Defense Technical Information Center, and at two National Institutes of Health research portfolio information sites. References cited within some of the collected documents also served as literature resources. We gathered, selected, and reviewed DoD and other government cloud computing policies and guidances published from 2009 to 2017. These policies were intended to consolidate computer resources within the government and reduce costs by decreasing the number of federal data centers and by migrating electronic data to cloud systems. Initial White House Office of Management and Budget information technology guidelines were developed for cloud usage, followed by policies and other documents from the DoD, the Defense Health Agency, and the Armed Services. Security standards from the National Institute of Standards and Technology, the Government Services Administration, the DoD, and the Army were also developed. Government Services Administration and DoD Inspectors General monitored cloud usage by the DoD. A 2016 Government Accountability Office report characterized cloud computing as being economical, flexible and fast. A congressionally mandated independent study reported that the DoD was active in offering a wide selection of commercial cloud services in addition to its milCloud system. Our findings from the Department of Health and Human Services indicated that the security infrastructure in cloud services may be more compliant with the Health Insurance Portability and Accountability Act of 1996 regulations than traditional methods. To gauge the DoD's adoption of cloud technologies proposed metrics included cost factors, ease of use, automation, availability, accessibility, security, and policy compliance. Since 2009, plans and policies were developed for the use of cloud technology to help consolidate and reduce the number of data centers which were expected to reduce costs, improve environmental factors, enhance information technology security, and maintain mission support for service members. Cloud technologies were also expected to improve employee efficiency and productivity. Federal cloud computing policies within the last decade also offered increased opportunities to advance military healthcare. It was assumed that these opportunities would benefit consumers of healthcare and health science data by allowing more access to centralized cloud computer facilities to store, analyze, search and share relevant data, to enhance standardization, and to reduce potential duplications of effort. We recommend that cloud computing be considered by DoD biomedical researchers for increasing connectivity, presumably by facilitating communications and data sharing, among the various intra- and extramural laboratories. We also recommend that policies and other guidances be updated to include developing additional metrics that will help stakeholders evaluate the above mentioned assumptions and expectations. Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2018. This work is written by (a) US Government employee(s) and is in the public domain in the US.

A New Heuristic Anonymization Technique for Privacy Preserved Datasets Publication on Cloud Computing

NASA Astrophysics Data System (ADS)

Aldeen Yousra, S.; Mazleena, Salleh

2018-05-01

Recent advancement in Information and Communication Technologies (ICT) demanded much of cloud services to sharing users’ private data. Data from various organizations are the vital information source for analysis and research. Generally, this sensitive or private data information involves medical, census, voter registration, social network, and customer services. Primary concern of cloud service providers in data publishing is to hide the sensitive information of individuals. One of the cloud services that fulfill the confidentiality concerns is Privacy Preserving Data Mining (PPDM). The PPDM service in Cloud Computing (CC) enables data publishing with minimized distortion and absolute privacy. In this method, datasets are anonymized via generalization to accomplish the privacy requirements. However, the well-known privacy preserving data mining technique called K-anonymity suffers from several limitations. To surmount those shortcomings, I propose a new heuristic anonymization framework for preserving the privacy of sensitive datasets when publishing on cloud. The advantages of K-anonymity, L-diversity and (α, k)-anonymity methods for efficient information utilization and privacy protection are emphasized. Experimental results revealed the superiority and outperformance of the developed technique than K-anonymity, L-diversity, and (α, k)-anonymity measure.

Use of several Cloud Computing approaches for climate modelling: performance, costs and opportunities

NASA Astrophysics Data System (ADS)

Perez Montes, Diego A.; Añel Cabanelas, Juan A.; Wallom, David C. H.; Arribas, Alberto; Uhe, Peter; Caderno, Pablo V.; Pena, Tomas F.

2017-04-01

Cloud Computing is a technological option that offers great possibilities for modelling in geosciences. We have studied how two different climate models, HadAM3P-HadRM3P and CESM-WACCM, can be adapted in two different ways to run on Cloud Computing Environments from three different vendors: Amazon, Google and Microsoft. Also, we have evaluated qualitatively how the use of Cloud Computing can affect the allocation of resources by funding bodies and issues related to computing security, including scientific reproducibility. Our first experiments were developed using the well known ClimatePrediction.net (CPDN), that uses BOINC, over the infrastructure from two cloud providers, namely Microsoft Azure and Amazon Web Services (hereafter AWS). For this comparison we ran a set of thirteen month climate simulations for CPDN in Azure and AWS using a range of different virtual machines (VMs) for HadRM3P (50 km resolution over South America CORDEX region) nested in the global atmosphere-only model HadAM3P. These simulations were run on a single processor and took between 3 and 5 days to compute depending on the VM type. The last part of our simulation experiments was running WACCM over different VMS on the Google Compute Engine (GCE) and make a comparison with the supercomputer (SC) Finisterrae1 from the Centro de Supercomputacion de Galicia. It was shown that GCE gives better performance than the SC for smaller number of cores/MPI tasks but the model throughput shows clearly how the SC performance is better after approximately 100 cores (related with network speed and latency differences). From a cost point of view, Cloud Computing moves researchers from a traditional approach where experiments were limited by the available hardware resources to monetary resources (how many resources can be afforded). As there is an increasing movement and recommendation for budgeting HPC projects on this technology (budgets can be calculated in a more realistic way) we could see a shift on the trends over the next years to consolidate Cloud as the preferred solution.

Design and implementation of a reliable and cost-effective cloud computing infrastructure: the INFN Napoli experience

NASA Astrophysics Data System (ADS)

Capone, V.; Esposito, R.; Pardi, S.; Taurino, F.; Tortone, G.

2012-12-01

Over the last few years we have seen an increasing number of services and applications needed to manage and maintain cloud computing facilities. This is particularly true for computing in high energy physics, which often requires complex configurations and distributed infrastructures. In this scenario a cost effective rationalization and consolidation strategy is the key to success in terms of scalability and reliability. In this work we describe an IaaS (Infrastructure as a Service) cloud computing system, with high availability and redundancy features, which is currently in production at INFN-Naples and ATLAS Tier-2 data centre. The main goal we intended to achieve was a simplified method to manage our computing resources and deliver reliable user services, reusing existing hardware without incurring heavy costs. A combined usage of virtualization and clustering technologies allowed us to consolidate our services on a small number of physical machines, reducing electric power costs. As a result of our efforts we developed a complete solution for data and computing centres that can be easily replicated using commodity hardware. Our architecture consists of 2 main subsystems: a clustered storage solution, built on top of disk servers running GlusterFS file system, and a virtual machines execution environment. GlusterFS is a network file system able to perform parallel writes on multiple disk servers, providing this way live replication of data. High availability is also achieved via a network configuration using redundant switches and multiple paths between hypervisor hosts and disk servers. We also developed a set of management scripts to easily perform basic system administration tasks such as automatic deployment of new virtual machines, adaptive scheduling of virtual machines on hypervisor hosts, live migration and automated restart in case of hypervisor failures.

FRR: fair remote retrieval of outsourced private medical records in electronic health networks.

PubMed

Wang, Huaqun; Wu, Qianhong; Qin, Bo; Domingo-Ferrer, Josep

2014-08-01

Cloud computing is emerging as the next-generation IT architecture. However, cloud computing also raises security and privacy concerns since the users have no physical control over the outsourced data. This paper focuses on fairly retrieving encrypted private medical records outsourced to remote untrusted cloud servers in the case of medical accidents and disputes. Our goal is to enable an independent committee to fairly recover the original private medical records so that medical investigation can be carried out in a convincing way. We achieve this goal with a fair remote retrieval (FRR) model in which either t investigation committee members cooperatively retrieve the original medical data or none of them can get any information on the medical records. We realize the first FRR scheme by exploiting fair multi-member key exchange and homomorphic privately verifiable tags. Based on the standard computational Diffie-Hellman (CDH) assumption, our scheme is provably secure in the random oracle model (ROM). A detailed performance analysis and experimental results show that our scheme is efficient in terms of communication and computation. Copyright © 2014 Elsevier Inc. All rights reserved.

Cloud Computing Fundamentals

NASA Astrophysics Data System (ADS)

Furht, Borko

In the introductory chapter we define the concept of cloud computing and cloud services, and we introduce layers and types of cloud computing. We discuss the differences between cloud computing and cloud services. New technologies that enabled cloud computing are presented next. We also discuss cloud computing features, standards, and security issues. We introduce the key cloud computing platforms, their vendors, and their offerings. We discuss cloud computing challenges and the future of cloud computing.

Virtualized Networks and Virtualized Optical Line Terminal (vOLT)

NASA Astrophysics Data System (ADS)

Ma, Jonathan; Israel, Stephen

2017-03-01

The success of the Internet and the proliferation of the Internet of Things (IoT) devices is forcing telecommunications carriers to re-architecture a central office as a datacenter (CORD) so as to bring the datacenter economics and cloud agility to a central office (CO). The Open Network Operating System (ONOS) is the first open-source software-defined network (SDN) operating system which is capable of managing and controlling network, computing, and storage resources to support CORD infrastructure and network virtualization. The virtualized Optical Line Termination (vOLT) is one of the key components in such virtualized networks.

Automatic identification of watercourses in flat and engineered landscapes by computing the skeleton of a LiDAR point cloud

NASA Astrophysics Data System (ADS)

Broersen, Tom; Peters, Ravi; Ledoux, Hugo

2017-09-01

Drainage networks play a crucial role in protecting land against floods. It is therefore important to have an accurate map of the watercourses that form the drainage network. Previous work on the automatic identification of watercourses was typically based on grids, focused on natural landscapes, and used mostly the slope and curvature of the terrain. We focus in this paper on areas that are characterised by low-lying, flat, and engineered landscapes; these are characteristic to the Netherlands for instance. We propose a new methodology to identify watercourses automatically from elevation data, it uses solely a raw classified LiDAR point cloud as input. We show that by computing twice a skeleton of the point cloud-once in 2D and once in 3D-and that by using the properties of the skeletons we can identify most of the watercourses. We have implemented our methodology and tested it for three different soil types around Utrecht, the Netherlands. We were able to detect 98% of the watercourses for one soil type, and around 75% for the worst case, when we compared to a reference dataset that was obtained semi-automatically.

Mobile cloud-computing-based healthcare service by noncontact ECG monitoring.

PubMed

Fong, Ee-May; Chung, Wan-Young

2013-12-02

Noncontact electrocardiogram (ECG) measurement technique has gained popularity these days owing to its noninvasive features and convenience in daily life use. This paper presents mobile cloud computing for a healthcare system where a noncontact ECG measurement method is employed to capture biomedical signals from users. Healthcare service is provided to continuously collect biomedical signals from multiple locations. To observe and analyze the ECG signals in real time, a mobile device is used as a mobile monitoring terminal. In addition, a personalized healthcare assistant is installed on the mobile device; several healthcare features such as health status summaries, medication QR code scanning, and reminders are integrated into the mobile application. Health data are being synchronized into the healthcare cloud computing service (Web server system and Web server dataset) to ensure a seamless healthcare monitoring system and anytime and anywhere coverage of network connection is available. Together with a Web page application, medical data are easily accessed by medical professionals or family members. Web page performance evaluation was conducted to ensure minimal Web server latency. The system demonstrates better availability of off-site and up-to-the-minute patient data, which can help detect health problems early and keep elderly patients out of the emergency room, thus providing a better and more comprehensive healthcare cloud computing service.

Mobile Cloud-Computing-Based Healthcare Service by Noncontact ECG Monitoring

PubMed Central

Fong, Ee-May; Chung, Wan-Young

2013-01-01

Noncontact electrocardiogram (ECG) measurement technique has gained popularity these days owing to its noninvasive features and convenience in daily life use. This paper presents mobile cloud computing for a healthcare system where a noncontact ECG measurement method is employed to capture biomedical signals from users. Healthcare service is provided to continuously collect biomedical signals from multiple locations. To observe and analyze the ECG signals in real time, a mobile device is used as a mobile monitoring terminal. In addition, a personalized healthcare assistant is installed on the mobile device; several healthcare features such as health status summaries, medication QR code scanning, and reminders are integrated into the mobile application. Health data are being synchronized into the healthcare cloud computing service (Web server system and Web server dataset) to ensure a seamless healthcare monitoring system and anytime and anywhere coverage of network connection is available. Together with a Web page application, medical data are easily accessed by medical professionals or family members. Web page performance evaluation was conducted to ensure minimal Web server latency. The system demonstrates better availability of off-site and up-to-the-minute patient data, which can help detect health problems early and keep elderly patients out of the emergency room, thus providing a better and more comprehensive healthcare cloud computing service. PMID:24316562

Human Computer Interaction (HCI) and Internet Residency: Implications for Both Personal Life and Teaching/Learning

ERIC Educational Resources Information Center

Crearie, Linda

2016-01-01

Technological advances over the last decade have had a significant impact on the teaching and learning experiences students encounter today. We now take technologies such as Web 2.0, mobile devices, cloud computing, podcasts, social networking, super-fast broadband, and connectedness for granted. So what about the student use of these types of…

Astrochem: Abundances of chemical species in the interstellar medium

NASA Astrophysics Data System (ADS)

Maret, Sébastien; Bergin, Edwin A.

2015-07-01

Astrochem computes the abundances of chemical species in the interstellar medium, as function of time. It studies the chemistry in a variety of astronomical objects, including diffuse clouds, dense clouds, photodissociation regions, prestellar cores, protostars, and protostellar disks. Astrochem reads a network of chemical reactions from a text file, builds up a system of kinetic rates equations, and solves it using a state-of-the-art stiff ordinary differential equation (ODE) solver. The Jacobian matrix of the system is computed implicitly, so the resolution of the system is extremely fast: large networks containing several thousands of reactions are usually solved in a few seconds. A variety of gas phase process are considered, as well as simple gas-grain interactions, such as the freeze-out and the desorption via several mechanisms (thermal desorption, cosmic-ray desorption and photo-desorption). The computed abundances are written in a HDF5 file, and can be plotted in different ways with the tools provided with Astrochem. Chemical reactions and their rates are written in a format which is meant to be easy to read and to edit. A tool to convert the chemical networks from the OSU and KIDA databases into this format is also provided. Astrochem is written in C, and its source code is distributed under the terms of the GNU General Public License (GPL).

Approaches in highly parameterized inversion-PESTCommander, a graphical user interface for file and run management across networks

USGS Publications Warehouse

Karanovic, Marinko; Muffels, Christopher T.; Tonkin, Matthew J.; Hunt, Randall J.

2012-01-01

Models of environmental systems have become increasingly complex, incorporating increasingly large numbers of parameters in an effort to represent physical processes on a scale approaching that at which they occur in nature. Consequently, the inverse problem of parameter estimation (specifically, model calibration) and subsequent uncertainty analysis have become increasingly computation-intensive endeavors. Fortunately, advances in computing have made computational power equivalent to that of dozens to hundreds of desktop computers accessible through a variety of alternate means: modelers have various possibilities, ranging from traditional Local Area Networks (LANs) to cloud computing. Commonly used parameter estimation software is well suited to take advantage of the availability of such increased computing power. Unfortunately, logistical issues become increasingly important as an increasing number and variety of computers are brought to bear on the inverse problem. To facilitate efficient access to disparate computer resources, the PESTCommander program documented herein has been developed to provide a Graphical User Interface (GUI) that facilitates the management of model files ("file management") and remote launching and termination of "slave" computers across a distributed network of computers ("run management"). In version 1.0 described here, PESTCommander can access and ascertain resources across traditional Windows LANs: however, the architecture of PESTCommander has been developed with the intent that future releases will be able to access computing resources (1) via trusted domains established in Wide Area Networks (WANs) in multiple remote locations and (2) via heterogeneous networks of Windows- and Unix-based operating systems. The design of PESTCommander also makes it suitable for extension to other computational resources, such as those that are available via cloud computing. Version 1.0 of PESTCommander was developed primarily to work with the parameter estimation software PEST; the discussion presented in this report focuses on the use of the PESTCommander together with Parallel PEST. However, PESTCommander can be used with a wide variety of programs and models that require management, distribution, and cleanup of files before or after model execution. In addition to its use with the Parallel PEST program suite, discussion is also included in this report regarding the use of PESTCommander with the Global Run Manager GENIE, which was developed simultaneously with PESTCommander.

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

Cloud Computing and Virtual Desktop Infrastructures in Afloat Environments

DTIC Science & Technology

2012-06-01

Institute of Standards and Technology NPS Naval Postgraduate School OCONUS Outside of the Continental United States ONE- NET OCONUS Navy Enterprise... framework of technology that allows all interested systems, inside and outside of an organization, to expose and access well-defined services, and...was established to manage the Navy’s three largest enterprise networks; the OCONUS Navy Enterprise 22 Network (ONE- NET ), the Navy-Marine Corps

Automation of multi-agent control for complex dynamic systems in heterogeneous computational network

NASA Astrophysics Data System (ADS)

Oparin, Gennady; Feoktistov, Alexander; Bogdanova, Vera; Sidorov, Ivan

2017-01-01

The rapid progress of high-performance computing entails new challenges related to solving large scientific problems for various subject domains in a heterogeneous distributed computing environment (e.g., a network, Grid system, or Cloud infrastructure). The specialists in the field of parallel and distributed computing give the special attention to a scalability of applications for problem solving. An effective management of the scalable application in the heterogeneous distributed computing environment is still a non-trivial issue. Control systems that operate in networks, especially relate to this issue. We propose a new approach to the multi-agent management for the scalable applications in the heterogeneous computational network. The fundamentals of our approach are the integrated use of conceptual programming, simulation modeling, network monitoring, multi-agent management, and service-oriented programming. We developed a special framework for an automation of the problem solving. Advantages of the proposed approach are demonstrated on the parametric synthesis example of the static linear regulator for complex dynamic systems. Benefits of the scalable application for solving this problem include automation of the multi-agent control for the systems in a parallel mode with various degrees of its detailed elaboration.

A robust cloud registration method based on redundant data reduction using backpropagation neural network and shift window

NASA Astrophysics Data System (ADS)

Xin, Meiting; Li, Bing; Yan, Xiao; Chen, Lei; Wei, Xiang

2018-02-01

A robust coarse-to-fine registration method based on the backpropagation (BP) neural network and shift window technology is proposed in this study. Specifically, there are three steps: coarse alignment between the model data and measured data, data simplification based on the BP neural network and point reservation in the contour region of point clouds, and fine registration with the reweighted iterative closest point algorithm. In the process of rough alignment, the initial rotation matrix and the translation vector between the two datasets are obtained. After performing subsequent simplification operations, the number of points can be reduced greatly. Therefore, the time and space complexity of the accurate registration can be significantly reduced. The experimental results show that the proposed method improves the computational efficiency without loss of accuracy.

Statistical retrieval of thin liquid cloud microphysical properties using ground-based infrared and microwave observations

NASA Astrophysics Data System (ADS)

Marke, Tobias; Ebell, Kerstin; Löhnert, Ulrich; Turner, David D.

2016-12-01

In this article, liquid water cloud microphysical properties are retrieved by a combination of microwave and infrared ground-based observations. Clouds containing liquid water are frequently occurring in most climate regimes and play a significant role in terms of interaction with radiation. Small perturbations in the amount of liquid water contained in the cloud can cause large variations in the radiative fluxes. This effect is enhanced for thin clouds (liquid water path, LWP <100 g/m2), which makes accurate retrieval information of the cloud properties crucial. Due to large relative errors in retrieving low LWP values from observations in the microwave domain and a high sensitivity for infrared methods when the LWP is low, a synergistic retrieval based on a neural network approach is built to estimate both LWP and cloud effective radius (reff). These statistical retrievals can be applied without high computational demand but imply constraints like prior information on cloud phase and cloud layering. The neural network retrievals are able to retrieve LWP and reff for thin clouds with a mean relative error of 9% and 17%, respectively. This is demonstrated using synthetic observations of a microwave radiometer (MWR) and a spectrally highly resolved infrared interferometer. The accuracy and robustness of the synergistic retrievals is confirmed by a low bias in a radiative closure study for the downwelling shortwave flux, even for marginally invalid scenes. Also, broadband infrared radiance observations, in combination with the MWR, have the potential to retrieve LWP with a higher accuracy than a MWR-only retrieval.

A cloud-based X73 ubiquitous mobile healthcare system: design and implementation.

PubMed

Ji, Zhanlin; Ganchev, Ivan; O'Droma, Máirtín; Zhang, Xin; Zhang, Xueji

2014-01-01

Based on the user-centric paradigm for next generation networks, this paper describes a ubiquitous mobile healthcare (uHealth) system based on the ISO/IEEE 11073 personal health data (PHD) standards (X73) and cloud computing techniques. A number of design issues associated with the system implementation are outlined. The system includes a middleware on the user side, providing a plug-and-play environment for heterogeneous wireless sensors and mobile terminals utilizing different communication protocols and a distributed "big data" processing subsystem in the cloud. The design and implementation of this system are envisaged as an efficient solution for the next generation of uHealth systems.

Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles.

PubMed

Wan, Jiafu; Liu, Jianqi; Shao, Zehui; Vasilakos, Athanasios V; Imran, Muhammad; Zhou, Keliang

2016-01-11

The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV. Then, we review the traditional traffic prediction approached used by both Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications. On this basis, we propose a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion. Experiments were carried out to verify the proposed approaches. Finally, we discuss the outlook of reliable traffic prediction.

Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles

PubMed Central

Wan, Jiafu; Liu, Jianqi; Shao, Zehui; Vasilakos, Athanasios V.; Imran, Muhammad; Zhou, Keliang

2016-01-01

The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV. Then, we review the traditional traffic prediction approached used by both Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications. On this basis, we propose a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion. Experiments were carried out to verify the proposed approaches. Finally, we discuss the outlook of reliable traffic prediction. PMID:26761013

User friendly IT Services for Monitoring and Prevention during Pregnancy.

PubMed

Crişan-Vida, Mihaela; Serban, Alexandru; Ghihor-Izdrăilă, Ioana; Mirea, Adrian; Stoicu-Tivadar, Lacramioara

2014-01-01

A healthy lifestyle for a mother and monitoring both mother and fetus activities are crucial factors for a normal pregnancy without hazardous conditions. This paper proposes a cloud computing solution and a mobile application which collect data from the sensors to be used in Obstetrics-Gynecology Department. This application monitors the dietary plan of the pregnant and gives her the possibility to socialize and share pregnancy experience with the rest of women from the social network from the hospital. The physicians can access the information's of the patient in real time and they can alert mothers in some situations. Using this cloud computing device, the health condition of the pregnant women may be improved.

Expeditionary Oblong Mezzanine

DTIC Science & Technology

2016-03-01

Operating System OSI Open Systems Interconnection OS X Operating System Ten PDU Power Distribution Unit POE Power Over Ethernet xvii SAAS ...providing infrastructure as a service (IaaS) and software as a service ( SaaS ) cloud computing technologies. IaaS is a way of providing computing services...such as servers, storage, and network equipment services (Mell & Grance, 2009). SaaS is a means of providing software and applications as an on

Seismic waveform modeling over cloud

NASA Astrophysics Data System (ADS)

Luo, Cong; Friederich, Wolfgang

2016-04-01

With the fast growing computational technologies, numerical simulation of seismic wave propagation achieved huge successes. Obtaining the synthetic waveforms through numerical simulation receives an increasing amount of attention from seismologists. However, computational seismology is a data-intensive research field, and the numerical packages usually come with a steep learning curve. Users are expected to master considerable amount of computer knowledge and data processing skills. Training users to use the numerical packages, correctly access and utilize the computational resources is a troubled task. In addition to that, accessing to HPC is also a common difficulty for many users. To solve these problems, a cloud based solution dedicated on shallow seismic waveform modeling has been developed with the state-of-the-art web technologies. It is a web platform integrating both software and hardware with multilayer architecture: a well designed SQL database serves as the data layer, HPC and dedicated pipeline for it is the business layer. Through this platform, users will no longer need to compile and manipulate various packages on the local machine within local network to perform a simulation. By providing users professional access to the computational code through its interfaces and delivering our computational resources to the users over cloud, users can customize the simulation at expert-level, submit and run the job through it.

iMAGE cloud: medical image processing as a service for regional healthcare in a hybrid cloud environment.

PubMed

Liu, Li; Chen, Weiping; Nie, Min; Zhang, Fengjuan; Wang, Yu; He, Ailing; Wang, Xiaonan; Yan, Gen

2016-11-01

To handle the emergence of the regional healthcare ecosystem, physicians and surgeons in various departments and healthcare institutions must process medical images securely, conveniently, and efficiently, and must integrate them with electronic medical records (EMRs). In this manuscript, we propose a software as a service (SaaS) cloud called the iMAGE cloud. A three-layer hybrid cloud was created to provide medical image processing services in the smart city of Wuxi, China, in April 2015. In the first step, medical images and EMR data were received and integrated via the hybrid regional healthcare network. Then, traditional and advanced image processing functions were proposed and computed in a unified manner in the high-performance cloud units. Finally, the image processing results were delivered to regional users using the virtual desktop infrastructure (VDI) technology. Security infrastructure was also taken into consideration. Integrated information query and many advanced medical image processing functions-such as coronary extraction, pulmonary reconstruction, vascular extraction, intelligent detection of pulmonary nodules, image fusion, and 3D printing-were available to local physicians and surgeons in various departments and healthcare institutions. Implementation results indicate that the iMAGE cloud can provide convenient, efficient, compatible, and secure medical image processing services in regional healthcare networks. The iMAGE cloud has been proven to be valuable in applications in the regional healthcare system, and it could have a promising future in the healthcare system worldwide.

Distributed Network, Wireless and Cloud Computing Enabled 3-D Ultrasound; a New Medical Technology Paradigm

PubMed Central

Meir, Arie; Rubinsky, Boris

2009-01-01

Medical technologies are indispensable to modern medicine. However, they have become exceedingly expensive and complex and are not available to the economically disadvantaged majority of the world population in underdeveloped as well as developed parts of the world. For example, according to the World Health Organization about two thirds of the world population does not have access to medical imaging. In this paper we introduce a new medical technology paradigm centered on wireless technology and cloud computing that was designed to overcome the problems of increasing health technology costs. We demonstrate the value of the concept with an example; the design of a wireless, distributed network and central (cloud) computing enabled three-dimensional (3-D) ultrasound system. Specifically, we demonstrate the feasibility of producing a 3-D high end ultrasound scan at a central computing facility using the raw data acquired at the remote patient site with an inexpensive low end ultrasound transducer designed for 2-D, through a mobile device and wireless connection link between them. Producing high-end 3D ultrasound images with simple low-end transducers reduces the cost of imaging by orders of magnitude. It also removes the requirement of having a highly trained imaging expert at the patient site, since the need for hand-eye coordination and the ability to reconstruct a 3-D mental image from 2-D scans, which is a necessity for high quality ultrasound imaging, is eliminated. This could enable relatively untrained medical workers in developing nations to administer imaging and a more accurate diagnosis, effectively saving the lives of people. PMID:19936236

Distributed network, wireless and cloud computing enabled 3-D ultrasound; a new medical technology paradigm.

PubMed

Meir, Arie; Rubinsky, Boris

2009-11-19

Medical technologies are indispensable to modern medicine. However, they have become exceedingly expensive and complex and are not available to the economically disadvantaged majority of the world population in underdeveloped as well as developed parts of the world. For example, according to the World Health Organization about two thirds of the world population does not have access to medical imaging. In this paper we introduce a new medical technology paradigm centered on wireless technology and cloud computing that was designed to overcome the problems of increasing health technology costs. We demonstrate the value of the concept with an example; the design of a wireless, distributed network and central (cloud) computing enabled three-dimensional (3-D) ultrasound system. Specifically, we demonstrate the feasibility of producing a 3-D high end ultrasound scan at a central computing facility using the raw data acquired at the remote patient site with an inexpensive low end ultrasound transducer designed for 2-D, through a mobile device and wireless connection link between them. Producing high-end 3D ultrasound images with simple low-end transducers reduces the cost of imaging by orders of magnitude. It also removes the requirement of having a highly trained imaging expert at the patient site, since the need for hand-eye coordination and the ability to reconstruct a 3-D mental image from 2-D scans, which is a necessity for high quality ultrasound imaging, is eliminated. This could enable relatively untrained medical workers in developing nations to administer imaging and a more accurate diagnosis, effectively saving the lives of people.

Indoor A* Pathfinding Through an Octree Representation of a Point Cloud

NASA Astrophysics Data System (ADS)

Rodenberg, O. B. P. M.; Verbree, E.; Zlatanova, S.

2016-10-01

There is a growing demand of 3D indoor pathfinding applications. Researched in the field of robotics during the last decades of the 20th century, these methods focussed on 2D navigation. Nowadays we would like to have the ability to help people navigate inside buildings or send a drone inside a building when this is too dangerous for people. What these examples have in common is that an object with a certain geometry needs to find an optimal collision free path between a start and goal point. This paper presents a new workflow for pathfinding through an octree representation of a point cloud. We applied the following steps: 1) the point cloud is processed so it fits best in an octree; 2) during the octree generation the interior empty nodes are filtered and further processed; 3) for each interior empty node the distance to the closest occupied node directly under it is computed; 4) a network graph is computed for all empty nodes; 5) the A* pathfinding algorithm is conducted. This workflow takes into account the connectivity for each node to all possible neighbours (face, edge and vertex and all sizes). Besides, a collision avoidance system is pre-processed in two steps: first, the clearance of each empty node is computed, and then the maximal crossing value between two empty neighbouring nodes is computed. The clearance is used to select interior empty nodes of appropriate size and the maximal crossing value is used to filter the network graph. Finally, both these datasets are used in A* pathfinding.

Assessment of cirrus cloud and aerosol radiative effect in South-East Asia by ground-based NASA MPLNET lidar network data and CALIPSO satellite measurements

NASA Astrophysics Data System (ADS)

Lolli, Simone; Campbell, James R.; Lewis, Jasper R.; Welton, Ellsworth J.; Di Girolamo, Paolo; Fatkhuroyan, Fatkhuroyan; Gu, Yu; Marquis, Jared W.

2017-10-01

Aerosol, together with cirrus clouds, play a fundamental role in the earth-atmosphere system radiation budget, especially at tropical latitudes, where the Earth surface coverage by cirrus cloud can easily reach 70%. In this study we evaluate the combined aerosol and cirrus cloud net radiative effects in a wild and barren region like South East Asia. This part of the world is extremely vulnerable to climate change and it is source of important anthropogenic and natural aerosol emissions. The analysis has been carried out by computing cirrus cloud and aerosol net radiative effects through the Fu-Liou-Gu atmospheric radiative transfer model, adequately adapted to input lidar measurements, at surface and top-of-the atmosphere. The aerosol radiative effects were computed respectively using the retrieved lidar extinction from Cloud-Aerosol Lidar with Orthogonal Polarization in 2011 and 2012 and the lidar on-board of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations for the South East Asia Region (27N-12S, 77E-132E) with 5° x 5° spatial resolution. To assess the cirrus cloud radiative effect, we used the ground-based Micro Pulse Lidar Network measurements at Singapore permanent observational site. Results put in evidence that strong aerosol emission areas are related on average to a net surface cooling. On the contrary, cirrus cloud radiative effect shows a net daytime positive warming of the system earth-atmosphere. This effect is weak over the ocean where the albedo is lower and never counter-balances the net cooling produced by aerosols. The net cooling is stronger in 2011, with an associated reduction in precipitations by the four of the five rain-gauges stations deployed in three regions as Sumatra, Kalimantan and Java with respect to 2012. We can speculate that aerosol emissions may be associated with lower rainfall, however some very important phenomena as El Nino Southern Oscillation , Madden-Julian Oscillation, Monsoon and Indian Dipole are not considered in the analysis.

Interfacing with in-Situ Data Networks during the Arctic Boreal Vulnerability Experiment (ABoVE)

NASA Astrophysics Data System (ADS)

McInerney, M.; Griffith, P. C.; Duffy, D.; Hoy, E.; Schnase, J. L.; Sinno, S.; Thompson, J. H.

2014-12-01

The Arctic Boreal Vulnerability Experiment (ABoVE) is designed to improve understanding of the causes and impacts of ecological changes in Arctic/boreal regions, and will integrate field-based studies, modeling, and data from airborne and satellite remote sensing. ABoVE will result in a fuller understanding of ecosystem vulnerability and resilience to environmental change in the Arctic and boreal regions of western North America, and provide scientific information required to develop options for societal responses to the impacts of these changes. The studies sponsored by NASA during ABoVE will be coordinated with research and in-situ monitoring activities being sponsored by a number of national and international partners. The NASA Center for Climate Simulation at the Goddard Space Flight Center has partnered with the NASA Carbon Cycle & Ecosystems Office to create a science cloud designed for this field campaign - the ABoVE Science Cloud (ASC). The ASC combines high performance computing with emerging technologies to create an environment specifically designed for large-scale modeling, analysis of remote sensing data, copious disk storage with integrated data management, and integration of core variables from in-situ networks identified by the ABoVE Science Definition Team. In this talk, we will present the scientific requirements driving the development of the ABoVE Science Cloud, discuss the necessary interfaces, both computational and human, with in-situ monitoring networks, and show examples of how the ASC is being used to meet the needs of the ABoVE campaign.

Analyzing the requirements for a robust security criteria and management of multi-level security in the clouds

NASA Astrophysics Data System (ADS)

Farroha, Bassam S.; Farroha, Deborah L.

2011-06-01

The new corporate approach to efficient processing and storage is migrating from in-house service-center services to the newly coined approach of Cloud Computing. This approach advocates thin clients and providing services by the service provider over time-shared resources. The concept is not new, however the implementation approach presents a strategic shift in the way organizations provision and manage their IT resources. The requirements on some of the data sets targeted to be run on the cloud vary depending on the data type, originator, user, and confidentiality level. Additionally, the systems that fuse such data would have to deal with the classifying the product and clearing the computing resources prior to allowing new application to be executed. This indicates that we could end up with a multi-level security system that needs to follow specific rules and can send the output to a protected network and systems in order not to have data spill or contaminated resources. The paper discusses these requirements and potential impact on the cloud architecture. Additionally, the paper discusses the unexpected advantages of the cloud framework providing a sophisticated environment for information sharing and data mining.

DICOM relay over the cloud.

PubMed

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

2013-05-01

Healthcare institutions worldwide have adopted picture archiving and communication system (PACS) for enterprise access to images, relying on Digital Imaging Communication in Medicine (DICOM) standards for data exchange. However, communication over a wider domain of independent medical institutions is not well standardized. A DICOM-compliant bridge was developed for extending and sharing DICOM services across healthcare institutions without requiring complex network setups or dedicated communication channels. A set of DICOM routers interconnected through a public cloud infrastructure was implemented to support medical image exchange among institutions. Despite the advantages of cloud computing, new challenges were encountered regarding data privacy, particularly when medical data are transmitted over different domains. To address this issue, a solution was introduced by creating a ciphered data channel between the entities sharing DICOM services. Two main DICOM services were implemented in the bridge: Storage and Query/Retrieve. The performance measures demonstrated it is quite simple to exchange information and processes between several institutions. The solution can be integrated with any currently installed PACS-DICOM infrastructure. This method works transparently with well-known cloud service providers. Cloud computing was introduced to augment enterprise PACS by providing standard medical imaging services across different institutions, offering communication privacy and enabling creation of wider PACS scenarios with suitable technical solutions.

Status and Roadmap of CernVM

NASA Astrophysics Data System (ADS)

Berzano, D.; Blomer, J.; Buncic, P.; Charalampidis, I.; Ganis, G.; Meusel, R.

2015-12-01

Cloud resources nowadays contribute an essential share of resources for computing in high-energy physics. Such resources can be either provided by private or public IaaS clouds (e.g. OpenStack, Amazon EC2, Google Compute Engine) or by volunteers computers (e.g. LHC@Home 2.0). In any case, experiments need to prepare a virtual machine image that provides the execution environment for the physics application at hand. The CernVM virtual machine since version 3 is a minimal and versatile virtual machine image capable of booting different operating systems. The virtual machine image is less than 20 megabyte in size. The actual operating system is delivered on demand by the CernVM File System. CernVM 3 has matured from a prototype to a production environment. It is used, for instance, to run LHC applications in the cloud, to tune event generators using a network of volunteer computers, and as a container for the historic Scientific Linux 5 and Scientific Linux 4 based software environments in the course of long-term data preservation efforts of the ALICE, CMS, and ALEPH experiments. We present experience and lessons learned from the use of CernVM at scale. We also provide an outlook on the upcoming developments. These developments include adding support for Scientific Linux 7, the use of container virtualization, such as provided by Docker, and the streamlining of virtual machine contextualization towards the cloud-init industry standard.

A Study on Secure Medical-Contents Strategies with DRM Based on Cloud Computing

PubMed Central

Měsíček, Libor; Choi, Jongsun

2018-01-01

Many hospitals and medical clinics have been using a wearable sensor in its health care system because the wearable sensor, which is able to measure the patients' biometric information, has been developed to analyze their patients remotely. The measured information is saved to a server in a medical center, and the server keeps the medical information, which also involves personal information, on a cloud system. The server and network devices are used by connecting each other, and sensitive medical records are dealt with remotely. However, these days, the attackers, who try to attack the server or the network systems, are increasing. In addition, the server and the network system have a weak protection and security policy against the attackers. In this paper, it is suggested that security compliance of medical contents should be followed to improve the level of security. As a result, the medical contents are kept safely. PMID:29796233

A Study on Secure Medical-Contents Strategies with DRM Based on Cloud Computing.

PubMed

Ko, Hoon; Měsíček, Libor; Choi, Jongsun; Hwang, Seogchan

2018-01-01

Many hospitals and medical clinics have been using a wearable sensor in its health care system because the wearable sensor, which is able to measure the patients' biometric information, has been developed to analyze their patients remotely. The measured information is saved to a server in a medical center, and the server keeps the medical information, which also involves personal information, on a cloud system. The server and network devices are used by connecting each other, and sensitive medical records are dealt with remotely. However, these days, the attackers, who try to attack the server or the network systems, are increasing. In addition, the server and the network system have a weak protection and security policy against the attackers. In this paper, it is suggested that security compliance of medical contents should be followed to improve the level of security. As a result, the medical contents are kept safely.

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.

Machine learning based cloud mask algorithm driven by radiative transfer modeling

NASA Astrophysics Data System (ADS)

Chen, N.; Li, W.; Tanikawa, T.; Hori, M.; Shimada, R.; Stamnes, K. H.

2017-12-01

Cloud detection is a critically important first step required to derive many satellite data products. Traditional threshold based cloud mask algorithms require a complicated design process and fine tuning for each sensor, and have difficulty over snow/ice covered areas. With the advance of computational power and machine learning techniques, we have developed a new algorithm based on a neural network classifier driven by extensive radiative transfer modeling. Statistical validation results obtained by using collocated CALIOP and MODIS data show that its performance is consistent over different ecosystems and significantly better than the MODIS Cloud Mask (MOD35 C6) during the winter seasons over mid-latitude snow covered areas. Simulations using a reduced number of satellite channels also show satisfactory results, indicating its flexibility to be configured for different sensors.

CE-ACCE: The Cloud Enabled Advanced sCience Compute Environment

NASA Astrophysics Data System (ADS)

Cinquini, L.; Freeborn, D. J.; Hardman, S. H.; Wong, C.

2017-12-01

Traditionally, Earth Science data from NASA remote sensing instruments has been processed by building custom data processing pipelines (often based on a common workflow engine or framework) which are typically deployed and run on an internal cluster of computing resources. This approach has some intrinsic limitations: it requires each mission to develop and deploy a custom software package on top of the adopted framework; it makes use of dedicated hardware, network and storage resources, which must be specifically purchased, maintained and re-purposed at mission completion; and computing services cannot be scaled on demand beyond the capability of the available servers.More recently, the rise of Cloud computing, coupled with other advances in containerization technology (most prominently, Docker) and micro-services architecture, has enabled a new paradigm, whereby space mission data can be processed through standard system architectures, which can be seamlessly deployed and scaled on demand on either on-premise clusters, or commercial Cloud providers. In this talk, we will present one such architecture named CE-ACCE ("Cloud Enabled Advanced sCience Compute Environment"), which we have been developing at the NASA Jet Propulsion Laboratory over the past year. CE-ACCE is based on the Apache OODT ("Object Oriented Data Technology") suite of services for full data lifecycle management, which are turned into a composable array of Docker images, and complemented by a plug-in model for mission-specific customization. We have applied this infrastructure to both flying and upcoming NASA missions, such as ECOSTRESS and SMAP, and demonstrated deployment on the Amazon Cloud, either using simple EC2 instances, or advanced AWS services such as Amazon Lambda and ECS (EC2 Container Services).

A Mobility Management Using Follow-Me Cloud-Cloudlet in Fog-Computing-Based RANs for Smart Cities.

PubMed

Chen, Yuh-Shyan; Tsai, Yi-Ting

2018-02-06

Mobility management for supporting the location tracking and location-based service (LBS) is an important issue of smart city by providing the means for the smooth transportation of people and goods. The mobility is useful to contribute the innovation in both public and private transportation infrastructures for smart cities. With the assistance of edge/fog computing, this paper presents a fully new mobility management using the proposed follow-me cloud-cloudlet (FMCL) approach in fog-computing-based radio access networks (Fog-RANs) for smart cities. The proposed follow-me cloud-cloudlet approach is an integration strategy of follow-me cloud (FMC) and follow-me edge (FME) (or called cloudlet). A user equipment (UE) receives the data, transmitted from original cloud, into the original edge cloud before the handover operation. After the handover operation, an UE searches for a new cloud, called as a migrated cloud, and a new edge cloud, called as a migrated edge cloud near to UE, where the remaining data is migrated from the original cloud to the migrated cloud and all the remaining data are received in the new edge cloud. Existing FMC results do not have the property of the VM migration between cloudlets for the purpose of reducing the transmission latency, and existing FME results do not keep the property of the service migration between data centers for reducing the transmission latency. Our proposed FMCL approach can simultaneously keep the VM migration between cloudlets and service migration between data centers to significantly reduce the transmission latency. The new proposed mobility management using FMCL approach aims to reduce the total transmission time if some data packets are pre-scheduled and pre-stored into the cache of cloudlet if UE is switching from the previous Fog-RAN to the serving Fog-RAN. To illustrate the performance achievement, the mathematical analysis and simulation results are examined in terms of the total transmission time, the throughput, the probability of packet loss, and the number of control messages.

A Mobility Management Using Follow-Me Cloud-Cloudlet in Fog-Computing-Based RANs for Smart Cities

PubMed Central

Tsai, Yi-Ting

2018-01-01

Mobility management for supporting the location tracking and location-based service (LBS) is an important issue of smart city by providing the means for the smooth transportation of people and goods. The mobility is useful to contribute the innovation in both public and private transportation infrastructures for smart cities. With the assistance of edge/fog computing, this paper presents a fully new mobility management using the proposed follow-me cloud-cloudlet (FMCL) approach in fog-computing-based radio access networks (Fog-RANs) for smart cities. The proposed follow-me cloud-cloudlet approach is an integration strategy of follow-me cloud (FMC) and follow-me edge (FME) (or called cloudlet). A user equipment (UE) receives the data, transmitted from original cloud, into the original edge cloud before the handover operation. After the handover operation, an UE searches for a new cloud, called as a migrated cloud, and a new edge cloud, called as a migrated edge cloud near to UE, where the remaining data is migrated from the original cloud to the migrated cloud and all the remaining data are received in the new edge cloud. Existing FMC results do not have the property of the VM migration between cloudlets for the purpose of reducing the transmission latency, and existing FME results do not keep the property of the service migration between data centers for reducing the transmission latency. Our proposed FMCL approach can simultaneously keep the VM migration between cloudlets and service migration between data centers to significantly reduce the transmission latency. The new proposed mobility management using FMCL approach aims to reduce the total transmission time if some data packets are pre-scheduled and pre-stored into the cache of cloudlet if UE is switching from the previous Fog-RAN to the serving Fog-RAN. To illustrate the performance achievement, the mathematical analysis and simulation results are examined in terms of the total transmission time, the throughput, the probability of packet loss, and the number of control messages. PMID:29415510

Load balancing prediction method of cloud storage based on analytic hierarchy process and hybrid hierarchical genetic algorithm.

PubMed

Zhou, Xiuze; Lin, Fan; Yang, Lvqing; Nie, Jing; Tan, Qian; Zeng, Wenhua; Zhang, Nian

2016-01-01

With the continuous expansion of the cloud computing platform scale and rapid growth of users and applications, how to efficiently use system resources to improve the overall performance of cloud computing has become a crucial issue. To address this issue, this paper proposes a method that uses an analytic hierarchy process group decision (AHPGD) to evaluate the load state of server nodes. Training was carried out by using a hybrid hierarchical genetic algorithm (HHGA) for optimizing a radial basis function neural network (RBFNN). The AHPGD makes the aggregative indicator of virtual machines in cloud, and become input parameters of predicted RBFNN. Also, this paper proposes a new dynamic load balancing scheduling algorithm combined with a weighted round-robin algorithm, which uses the predictive periodical load value of nodes based on AHPPGD and RBFNN optimized by HHGA, then calculates the corresponding weight values of nodes and makes constant updates. Meanwhile, it keeps the advantages and avoids the shortcomings of static weighted round-robin algorithm.

Geographically distributed Batch System as a Service: the INDIGO-DataCloud approach exploiting HTCondor

NASA Astrophysics Data System (ADS)

Aiftimiei, D. C.; Antonacci, M.; Bagnasco, S.; Boccali, T.; Bucchi, R.; Caballer, M.; Costantini, A.; Donvito, G.; Gaido, L.; Italiano, A.; Michelotto, D.; Panella, M.; Salomoni, D.; Vallero, S.

2017-10-01

One of the challenges a scientific computing center has to face is to keep delivering well consolidated computational frameworks (i.e. the batch computing farm), while conforming to modern computing paradigms. The aim is to ease system administration at all levels (from hardware to applications) and to provide a smooth end-user experience. Within the INDIGO- DataCloud project, we adopt two different approaches to implement a PaaS-level, on-demand Batch Farm Service based on HTCondor and Mesos. In the first approach, described in this paper, the various HTCondor daemons are packaged inside pre-configured Docker images and deployed as Long Running Services through Marathon, profiting from its health checks and failover capabilities. In the second approach, we are going to implement an ad-hoc HTCondor framework for Mesos. Container-to-container communication and isolation have been addressed exploring a solution based on overlay networks (based on the Calico Project). Finally, we have studied the possibility to deploy an HTCondor cluster that spans over different sites, exploiting the Condor Connection Broker component, that allows communication across a private network boundary or firewall as in case of multi-site deployments. In this paper, we are going to describe and motivate our implementation choices and to show the results of the first tests performed.

Cloud-based opportunities in scientific computing: insights from processing Suomi National Polar-Orbiting Partnership (S-NPP) Direct Broadcast data

NASA Astrophysics Data System (ADS)

Evans, J. D.; Hao, W.; Chettri, S.

2013-12-01

The cloud is proving to be a uniquely promising platform for scientific computing. Our experience with processing satellite data using Amazon Web Services highlights several opportunities for enhanced performance, flexibility, and cost effectiveness in the cloud relative to traditional computing -- for example: - Direct readout from a polar-orbiting satellite such as the Suomi National Polar-Orbiting Partnership (S-NPP) requires bursts of processing a few times a day, separated by quiet periods when the satellite is out of receiving range. In the cloud, by starting and stopping virtual machines in minutes, we can marshal significant computing resources quickly when needed, but not pay for them when not needed. To take advantage of this capability, we are automating a data-driven approach to the management of cloud computing resources, in which new data availability triggers the creation of new virtual machines (of variable size and processing power) which last only until the processing workflow is complete. - 'Spot instances' are virtual machines that run as long as one's asking price is higher than the provider's variable spot price. Spot instances can greatly reduce the cost of computing -- for software systems that are engineered to withstand unpredictable interruptions in service (as occurs when a spot price exceeds the asking price). We are implementing an approach to workflow management that allows data processing workflows to resume with minimal delays after temporary spot price spikes. This will allow systems to take full advantage of variably-priced 'utility computing.' - Thanks to virtual machine images, we can easily launch multiple, identical machines differentiated only by 'user data' containing individualized instructions (e.g., to fetch particular datasets or to perform certain workflows or algorithms) This is particularly useful when (as is the case with S-NPP data) we need to launch many very similar machines to process an unpredictable number of data files concurrently. Our experience shows the viability and flexibility of this approach to workflow management for scientific data processing. - Finally, cloud computing is a promising platform for distributed volunteer ('interstitial') computing, via mechanisms such as the Berkeley Open Infrastructure for Network Computing (BOINC) popularized with the SETI@Home project and others such as ClimatePrediction.net and NASA's Climate@Home. Interstitial computing faces significant challenges as commodity computing shifts from (always on) desktop computers towards smartphones and tablets (untethered and running on scarce battery power); but cloud computing offers significant slack capacity. This capacity includes virtual machines with unused RAM or underused CPUs; virtual storage volumes allocated (& paid for) but not full; and virtual machines that are paid up for the current hour but whose work is complete. We are devising ways to facilitate the reuse of these resources (i.e., cloud-based interstitial computing) for satellite data processing and related analyses. We will present our findings and research directions on these and related topics.

Integrating Flexible Sensor and Virtual Self-Organizing DC Grid Model With Cloud Computing for Blood Leakage Detection During Hemodialysis.

PubMed

Huang, Ping-Tzan; Jong, Tai-Lang; Li, Chien-Ming; Chen, Wei-Ling; Lin, Chia-Hung

2017-08-01

Blood leakage and blood loss are serious complications during hemodialysis. From the hemodialysis survey reports, these life-threatening events occur to attract nephrology nurses and patients themselves. When the venous needle and blood line are disconnected, it takes only a few minutes for an adult patient to lose over 40% of his / her blood, which is a sufficient amount of blood loss to cause the patient to die. Therefore, we propose integrating a flexible sensor and self-organizing algorithm to design a cloud computing-based warning device for blood leakage detection. The flexible sensor is fabricated via a screen-printing technique using metallic materials on a soft substrate in an array configuration. The self-organizing algorithm constructs a virtual direct current grid-based alarm unit in an embedded system. This warning device is employed to identify blood leakage levels via a wireless network and cloud computing. It has been validated experimentally, and the experimental results suggest specifications for its commercial designs. The proposed model can also be implemented in an embedded system.

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.

Cloud-ECG for real time ECG monitoring and analysis.

PubMed

Xia, Henian; Asif, Irfan; Zhao, Xiaopeng

2013-06-01

Recent advances in mobile technology and cloud computing have inspired numerous designs of cloud-based health care services and devices. Within the cloud system, medical data can be collected and transmitted automatically to medical professionals from anywhere and feedback can be returned to patients through the network. In this article, we developed a cloud-based system for clients with mobile devices or web browsers. Specially, we aim to address the issues regarding the usefulness of the ECG data collected from patients themselves. Algorithms for ECG enhancement, ECG quality evaluation and ECG parameters extraction were implemented in the system. The system was demonstrated by a use case, in which ECG data was uploaded to the web server from a mobile phone at a certain frequency and analysis was performed in real time using the server. The system has been proven to be functional, accurate and efficient. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Impact of different cloud deployments on real-time video applications for mobile video cloud users

NASA Astrophysics Data System (ADS)

Khan, Kashif A.; Wang, Qi; Luo, Chunbo; Wang, Xinheng; Grecos, Christos

2015-02-01

The latest trend to access mobile cloud services through wireless network connectivity has amplified globally among both entrepreneurs and home end users. Although existing public cloud service vendors such as Google, Microsoft Azure etc. are providing on-demand cloud services with affordable cost for mobile users, there are still a number of challenges to achieve high-quality mobile cloud based video applications, especially due to the bandwidth-constrained and errorprone mobile network connectivity, which is the communication bottleneck for end-to-end video delivery. In addition, existing accessible clouds networking architectures are different in term of their implementation, services, resources, storage, pricing, support and so on, and these differences have varied impact on the performance of cloud-based real-time video applications. Nevertheless, these challenges and impacts have not been thoroughly investigated in the literature. In our previous work, we have implemented a mobile cloud network model that integrates localized and decentralized cloudlets (mini-clouds) and wireless mesh networks. In this paper, we deploy a real-time framework consisting of various existing Internet cloud networking architectures (Google Cloud, Microsoft Azure and Eucalyptus Cloud) and a cloudlet based on Ubuntu Enterprise Cloud over wireless mesh networking technology for mobile cloud end users. It is noted that the increasing trend to access real-time video streaming over HTTP/HTTPS is gaining popularity among both research and industrial communities to leverage the existing web services and HTTP infrastructure in the Internet. To study the performance under different deployments using different public and private cloud service providers, we employ real-time video streaming over the HTTP/HTTPS standard, and conduct experimental evaluation and in-depth comparative analysis of the impact of different deployments on the quality of service for mobile video cloud users. Empirical results are presented and discussed to quantify and explain the different impacts resulted from various cloud deployments, video application and wireless/mobile network setting, and user mobility. Additionally, this paper analyses the advantages, disadvantages, limitations and optimization techniques in various cloud networking deployments, in particular the cloudlet approach compared with the Internet cloud approach, with recommendations of optimized deployments highlighted. Finally, federated clouds and inter-cloud collaboration challenges and opportunities are discussed in the context of supporting real-time video applications for mobile users.

Cloud Computing

DTIC Science & Technology

2010-04-29

Cloud Computing   The answer, my friend, is blowing in the wind.   The answer is blowing in the wind. 1Bingue ‐ Cook  Cloud   Computing  STSC 2010... Cloud   Computing  STSC 2010 Objectives • Define the cloud    • Risks of  cloud   computing f l d i• Essence o  c ou  comput ng • Deployed clouds in DoD 3Bingue...Cook  Cloud   Computing  STSC 2010 Definitions of Cloud Computing       Cloud   computing  is a model for enabling  b d d ku

Modeling and simulation of dense cloud dispersion in urban areas by means of computational fluid dynamics.

PubMed

Scargiali, F; Grisafi, F; Busciglio, A; Brucato, A

2011-12-15

The formation of toxic heavy clouds as a result of sudden accidental releases from mobile containers, such as road tankers or railway tank cars, may occur inside urban areas so the problem arises of their consequences evaluation. Due to the semi-confined nature of the dispersion site simplified models may often be inappropriate. As an alternative, computational fluid dynamics (CFD) has the potential to provide realistic simulations even for geometrically complex scenarios since the heavy gas dispersion process is described by basic conservation equations with a reduced number of approximations. In the present work a commercial general purpose CFD code (CFX 4.4 by Ansys(®)) is employed for the simulation of dense cloud dispersion in urban areas. The simulation strategy proposed involves a stationary pre-release flow field simulation followed by a dynamic after-release flow and concentration field simulations. In order to try a generalization of results, the computational domain is modeled as a simple network of straight roads with regularly distributed blocks mimicking the buildings. Results show that the presence of buildings lower concentration maxima and enlarge the side spread of the cloud. Dispersion dynamics is also found to be strongly affected by the quantity of heavy-gas released. Copyright © 2011 Elsevier B.V. All rights reserved.

Scalable computing for evolutionary genomics.

PubMed

Prins, Pjotr; Belhachemi, Dominique; Möller, Steffen; Smant, Geert

2012-01-01

Genomic data analysis in evolutionary biology is becoming so computationally intensive that analysis of multiple hypotheses and scenarios takes too long on a single desktop computer. In this chapter, we discuss techniques for scaling computations through parallelization of calculations, after giving a quick overview of advanced programming techniques. Unfortunately, parallel programming is difficult and requires special software design. The alternative, especially attractive for legacy software, is to introduce poor man's parallelization by running whole programs in parallel as separate processes, using job schedulers. Such pipelines are often deployed on bioinformatics computer clusters. Recent advances in PC virtualization have made it possible to run a full computer operating system, with all of its installed software, on top of another operating system, inside a "box," or virtual machine (VM). Such a VM can flexibly be deployed on multiple computers, in a local network, e.g., on existing desktop PCs, and even in the Cloud, to create a "virtual" computer cluster. Many bioinformatics applications in evolutionary biology can be run in parallel, running processes in one or more VMs. Here, we show how a ready-made bioinformatics VM image, named BioNode, effectively creates a computing cluster, and pipeline, in a few steps. This allows researchers to scale-up computations from their desktop, using available hardware, anytime it is required. BioNode is based on Debian Linux and can run on networked PCs and in the Cloud. Over 200 bioinformatics and statistical software packages, of interest to evolutionary biology, are included, such as PAML, Muscle, MAFFT, MrBayes, and BLAST. Most of these software packages are maintained through the Debian Med project. In addition, BioNode contains convenient configuration scripts for parallelizing bioinformatics software. Where Debian Med encourages packaging free and open source bioinformatics software through one central project, BioNode encourages creating free and open source VM images, for multiple targets, through one central project. BioNode can be deployed on Windows, OSX, Linux, and in the Cloud. Next to the downloadable BioNode images, we provide tutorials online, which empower bioinformaticians to install and run BioNode in different environments, as well as information for future initiatives, on creating and building such images.

A Cloud-Based X73 Ubiquitous Mobile Healthcare System: Design and Implementation

PubMed Central

Ji, Zhanlin; O'Droma, Máirtín; Zhang, Xin; Zhang, Xueji

2014-01-01

Based on the user-centric paradigm for next generation networks, this paper describes a ubiquitous mobile healthcare (uHealth) system based on the ISO/IEEE 11073 personal health data (PHD) standards (X73) and cloud computing techniques. A number of design issues associated with the system implementation are outlined. The system includes a middleware on the user side, providing a plug-and-play environment for heterogeneous wireless sensors and mobile terminals utilizing different communication protocols and a distributed “big data” processing subsystem in the cloud. The design and implementation of this system are envisaged as an efficient solution for the next generation of uHealth systems. PMID:24737958

The EPOS Vision for the Open Science Cloud

NASA Astrophysics Data System (ADS)

Jeffery, Keith; Harrison, Matt; Cocco, Massimo

2016-04-01

Cloud computing offers dynamic elastic scalability for data processing on demand. For much research activity, demand for computing is uneven over time and so CLOUD computing offers both cost-effectiveness and capacity advantages. However, as reported repeatedly by the EC Cloud Expert Group, there are barriers to the uptake of Cloud Computing: (1) security and privacy; (2) interoperability (avoidance of lock-in); (3) lack of appropriate systems development environments for application programmers to characterise their applications to allow CLOUD middleware to optimize their deployment and execution. From CERN, the Helix-Nebula group has proposed the architecture for the European Open Science Cloud. They are discussing with other e-Infrastructure groups such as EGI (GRIDs), EUDAT (data curation), AARC (network authentication and authorisation) and also with the EIROFORUM group of 'international treaty' RIs (Research Infrastructures) and the ESFRI (European Strategic Forum for Research Infrastructures) RIs including EPOS. Many of these RIs are either e-RIs (electronic-RIs) or have an e-RI interface for access and use. The EPOS architecture is centred on a portal: ICS (Integrated Core Services). The architectural design already allows for access to e-RIs (which may include any or all of data, software, users and resources such as computers or instruments). Those within any one domain (subject area) of EPOS are considered within the TCS (Thematic Core Services). Those outside, or available across multiple domains of EPOS, are ICS-d (Integrated Core Services-Distributed) since the intention is that they will be used by any or all of the TCS via the ICS. Another such service type is CES (Computational Earth Science); effectively an ICS-d specializing in high performance computation, analytics, simulation or visualization offered by a TCS for others to use. Already discussions are underway between EPOS and EGI, EUDAT, AARC and Helix-Nebula for those offerings to be considered as ICS-ds by EPOS.. Provision of access to ICS-Ds from ICS-C concerns several aspects: (a) Technical : it may be more or less difficult to connect and pass from ICS-C to the ICS-d/ CES the 'package' (probably a virtual machine) of data and software; (b) Security/privacy : including passing personal information e.g. related to AAAI (Authentication, authorization, accounting Infrastructure); (c) financial and legal : such as payment, licence conditions; Appropriate interfaces from ICS-C to ICS-d are being designed to accommodate these aspects. The Open Science Cloud is timely because it provides a framework to discuss governance and sustainability for computational resource provision as well as an effective interpretation of federated approach to HPC(High Performance Computing) -HTC (High Throughput Computing). It will be a unique opportunity to share and adopt procurement policies to provide access to computational resources for RIs. The current state of discussions and expected roadmap for the EPOS-Open Science Cloud relationship are presented.

Public Auditing with Privacy Protection in a Multi-User Model of Cloud-Assisted Body Sensor Networks

PubMed Central

Li, Song; Cui, Jie; Zhong, Hong; Liu, Lu

2017-01-01

Wireless Body Sensor Networks (WBSNs) are gaining importance in the era of the Internet of Things (IoT). The modern medical system is a particular area where the WBSN techniques are being increasingly adopted for various fundamental operations. Despite such increasing deployments of WBSNs, issues such as the infancy in the size, capabilities and limited data processing capacities of the sensor devices restrain their adoption in resource-demanding applications. Though providing computing and storage supplements from cloud servers can potentially enrich the capabilities of the WBSNs devices, data security is one of the prevailing issues that affects the reliability of cloud-assisted services. Sensitive applications such as modern medical systems demand assurance of the privacy of the users’ medical records stored in distant cloud servers. Since it is economically impossible to set up private cloud servers for every client, auditing data security managed in the remote servers has necessarily become an integral requirement of WBSNs’ applications relying on public cloud servers. To this end, this paper proposes a novel certificateless public auditing scheme with integrated privacy protection. The multi-user model in our scheme supports groups of users to store and share data, thus exhibiting the potential for WBSNs’ deployments within community environments. Furthermore, our scheme enriches user experiences by offering public verifiability, forward security mechanisms and revocation of illegal group members. Experimental evaluations demonstrate the security effectiveness of our proposed scheme under the Random Oracle Model (ROM) by outperforming existing cloud-assisted WBSN models. PMID:28475110

Public Auditing with Privacy Protection in a Multi-User Model of Cloud-Assisted Body Sensor Networks.

PubMed

Li, Song; Cui, Jie; Zhong, Hong; Liu, Lu

2017-05-05

Wireless Body Sensor Networks (WBSNs) are gaining importance in the era of the Internet of Things (IoT). The modern medical system is a particular area where the WBSN techniques are being increasingly adopted for various fundamental operations. Despite such increasing deployments of WBSNs, issues such as the infancy in the size, capabilities and limited data processing capacities of the sensor devices restrain their adoption in resource-demanding applications. Though providing computing and storage supplements from cloud servers can potentially enrich the capabilities of the WBSNs devices, data security is one of the prevailing issues that affects the reliability of cloud-assisted services. Sensitive applications such as modern medical systems demand assurance of the privacy of the users' medical records stored in distant cloud servers. Since it is economically impossible to set up private cloud servers for every client, auditing data security managed in the remote servers has necessarily become an integral requirement of WBSNs' applications relying on public cloud servers. To this end, this paper proposes a novel certificateless public auditing scheme with integrated privacy protection. The multi-user model in our scheme supports groups of users to store and share data, thus exhibiting the potential for WBSNs' deployments within community environments. Furthermore, our scheme enriches user experiences by offering public verifiability, forward security mechanisms and revocation of illegal group members. Experimental evaluations demonstrate the security effectiveness of our proposed scheme under the Random Oracle Model (ROM) by outperforming existing cloud-assisted WBSN models.

Unified Geophysical Cloud Platform (UGCP) for Seismic Monitoring and other Geophysical Applications.

NASA Astrophysics Data System (ADS)

Synytsky, R.; Starovoit, Y. O.; Henadiy, S.; Lobzakov, V.; Kolesnikov, L.

2016-12-01

We present Unified Geophysical Cloud Platform (UGCP) or UniGeoCloud as an innovative approach for geophysical data processing in the Cloud environment with the ability to run any type of data processing software in isolated environment within the single Cloud platform. We've developed a simple and quick method of several open-source widely known software seismic packages (SeisComp3, Earthworm, Geotool, MSNoise) installation which does not require knowledge of system administration, configuration, OS compatibility issues etc. and other often annoying details preventing time wasting for system configuration work. Installation process is simplified as "mouse click" on selected software package from the Cloud market place. The main objective of the developed capability was the software tools conception with which users are able to design and install quickly their own highly reliable and highly available virtual IT-infrastructure for the organization of seismic (and in future other geophysical) data processing for either research or monitoring purposes. These tools provide access to any seismic station data available in open IP configuration from the different networks affiliated with different Institutions and Organizations. It allows also setting up your own network as you desire by selecting either regionally deployed stations or the worldwide global network based on stations selection form the global map. The processing software and products and research results could be easily monitored from everywhere using variety of user's devices form desk top computers to IT gadgets. Currents efforts of the development team are directed to achieve Scalability, Reliability and Sustainability (SRS) of proposed solutions allowing any user to run their applications with the confidence of no data loss and no failure of the monitoring or research software components. The system is suitable for quick rollout of NDC-in-Box software package developed for State Signatories and aimed for promotion of data processing collected by the IMS Network.

Demonstration of NICT Space Weather Cloud --Integration of Supercomputer into Analysis and Visualization Environment--

NASA Astrophysics Data System (ADS)

Watari, S.; Morikawa, Y.; Yamamoto, K.; Inoue, S.; Tsubouchi, K.; Fukazawa, K.; Kimura, E.; Tatebe, O.; Kato, H.; Shimojo, S.; Murata, K. T.

2010-12-01

In the Solar-Terrestrial Physics (STP) field, spatio-temporal resolution of computer simulations is getting higher and higher because of tremendous advancement of supercomputers. A more advanced technology is Grid Computing that integrates distributed computational resources to provide scalable computing resources. In the simulation research, it is effective that a researcher oneself designs his physical model, performs calculations with a supercomputer, and analyzes and visualizes for consideration by a familiar method. A supercomputer is far from an analysis and visualization environment. In general, a researcher analyzes and visualizes in the workstation (WS) managed at hand because the installation and the operation of software in the WS are easy. Therefore, it is necessary to copy the data from the supercomputer to WS manually. Time necessary for the data transfer through long delay network disturbs high-accuracy simulations actually. In terms of usefulness, integrating a supercomputer and an analysis and visualization environment seamlessly with a researcher's familiar method is important. NICT has been developing a cloud computing environment (NICT Space Weather Cloud). In the NICT Space Weather Cloud, disk servers are located near its supercomputer and WSs for data analysis and visualization. They are connected to JGN2plus that is high-speed network for research and development. Distributed virtual high-capacity storage is also constructed by Grid Datafarm (Gfarm v2). Huge-size data output from the supercomputer is transferred to the virtual storage through JGN2plus. A researcher can concentrate on the research by a familiar method without regard to distance between a supercomputer and an analysis and visualization environment. Now, total 16 disk servers are setup in NICT headquarters (at Koganei, Tokyo), JGN2plus NOC (at Otemachi, Tokyo), Okinawa Subtropical Environment Remote-Sensing Center, and Cybermedia Center, Osaka University. They are connected on JGN2plus, and they constitute 1PB (physical size) virtual storage by Gfarm v2. These disk servers are connected with supercomputers of NICT and Osaka University. A system that data output from the supercomputers are automatically transferred to the virtual storage had been built up. Transfer rate is about 50 GB/hrs by actual measurement. It is estimated that the performance is reasonable for a certain simulation and analysis for reconstruction of coronal magnetic field. This research is assumed an experiment of the system, and the verification of practicality is advanced at the same time. Herein we introduce an overview of the space weather cloud system so far we have developed. We also demonstrate several scientific results using the space weather cloud system. We also introduce several web applications of the cloud as a service of the space weather cloud, which is named as "e-SpaceWeather" (e-SW). The e-SW provides with a variety of space weather online services from many aspects.

Hermes: Seamless delivery of containerized bioinformatics workflows in hybrid cloud (HTC) environments

NASA Astrophysics Data System (ADS)

Kintsakis, Athanassios M.; Psomopoulos, Fotis E.; Symeonidis, Andreas L.; Mitkas, Pericles A.

Hermes introduces a new "describe once, run anywhere" paradigm for the execution of bioinformatics workflows in hybrid cloud environments. It combines the traditional features of parallelization-enabled workflow management systems and of distributed computing platforms in a container-based approach. It offers seamless deployment, overcoming the burden of setting up and configuring the software and network requirements. Most importantly, Hermes fosters the reproducibility of scientific workflows by supporting standardization of the software execution environment, thus leading to consistent scientific workflow results and accelerating scientific output.

An Overview of Cloud Computing in Distributed Systems

NASA Astrophysics Data System (ADS)

Divakarla, Usha; Kumari, Geetha

2010-11-01

Cloud computing is the emerging trend in the field of distributed computing. Cloud computing evolved from grid computing and distributed computing. Cloud plays an important role in huge organizations in maintaining huge data with limited resources. Cloud also helps in resource sharing through some specific virtual machines provided by the cloud service provider. This paper gives an overview of the cloud organization and some of the basic security issues pertaining to the cloud.

Analysis of the Security and Privacy Requirements of Cloud-Based Electronic Health Records Systems

PubMed Central

Fernández, Gonzalo; López-Coronado, Miguel

2013-01-01

Background The Cloud Computing paradigm offers eHealth systems the opportunity to enhance the features and functionality that they offer. However, moving patients’ medical information to the Cloud implies several risks in terms of the security and privacy of sensitive health records. In this paper, the risks of hosting Electronic Health Records (EHRs) on the servers of third-party Cloud service providers are reviewed. To protect the confidentiality of patient information and facilitate the process, some suggestions for health care providers are made. Moreover, security issues that Cloud service providers should address in their platforms are considered. Objective To show that, before moving patient health records to the Cloud, security and privacy concerns must be considered by both health care providers and Cloud service providers. Security requirements of a generic Cloud service provider are analyzed. Methods To study the latest in Cloud-based computing solutions, bibliographic material was obtained mainly from Medline sources. Furthermore, direct contact was made with several Cloud service providers. Results Some of the security issues that should be considered by both Cloud service providers and their health care customers are role-based access, network security mechanisms, data encryption, digital signatures, and access monitoring. Furthermore, to guarantee the safety of the information and comply with privacy policies, the Cloud service provider must be compliant with various certifications and third-party requirements, such as SAS70 Type II, PCI DSS Level 1, ISO 27001, and the US Federal Information Security Management Act (FISMA). Conclusions Storing sensitive information such as EHRs in the Cloud means that precautions must be taken to ensure the safety and confidentiality of the data. A relationship built on trust with the Cloud service provider is essential to ensure a transparent process. Cloud service providers must make certain that all security mechanisms are in place to avoid unauthorized access and data breaches. Patients must be kept informed about how their data are being managed. PMID:23965254

Analysis of the security and privacy requirements of cloud-based electronic health records systems.

PubMed

Rodrigues, Joel J P C; de la Torre, Isabel; Fernández, Gonzalo; López-Coronado, Miguel

2013-08-21

The Cloud Computing paradigm offers eHealth systems the opportunity to enhance the features and functionality that they offer. However, moving patients' medical information to the Cloud implies several risks in terms of the security and privacy of sensitive health records. In this paper, the risks of hosting Electronic Health Records (EHRs) on the servers of third-party Cloud service providers are reviewed. To protect the confidentiality of patient information and facilitate the process, some suggestions for health care providers are made. Moreover, security issues that Cloud service providers should address in their platforms are considered. To show that, before moving patient health records to the Cloud, security and privacy concerns must be considered by both health care providers and Cloud service providers. Security requirements of a generic Cloud service provider are analyzed. To study the latest in Cloud-based computing solutions, bibliographic material was obtained mainly from Medline sources. Furthermore, direct contact was made with several Cloud service providers. Some of the security issues that should be considered by both Cloud service providers and their health care customers are role-based access, network security mechanisms, data encryption, digital signatures, and access monitoring. Furthermore, to guarantee the safety of the information and comply with privacy policies, the Cloud service provider must be compliant with various certifications and third-party requirements, such as SAS70 Type II, PCI DSS Level 1, ISO 27001, and the US Federal Information Security Management Act (FISMA). Storing sensitive information such as EHRs in the Cloud means that precautions must be taken to ensure the safety and confidentiality of the data. A relationship built on trust with the Cloud service provider is essential to ensure a transparent process. Cloud service providers must make certain that all security mechanisms are in place to avoid unauthorized access and data breaches. Patients must be kept informed about how their data are being managed.

Analysis on the security of cloud computing

NASA Astrophysics Data System (ADS)

He, Zhonglin; He, Yuhua

2011-02-01

Cloud computing is a new technology, which is the fusion of computer technology and Internet development. It will lead the revolution of IT and information field. However, in cloud computing data and application software is stored at large data centers, and the management of data and service is not completely trustable, resulting in safety problems, which is the difficult point to improve the quality of cloud service. This paper briefly introduces the concept of cloud computing. Considering the characteristics of cloud computing, it constructs the security architecture of cloud computing. At the same time, with an eye toward the security threats cloud computing faces, several corresponding strategies are provided from the aspect of cloud computing users and service providers.

Future of Department of Defense Cloud Computing Amid Cultural Confusion

DTIC Science & Technology

2013-03-01

enterprise cloud - computing environment and transition to a public cloud service provider. Services have started the development of individual cloud - computing environments...endorsing cloud computing . It addresses related issues in matters of service culture changes and how strategic leaders will dictate the future of cloud ...through data center consolidation and individual Service provided cloud computing .

Community Seismic Network

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Kohler, M. D.; Massari, A.; Heaton, T. H.; Guy, R.; Chandy, M.; Bunn, J.; Strand, L.

2014-12-01

The CSN is now in its 3rdyear of operation and has expanded to 400 stations in the Los Angeles region. The goal of the network is to produce a map of strong shaking immediately following a major earthquake as a proxy for damage and a guide for first responders. We have also instrumented a number of buildings with the goal of determining the state of health of these structures before and after they have been shaken. In one 15-story structure, our sensors distributed two per floor, and show body waves propagating in the structure after a moderate local earthquake (M4.4 in Encino, CA). Sensors in a 52-story structure, which we plan to instrument with two sensors per floor as well, show the modes of the building (see Figure) down to the fundamental mode at 5 sec due to a M5.1 earthquake in La Habra, CA. The CSN utilizes a number of technologies that will likely be important in building robust low-cost networks. These include: Distributed computing - the sensors themselves are smart-sensors that perform the basic detection and size estimation in the onboard computers and send the results immediately (without packetization latency) to the central facility. Cloud computing - the central facility is housed in the cloud, which means it is more robust than a local site, and has expandable computing resources available so that it can operate with minimal resources during quiet times but still be able to exploit an very large computing facility during an earthquake. Low-cost/low-maintenance sensors - the MEM sensors are capable of staying onscale to +/- 2g, and can measure events in the Los Angeles Basin a low as magnitude 3.

Fully Convolutional Networks for Ground Classification from LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Rizaldy, A.; Persello, C.; Gevaert, C. M.; Oude Elberink, S. J.

2018-05-01

Deep Learning has been massively used for image classification in recent years. The use of deep learning for ground classification from LIDAR point clouds has also been recently studied. However, point clouds need to be converted into an image in order to use Convolutional Neural Networks (CNNs). In state-of-the-art techniques, this conversion is slow because each point is converted into a separate image. This approach leads to highly redundant computation during conversion and classification. The goal of this study is to design a more efficient data conversion and ground classification. This goal is achieved by first converting the whole point cloud into a single image. The classification is then performed by a Fully Convolutional Network (FCN), a modified version of CNN designed for pixel-wise image classification. The proposed method is significantly faster than state-of-the-art techniques. On the ISPRS Filter Test dataset, it is 78 times faster for conversion and 16 times faster for classification. Our experimental analysis on the same dataset shows that the proposed method results in 5.22 % of total error, 4.10 % of type I error, and 15.07 % of type II error. Compared to the previous CNN-based technique and LAStools software, the proposed method reduces the total error and type I error (while type II error is slightly higher). The method was also tested on a very high point density LIDAR point clouds resulting in 4.02 % of total error, 2.15 % of type I error and 6.14 % of type II error.

MWR3C physical retrievals of precipitable water vapor and cloud liquid water path

DOE Data Explorer

Cadeddu, Maria

2016-10-12

The data set contains physical retrievals of PWV and cloud LWP retrieved from MWR3C measurements during the MAGIC campaign. Additional data used in the retrieval process include radiosondes and ceilometer. The retrieval is based on an optimal estimation technique that starts from a first guess and iteratively repeats the forward model calculations until a predefined convergence criterion is satisfied. The first guess is a vector of [PWV,LWP] from the neural network retrieval fields in the netcdf file. When convergence is achieved the 'a posteriori' covariance is computed and its square root is expressed in the file as the retrieval 1-sigma uncertainty. The closest radiosonde profile is used for the radiative transfer calculations and ceilometer data are used to constrain the cloud base height. The RMS error between the brightness temperatures is computed at the last iterations as a consistency check and is written in the last column of the output file.

Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Kühnlein, Meike; Appelhans, Tim; Nauss, Thomas

2016-03-01

Machine learning (ML) algorithms have successfully been demonstrated to be valuable tools in satellite-based rainfall retrievals which show the practicability of using ML algorithms when faced with high dimensional and complex data. Moreover, recent developments in parallel computing with ML present new possibilities for training and prediction speed and therefore make their usage in real-time systems feasible. This study compares four ML algorithms - random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) - for rainfall area detection and rainfall rate assignment using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path serve as predictor variables. The results indicate an overestimation of rainfall area delineation regardless of the ML algorithm (averaged bias = 1.8) but a high probability of detection ranging from 81% (SVM) to 85% (NNET). On a 24-hour basis, the performance of the rainfall rate assignment yielded R2 values between 0.39 (SVM) and 0.44 (AVNNET). Though the differences in the algorithms' performance were rather small, NNET and AVNNET were identified as the most suitable algorithms. On average, they demonstrated the best performance in rainfall area delineation as well as in rainfall rate assignment. NNET's computational speed is an additional advantage in work with large datasets such as in remote sensing based rainfall retrievals. However, since no single algorithm performed considerably better than the others we conclude that further research in providing suitable predictors for rainfall is of greater necessity than an optimization through the choice of the ML algorithm.

Energy-Aware Computation Offloading of IoT Sensors in Cloudlet-Based Mobile Edge Computing.

PubMed

Ma, Xiao; Lin, Chuang; Zhang, Han; Liu, Jianwei

2018-06-15

Mobile edge computing is proposed as a promising computing paradigm to relieve the excessive burden of data centers and mobile networks, which is induced by the rapid growth of Internet of Things (IoT). This work introduces the cloud-assisted multi-cloudlet framework to provision scalable services in cloudlet-based mobile edge computing. Due to the constrained computation resources of cloudlets and limited communication resources of wireless access points (APs), IoT sensors with identical computation offloading decisions interact with each other. To optimize the processing delay and energy consumption of computation tasks, theoretic analysis of the computation offloading decision problem of IoT sensors is presented in this paper. In more detail, the computation offloading decision problem of IoT sensors is formulated as a computation offloading game and the condition of Nash equilibrium is derived by introducing the tool of a potential game. By exploiting the finite improvement property of the game, the Computation Offloading Decision (COD) algorithm is designed to provide decentralized computation offloading strategies for IoT sensors. Simulation results demonstrate that the COD algorithm can significantly reduce the system cost compared with the random-selection algorithm and the cloud-first algorithm. Furthermore, the COD algorithm can scale well with increasing IoT sensors.

3D Cloud Field Prediction using A-Train Data and Machine Learning Techniques

NASA Astrophysics Data System (ADS)

Johnson, C. L.

2017-12-01

Validation of cloud process parameterizations used in global climate models (GCMs) would greatly benefit from observed 3D cloud fields at the size comparable to that of a GCM grid cell. For the highest resolution simulations, surface grid cells are on the order of 100 km by 100 km. CloudSat/CALIPSO data provides 1 km width of detailed vertical cloud fraction profile (CFP) and liquid and ice water content (LWC/IWC). This work utilizes four machine learning algorithms to create nonlinear regressions of CFP, LWC, and IWC data using radiances, surface type and location of measurement as predictors and applies the regression equations to off-track locations generating 3D cloud fields for 100 km by 100 km domains. The CERES-CloudSat-CALIPSO-MODIS (C3M) merged data set for February 2007 is used. Support Vector Machines, Artificial Neural Networks, Gaussian Processes and Decision Trees are trained on 1000 km of continuous C3M data. Accuracy is computed using existing vertical profiles that are excluded from the training data and occur within 100 km of the training data. Accuracy of the four algorithms is compared. Average accuracy for one day of predicted data is 86% for the most successful algorithm. The methodology for training the algorithms, determining valid prediction regions and applying the equations off-track is discussed. Predicted 3D cloud fields are provided as inputs to the Ed4 NASA LaRC Fu-Liou radiative transfer code and resulting TOA radiances compared to observed CERES/MODIS radiances. Differences in computed radiances using predicted profiles and observed radiances are compared.

Pervasive Knowledge, Social Networks, and Cloud Computing: E-Learning 2.0

ERIC Educational Resources Information Center

Anshari, Muhammad; Alas, Yabit; Guan, Lim Sei

2015-01-01

Embedding Web 2.0 in learning processes has extended learning from traditional based learning-centred to a collaborative based learning-centred institution that emphasises learning anywhere and anytime. While deploying Semantic Web into e-learning offers a broader spectrum of pervasive knowledge acquisition to enrich users' experience in learning.…

Novel Techniques for Secure Use of Public Cloud Computing Resources

DTIC Science & Technology

2015-09-17

applications such as Twitter and Instagram . It allows users to post messages to their public feed, where any followers of that feed will receive them...86]) and topic based systems, this work focuses on a topic based systems. Due to the recent popularity of social networks such as Twitter and Instagram

Staying on your your feet.

PubMed

DeGaspari, John

2011-10-01

CIOs are hard at work coming up with the most effective and affordable strategies for protecting electronic data as their hospitals move forward on electronic medical records. While the rise of cloud computing and declining network costs are offering new opportunities in dealing with potential disasters, many find there is no substitute for good planning and constant testing.

Internet of Things (IoT) Based Design of a Secure and Lightweight Body Area Network (BAN) Healthcare System.

PubMed

Deng, Yong-Yuan; Chen, Chin-Ling; Tsaur, Woei-Jiunn; Tang, Yung-Wen; Chen, Jung-Hsuan

2017-12-15

As sensor networks and cloud computation technologies have rapidly developed over recent years, many services and applications integrating these technologies into daily life have come together as an Internet of Things (IoT). At the same time, aging populations have increased the need for expanded and more efficient elderly care services. Fortunately, elderly people can now wear sensing devices which relay data to a personal wireless device, forming a body area network (BAN). These personal wireless devices collect and integrate patients' personal physiological data, and then transmit the data to the backend of the network for related diagnostics. However, a great deal of the information transmitted by such systems is sensitive data, and must therefore be subject to stringent security protocols. Protecting this data from unauthorized access is thus an important issue in IoT-related research. In regard to a cloud healthcare environment, scholars have proposed a secure mechanism to protect sensitive patient information. Their schemes provide a general architecture; however, these previous schemes still have some vulnerability, and thus cannot guarantee complete security. This paper proposes a secure and lightweight body-sensor network based on the Internet of Things for cloud healthcare environments, in order to address the vulnerabilities discovered in previous schemes. The proposed authentication mechanism is applied to a medical reader to provide a more comprehensive architecture while also providing mutual authentication, and guaranteeing data integrity, user untraceability, and forward and backward secrecy, in addition to being resistant to replay attack.

Mobile, Cloud, and Big Data Computing: Contributions, Challenges, and New Directions in Telecardiology

PubMed Central

Hsieh, Jui-Chien; Li, Ai-Hsien; Yang, Chung-Chi

2013-01-01

Many studies have indicated that computing technology can enable off-site cardiologists to read patients’ electrocardiograph (ECG), echocardiography (ECHO), and relevant images via smart phones during pre-hospital, in-hospital, and post-hospital teleconsultation, which not only identifies emergency cases in need of immediate treatment, but also prevents the unnecessary re-hospitalizations. Meanwhile, several studies have combined cloud computing and mobile computing to facilitate better storage, delivery, retrieval, and management of medical files for telecardiology. In the future, the aggregated ECG and images from hospitals worldwide will become big data, which should be used to develop an e-consultation program helping on-site practitioners deliver appropriate treatment. With information technology, real-time tele-consultation and tele-diagnosis of ECG and images can be practiced via an e-platform for clinical, research, and educational purposes. While being devoted to promote the application of information technology onto telecardiology, we need to resolve several issues: (1) data confidentiality in the cloud, (2) data interoperability among hospitals, and (3) network latency and accessibility. If these challenges are overcome, tele-consultation will be ubiquitous, easy to perform, inexpensive, and beneficial. Most importantly, these services will increase global collaboration and advance clinical practice, education, and scientific research in cardiology. PMID:24232290

Mobile, cloud, and big data computing: contributions, challenges, and new directions in telecardiology.

PubMed

Hsieh, Jui-Chien; Li, Ai-Hsien; Yang, Chung-Chi

2013-11-13

Many studies have indicated that computing technology can enable off-site cardiologists to read patients' electrocardiograph (ECG), echocardiography (ECHO), and relevant images via smart phones during pre-hospital, in-hospital, and post-hospital teleconsultation, which not only identifies emergency cases in need of immediate treatment, but also prevents the unnecessary re-hospitalizations. Meanwhile, several studies have combined cloud computing and mobile computing to facilitate better storage, delivery, retrieval, and management of medical files for telecardiology. In the future, the aggregated ECG and images from hospitals worldwide will become big data, which should be used to develop an e-consultation program helping on-site practitioners deliver appropriate treatment. With information technology, real-time tele-consultation and tele-diagnosis of ECG and images can be practiced via an e-platform for clinical, research, and educational purposes. While being devoted to promote the application of information technology onto telecardiology, we need to resolve several issues: (1) data confidentiality in the cloud, (2) data interoperability among hospitals, and (3) network latency and accessibility. If these challenges are overcome, tele-consultation will be ubiquitous, easy to perform, inexpensive, and beneficial. Most importantly, these services will increase global collaboration and advance clinical practice, education, and scientific research in cardiology.

Cloud Computing for radiologists.

PubMed

Kharat, Amit T; Safvi, Amjad; Thind, Ss; Singh, Amarjit

2012-07-01

Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future.

Cloud Computing for radiologists

PubMed Central

Kharat, Amit T; Safvi, Amjad; Thind, SS; Singh, Amarjit

2012-01-01

Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future. PMID:23599560

The HSP, the QCN, and the Dragon: Developing inquiry-based QCN instructional modules in Taiwan

NASA Astrophysics Data System (ADS)

Chen, K. H.; Liang, W.; Chang, C.; Yen, E.; Lin, C.; Lin, G.

2012-12-01

High Scope Program (HSP) is a long-term project funded by NSC in Taiwan since 2006. It is designed to elevate the quality of science education by means of incorporating emerging science and technology into the traditional curricula in senior high schools. Quake-Catcher Network (QCN), a distributed computing project initiated by Stanford University and UC Riverside, encourages the volunteers to install the low-cost, novel sensors at home and school to build a seismic network. To meet both needs, we have developed a model curriculum that introduces QCN, earthquake science, and cloud computing into high school classrooms. Through professional development workshops, Taiwan cloud-based earthquake science learning platform, and QCN club on Facebook, we have worked closely with Lan-Yang Girl's Senior High School teachers' team to design workable teaching plans through a practical operation of seismic monitoring at home or school. However, some obstacles to learning appear including QCN installation/maintain problems, high self-noise of the sensor, difficulty of introducing earthquake sciences for high school teachers. The challenges of QCN outreach in Taiwan bring out our future plans: (1) development of easy, frequently updated, physics-based QCN-experiments for high school teachers, and (2) design of an interactive learning platform with social networking function for students.

Uncover the Cloud for Geospatial Sciences and Applications to Adopt Cloud Computing

NASA Astrophysics Data System (ADS)

Yang, C.; Huang, Q.; Xia, J.; Liu, K.; Li, J.; Xu, C.; Sun, M.; Bambacus, M.; Xu, Y.; Fay, D.

2012-12-01

Cloud computing is emerging as the future infrastructure for providing computing resources to support and enable scientific research, engineering development, and application construction, as well as work force education. On the other hand, there is a lot of doubt about the readiness of cloud computing to support a variety of scientific research, development and educations. This research is a project funded by NASA SMD to investigate through holistic studies how ready is the cloud computing to support geosciences. Four applications with different computing characteristics including data, computing, concurrent, and spatiotemporal intensities are taken to test the readiness of cloud computing to support geosciences. Three popular and representative cloud platforms including Amazon EC2, Microsoft Azure, and NASA Nebula as well as a traditional cluster are utilized in the study. Results illustrates that cloud is ready to some degree but more research needs to be done to fully implemented the cloud benefit as advertised by many vendors and defined by NIST. Specifically, 1) most cloud platform could help stand up new computing instances, a new computer, in a few minutes as envisioned, therefore, is ready to support most computing needs in an on demand fashion; 2) the load balance and elasticity, a defining characteristic, is ready in some cloud platforms, such as Amazon EC2, to support bigger jobs, e.g., needs response in minutes, while some are not ready to support the elasticity and load balance well. All cloud platform needs further research and development to support real time application at subminute level; 3) the user interface and functionality of cloud platforms vary a lot and some of them are very professional and well supported/documented, such as Amazon EC2, some of them needs significant improvement for the general public to adopt cloud computing without professional training or knowledge about computing infrastructure; 4) the security is a big concern in cloud computing platform, with the sharing spirit of cloud computing, it is very hard to ensure higher level security, except a private cloud is built for a specific organization without public access, public cloud platform does not support FISMA medium level yet and may never be able to support FISMA high level; 5) HPC jobs needs of cloud computing is not well supported and only Amazon EC2 supports this well. The research is being taken by NASA and other agencies to consider cloud computing adoption. We hope the publication of the research would also benefit the public to adopt cloud computing.

Point-Cloud Compression for Vehicle-Based Mobile Mapping Systems Using Portable Network Graphics

NASA Astrophysics Data System (ADS)

Kohira, K.; Masuda, H.

2017-09-01

A mobile mapping system is effective for capturing dense point-clouds of roads and roadside objects Point-clouds of urban areas, residential areas, and arterial roads are useful for maintenance of infrastructure, map creation, and automatic driving. However, the data size of point-clouds measured in large areas is enormously large. A large storage capacity is required to store such point-clouds, and heavy loads will be taken on network if point-clouds are transferred through the network. Therefore, it is desirable to reduce data sizes of point-clouds without deterioration of quality. In this research, we propose a novel point-cloud compression method for vehicle-based mobile mapping systems. In our compression method, point-clouds are mapped onto 2D pixels using GPS time and the parameters of the laser scanner. Then, the images are encoded in the Portable Networking Graphics (PNG) format and compressed using the PNG algorithm. In our experiments, our method could efficiently compress point-clouds without deteriorating the quality.

Distributed storage and cloud computing: a test case

NASA Astrophysics Data System (ADS)

Piano, S.; Delia Ricca, G.

2014-06-01

Since 2003 the computing farm hosted by the INFN Tier3 facility in Trieste supports the activities of many scientific communities. Hundreds of jobs from 45 different VOs, including those of the LHC experiments, are processed simultaneously. Given that normally the requirements of the different computational communities are not synchronized, the probability that at any given time the resources owned by one of the participants are not fully utilized is quite high. A balanced compensation should in principle allocate the free resources to other users, but there are limits to this mechanism. In fact, the Trieste site may not hold the amount of data needed to attract enough analysis jobs, and even in that case there could be a lack of bandwidth for their access. The Trieste ALICE and CMS computing groups, in collaboration with other Italian groups, aim to overcome the limitations of existing solutions using two approaches: sharing the data among all the participants taking full advantage of GARR-X wide area networks (10 GB/s) and integrating the resources dedicated to batch analysis with the ones reserved for dynamic interactive analysis, through modern solutions as cloud computing.

Cloud Computing for DoD

DTIC Science & Technology

2012-05-01

cloud computing 17 NASA Nebula Platform •  Cloud computing pilot program at NASA Ames •  Integrates open-source components into seamless, self...Mission support •  Education and public outreach (NASA Nebula , 2010) 18 NSF Supported Cloud Research •  Support for Cloud Computing in...Mell, P. & Grance, T. (2011). The NIST Definition of Cloud Computing. NIST Special Publication 800-145 •  NASA Nebula (2010). Retrieved from

Hybrid architecture for building secure sensor networks

NASA Astrophysics Data System (ADS)

Owens, Ken R., Jr.; Watkins, Steve E.

2012-04-01

Sensor networks have various communication and security architectural concerns. Three approaches are defined to address these concerns for sensor networks. The first area is the utilization of new computing architectures that leverage embedded virtualization software on the sensor. Deploying a small, embedded virtualization operating system on the sensor nodes that is designed to communicate to low-cost cloud computing infrastructure in the network is the foundation to delivering low-cost, secure sensor networks. The second area focuses on securing the sensor. Sensor security components include developing an identification scheme, and leveraging authentication algorithms and protocols that address security assurance within the physical, communication network, and application layers. This function will primarily be accomplished through encrypting the communication channel and integrating sensor network firewall and intrusion detection/prevention components to the sensor network architecture. Hence, sensor networks will be able to maintain high levels of security. The third area addresses the real-time and high priority nature of the data that sensor networks collect. This function requires that a quality-of-service (QoS) definition and algorithm be developed for delivering the right data at the right time. A hybrid architecture is proposed that combines software and hardware features to handle network traffic with diverse QoS requirements.

A Hybrid Cloud Computing Service for Earth Sciences

NASA Astrophysics Data System (ADS)

Yang, C. P.

2016-12-01

Cloud Computing is becoming a norm for providing computing capabilities for advancing Earth sciences including big Earth data management, processing, analytics, model simulations, and many other aspects. A hybrid spatiotemporal cloud computing service is bulit at George Mason NSF spatiotemporal innovation center to meet this demands. This paper will report the service including several aspects: 1) the hardware includes 500 computing services and close to 2PB storage as well as connection to XSEDE Jetstream and Caltech experimental cloud computing environment for sharing the resource; 2) the cloud service is geographically distributed at east coast, west coast, and central region; 3) the cloud includes private clouds managed using open stack and eucalyptus, DC2 is used to bridge these and the public AWS cloud for interoperability and sharing computing resources when high demands surfing; 4) the cloud service is used to support NSF EarthCube program through the ECITE project, ESIP through the ESIP cloud computing cluster, semantics testbed cluster, and other clusters; 5) the cloud service is also available for the earth science communities to conduct geoscience. A brief introduction about how to use the cloud service will be included.

Virtual pools for interactive analysis and software development through an integrated Cloud environment

NASA Astrophysics Data System (ADS)

Grandi, C.; Italiano, A.; Salomoni, D.; Calabrese Melcarne, A. K.

2011-12-01

WNoDeS, an acronym for Worker Nodes on Demand Service, is software developed at CNAF-Tier1, the National Computing Centre of the Italian Institute for Nuclear Physics (INFN) located in Bologna. WNoDeS provides on demand, integrated access to both Grid and Cloud resources through virtualization technologies. Besides the traditional use of computing resources in batch mode, users need to have interactive and local access to a number of systems. WNoDeS can dynamically select these computers instantiating Virtual Machines, according to the requirements (computing, storage and network resources) of users through either the Open Cloud Computing Interface API, or through a web console. An interactive use is usually limited to activities in user space, i.e. where the machine configuration is not modified. In some other instances the activity concerns development and testing of services and thus implies the modification of the system configuration (and, therefore, root-access to the resource). The former use case is a simple extension of the WNoDeS approach, where the resource is provided in interactive mode. The latter implies saving the virtual image at the end of each user session so that it can be presented to the user at subsequent requests. This work describes how the LHC experiments at INFN-Bologna are testing and making use of these dynamically created ad-hoc machines via WNoDeS to support flexible, interactive analysis and software development at the INFN Tier-1 Computing Centre.

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.

Cloud Computing and Its Applications in GIS

NASA Astrophysics Data System (ADS)

Kang, Cao

2011-12-01

Cloud computing is a novel computing paradigm that offers highly scalable and highly available distributed computing services. The objectives of this research are to: 1. analyze and understand cloud computing and its potential for GIS; 2. discover the feasibilities of migrating truly spatial GIS algorithms to distributed computing infrastructures; 3. explore a solution to host and serve large volumes of raster GIS data efficiently and speedily. These objectives thus form the basis for three professional articles. The first article is entitled "Cloud Computing and Its Applications in GIS". This paper introduces the concept, structure, and features of cloud computing. Features of cloud computing such as scalability, parallelization, and high availability make it a very capable computing paradigm. Unlike High Performance Computing (HPC), cloud computing uses inexpensive commodity computers. The uniform administration systems in cloud computing make it easier to use than GRID computing. Potential advantages of cloud-based GIS systems such as lower barrier to entry are consequently presented. Three cloud-based GIS system architectures are proposed: public cloud- based GIS systems, private cloud-based GIS systems and hybrid cloud-based GIS systems. Public cloud-based GIS systems provide the lowest entry barriers for users among these three architectures, but their advantages are offset by data security and privacy related issues. Private cloud-based GIS systems provide the best data protection, though they have the highest entry barriers. Hybrid cloud-based GIS systems provide a compromise between these extremes. The second article is entitled "A cloud computing algorithm for the calculation of Euclidian distance for raster GIS". Euclidean distance is a truly spatial GIS algorithm. Classical algorithms such as the pushbroom and growth ring techniques require computational propagation through the entire raster image, which makes it incompatible with the distributed nature of cloud computing. This paper presents a parallel Euclidean distance algorithm that works seamlessly with the distributed nature of cloud computing infrastructures. The mechanism of this algorithm is to subdivide a raster image into sub-images and wrap them with a one pixel deep edge layer of individually computed distance information. Each sub-image is then processed by a separate node, after which the resulting sub-images are reassembled into the final output. It is shown that while any rectangular sub-image shape can be used, those approximating squares are computationally optimal. This study also serves as a demonstration of this subdivide and layer-wrap strategy, which would enable the migration of many truly spatial GIS algorithms to cloud computing infrastructures. However, this research also indicates that certain spatial GIS algorithms such as cost distance cannot be migrated by adopting this mechanism, which presents significant challenges for the development of cloud-based GIS systems. The third article is entitled "A Distributed Storage Schema for Cloud Computing based Raster GIS Systems". This paper proposes a NoSQL Database Management System (NDDBMS) based raster GIS data storage schema. NDDBMS has good scalability and is able to use distributed commodity computers, which make it superior to Relational Database Management Systems (RDBMS) in a cloud computing environment. In order to provide optimized data service performance, the proposed storage schema analyzes the nature of commonly used raster GIS data sets. It discriminates two categories of commonly used data sets, and then designs corresponding data storage models for both categories. As a result, the proposed storage schema is capable of hosting and serving enormous volumes of raster GIS data speedily and efficiently on cloud computing infrastructures. In addition, the scheme also takes advantage of the data compression characteristics of Quadtrees, thus promoting efficient data storage. Through this assessment of cloud computing technology, the exploration of the challenges and solutions to the migration of GIS algorithms to cloud computing infrastructures, and the examination of strategies for serving large amounts of GIS data in a cloud computing infrastructure, this dissertation lends support to the feasibility of building a cloud-based GIS system. However, there are still challenges that need to be addressed before a full-scale functional cloud-based GIS system can be successfully implemented. (Abstract shortened by UMI.)

Integrating Containers in the CERN Private Cloud

NASA Astrophysics Data System (ADS)

Noel, Bertrand; Michelino, Davide; Velten, Mathieu; Rocha, Ricardo; Trigazis, Spyridon

2017-10-01

Containers remain a hot topic in computing, with new use cases and tools appearing every day. Basic functionality such as spawning containers seems to have settled, but topics like volume support or networking are still evolving. Solutions like Docker Swarm, Kubernetes or Mesos provide similar functionality but target different use cases, exposing distinct interfaces and APIs. The CERN private cloud is made of thousands of nodes and users, with many different use cases. A single solution for container deployment would not cover every one of them, and supporting multiple solutions involves repeating the same process multiple times for integration with authentication services, storage services or networking. In this paper we describe OpenStack Magnum as the solution to offer container management in the CERN cloud. We will cover its main functionality and some advanced use cases using Docker Swarm and Kubernetes, highlighting some relevant differences between the two. We will describe the most common use cases in HEP and how we integrated popular services like CVMFS or AFS in the most transparent way possible, along with some limitations found. Finally we will look into ongoing work on advanced scheduling for both Swarm and Kubernetes, support for running batch like workloads and integration of container networking technologies with the CERN infrastructure.

IBM Cloud Computing Powering a Smarter Planet

NASA Astrophysics Data System (ADS)

Zhu, Jinzy; Fang, Xing; Guo, Zhe; Niu, Meng Hua; Cao, Fan; Yue, Shuang; Liu, Qin Yu

With increasing need for intelligent systems supporting the world's businesses, Cloud Computing has emerged as a dominant trend to provide a dynamic infrastructure to make such intelligence possible. The article introduced how to build a smarter planet with cloud computing technology. First, it introduced why we need cloud, and the evolution of cloud technology. Secondly, it analyzed the value of cloud computing and how to apply cloud technology. Finally, it predicted the future of cloud in the smarter planet.

Cloud Computing Security Issue: Survey

NASA Astrophysics Data System (ADS)

Kamal, Shailza; Kaur, Rajpreet

2011-12-01

Cloud computing is the growing field in IT industry since 2007 proposed by IBM. Another company like Google, Amazon, and Microsoft provides further products to cloud computing. The cloud computing is the internet based computing that shared recourses, information on demand. It provides the services like SaaS, IaaS and PaaS. The services and recourses are shared by virtualization that run multiple operation applications on cloud computing. This discussion gives the survey on the challenges on security issues during cloud computing and describes some standards and protocols that presents how security can be managed.

Lost in Virtual Reality: Pathfinding Algorithms Detect Rock Fractures and Contacts in Point Clouds

NASA Astrophysics Data System (ADS)

Thiele, S.; Grose, L.; Micklethwaite, S.

2016-12-01

UAV-based photogrammetric and LiDAR techniques provide high resolution 3D point clouds and ortho-rectified photomontages that can capture surface geology in outstanding detail over wide areas. Automated and semi-automated methods are vital to extract full value from these data in practical time periods, though the nuances of geological structures and materials (natural variability in colour and geometry, soft and hard linkage, shadows and multiscale properties) make this a challenging task. We present a novel method for computer assisted trace detection in dense point clouds, using a lowest cost path solver to "follow" fracture traces and lithological contacts between user defined end points. This is achieved by defining a local neighbourhood network where each point in the cloud is linked to its neighbours, and then using a least-cost path algorithm to search this network and estimate the trace of the fracture or contact. A variety of different algorithms can then be applied to calculate the best fit plane, produce a fracture network, or map properties such as roughness, curvature and fracture intensity. Our prototype of this method (Fig. 1) suggests the technique is feasible and remarkably good at following traces under non-optimal conditions such as variable-shadow, partial occlusion and complex fracturing. Furthermore, if a fracture is initially mapped incorrectly, the user can easily provide further guidance by defining intermediate waypoints. Future development will include optimization of the algorithm to perform well on large point clouds and modifications that permit the detection of features such as step-overs. We also plan on implementing this approach in an interactive graphical user environment.

T-Check in System-of-Systems Technologies: Cloud Computing

DTIC Science & Technology

2010-09-01

T-Check in System-of-Systems Technologies: Cloud Computing Harrison D. Strowd Grace A. Lewis September 2010 TECHNICAL NOTE CMU/SEI-2010... Cloud Computing 1 1.2 Types of Cloud Computing 2 1.3 Drivers and Barriers to Cloud Computing Adoption 5 2 Using the T-Check Method 7 2.1 T-Check...Hypothesis 3 25 3.4.2 Deployment View of the Solution for Testing Hypothesis 3 27 3.5 Selecting Cloud Computing Providers 30 3.6 Implementing the T-Check

Information Security: Governmentwide Guidance Needed to Assist Agencies in Implementing Cloud Computing

DTIC Science & Technology

2010-07-01

Cloud computing , an emerging form of computing in which users have access to scalable, on-demand capabilities that are provided through Internet... cloud computing , (2) the information security implications of using cloud computing services in the Federal Government, and (3) federal guidance and...efforts to address information security when using cloud computing . The complete report is titled Information Security: Federal Guidance Needed to

E-Learning 3.0 = E-Learning 2.0 + Web 3.0?

ERIC Educational Resources Information Center

Hussain, Fehmida

2012-01-01

Web 3.0, termed as the semantic web or the web of data is the transformed version of Web 2.0 with technologies and functionalities such as intelligent collaborative filtering, cloud computing, big data, linked data, openness, interoperability and smart mobility. If Web 2.0 is about social networking and mass collaboration between the creator and…

HammerCloud: A Stress Testing System for Distributed Analysis

NASA Astrophysics Data System (ADS)

van der Ster, Daniel C.; Elmsheuser, Johannes; Úbeda García, Mario; Paladin, Massimo

2011-12-01

Distributed analysis of LHC data is an I/O-intensive activity which places large demands on the internal network, storage, and local disks at remote computing facilities. Commissioning and maintaining a site to provide an efficient distributed analysis service is therefore a challenge which can be aided by tools to help evaluate a variety of infrastructure designs and configurations. HammerCloud is one such tool; it is a stress testing service which is used by central operations teams, regional coordinators, and local site admins to (a) submit arbitrary number of analysis jobs to a number of sites, (b) maintain at a steady-state a predefined number of jobs running at the sites under test, (c) produce web-based reports summarizing the efficiency and performance of the sites under test, and (d) present a web-interface for historical test results to both evaluate progress and compare sites. HammerCloud was built around the distributed analysis framework Ganga, exploiting its API for grid job management. HammerCloud has been employed by the ATLAS experiment for continuous testing of many sites worldwide, and also during large scale computing challenges such as STEP'09 and UAT'09, where the scale of the tests exceeded 10,000 concurrently running and 1,000,000 total jobs over multi-day periods. In addition, HammerCloud is being adopted by the CMS experiment; the plugin structure of HammerCloud allows the execution of CMS jobs using their official tool (CRAB).

Risk in the Clouds?: Security Issues Facing Government Use of Cloud Computing

NASA Astrophysics Data System (ADS)

Wyld, David C.

Cloud computing is poised to become one of the most important and fundamental shifts in how computing is consumed and used. Forecasts show that government will play a lead role in adopting cloud computing - for data storage, applications, and processing power, as IT executives seek to maximize their returns on limited procurement budgets in these challenging economic times. After an overview of the cloud computing concept, this article explores the security issues facing public sector use of cloud computing and looks to the risk and benefits of shifting to cloud-based models. It concludes with an analysis of the challenges that lie ahead for government use of cloud resources.

A Review Study on Cloud Computing Issues

NASA Astrophysics Data System (ADS)

Kanaan Kadhim, Qusay; Yusof, Robiah; Sadeq Mahdi, Hamid; Al-shami, Sayed Samer Ali; Rahayu Selamat, Siti

2018-05-01

Cloud computing is the most promising current implementation of utility computing in the business world, because it provides some key features over classic utility computing, such as elasticity to allow clients dynamically scale-up and scale-down the resources in execution time. Nevertheless, cloud computing is still in its premature stage and experiences lack of standardization. The security issues are the main challenges to cloud computing adoption. Thus, critical industries such as government organizations (ministries) are reluctant to trust cloud computing due to the fear of losing their sensitive data, as it resides on the cloud with no knowledge of data location and lack of transparency of Cloud Service Providers (CSPs) mechanisms used to secure their data and applications which have created a barrier against adopting this agile computing paradigm. This study aims to review and classify the issues that surround the implementation of cloud computing which a hot area that needs to be addressed by future research.

Accelerating Astronomy & Astrophysics in the New Era of Parallel Computing: GPUs, Phi and Cloud Computing

NASA Astrophysics Data System (ADS)

Ford, Eric B.; Dindar, Saleh; Peters, Jorg

2015-08-01

The realism of astrophysical simulations and statistical analyses of astronomical data are set by the available computational resources. Thus, astronomers and astrophysicists are constantly pushing the limits of computational capabilities. For decades, astronomers benefited from massive improvements in computational power that were driven primarily by increasing clock speeds and required relatively little attention to details of the computational hardware. For nearly a decade, increases in computational capabilities have come primarily from increasing the degree of parallelism, rather than increasing clock speeds. Further increases in computational capabilities will likely be led by many-core architectures such as Graphical Processing Units (GPUs) and Intel Xeon Phi. Successfully harnessing these new architectures, requires significantly more understanding of the hardware architecture, cache hierarchy, compiler capabilities and network network characteristics.I will provide an astronomer's overview of the opportunities and challenges provided by modern many-core architectures and elastic cloud computing. The primary goal is to help an astronomical audience understand what types of problems are likely to yield more than order of magnitude speed-ups and which problems are unlikely to parallelize sufficiently efficiently to be worth the development time and/or costs.I will draw on my experience leading a team in developing the Swarm-NG library for parallel integration of large ensembles of small n-body systems on GPUs, as well as several smaller software projects. I will share lessons learned from collaborating with computer scientists, including both technical and soft skills. Finally, I will discuss the challenges of training the next generation of astronomers to be proficient in this new era of high-performance computing, drawing on experience teaching a graduate class on High-Performance Scientific Computing for Astrophysics and organizing a 2014 advanced summer school on Bayesian Computing for Astronomical Data Analysis with support of the Penn State Center for Astrostatistics and Institute for CyberScience.

78 FR 54453 - Notice of Public Meeting-Intersection of Cloud Computing and Mobility Forum and Workshop

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-04

...--Intersection of Cloud Computing and Mobility Forum and Workshop AGENCY: National Institute of Standards and.../intersection-of-cloud-and-mobility.cfm . SUPPLEMENTARY INFORMATION: NIST hosted six prior Cloud Computing Forum... interoperability, portability, and security, discuss the Federal Government's experience with cloud computing...

Embracing the Cloud: Six Ways to Look at the Shift to Cloud Computing

ERIC Educational Resources Information Center

Ullman, David F.; Haggerty, Blake

2010-01-01

Cloud computing is the latest paradigm shift for the delivery of IT services. Where previous paradigms (centralized, decentralized, distributed) were based on fairly straightforward approaches to technology and its management, cloud computing is radical in comparison. The literature on cloud computing, however, suffers from many divergent…

The Research of the Parallel Computing Development from the Angle of Cloud Computing

NASA Astrophysics Data System (ADS)

Peng, Zhensheng; Gong, Qingge; Duan, Yanyu; Wang, Yun

2017-10-01

Cloud computing is the development of parallel computing, distributed computing and grid computing. The development of cloud computing makes parallel computing come into people’s lives. Firstly, this paper expounds the concept of cloud computing and introduces two several traditional parallel programming model. Secondly, it analyzes and studies the principles, advantages and disadvantages of OpenMP, MPI and Map Reduce respectively. Finally, it takes MPI, OpenMP models compared to Map Reduce from the angle of cloud computing. The results of this paper are intended to provide a reference for the development of parallel computing.

Cloud computing basics for librarians.

PubMed

Hoy, Matthew B

2012-01-01

"Cloud computing" is the name for the recent trend of moving software and computing resources to an online, shared-service model. This article briefly defines cloud computing, discusses different models, explores the advantages and disadvantages, and describes some of the ways cloud computing can be used in libraries. Examples of cloud services are included at the end of the article. Copyright © Taylor & Francis Group, LLC

Large-scale virtual screening on public cloud resources with Apache Spark.

PubMed

Capuccini, Marco; Ahmed, Laeeq; Schaal, Wesley; Laure, Erwin; Spjuth, Ola

2017-01-01

Structure-based virtual screening is an in-silico method to screen a target receptor against a virtual molecular library. Applying docking-based screening to large molecular libraries can be computationally expensive, however it constitutes a trivially parallelizable task. Most of the available parallel implementations are based on message passing interface, relying on low failure rate hardware and fast network connection. Google's MapReduce revolutionized large-scale analysis, enabling the processing of massive datasets on commodity hardware and cloud resources, providing transparent scalability and fault tolerance at the software level. Open source implementations of MapReduce include Apache Hadoop and the more recent Apache Spark. We developed a method to run existing docking-based screening software on distributed cloud resources, utilizing the MapReduce approach. We benchmarked our method, which is implemented in Apache Spark, docking a publicly available target receptor against [Formula: see text]2.2 M compounds. The performance experiments show a good parallel efficiency (87%) when running in a public cloud environment. Our method enables parallel Structure-based virtual screening on public cloud resources or commodity computer clusters. The degree of scalability that we achieve allows for trying out our method on relatively small libraries first and then to scale to larger libraries. Our implementation is named Spark-VS and it is freely available as open source from GitHub (https://github.com/mcapuccini/spark-vs).Graphical abstract.

On the way to the smart education in the cloud: The experience of using a virtual learning environment and webinars in educational and career guidance process

NASA Astrophysics Data System (ADS)

Lapshinsky, V. A.

2017-01-01

The article is devoted to the consideration of issues of functionality and application of educational portal as virtual learning environments and webinars as SaaS services. Examples of their use in educational and vocational guidance processes are presented. The prospects of transition from portal VLE to SaaS and cloud services are marked. Portal www.valinfo.ru with original learning management system has been used in the educational process since 2003 in the National Research Nuclear University MEPhI and in the Peoples' Friendship University of Russia. Supported courses: Computer Science, Computer Workshop, Networks, Information Technology, The Introduction to Nano-Engineer, Nanotechnology and Nanomaterials etc. For webinars as SaaS services, used the "virtual classroom," kindly provided by WebSoft Company.

Ground-based cloud classification by learning stable local binary patterns

NASA Astrophysics Data System (ADS)

Wang, Yu; Shi, Cunzhao; Wang, Chunheng; Xiao, Baihua

2018-07-01

Feature selection and extraction is the first step in implementing pattern classification. The same is true for ground-based cloud classification. Histogram features based on local binary patterns (LBPs) are widely used to classify texture images. However, the conventional uniform LBP approach cannot capture all the dominant patterns in cloud texture images, thereby resulting in low classification performance. In this study, a robust feature extraction method by learning stable LBPs is proposed based on the averaged ranks of the occurrence frequencies of all rotation invariant patterns defined in the LBPs of cloud images. The proposed method is validated with a ground-based cloud classification database comprising five cloud types. Experimental results demonstrate that the proposed method achieves significantly higher classification accuracy than the uniform LBP, local texture patterns (LTP), dominant LBP (DLBP), completed LBP (CLTP) and salient LBP (SaLBP) methods in this cloud image database and under different noise conditions. And the performance of the proposed method is comparable with that of the popular deep convolutional neural network (DCNN) method, but with less computation complexity. Furthermore, the proposed method also achieves superior performance on an independent test data set.

Internet of Things (IoT) Based Design of a Secure and Lightweight Body Area Network (BAN) Healthcare System

PubMed Central

Deng, Yong-Yuan; Chen, Chin-Ling; Tsaur, Woei-Jiunn; Tang, Yung-Wen; Chen, Jung-Hsuan

2017-01-01

As sensor networks and cloud computation technologies have rapidly developed over recent years, many services and applications integrating these technologies into daily life have come together as an Internet of Things (IoT). At the same time, aging populations have increased the need for expanded and more efficient elderly care services. Fortunately, elderly people can now wear sensing devices which relay data to a personal wireless device, forming a body area network (BAN). These personal wireless devices collect and integrate patients’ personal physiological data, and then transmit the data to the backend of the network for related diagnostics. However, a great deal of the information transmitted by such systems is sensitive data, and must therefore be subject to stringent security protocols. Protecting this data from unauthorized access is thus an important issue in IoT-related research. In regard to a cloud healthcare environment, scholars have proposed a secure mechanism to protect sensitive patient information. Their schemes provide a general architecture; however, these previous schemes still have some vulnerability, and thus cannot guarantee complete security. This paper proposes a secure and lightweight body-sensor network based on the Internet of Things for cloud healthcare environments, in order to address the vulnerabilities discovered in previous schemes. The proposed authentication mechanism is applied to a medical reader to provide a more comprehensive architecture while also providing mutual authentication, and guaranteeing data integrity, user untraceability, and forward and backward secrecy, in addition to being resistant to replay attack. PMID:29244776

Eleven quick tips for architecting biomedical informatics workflows with cloud computing.

PubMed

Cole, Brian S; Moore, Jason H

2018-03-01

Cloud computing has revolutionized the development and operations of hardware and software across diverse technological arenas, yet academic biomedical research has lagged behind despite the numerous and weighty advantages that cloud computing offers. Biomedical researchers who embrace cloud computing can reap rewards in cost reduction, decreased development and maintenance workload, increased reproducibility, ease of sharing data and software, enhanced security, horizontal and vertical scalability, high availability, a thriving technology partner ecosystem, and much more. Despite these advantages that cloud-based workflows offer, the majority of scientific software developed in academia does not utilize cloud computing and must be migrated to the cloud by the user. In this article, we present 11 quick tips for architecting biomedical informatics workflows on compute clouds, distilling knowledge gained from experience developing, operating, maintaining, and distributing software and virtualized appliances on the world's largest cloud. Researchers who follow these tips stand to benefit immediately by migrating their workflows to cloud computing and embracing the paradigm of abstraction.

Eleven quick tips for architecting biomedical informatics workflows with cloud computing

PubMed Central

Moore, Jason H.

2018-01-01

Cloud computing has revolutionized the development and operations of hardware and software across diverse technological arenas, yet academic biomedical research has lagged behind despite the numerous and weighty advantages that cloud computing offers. Biomedical researchers who embrace cloud computing can reap rewards in cost reduction, decreased development and maintenance workload, increased reproducibility, ease of sharing data and software, enhanced security, horizontal and vertical scalability, high availability, a thriving technology partner ecosystem, and much more. Despite these advantages that cloud-based workflows offer, the majority of scientific software developed in academia does not utilize cloud computing and must be migrated to the cloud by the user. In this article, we present 11 quick tips for architecting biomedical informatics workflows on compute clouds, distilling knowledge gained from experience developing, operating, maintaining, and distributing software and virtualized appliances on the world’s largest cloud. Researchers who follow these tips stand to benefit immediately by migrating their workflows to cloud computing and embracing the paradigm of abstraction. PMID:29596416

Research on Quantum Authentication Methods for the Secure Access Control Among Three Elements of Cloud Computing

NASA Astrophysics Data System (ADS)

Dong, Yumin; Xiao, Shufen; Ma, Hongyang; Chen, Libo

2016-12-01

Cloud computing and big data have become the developing engine of current information technology (IT) as a result of the rapid development of IT. However, security protection has become increasingly important for cloud computing and big data, and has become a problem that must be solved to develop cloud computing. The theft of identity authentication information remains a serious threat to the security of cloud computing. In this process, attackers intrude into cloud computing services through identity authentication information, thereby threatening the security of data from multiple perspectives. Therefore, this study proposes a model for cloud computing protection and management based on quantum authentication, introduces the principle of quantum authentication, and deduces the quantum authentication process. In theory, quantum authentication technology can be applied in cloud computing for security protection. This technology cannot be cloned; thus, it is more secure and reliable than classical methods.

Mobility and Cloud: Operating in Intermittent, Austere Network Conditions

DTIC Science & Technology

2014-09-01

consume information, and are connected to cloud-based servers over wired or wireless network connections. For mobile clients, this connection, by...near future. In addition to intermittent connectivity issues, many wireless networks introduce additional delay due to excessive buffering. This can...requirements, commercial cloud applications have grown at a fast rate. Similar to other mobile systems, navy ships connected over wireless networks

Application-oriented integrated control center (AICC) for heterogeneous optical networks

NASA Astrophysics Data System (ADS)

Zhao, Yongli; Zhang, Jie; Cao, Xuping; Wang, Dajiang; Wu, Koubo; Cai, Yinxiang; Gu, Wanyi

2011-12-01

Various broad bandwidth services have being swallowing the bandwidth resource of optical networks, such as the data center application and cloud computation. There are still some challenges for future optical networks although the available bandwidth is increasing with the development of transmission technologies. The relationship between upper application layer and lower network resource layer is necessary to be researched further. In order to improve the efficiency of network resources and capability of service provisioning, heterogeneous optical networks resource can be abstracted as unified Application Programming Interfaces (APIs) which can be open to various upper applications through Application-oriented Integrated Control Center (AICC) proposed in the paper. A novel Openflow-based unified control architecture is proposed for the optimization of cross layer resources. Numeric results show good performance of AICC through simulation experiments.

Establishing a Cloud Computing Success Model for Hospitals in Taiwan.

PubMed

Lian, Jiunn-Woei

2017-01-01

The purpose of this study is to understand the critical quality-related factors that affect cloud computing success of hospitals in Taiwan. In this study, private cloud computing is the major research target. The chief information officers participated in a questionnaire survey. The results indicate that the integration of trust into the information systems success model will have acceptable explanatory power to understand cloud computing success in the hospital. Moreover, information quality and system quality directly affect cloud computing satisfaction, whereas service quality indirectly affects the satisfaction through trust. In other words, trust serves as the mediator between service quality and satisfaction. This cloud computing success model will help hospitals evaluate or achieve success after adopting private cloud computing health care services.

Establishing a Cloud Computing Success Model for Hospitals in Taiwan

PubMed Central

Lian, Jiunn-Woei

2017-01-01

The purpose of this study is to understand the critical quality-related factors that affect cloud computing success of hospitals in Taiwan. In this study, private cloud computing is the major research target. The chief information officers participated in a questionnaire survey. The results indicate that the integration of trust into the information systems success model will have acceptable explanatory power to understand cloud computing success in the hospital. Moreover, information quality and system quality directly affect cloud computing satisfaction, whereas service quality indirectly affects the satisfaction through trust. In other words, trust serves as the mediator between service quality and satisfaction. This cloud computing success model will help hospitals evaluate or achieve success after adopting private cloud computing health care services. PMID:28112020

Implementation of cloud computing in higher education

NASA Astrophysics Data System (ADS)

Asniar; Budiawan, R.

2016-04-01

Cloud computing research is a new trend in distributed computing, where people have developed service and SOA (Service Oriented Architecture) based application. This technology is very useful to be implemented, especially for higher education. This research is studied the need and feasibility for the suitability of cloud computing in higher education then propose the model of cloud computing service in higher education in Indonesia that can be implemented in order to support academic activities. Literature study is used as the research methodology to get a proposed model of cloud computing in higher education. Finally, SaaS and IaaS are cloud computing service that proposed to be implemented in higher education in Indonesia and cloud hybrid is the service model that can be recommended.

Research on Key Technologies of Cloud Computing

NASA Astrophysics Data System (ADS)

Zhang, Shufen; Yan, Hongcan; Chen, Xuebin

With the development of multi-core processors, virtualization, distributed storage, broadband Internet and automatic management, a new type of computing mode named cloud computing is produced. It distributes computation task on the resource pool which consists of massive computers, so the application systems can obtain the computing power, the storage space and software service according to its demand. It can concentrate all the computing resources and manage them automatically by the software without intervene. This makes application offers not to annoy for tedious details and more absorbed in his business. It will be advantageous to innovation and reduce cost. It's the ultimate goal of cloud computing to provide calculation, services and applications as a public facility for the public, So that people can use the computer resources just like using water, electricity, gas and telephone. Currently, the understanding of cloud computing is developing and changing constantly, cloud computing still has no unanimous definition. This paper describes three main service forms of cloud computing: SAAS, PAAS, IAAS, compared the definition of cloud computing which is given by Google, Amazon, IBM and other companies, summarized the basic characteristics of cloud computing, and emphasized on the key technologies such as data storage, data management, virtualization and programming model.

Trust models for efficient communication in Mobile Cloud Computing and their applications to e-Commerce

NASA Astrophysics Data System (ADS)

Pop, Florin; Dobre, Ciprian; Mocanu, Bogdan-Costel; Citoteanu, Oana-Maria; Xhafa, Fatos

2016-11-01

Managing the large dimensions of data processed in distributed systems that are formed by datacentres and mobile devices has become a challenging issue with an important impact on the end-user. Therefore, the management process of such systems can be achieved efficiently by using uniform overlay networks, interconnected through secure and efficient routing protocols. The aim of this article is to advance our previous work with a novel trust model based on a reputation metric that actively uses the social links between users and the model of interaction between them. We present and evaluate an adaptive model for the trust management in structured overlay networks, based on a Mobile Cloud architecture and considering a honeycomb overlay. Such a model can be useful for supporting advanced mobile market-share e-Commerce platforms, where users collaborate and exchange reliable information about, for example, products of interest and supporting ad-hoc business campaigns

Cloud-based application for rice moisture content measurement using image processing technique and perceptron neural network

NASA Astrophysics Data System (ADS)

Cruz, Febus Reidj G.; Padilla, Dionis A.; Hortinela, Carlos C.; Bucog, Krissel C.; Sarto, Mildred C.; Sia, Nirlu Sebastian A.; Chung, Wen-Yaw

2017-02-01

This study is about the determination of moisture content of milled rice using image processing technique and perceptron neural network algorithm. The algorithm involves several inputs that produces an output which is the moisture content of the milled rice. Several types of milled rice are used in this study, namely: Jasmine, Kokuyu, 5-Star, Ifugao, Malagkit, and NFA rice. The captured images are processed using MATLAB R2013a software. There is a USB dongle connected to the router which provided internet connection for online web access. The GizDuino IOT-644 is used for handling the temperature and humidity sensor, and for sending and receiving of data from computer to the cloud storage. The result is compared to the actual moisture content range using a moisture tester for milled rice. Based on results, this study provided accurate data in determining the moisture content of the milled rice.

Design and implementation of website information disclosure assessment system.

PubMed

Cho, Ying-Chiang; Pan, Jen-Yi

2015-01-01

Internet application technologies, such as cloud computing and cloud storage, have increasingly changed people's lives. Websites contain vast amounts of personal privacy information. In order to protect this information, network security technologies, such as database protection and data encryption, attract many researchers. The most serious problems concerning web vulnerability are e-mail address and network database leakages. These leakages have many causes. For example, malicious users can steal database contents, taking advantage of mistakes made by programmers and administrators. In order to mitigate this type of abuse, a website information disclosure assessment system is proposed in this study. This system utilizes a series of technologies, such as web crawler algorithms, SQL injection attack detection, and web vulnerability mining, to assess a website's information disclosure. Thirty websites, randomly sampled from the top 50 world colleges, were used to collect leakage information. This testing showed the importance of increasing the security and privacy of website information for academic websites.

The Many Colors and Shapes of Cloud

NASA Astrophysics Data System (ADS)

Yeh, James T.

While many enterprises and business entities are deploying and exploiting Cloud Computing, the academic institutes and researchers are also busy trying to wrestle this beast and put a leash on this possible paradigm changing computing model. Many have argued that Cloud Computing is nothing more than a name change of Utility Computing. Others have argued that Cloud Computing is a revolutionary change of the computing architecture. So it has been difficult to put a boundary of what is in Cloud Computing, and what is not. I assert that it is equally difficult to find a group of people who would agree on even the definition of Cloud Computing. In actuality, may be all that arguments are not necessary, as Clouds have many shapes and colors. In this presentation, the speaker will attempt to illustrate that the shape and the color of the cloud depend very much on the business goals one intends to achieve. It will be a very rich territory for both the businesses to take the advantage of the benefits of Cloud Computing and the academia to integrate the technology research and business research.

ATLAS Cloud R&D

NASA Astrophysics Data System (ADS)

Panitkin, Sergey; Barreiro Megino, Fernando; Caballero Bejar, Jose; Benjamin, Doug; Di Girolamo, Alessandro; Gable, Ian; Hendrix, Val; Hover, John; Kucharczyk, Katarzyna; Medrano Llamas, Ramon; Love, Peter; Ohman, Henrik; Paterson, Michael; Sobie, Randall; Taylor, Ryan; Walker, Rodney; Zaytsev, Alexander; Atlas Collaboration

2014-06-01

The computing model of the ATLAS experiment was designed around the concept of grid computing and, since the start of data taking, this model has proven very successful. However, new cloud computing technologies bring attractive features to improve the operations and elasticity of scientific distributed computing. ATLAS sees grid and cloud computing as complementary technologies that will coexist at different levels of resource abstraction, and two years ago created an R&D working group to investigate the different integration scenarios. The ATLAS Cloud Computing R&D has been able to demonstrate the feasibility of offloading work from grid to cloud sites and, as of today, is able to integrate transparently various cloud resources into the PanDA workload management system. The ATLAS Cloud Computing R&D is operating various PanDA queues on private and public resources and has provided several hundred thousand CPU days to the experiment. As a result, the ATLAS Cloud Computing R&D group has gained a significant insight into the cloud computing landscape and has identified points that still need to be addressed in order to fully utilize this technology. This contribution will explain the cloud integration models that are being evaluated and will discuss ATLAS' learning during the collaboration with leading commercial and academic cloud providers.

Short-term solar irradiance forecasting via satellite/model coupling

DOE PAGES

Miller, Steven D.; Rogers, Matthew A.; Haynes, John M.; ...

2017-12-01

The short-term (0-3 h) prediction of solar insolation for renewable energy production is a problem well-suited to satellite-based techniques. The spatial, spectral, temporal and radiometric resolution of instrumentation hosted on the geostationary platform allows these satellites to describe the current cloud spatial distribution and optical properties. These properties relate directly to the transient properties of the downwelling solar irradiance at the surface, which come in the form of 'ramps' that pose a central challenge to energy load balancing in a spatially distributed network of solar farms. The short-term evolution of the cloud field may be approximated to first order simplymore » as translational, but care must be taken in how the advection is handled and where the impacts are assigned. In this research, we describe how geostationary satellite observations are used with operational cloud masking and retrieval algorithms, wind field data from Numerical Weather Prediction (NWP), and radiative transfer calculations to produce short-term forecasts of solar insolation for applications in solar power generation. The scheme utilizes retrieved cloud properties to group pixels into contiguous cloud objects whose future positions are predicted using four-dimensional (space + time) model wind fields, selecting steering levels corresponding to the cloud height properties of each cloud group. The shadows associated with these clouds are adjusted for sensor viewing parallax displacement and combined with solar geometry and terrain height to determine the actual location of cloud shadows. For mid/high-level clouds at mid-latitudes and high solar zenith angles, the combined displacements from these geometric considerations are non-negligible. The cloud information is used to initialize a radiative transfer model that computes the direct and diffuse-sky solar insolation at both shadow locations and intervening clear-sky regions. Here, we describe the formulation of the algorithm and validate its performance against Surface Radiation (SURFRAD; Augustine et al., 2000, 2005) network observations. Typical errors range from 8.5% to 17.2% depending on the complexity of cloud regimes, and an operational demonstration outperformed persistence-based forecasting of Global Horizontal Irradiance (GHI) under all conditions by ~10 W/m2.« less

Short-term solar irradiance forecasting via satellite/model coupling

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

Miller, Steven D.; Rogers, Matthew A.; Haynes, John M.

The short-term (0-3 h) prediction of solar insolation for renewable energy production is a problem well-suited to satellite-based techniques. The spatial, spectral, temporal and radiometric resolution of instrumentation hosted on the geostationary platform allows these satellites to describe the current cloud spatial distribution and optical properties. These properties relate directly to the transient properties of the downwelling solar irradiance at the surface, which come in the form of 'ramps' that pose a central challenge to energy load balancing in a spatially distributed network of solar farms. The short-term evolution of the cloud field may be approximated to first order simplymore » as translational, but care must be taken in how the advection is handled and where the impacts are assigned. In this research, we describe how geostationary satellite observations are used with operational cloud masking and retrieval algorithms, wind field data from Numerical Weather Prediction (NWP), and radiative transfer calculations to produce short-term forecasts of solar insolation for applications in solar power generation. The scheme utilizes retrieved cloud properties to group pixels into contiguous cloud objects whose future positions are predicted using four-dimensional (space + time) model wind fields, selecting steering levels corresponding to the cloud height properties of each cloud group. The shadows associated with these clouds are adjusted for sensor viewing parallax displacement and combined with solar geometry and terrain height to determine the actual location of cloud shadows. For mid/high-level clouds at mid-latitudes and high solar zenith angles, the combined displacements from these geometric considerations are non-negligible. The cloud information is used to initialize a radiative transfer model that computes the direct and diffuse-sky solar insolation at both shadow locations and intervening clear-sky regions. Here, we describe the formulation of the algorithm and validate its performance against Surface Radiation (SURFRAD; Augustine et al., 2000, 2005) network observations. Typical errors range from 8.5% to 17.2% depending on the complexity of cloud regimes, and an operational demonstration outperformed persistence-based forecasting of Global Horizontal Irradiance (GHI) under all conditions by ~10 W/m2.« less

The Education Value of Cloud Computing

ERIC Educational Resources Information Center

Katzan, Harry, Jr.

2010-01-01

Cloud computing is a technique for supplying computer facilities and providing access to software via the Internet. Cloud computing represents a contextual shift in how computers are provisioned and accessed. One of the defining characteristics of cloud software service is the transfer of control from the client domain to the service provider.…

Cloud Computing. Technology Briefing. Number 1

ERIC Educational Resources Information Center

Alberta Education, 2013

2013-01-01

Cloud computing is Internet-based computing in which shared resources, software and information are delivered as a service that computers or mobile devices can access on demand. Cloud computing is already used extensively in education. Free or low-cost cloud-based services are used daily by learners and educators to support learning, social…

Can cloud computing benefit health services? - a SWOT analysis.

PubMed

Kuo, Mu-Hsing; Kushniruk, Andre; Borycki, Elizabeth

2011-01-01

In this paper, we discuss cloud computing, the current state of cloud computing in healthcare, and the challenges and opportunities of adopting cloud computing in healthcare. A Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis was used to evaluate the feasibility of adopting this computing model in healthcare. The paper concludes that cloud computing could have huge benefits for healthcare but there are a number of issues that will need to be addressed before its widespread use in healthcare.

A Survey on Data Storage and Information Discovery in the WSANs-Based Edge Computing Systems

PubMed Central

Liang, Junbin; Liu, Renping; Ni, Wei; Li, Yin; Li, Ran; Ma, Wenpeng; Qi, Chuanda

2018-01-01

In the post-Cloud era, the proliferation of Internet of Things (IoT) has pushed the horizon of Edge computing, which is a new computing paradigm with data processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs) play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems. PMID:29439442

A Survey on Data Storage and Information Discovery in the WSANs-Based Edge Computing Systems.

PubMed

Ma, Xingpo; Liang, Junbin; Liu, Renping; Ni, Wei; Li, Yin; Li, Ran; Ma, Wenpeng; Qi, Chuanda

2018-02-10

In the post-Cloud era, the proliferation of Internet of Things (IoT) has pushed the horizon of Edge computing, which is a new computing paradigm with data are processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs) play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems.

Automatic Classification of Trees from Laser Scanning Point Clouds

NASA Astrophysics Data System (ADS)

Sirmacek, B.; Lindenbergh, R.

2015-08-01

Development of laser scanning technologies has promoted tree monitoring studies to a new level, as the laser scanning point clouds enable accurate 3D measurements in a fast and environmental friendly manner. In this paper, we introduce a probability matrix computation based algorithm for automatically classifying laser scanning point clouds into 'tree' and 'non-tree' classes. Our method uses the 3D coordinates of the laser scanning points as input and generates a new point cloud which holds a label for each point indicating if it belongs to the 'tree' or 'non-tree' class. To do so, a grid surface is assigned to the lowest height level of the point cloud. The grids are filled with probability values which are calculated by checking the point density above the grid. Since the tree trunk locations appear with very high values in the probability matrix, selecting the local maxima of the grid surface help to detect the tree trunks. Further points are assigned to tree trunks if they appear in the close proximity of trunks. Since heavy mathematical computations (such as point cloud organization, detailed shape 3D detection methods, graph network generation) are not required, the proposed algorithm works very fast compared to the existing methods. The tree classification results are found reliable even on point clouds of cities containing many different objects. As the most significant weakness, false detection of light poles, traffic signs and other objects close to trees cannot be prevented. Nevertheless, the experimental results on mobile and airborne laser scanning point clouds indicate the possible usage of the algorithm as an important step for tree growth observation, tree counting and similar applications. While the laser scanning point cloud is giving opportunity to classify even very small trees, accuracy of the results is reduced in the low point density areas further away than the scanning location. These advantages and disadvantages of two laser scanning point cloud sources are discussed in detail.

If It's in the Cloud, Get It on Paper: Cloud Computing Contract Issues

ERIC Educational Resources Information Center

Trappler, Thomas J.

2010-01-01

Much recent discussion has focused on the pros and cons of cloud computing. Some institutions are attracted to cloud computing benefits such as rapid deployment, flexible scalability, and low initial start-up cost, while others are concerned about cloud computing risks such as those related to data location, level of service, and security…

Introducing the Cloud in an Introductory IT Course

ERIC Educational Resources Information Center

Woods, David M.

2018-01-01

Cloud computing is a rapidly emerging topic, but should it be included in an introductory IT course? The magnitude of cloud computing use, especially cloud infrastructure, along with students' limited knowledge of the topic support adding cloud content to the IT curriculum. There are several arguments that support including cloud computing in an…

Enabling Earth Science Through Cloud Computing

NASA Technical Reports Server (NTRS)

Hardman, Sean; Riofrio, Andres; Shams, Khawaja; Freeborn, Dana; Springer, Paul; Chafin, Brian

2012-01-01

Cloud Computing holds tremendous potential for missions across the National Aeronautics and Space Administration. Several flight missions are already benefiting from an investment in cloud computing for mission critical pipelines and services through faster processing time, higher availability, and drastically lower costs available on cloud systems. However, these processes do not currently extend to general scientific algorithms relevant to earth science missions. The members of the Airborne Cloud Computing Environment task at the Jet Propulsion Laboratory have worked closely with the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) mission to integrate cloud computing into their science data processing pipeline. This paper details the efforts involved in deploying a science data system for the CARVE mission, evaluating and integrating cloud computing solutions with the system and porting their science algorithms for execution in a cloud environment.

Enhancing Security by System-Level Virtualization in Cloud Computing Environments

NASA Astrophysics Data System (ADS)

Sun, Dawei; Chang, Guiran; Tan, Chunguang; Wang, Xingwei

Many trends are opening up the era of cloud computing, which will reshape the IT industry. Virtualization techniques have become an indispensable ingredient for almost all cloud computing system. By the virtual environments, cloud provider is able to run varieties of operating systems as needed by each cloud user. Virtualization can improve reliability, security, and availability of applications by using consolidation, isolation, and fault tolerance. In addition, it is possible to balance the workloads by using live migration techniques. In this paper, the definition of cloud computing is given; and then the service and deployment models are introduced. An analysis of security issues and challenges in implementation of cloud computing is identified. Moreover, a system-level virtualization case is established to enhance the security of cloud computing environments.

Neural network cloud top pressure and height for MODIS

NASA Astrophysics Data System (ADS)

Håkansson, Nina; Adok, Claudia; Thoss, Anke; Scheirer, Ronald; Hörnquist, Sara

2018-06-01

Cloud top height retrieval from imager instruments is important for nowcasting and for satellite climate data records. A neural network approach for cloud top height retrieval from the imager instrument MODIS (Moderate Resolution Imaging Spectroradiometer) is presented. The neural networks are trained using cloud top layer pressure data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) dataset. Results are compared with two operational reference algorithms for cloud top height: the MODIS Collection 6 Level 2 height product and the cloud top temperature and height algorithm in the 2014 version of the NWC SAF (EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting) PPS (Polar Platform System). All three techniques are evaluated using both CALIOP and CPR (Cloud Profiling Radar for CloudSat (CLOUD SATellite)) height. Instruments like AVHRR (Advanced Very High Resolution Radiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) contain fewer channels useful for cloud top height retrievals than MODIS, therefore several different neural networks are investigated to test how infrared channel selection influences retrieval performance. Also a network with only channels available for the AVHRR1 instrument is trained and evaluated. To examine the contribution of different variables, networks with fewer variables are trained. It is shown that variables containing imager information for neighboring pixels are very important. The error distributions of the involved cloud top height algorithms are found to be non-Gaussian. Different descriptive statistic measures are presented and it is exemplified that bias and SD (standard deviation) can be misleading for non-Gaussian distributions. The median and mode are found to better describe the tendency of the error distributions and IQR (interquartile range) and MAE (mean absolute error) are found to give the most useful information of the spread of the errors. For all descriptive statistics presented MAE, IQR, RMSE (root mean square error), SD, mode, median, bias and percentage of absolute errors above 0.25, 0.5, 1 and 2 km the neural network perform better than the reference algorithms both validated with CALIOP and CPR (CloudSat). The neural networks using the brightness temperatures at 11 and 12 µm show at least 32 % (or 623 m) lower MAE compared to the two operational reference algorithms when validating with CALIOP height. Validation with CPR (CloudSat) height gives at least 25 % (or 430 m) reduction of MAE.

Dynamic virtual machine allocation policy in cloud computing complying with service level agreement using CloudSim

NASA Astrophysics Data System (ADS)

Aneri, Parikh; Sumathy, S.

2017-11-01

Cloud computing provides services over the internet and provides application resources and data to the users based on their demand. Base of the Cloud Computing is consumer provider model. Cloud provider provides resources which consumer can access using cloud computing model in order to build their application based on their demand. Cloud data center is a bulk of resources on shared pool architecture for cloud user to access. Virtualization is the heart of the Cloud computing model, it provides virtual machine as per application specific configuration and those applications are free to choose their own configuration. On one hand, there is huge number of resources and on other hand it has to serve huge number of requests effectively. Therefore, resource allocation policy and scheduling policy play very important role in allocation and managing resources in this cloud computing model. This paper proposes the load balancing policy using Hungarian algorithm. Hungarian Algorithm provides dynamic load balancing policy with a monitor component. Monitor component helps to increase cloud resource utilization by managing the Hungarian algorithm by monitoring its state and altering its state based on artificial intelligent. CloudSim used in this proposal is an extensible toolkit and it simulates cloud computing environment.

Stream network analysis from orbital and suborbital imagery, Colorado River Basin, Texas

NASA Technical Reports Server (NTRS)

Baker, V. R. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Orbital SL-2 imagery (earth terrain camera S-190B), received September 5, 1973, was subjected to quantitative network analysis and compared to 7.5 minute topographic mapping (scale: 1/24,000) and U.S.D.A. conventional black and white aerial photography (scale: 1/22,200). Results can only be considered suggestive because detail on the SL-2 imagery was badly obscured by heavy cloud cover. The upper Bee Creek basin was chosen for analysis because it appeared in a relatively cloud-free portion of the orbital imagery. Drainage maps were drawn from the three sources digitized into a computer-compatible format, and analyzed by the WATER system computer program. Even at its small scale (1/172,000) and with bad haze the orbital photo showed much drainage detail. The contour-like character of the Glen Rose Formation's resistant limestone units allowed channel definition. The errors in pattern recognition can be attributed to local areas of dense vegetation and to other areas of very high albedo caused by surficial exposure of caliche. The latter effect caused particular difficulty in the determination of drainage divides.

Using Cloud Computing infrastructure with CloudBioLinux, CloudMan and Galaxy

PubMed Central

Afgan, Enis; Chapman, Brad; Jadan, Margita; Franke, Vedran; Taylor, James

2012-01-01

Cloud computing has revolutionized availability and access to computing and storage resources; making it possible to provision a large computational infrastructure with only a few clicks in a web browser. However, those resources are typically provided in the form of low-level infrastructure components that need to be procured and configured before use. In this protocol, we demonstrate how to utilize cloud computing resources to perform open-ended bioinformatics analyses, with fully automated management of the underlying cloud infrastructure. By combining three projects, CloudBioLinux, CloudMan, and Galaxy into a cohesive unit, we have enabled researchers to gain access to more than 100 preconfigured bioinformatics tools and gigabytes of reference genomes on top of the flexible cloud computing infrastructure. The protocol demonstrates how to setup the available infrastructure and how to use the tools via a graphical desktop interface, a parallel command line interface, and the web-based Galaxy interface. PMID:22700313

Using cloud computing infrastructure with CloudBioLinux, CloudMan, and Galaxy.

PubMed

Afgan, Enis; Chapman, Brad; Jadan, Margita; Franke, Vedran; Taylor, James

2012-06-01

Cloud computing has revolutionized availability and access to computing and storage resources, making it possible to provision a large computational infrastructure with only a few clicks in a Web browser. However, those resources are typically provided in the form of low-level infrastructure components that need to be procured and configured before use. In this unit, we demonstrate how to utilize cloud computing resources to perform open-ended bioinformatic analyses, with fully automated management of the underlying cloud infrastructure. By combining three projects, CloudBioLinux, CloudMan, and Galaxy, into a cohesive unit, we have enabled researchers to gain access to more than 100 preconfigured bioinformatics tools and gigabytes of reference genomes on top of the flexible cloud computing infrastructure. The protocol demonstrates how to set up the available infrastructure and how to use the tools via a graphical desktop interface, a parallel command-line interface, and the Web-based Galaxy interface.

Identity-Based Authentication for Cloud Computing

NASA Astrophysics Data System (ADS)

Li, Hongwei; Dai, Yuanshun; Tian, Ling; Yang, Haomiao

Cloud computing is a recently developed new technology for complex systems with massive-scale services sharing among numerous users. Therefore, authentication of both users and services is a significant issue for the trust and security of the cloud computing. SSL Authentication Protocol (SAP), once applied in cloud computing, will become so complicated that users will undergo a heavily loaded point both in computation and communication. This paper, based on the identity-based hierarchical model for cloud computing (IBHMCC) and its corresponding encryption and signature schemes, presented a new identity-based authentication protocol for cloud computing and services. Through simulation testing, it is shown that the authentication protocol is more lightweight and efficient than SAP, specially the more lightweight user side. Such merit of our model with great scalability is very suited to the massive-scale cloud.

a Cloud Boundary Detection Scheme Combined with Aslic and Cnn Using ZY-3, GF-1/2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Guo, Z.; Li, C.; Wang, Z.; Kwok, E.; Wei, X.

2018-04-01

Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN) is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC) method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.

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

Automating NEURON Simulation Deployment in Cloud Resources.

PubMed

Stockton, David B; Santamaria, Fidel

2017-01-01

Simulations in neuroscience are performed on local servers or High Performance Computing (HPC) facilities. Recently, cloud computing has emerged as a potential computational platform for neuroscience simulation. In this paper we compare and contrast HPC and cloud resources for scientific computation, then report how we deployed NEURON, a widely used simulator of neuronal activity, in three clouds: Chameleon Cloud, a hybrid private academic cloud for cloud technology research based on the OpenStack software; Rackspace, a public commercial cloud, also based on OpenStack; and Amazon Elastic Cloud Computing, based on Amazon's proprietary software. We describe the manual procedures and how to automate cloud operations. We describe extending our simulation automation software called NeuroManager (Stockton and Santamaria, Frontiers in Neuroinformatics, 2015), so that the user is capable of recruiting private cloud, public cloud, HPC, and local servers simultaneously with a simple common interface. We conclude by performing several studies in which we examine speedup, efficiency, total session time, and cost for sets of simulations of a published NEURON model.

Automating NEURON Simulation Deployment in Cloud Resources

PubMed Central

Santamaria, Fidel

2016-01-01

Simulations in neuroscience are performed on local servers or High Performance Computing (HPC) facilities. Recently, cloud computing has emerged as a potential computational platform for neuroscience simulation. In this paper we compare and contrast HPC and cloud resources for scientific computation, then report how we deployed NEURON, a widely used simulator of neuronal activity, in three clouds: Chameleon Cloud, a hybrid private academic cloud for cloud technology research based on the Open-Stack software; Rackspace, a public commercial cloud, also based on OpenStack; and Amazon Elastic Cloud Computing, based on Amazon’s proprietary software. We describe the manual procedures and how to automate cloud operations. We describe extending our simulation automation software called NeuroManager (Stockton and Santamaria, Frontiers in Neuroinformatics, 2015), so that the user is capable of recruiting private cloud, public cloud, HPC, and local servers simultaneously with a simple common interface. We conclude by performing several studies in which we examine speedup, efficiency, total session time, and cost for sets of simulations of a published NEURON model. PMID:27655341

Homomorphic encryption experiments on IBM's cloud quantum computing platform

NASA Astrophysics Data System (ADS)

Huang, He-Liang; Zhao, You-Wei; Li, Tan; Li, Feng-Guang; Du, Yu-Tao; Fu, Xiang-Qun; Zhang, Shuo; Wang, Xiang; Bao, Wan-Su

2017-02-01

Quantum computing has undergone rapid development in recent years. Owing to limitations on scalability, personal quantum computers still seem slightly unrealistic in the near future. The first practical quantum computer for ordinary users is likely to be on the cloud. However, the adoption of cloud computing is possible only if security is ensured. Homomorphic encryption is a cryptographic protocol that allows computation to be performed on encrypted data without decrypting them, so it is well suited to cloud computing. Here, we first applied homomorphic encryption on IBM's cloud quantum computer platform. In our experiments, we successfully implemented a quantum algorithm for linear equations while protecting our privacy. This demonstration opens a feasible path to the next stage of development of cloud quantum information technology.

Mobile Cloud Learning for Higher Education: A Case Study of Moodle in the Cloud

ERIC Educational Resources Information Center

Wang, Minjuan; Chen, Yong; Khan, Muhammad Jahanzaib

2014-01-01

Mobile cloud learning, a combination of mobile learning and cloud computing, is a relatively new concept that holds considerable promise for future development and delivery in the education sectors. Cloud computing helps mobile learning overcome obstacles related to mobile computing. The main focus of this paper is to explore how cloud computing…

76 FR 13984 - Cloud Computing Forum & Workshop III

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-15

... DEPARTMENT OF COMMERCE National Institute of Standards and Technology Cloud Computing Forum... public workshop. SUMMARY: NIST announces the Cloud Computing Forum & Workshop III to be held on April 7... provide information on the NIST strategic and tactical Cloud Computing program, including progress on the...

Community Seismic Network (CSN)

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Heaton, T. H.; Kohler, M. D.; Chandy, M.; Krause, A.

2010-12-01

In collaboration with computer science and earthquake engineering, we are developing a dense network of low-cost accelerometers that send their data via the Internet to a cloud-based center. The goal is to make block-by-block measurements of ground shaking in urban areas, which will provide emergency response information in the case of large earthquakes, and an unprecedented high-frequency seismic array to study structure and the earthquake process with moderate shaking. When deployed in high-rise buildings they can be used to monitor the state of health of the structure. The sensors are capable of a resolution of approximately 80 micro-g, connect via USB ports to desktop computers, and cost about $100 each. The network will adapt to its environment by using network-wide machine learning to adjust the picking sensitivity. We are also looking into using other motion sensing devices such as cell phones. For a pilot project, we plan to deploy more than 1000 sensors in the greater Pasadena area. The system is easily adaptable to other seismically vulnerable urban areas.

Cloud computing task scheduling strategy based on improved differential evolution algorithm

NASA Astrophysics Data System (ADS)

Ge, Junwei; He, Qian; Fang, Yiqiu

2017-04-01

In order to optimize the cloud computing task scheduling scheme, an improved differential evolution algorithm for cloud computing task scheduling is proposed. Firstly, the cloud computing task scheduling model, according to the model of the fitness function, and then used improved optimization calculation of the fitness function of the evolutionary algorithm, according to the evolution of generation of dynamic selection strategy through dynamic mutation strategy to ensure the global and local search ability. The performance test experiment was carried out in the CloudSim simulation platform, the experimental results show that the improved differential evolution algorithm can reduce the cloud computing task execution time and user cost saving, good implementation of the optimal scheduling of cloud computing tasks.

Massive Cloud-Based Big Data Processing for Ocean Sensor Networks and Remote Sensing

NASA Astrophysics Data System (ADS)

Schwehr, K. D.

2017-12-01

Until recently, the work required to integrate and analyze data for global-scale environmental issues was prohibitive both in cost and availability. Traditional desktop processing systems are not able to effectively store and process all the data, and super computer solutions are financially out of the reach of most people. The availability of large-scale cloud computing has created tools that are usable by small groups and individuals regardless of financial resources or locally available computational resources. These systems give scientists and policymakers the ability to see how critical resources are being used across the globe with little or no barrier to entry. Google Earth Engine has the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra, MODIS Aqua, and Global Land Data Assimilation Systems (GLDAS) data catalogs available live online. Here we demonstrate these data to calculate the correlation between lagged chlorophyll and rainfall to identify areas of eutrophication, matching these events to ocean currents from datasets like HYbrid Coordinate Ocean Model (HYCOM) to check if there are constraints from oceanographic configurations. The system can provide addition ground truth with observations from sensor networks like the International Comprehensive Ocean-Atmosphere Data Set / Voluntary Observing Ship (ICOADS/VOS) and Argo floats. This presentation is intended to introduce users to the datasets, programming idioms, and functionality of Earth Engine for large-scale, data-driven oceanography.

Cost-effective cloud computing: a case study using the comparative genomics tool, roundup.

PubMed

Kudtarkar, Parul; Deluca, Todd F; Fusaro, Vincent A; Tonellato, Peter J; Wall, Dennis P

2010-12-22

Comparative genomics resources, such as ortholog detection tools and repositories are rapidly increasing in scale and complexity. Cloud computing is an emerging technological paradigm that enables researchers to dynamically build a dedicated virtual cluster and may represent a valuable alternative for large computational tools in bioinformatics. In the present manuscript, we optimize the computation of a large-scale comparative genomics resource-Roundup-using cloud computing, describe the proper operating principles required to achieve computational efficiency on the cloud, and detail important procedures for improving cost-effectiveness to ensure maximal computation at minimal costs. Utilizing the comparative genomics tool, Roundup, as a case study, we computed orthologs among 902 fully sequenced genomes on Amazon's Elastic Compute Cloud. For managing the ortholog processes, we designed a strategy to deploy the web service, Elastic MapReduce, and maximize the use of the cloud while simultaneously minimizing costs. Specifically, we created a model to estimate cloud runtime based on the size and complexity of the genomes being compared that determines in advance the optimal order of the jobs to be submitted. We computed orthologous relationships for 245,323 genome-to-genome comparisons on Amazon's computing cloud, a computation that required just over 200 hours and cost $8,000 USD, at least 40% less than expected under a strategy in which genome comparisons were submitted to the cloud randomly with respect to runtime. Our cost savings projections were based on a model that not only demonstrates the optimal strategy for deploying RSD to the cloud, but also finds the optimal cluster size to minimize waste and maximize usage. Our cost-reduction model is readily adaptable for other comparative genomics tools and potentially of significant benefit to labs seeking to take advantage of the cloud as an alternative to local computing infrastructure.

75 FR 64258 - Cloud Computing Forum & Workshop II

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-19

... DEPARTMENT OF COMMERCE National Institute of Standards and Technology Cloud Computing Forum... workshop. SUMMARY: NIST announces the Cloud Computing Forum & Workshop II to be held on November 4 and 5, 2010. This workshop will provide information on a Cloud Computing Roadmap Strategy as well as provide...

76 FR 62373 - Notice of Public Meeting-Cloud Computing Forum & Workshop IV

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-07

...--Cloud Computing Forum & Workshop IV AGENCY: National Institute of Standards and Technology (NIST), Commerce. ACTION: Notice. SUMMARY: NIST announces the Cloud Computing Forum & Workshop IV to be held on... to help develop open standards in interoperability, portability and security in cloud computing. This...

Notification: Fieldwork for CIGIE Cloud Computing Initiative – Status of Cloud-Computing Within the Federal Government

EPA Pesticide Factsheets

Project #OA-FY14-0126, January 15, 2014. The EPA OIG is starting fieldwork on the Council of the Inspectors General on Integrity and Efficiency (CIGIE) Cloud Computing Initiative – Status of Cloud-Computing Environments Within the Federal Government.

Intelligent cloud computing security using genetic algorithm as a computational tools

NASA Astrophysics Data System (ADS)

Razuky AL-Shaikhly, Mazin H.

2018-05-01

An essential change had occurred in the field of Information Technology which represented with cloud computing, cloud giving virtual assets by means of web yet awesome difficulties in the field of information security and security assurance. Currently main problem with cloud computing is how to improve privacy and security for cloud “cloud is critical security”. This paper attempts to solve cloud security by using intelligent system with genetic algorithm as wall to provide cloud data secure, all services provided by cloud must detect who receive and register it to create list of users (trusted or un-trusted) depend on behavior. The execution of present proposal has shown great outcome.

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.

Energy Consumption Management of Virtual Cloud Computing Platform

NASA Astrophysics Data System (ADS)

Li, Lin

2017-11-01

For energy consumption management research on virtual cloud computing platforms, energy consumption management of virtual computers and cloud computing platform should be understood deeper. Only in this way can problems faced by energy consumption management be solved. In solving problems, the key to solutions points to data centers with high energy consumption, so people are in great need to use a new scientific technique. Virtualization technology and cloud computing have become powerful tools in people’s real life, work and production because they have strong strength and many advantages. Virtualization technology and cloud computing now is in a rapid developing trend. It has very high resource utilization rate. In this way, the presence of virtualization and cloud computing technologies is very necessary in the constantly developing information age. This paper has summarized, explained and further analyzed energy consumption management questions of the virtual cloud computing platform. It eventually gives people a clearer understanding of energy consumption management of virtual cloud computing platform and brings more help to various aspects of people’s live, work and son on.

Cloud-free resolution element statistics program

NASA Technical Reports Server (NTRS)

Liley, B.; Martin, C. D.

1971-01-01

Computer program computes number of cloud-free elements in field-of-view and percentage of total field-of-view occupied by clouds. Human error is eliminated by using visual estimation to compute cloud statistics from aerial photographs.

The effective use of virtualization for selection of data centers in a cloud computing environment

NASA Astrophysics Data System (ADS)

Kumar, B. Santhosh; Parthiban, Latha

2018-04-01

Data centers are the places which consist of network of remote servers to store, access and process the data. Cloud computing is a technology where users worldwide will submit the tasks and the service providers will direct the requests to the data centers which are responsible for execution of tasks. The servers in the data centers need to employ the virtualization concept so that multiple tasks can be executed simultaneously. In this paper we proposed an algorithm for data center selection based on energy of virtual machines created in server. The virtualization energy in each of the server is calculated and total energy of the data center is obtained by the summation of individual server energy. The tasks submitted are routed to the data center with least energy consumption which will result in minimizing the operational expenses of a service provider.

cadcVOFS: A FUSE Based File System Layer for VOSpace

NASA Astrophysics Data System (ADS)

Kavelaars, J.; Dowler, P.; Jenkins, D.; Hill, N.; Damian, A.

2012-09-01

The CADC is now making extensive use of the VOSpace protocol for user managed storage. The VOSpace standard allows a diverse set of rich data services to be delivered to users via a simple protocol. We have recently developed the cadcVOFS, a FUSE based file-system layer for VOSpace. cadcVOFS provides a filesystem layer on-top of VOSpace so that standard Unix tools (such as ‘find’, ‘emacs’, ‘awk’ etc) can be used directly on the data objects stored in VOSpace. Once mounted the VOSpace appears as a network storage volume inside the operating system. Within the CADC Cloud Computing project (CANFAR) we have used VOSpace as the method for retrieving and storing processing inputs and products. The abstraction of storage is an important component of Cloud Computing and the high use level of our VOSpace service reflects this.

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.

77 FR 26509 - Notice of Public Meeting-Cloud Computing Forum & Workshop V

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-04

...--Cloud Computing Forum & Workshop V AGENCY: National Institute of Standards & Technology (NIST), Commerce. ACTION: Notice. SUMMARY: NIST announces the Cloud Computing Forum & Workshop V to be held on Tuesday... workshop. This workshop will provide information on the U.S. Government (USG) Cloud Computing Technology...

National electronic medical records integration on cloud computing system.

PubMed

Mirza, Hebah; El-Masri, Samir

2013-01-01

Few Healthcare providers have an advanced level of Electronic Medical Record (EMR) adoption. Others have a low level and most have no EMR at all. Cloud computing technology is a new emerging technology that has been used in other industry and showed a great success. Despite the great features of Cloud computing, they haven't been utilized fairly yet in healthcare industry. This study presents an innovative Healthcare Cloud Computing system for Integrating Electronic Health Record (EHR). The proposed Cloud system applies the Cloud Computing technology on EHR system, to present a comprehensive EHR integrated environment.

Research on OpenStack of open source cloud computing in colleges and universities’ computer room

NASA Astrophysics Data System (ADS)

Wang, Lei; Zhang, Dandan

2017-06-01

In recent years, the cloud computing technology has a rapid development, especially open source cloud computing. Open source cloud computing has attracted a large number of user groups by the advantages of open source and low cost, have now become a large-scale promotion and application. In this paper, firstly we briefly introduced the main functions and architecture of the open source cloud computing OpenStack tools, and then discussed deeply the core problems of computer labs in colleges and universities. Combining with this research, it is not that the specific application and deployment of university computer rooms with OpenStack tool. The experimental results show that the application of OpenStack tool can efficiently and conveniently deploy cloud of university computer room, and its performance is stable and the functional value is good.

The Adoption of Cloud Computing in the Field of Genomics Research: The Influence of Ethical and Legal Issues

PubMed Central

Charlebois, Kathleen; Palmour, Nicole; Knoppers, Bartha Maria

2016-01-01

This study aims to understand the influence of the ethical and legal issues on cloud computing adoption in the field of genomics research. To do so, we adapted Diffusion of Innovation (DoI) theory to enable understanding of how key stakeholders manage the various ethical and legal issues they encounter when adopting cloud computing. Twenty semi-structured interviews were conducted with genomics researchers, patient advocates and cloud service providers. Thematic analysis generated five major themes: 1) Getting comfortable with cloud computing; 2) Weighing the advantages and the risks of cloud computing; 3) Reconciling cloud computing with data privacy; 4) Maintaining trust and 5) Anticipating the cloud by creating the conditions for cloud adoption. Our analysis highlights the tendency among genomics researchers to gradually adopt cloud technology. Efforts made by cloud service providers to promote cloud computing adoption are confronted by researchers’ perpetual cost and security concerns, along with a lack of familiarity with the technology. Further underlying those fears are researchers’ legal responsibility with respect to the data that is stored on the cloud. Alternative consent mechanisms aimed at increasing patients’ control over the use of their data also provide a means to circumvent various institutional and jurisdictional hurdles that restrict access by creating siloed databases. However, the risk of creating new, cloud-based silos may run counter to the goal in genomics research to increase data sharing on a global scale. PMID:27755563

The Adoption of Cloud Computing in the Field of Genomics Research: The Influence of Ethical and Legal Issues.

PubMed

Charlebois, Kathleen; Palmour, Nicole; Knoppers, Bartha Maria

2016-01-01

This study aims to understand the influence of the ethical and legal issues on cloud computing adoption in the field of genomics research. To do so, we adapted Diffusion of Innovation (DoI) theory to enable understanding of how key stakeholders manage the various ethical and legal issues they encounter when adopting cloud computing. Twenty semi-structured interviews were conducted with genomics researchers, patient advocates and cloud service providers. Thematic analysis generated five major themes: 1) Getting comfortable with cloud computing; 2) Weighing the advantages and the risks of cloud computing; 3) Reconciling cloud computing with data privacy; 4) Maintaining trust and 5) Anticipating the cloud by creating the conditions for cloud adoption. Our analysis highlights the tendency among genomics researchers to gradually adopt cloud technology. Efforts made by cloud service providers to promote cloud computing adoption are confronted by researchers' perpetual cost and security concerns, along with a lack of familiarity with the technology. Further underlying those fears are researchers' legal responsibility with respect to the data that is stored on the cloud. Alternative consent mechanisms aimed at increasing patients' control over the use of their data also provide a means to circumvent various institutional and jurisdictional hurdles that restrict access by creating siloed databases. However, the risk of creating new, cloud-based silos may run counter to the goal in genomics research to increase data sharing on a global scale.

Architecture Design and Experimental Platform Demonstration of Optical Network based on OpenFlow Protocol

NASA Astrophysics Data System (ADS)

Xing, Fangyuan; Wang, Honghuan; Yin, Hongxi; Li, Ming; Luo, Shenzi; Wu, Chenguang

2016-02-01

With the extensive application of cloud computing and data centres, as well as the constantly emerging services, the big data with the burst characteristic has brought huge challenges to optical networks. Consequently, the software defined optical network (SDON) that combines optical networks with software defined network (SDN), has attracted much attention. In this paper, an OpenFlow-enabled optical node employed in optical cross-connect (OXC) and reconfigurable optical add/drop multiplexer (ROADM), is proposed. An open source OpenFlow controller is extended on routing strategies. In addition, the experiment platform based on OpenFlow protocol for software defined optical network, is designed. The feasibility and availability of the OpenFlow-enabled optical nodes and the extended OpenFlow controller are validated by the connectivity test, protection switching and load balancing experiments in this test platform.

An efficient quantum scheme for Private Set Intersection

NASA Astrophysics Data System (ADS)

Shi, Run-hua; Mu, Yi; Zhong, Hong; Cui, Jie; Zhang, Shun

2016-01-01

Private Set Intersection allows a client to privately compute set intersection with the collaboration of the server, which is one of the most fundamental and key problems within the multiparty collaborative computation of protecting the privacy of the parties. In this paper, we first present a cheat-sensitive quantum scheme for Private Set Intersection. Compared with classical schemes, our scheme has lower communication complexity, which is independent of the size of the server's set. Therefore, it is very suitable for big data services in Cloud or large-scale client-server networks.

Imaging sensor constellation for tomographic chemical cloud mapping.

PubMed

Cosofret, Bogdan R; Konno, Daisei; Faghfouri, Aram; Kindle, Harry S; Gittins, Christopher M; Finson, Michael L; Janov, Tracy E; Levreault, Mark J; Miyashiro, Rex K; Marinelli, William J

2009-04-01

A sensor constellation capable of determining the location and detailed concentration distribution of chemical warfare agent simulant clouds has been developed and demonstrated on government test ranges. The constellation is based on the use of standoff passive multispectral infrared imaging sensors to make column density measurements through the chemical cloud from two or more locations around its periphery. A computed tomography inversion method is employed to produce a 3D concentration profile of the cloud from the 2D line density measurements. We discuss the theoretical basis of the approach and present results of recent field experiments where controlled releases of chemical warfare agent simulants were simultaneously viewed by three chemical imaging sensors. Systematic investigations of the algorithm using synthetic data indicate that for complex functions, 3D reconstruction errors are less than 20% even in the case of a limited three-sensor measurement network. Field data results demonstrate the capability of the constellation to determine 3D concentration profiles that account for ~?86%? of the total known mass of material released.

Linking Advanced Visualization and MATLAB for the Analysis of 3D Gene Expression Data

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

Ruebel, Oliver; Keranen, Soile V.E.; Biggin, Mark

Three-dimensional gene expression PointCloud data generated by the Berkeley Drosophila Transcription Network Project (BDTNP) provides quantitative information about the spatial and temporal expression of genes in early Drosophila embryos at cellular resolution. The BDTNP team visualizes and analyzes Point-Cloud data using the software application PointCloudXplore (PCX). To maximize the impact of novel, complex data sets, such as PointClouds, the data needs to be accessible to biologists and comprehensible to developers of analysis functions. We address this challenge by linking PCX and Matlab via a dedicated interface, thereby providing biologists seamless access to advanced data analysis functions and giving bioinformatics researchersmore » the opportunity to integrate their analysis directly into the visualization application. To demonstrate the usefulness of this approach, we computationally model parts of the expression pattern of the gene even skipped using a genetic algorithm implemented in Matlab and integrated into PCX via our Matlab interface.« less

Cloud Computing for Complex Performance Codes.

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

Appel, Gordon John; Hadgu, Teklu; Klein, Brandon Thorin

This report describes the use of cloud computing services for running complex public domain performance assessment problems. The work consisted of two phases: Phase 1 was to demonstrate complex codes, on several differently configured servers, could run and compute trivial small scale problems in a commercial cloud infrastructure. Phase 2 focused on proving non-trivial large scale problems could be computed in the commercial cloud environment. The cloud computing effort was successfully applied using codes of interest to the geohydrology and nuclear waste disposal modeling community.

Cloud Fingerprinting: Using Clock Skews To Determine Co Location Of Virtual Machines

DTIC Science & Technology

2016-09-01

DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) Cloud computing has quickly revolutionized computing practices of organizations, to include the Department of... Cloud computing has quickly revolutionized computing practices of organizations, to in- clude the Department of Defense. However, security concerns...vi Table of Contents 1 Introduction 1 1.1 Proliferation of Cloud Computing . . . . . . . . . . . . . . . . . . 1 1.2 Problem Statement

IoT gateways, cloud and the last mile for energy efficiency and sustainability in the era of CPS expansion: "A bot is irrigating my farm.. "

NASA Astrophysics Data System (ADS)

Papageorgas, Panagiotis G.; Agavanakis, Kyriakos; Dogas, Ioannis; Piromalis, Dimitrios D.

2018-05-01

A cloud-based architecture is presented for the internetworking of sensors and actuators through a universal gateway, network server and application user interface design. The proposed approach targets to Energy Efficiency and sustainability in a holistic way, by integrating an open-source test bed prototype based on long-range low-bandwidth wireless networking technology for sensing and actuation as the elementary block of a viable, cost-effective and reliable solution. The prototype presented is capable of supporting both sensors and actuators, processing data locally and transmitting the results of the imposed computations to a higher level node. Additionally, it is combined with a service-oriented architecture and involves publish/subscribe middleware protocols and cloud technology to confront with the system needs in terms of data volume and processing power. In this context, the integration of instant message (chat) services is demonstrated so that they can be part of an emerging global-scope eco-system of Cyber-Physical Systems to support a wide variety of IoT applications, with strong advantages such as usability, scalability and security, while adopting a unified gateway design and a simple - yet powerful - user interface.

GeoChronos: An On-line Collaborative Platform for Earth Observation Scientists

NASA Astrophysics Data System (ADS)

Gamon, J. A.; Kiddle, C.; Curry, R.; Markatchev, N.; Zonta-Pastorello, G., Jr.; Rivard, B.; Sanchez-Azofeifa, G. A.; Simmonds, R.; Tan, T.

2009-12-01

Recent advances in cyberinfrastructure are offering new solutions to the growing challenges of managing and sharing large data volumes. Web 2.0 and social networking technologies, provide the means for scientists to collaborate and share information more effectively. Cloud computing technologies can provide scientists with transparent and on-demand access to applications served over the Internet in a dynamic and scalable manner. Semantic Web technologies allow for data to be linked together in a manner understandable by machines, enabling greater automation. Combining all of these technologies together can enable the creation of very powerful platforms. GeoChronos (http://geochronos.org/), part of a CANARIE Network Enabled Platforms project, is an online collaborative platform that incorporates these technologies to enable members of the earth observation science community to share data and scientific applications and to collaborate more effectively. The GeoChronos portal is built on an open source social networking platform called Elgg. Elgg provides a full set of social networking functionalities similar to Facebook including blogs, tags, media/document sharing, wikis, friends/contacts, groups, discussions, message boards, calendars, status, activity feeds and more. An underlying cloud computing infrastructure enables scientists to access dynamically provisioned applications via the portal for visualizing and analyzing data. Users are able to access and run the applications from any computer that has a Web browser and Internet connectivity and do not need to manage and maintain the applications themselves. Semantic Web Technologies, such as the Resource Description Framework (RDF) are being employed for relating and linking together spectral, satellite, meteorological and other data. Social networking functionality plays an integral part in facilitating the sharing of data and applications. Examples of recent GeoChronos users during the early testing phase have included the IAI International Wireless Sensor Networking Summer School at the University of Alberta, and the IAI Tropi-Dry community. Current GeoChronos activities include the development of a web-based spectral library and related analytical and visualization tools, in collaboration with members of the SpecNet community. The GeoChronos portal will be open to all members of the earth observation science community when the project nears completion at the end of 2010.

Processing Shotgun Proteomics Data on the Amazon Cloud with the Trans-Proteomic Pipeline*

PubMed Central

Slagel, Joseph; Mendoza, Luis; Shteynberg, David; Deutsch, Eric W.; Moritz, Robert L.

2015-01-01

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost. PMID:25418363

Processing shotgun proteomics data on the Amazon cloud with the trans-proteomic pipeline.

PubMed

Slagel, Joseph; Mendoza, Luis; Shteynberg, David; Deutsch, Eric W; Moritz, Robert L

2015-02-01

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Proposal for a Security Management in Cloud Computing for Health Care

PubMed Central

Dzombeta, Srdan; Brandis, Knud

2014-01-01

Cloud computing is actually one of the most popular themes of information systems research. Considering the nature of the processed information especially health care organizations need to assess and treat specific risks according to cloud computing in their information security management system. Therefore, in this paper we propose a framework that includes the most important security processes regarding cloud computing in the health care sector. Starting with a framework of general information security management processes derived from standards of the ISO 27000 family the most important information security processes for health care organizations using cloud computing will be identified considering the main risks regarding cloud computing and the type of information processed. The identified processes will help a health care organization using cloud computing to focus on the most important ISMS processes and establish and operate them at an appropriate level of maturity considering limited resources. PMID:24701137

Proposal for a security management in cloud computing for health care.

PubMed

Haufe, Knut; Dzombeta, Srdan; Brandis, Knud

2014-01-01

Cloud computing is actually one of the most popular themes of information systems research. Considering the nature of the processed information especially health care organizations need to assess and treat specific risks according to cloud computing in their information security management system. Therefore, in this paper we propose a framework that includes the most important security processes regarding cloud computing in the health care sector. Starting with a framework of general information security management processes derived from standards of the ISO 27000 family the most important information security processes for health care organizations using cloud computing will be identified considering the main risks regarding cloud computing and the type of information processed. The identified processes will help a health care organization using cloud computing to focus on the most important ISMS processes and establish and operate them at an appropriate level of maturity considering limited resources.

The Basics of Cloud Computing

ERIC Educational Resources Information Center

Kaestner, Rich

2012-01-01

Most school business officials have heard the term "cloud computing" bandied about and may have some idea of what the term means. In fact, they likely already leverage a cloud-computing solution somewhere within their district. But what does cloud computing really mean? This brief article puts a bit of definition behind the term and helps one…

76 FR 67418 - Request for Comments on NIST Special Publication 500-293, US Government Cloud Computing...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-01

...-1659-01] Request for Comments on NIST Special Publication 500-293, US Government Cloud Computing... Publication 500-293, US Government Cloud Computing Technology Roadmap, Release 1.0 (Draft). This document is... (USG) agencies to accelerate their adoption of cloud computing. The roadmap has been developed through...

Reviews on Security Issues and Challenges in Cloud Computing

NASA Astrophysics Data System (ADS)

An, Y. Z.; Zaaba, Z. F.; Samsudin, N. F.

2016-11-01

Cloud computing is an Internet-based computing service provided by the third party allowing share of resources and data among devices. It is widely used in many organizations nowadays and becoming more popular because it changes the way of how the Information Technology (IT) of an organization is organized and managed. It provides lots of benefits such as simplicity and lower costs, almost unlimited storage, least maintenance, easy utilization, backup and recovery, continuous availability, quality of service, automated software integration, scalability, flexibility and reliability, easy access to information, elasticity, quick deployment and lower barrier to entry. While there is increasing use of cloud computing service in this new era, the security issues of the cloud computing become a challenges. Cloud computing must be safe and secure enough to ensure the privacy of the users. This paper firstly lists out the architecture of the cloud computing, then discuss the most common security issues of using cloud and some solutions to the security issues since security is one of the most critical aspect in cloud computing due to the sensitivity of user's data.

Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

NASA Astrophysics Data System (ADS)

Tang, Wenjun; Qin, Jun; Yang, Kun; Liu, Shaomin; Lu, Ning; Niu, Xiaolei

2016-03-01

Cloud parameters (cloud mask, effective particle radius, and liquid/ice water path) are the important inputs in estimating surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy, but their temporal resolution is too low to obtain high-temporal-resolution SSR retrievals. In order to obtain hourly cloud parameters, an artificial neural network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multifunctional Transport Satellite (MTSAT) geostationary satellite signals. In addition, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m-2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone) are input to the model, we can derive SSR at high spatiotemporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m-2 (or 3.5 %) and 98.5 W m-2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m-2 (or 5.4 %); the RMSEs in daily and monthly mean SSR estimates are 34.2 W m-2 (or 19.1 %) and 22.1 W m-2 (or 12.3 %), respectively. The accuracy is comparable to or even higher than two other radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.

Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

NASA Astrophysics Data System (ADS)

Tang, W.; Qin, J.; Yang, K.; Liu, S.; Lu, N.; Niu, X.

2015-12-01

Cloud parameters (cloud mask, effective particle radius and liquid/ice water path) are the important inputs in determining surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy but their temporal resolution is too low to obtain high temporal resolution SSR retrievals. In order to obtain hourly cloud parameters, the Artificial Neural Network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multi-functional Transport Satellite (MTSAT) geostationary satellite signals. Meanwhile, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m-2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone and so on) are input to the model, we can derive SSR at high spatio-temporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River Basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m-2 (or 3.5 %) and 98.5 W m-2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m-2 (5.4 %); the RMSEs in daily and monthly-mean SSR estimates are 34.2 W m-2 (19.1 %) and 22.1 W m-2 (12.3 %), respectively. The accuracy is comparable or even higher than other two radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.

A Comprehensive Review of Existing Risk Assessment Models in Cloud Computing

NASA Astrophysics Data System (ADS)

Amini, Ahmad; Jamil, Norziana

2018-05-01

Cloud computing is a popular paradigm in information technology and computing as it offers numerous advantages in terms of economical saving and minimal management effort. Although elasticity and flexibility brings tremendous benefits, it still raises many information security issues due to its unique characteristic that allows ubiquitous computing. Therefore, the vulnerabilities and threats in cloud computing have to be identified and proper risk assessment mechanism has to be in place for better cloud computing management. Various quantitative and qualitative risk assessment models have been proposed but up to our knowledge, none of them is suitable for cloud computing environment. This paper, we compare and analyse the strengths and weaknesses of existing risk assessment models. We then propose a new risk assessment model that sufficiently address all the characteristics of cloud computing, which was not appeared in the existing models.

Impacts and Opportunities for Engineering in the Era of Cloud Computing Systems

DTIC Science & Technology

2012-01-31

2012 UNCLASSIFIED 1 of 58 Impacts and Opportunities for Engineering in the Era of Cloud Computing Systems A Report to the U.S. Department...2.1.7 Engineering of Computational Behavior .............................................................18 2.2 How the Cloud Will Impact Systems...58 Executive Summary This report discusses the impact of cloud computing and the broader revolution in computing on systems, on the disciplines of

Cloud Computing Value Chains: Understanding Businesses and Value Creation in the Cloud

NASA Astrophysics Data System (ADS)

Mohammed, Ashraf Bany; Altmann, Jörn; Hwang, Junseok

Based on the promising developments in Cloud Computing technologies in recent years, commercial computing resource services (e.g. Amazon EC2) or software-as-a-service offerings (e.g. Salesforce. com) came into existence. However, the relatively weak business exploitation, participation, and adoption of other Cloud Computing services remain the main challenges. The vague value structures seem to be hindering business adoption and the creation of sustainable business models around its technology. Using an extensive analyze of existing Cloud business models, Cloud services, stakeholder relations, market configurations and value structures, this Chapter develops a reference model for value chains in the Cloud. Although this model is theoretically based on porter's value chain theory, the proposed Cloud value chain model is upgraded to fit the diversity of business service scenarios in the Cloud computing markets. Using this model, different service scenarios are explained. Our findings suggest new services, business opportunities, and policy practices for realizing more adoption and value creation paths in the Cloud.

Virtualization and cloud computing in dentistry.

PubMed

Chow, Frank; Muftu, Ali; Shorter, Richard

2014-01-01

The use of virtualization and cloud computing has changed the way we use computers. Virtualization is a method of placing software called a hypervisor on the hardware of a computer or a host operating system. It allows a guest operating system to run on top of the physical computer with a virtual machine (i.e., virtual computer). Virtualization allows multiple virtual computers to run on top of one physical computer and to share its hardware resources, such as printers, scanners, and modems. This increases the efficient use of the computer by decreasing costs (e.g., hardware, electricity administration, and management) since only one physical computer is needed and running. This virtualization platform is the basis for cloud computing. It has expanded into areas of server and storage virtualization. One of the commonly used dental storage systems is cloud storage. Patient information is encrypted as required by the Health Insurance Portability and Accountability Act (HIPAA) and stored on off-site private cloud services for a monthly service fee. As computer costs continue to increase, so too will the need for more storage and processing power. Virtual and cloud computing will be a method for dentists to minimize costs and maximize computer efficiency in the near future. This article will provide some useful information on current uses of cloud computing.

Global Software Development with Cloud Platforms

NASA Astrophysics Data System (ADS)

Yara, Pavan; Ramachandran, Ramaseshan; Balasubramanian, Gayathri; Muthuswamy, Karthik; Chandrasekar, Divya

Offshore and outsourced distributed software development models and processes are facing challenges, previously unknown, with respect to computing capacity, bandwidth, storage, security, complexity, reliability, and business uncertainty. Clouds promise to address these challenges by adopting recent advances in virtualization, parallel and distributed systems, utility computing, and software services. In this paper, we envision a cloud-based platform that addresses some of these core problems. We outline a generic cloud architecture, its design and our first implementation results for three cloud forms - a compute cloud, a storage cloud and a cloud-based software service- in the context of global distributed software development (GSD). Our ”compute cloud” provides computational services such as continuous code integration and a compile server farm, ”storage cloud” offers storage (block or file-based) services with an on-line virtual storage service, whereas the on-line virtual labs represent a useful cloud service. We note some of the use cases for clouds in GSD, the lessons learned with our prototypes and identify challenges that must be conquered before realizing the full business benefits. We believe that in the future, software practitioners will focus more on these cloud computing platforms and see clouds as a means to supporting a ecosystem of clients, developers and other key stakeholders.

Cloud Based Applications and Platforms (Presentation)

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

Brodt-Giles, D.

2014-05-15

Presentation to the Cloud Computing East 2014 Conference, where we are highlighting our cloud computing strategy, describing the platforms on the cloud (including Smartgrid.gov), and defining our process for implementing cloud based applications.

76 FR 52353 - Assumption Buster Workshop: “Current Implementations of Cloud Computing Indicate a New Approach...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-22

... explored in this series is cloud computing. The workshop on this topic will be held in Gaithersburg, MD on October 21, 2011. Assertion: ``Current implementations of cloud computing indicate a new approach to security'' Implementations of cloud computing have provided new ways of thinking about how to secure data...

77 FR 74829 - Notice of Public Meeting-Cloud Computing and Big Data Forum and Workshop

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-18

...--Cloud Computing and Big Data Forum and Workshop AGENCY: National Institute of Standards and Technology... Standards and Technology (NIST) announces a Cloud Computing and Big Data Forum and Workshop to be held on... followed by a one-day hands-on workshop. The NIST Cloud Computing and Big Data Forum and Workshop will...

Examining the Relationship between Technological, Organizational, and Environmental Factors and Cloud Computing Adoption

ERIC Educational Resources Information Center

Tweel, Abdeneaser

2012-01-01

High uncertainties related to cloud computing adoption may hinder IT managers from making solid decisions about adopting cloud computing. The problem addressed in this study was the lack of understanding of the relationship between factors related to the adoption of cloud computing and IT managers' interest in adopting this technology. In…

When cloud computing meets bioinformatics: a review.

PubMed

Zhou, Shuigeng; Liao, Ruiqi; Guan, Jihong

2013-10-01

In the past decades, with the rapid development of high-throughput technologies, biology research has generated an unprecedented amount of data. In order to store and process such a great amount of data, cloud computing and MapReduce were applied to many fields of bioinformatics. In this paper, we first introduce the basic concepts of cloud computing and MapReduce, and their applications in bioinformatics. We then highlight some problems challenging the applications of cloud computing and MapReduce to bioinformatics. Finally, we give a brief guideline for using cloud computing in biology research.

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.

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.

Cloud4Psi: cloud computing for 3D protein structure similarity searching.

PubMed

Mrozek, Dariusz; Małysiak-Mrozek, Bożena; Kłapciński, Artur

2014-10-01

Popular methods for 3D protein structure similarity searching, especially those that generate high-quality alignments such as Combinatorial Extension (CE) and Flexible structure Alignment by Chaining Aligned fragment pairs allowing Twists (FATCAT) are still time consuming. As a consequence, performing similarity searching against large repositories of structural data requires increased computational resources that are not always available. Cloud computing provides huge amounts of computational power that can be provisioned on a pay-as-you-go basis. We have developed the cloud-based system that allows scaling of the similarity searching process vertically and horizontally. Cloud4Psi (Cloud for Protein Similarity) was tested in the Microsoft Azure cloud environment and provided good, almost linearly proportional acceleration when scaled out onto many computational units. Cloud4Psi is available as Software as a Service for testing purposes at: http://cloud4psi.cloudapp.net/. For source code and software availability, please visit the Cloud4Psi project home page at http://zti.polsl.pl/dmrozek/science/cloud4psi.htm. © The Author 2014. Published by Oxford University Press.

Cloud4Psi: cloud computing for 3D protein structure similarity searching

PubMed Central

Mrozek, Dariusz; Małysiak-Mrozek, Bożena; Kłapciński, Artur

2014-01-01

Summary: Popular methods for 3D protein structure similarity searching, especially those that generate high-quality alignments such as Combinatorial Extension (CE) and Flexible structure Alignment by Chaining Aligned fragment pairs allowing Twists (FATCAT) are still time consuming. As a consequence, performing similarity searching against large repositories of structural data requires increased computational resources that are not always available. Cloud computing provides huge amounts of computational power that can be provisioned on a pay-as-you-go basis. We have developed the cloud-based system that allows scaling of the similarity searching process vertically and horizontally. Cloud4Psi (Cloud for Protein Similarity) was tested in the Microsoft Azure cloud environment and provided good, almost linearly proportional acceleration when scaled out onto many computational units. Availability and implementation: Cloud4Psi is available as Software as a Service for testing purposes at: http://cloud4psi.cloudapp.net/. For source code and software availability, please visit the Cloud4Psi project home page at http://zti.polsl.pl/dmrozek/science/cloud4psi.htm. Contact: dariusz.mrozek@polsl.pl PMID:24930141

Combining Fog Computing with Sensor Mote Machine Learning for Industrial IoT.

PubMed

Lavassani, Mehrzad; Forsström, Stefan; Jennehag, Ulf; Zhang, Tingting

2018-05-12

Digitalization is a global trend becoming ever more important to our connected and sustainable society. This trend also affects industry where the Industrial Internet of Things is an important part, and there is a need to conserve spectrum as well as energy when communicating data to a fog or cloud back-end system. In this paper we investigate the benefits of fog computing by proposing a novel distributed learning model on the sensor device and simulating the data stream in the fog, instead of transmitting all raw sensor values to the cloud back-end. To save energy and to communicate as few packets as possible, the updated parameters of the learned model at the sensor device are communicated in longer time intervals to a fog computing system. The proposed framework is implemented and tested in a real world testbed in order to make quantitative measurements and evaluate the system. Our results show that the proposed model can achieve a 98% decrease in the number of packets sent over the wireless link, and the fog node can still simulate the data stream with an acceptable accuracy of 97%. We also observe an end-to-end delay of 180 ms in our proposed three-layer framework. Hence, the framework shows that a combination of fog and cloud computing with a distributed data modeling at the sensor device for wireless sensor networks can be beneficial for Industrial Internet of Things applications.

Combining Fog Computing with Sensor Mote Machine Learning for Industrial IoT

PubMed Central

Lavassani, Mehrzad; Jennehag, Ulf; Zhang, Tingting

2018-01-01

Digitalization is a global trend becoming ever more important to our connected and sustainable society. This trend also affects industry where the Industrial Internet of Things is an important part, and there is a need to conserve spectrum as well as energy when communicating data to a fog or cloud back-end system. In this paper we investigate the benefits of fog computing by proposing a novel distributed learning model on the sensor device and simulating the data stream in the fog, instead of transmitting all raw sensor values to the cloud back-end. To save energy and to communicate as few packets as possible, the updated parameters of the learned model at the sensor device are communicated in longer time intervals to a fog computing system. The proposed framework is implemented and tested in a real world testbed in order to make quantitative measurements and evaluate the system. Our results show that the proposed model can achieve a 98% decrease in the number of packets sent over the wireless link, and the fog node can still simulate the data stream with an acceptable accuracy of 97%. We also observe an end-to-end delay of 180 ms in our proposed three-layer framework. Hence, the framework shows that a combination of fog and cloud computing with a distributed data modeling at the sensor device for wireless sensor networks can be beneficial for Industrial Internet of Things applications. PMID:29757227

Cost-Effective Cloud Computing: A Case Study Using the Comparative Genomics Tool, Roundup

PubMed Central

Kudtarkar, Parul; DeLuca, Todd F.; Fusaro, Vincent A.; Tonellato, Peter J.; Wall, Dennis P.

2010-01-01

Background Comparative genomics resources, such as ortholog detection tools and repositories are rapidly increasing in scale and complexity. Cloud computing is an emerging technological paradigm that enables researchers to dynamically build a dedicated virtual cluster and may represent a valuable alternative for large computational tools in bioinformatics. In the present manuscript, we optimize the computation of a large-scale comparative genomics resource—Roundup—using cloud computing, describe the proper operating principles required to achieve computational efficiency on the cloud, and detail important procedures for improving cost-effectiveness to ensure maximal computation at minimal costs. Methods Utilizing the comparative genomics tool, Roundup, as a case study, we computed orthologs among 902 fully sequenced genomes on Amazon’s Elastic Compute Cloud. For managing the ortholog processes, we designed a strategy to deploy the web service, Elastic MapReduce, and maximize the use of the cloud while simultaneously minimizing costs. Specifically, we created a model to estimate cloud runtime based on the size and complexity of the genomes being compared that determines in advance the optimal order of the jobs to be submitted. Results We computed orthologous relationships for 245,323 genome-to-genome comparisons on Amazon’s computing cloud, a computation that required just over 200 hours and cost $8,000 USD, at least 40% less than expected under a strategy in which genome comparisons were submitted to the cloud randomly with respect to runtime. Our cost savings projections were based on a model that not only demonstrates the optimal strategy for deploying RSD to the cloud, but also finds the optimal cluster size to minimize waste and maximize usage. Our cost-reduction model is readily adaptable for other comparative genomics tools and potentially of significant benefit to labs seeking to take advantage of the cloud as an alternative to local computing infrastructure. PMID:21258651

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.

The emerging role of cloud computing in molecular modelling.

PubMed

Ebejer, Jean-Paul; Fulle, Simone; Morris, Garrett M; Finn, Paul W

2013-07-01

There is a growing recognition of the importance of cloud computing for large-scale and data-intensive applications. The distinguishing features of cloud computing and their relationship to other distributed computing paradigms are described, as are the strengths and weaknesses of the approach. We review the use made to date of cloud computing for molecular modelling projects and the availability of front ends for molecular modelling applications. Although the use of cloud computing technologies for molecular modelling is still in its infancy, we demonstrate its potential by presenting several case studies. Rapid growth can be expected as more applications become available and costs continue to fall; cloud computing can make a major contribution not just in terms of the availability of on-demand computing power, but could also spur innovation in the development of novel approaches that utilize that capacity in more effective ways. Copyright © 2013 Elsevier Inc. All rights reserved.

An Architecture for Cross-Cloud System Management

NASA Astrophysics Data System (ADS)

Dodda, Ravi Teja; Smith, Chris; van Moorsel, Aad

The emergence of the cloud computing paradigm promises flexibility and adaptability through on-demand provisioning of compute resources. As the utilization of cloud resources extends beyond a single provider, for business as well as technical reasons, the issue of effectively managing such resources comes to the fore. Different providers expose different interfaces to their compute resources utilizing varied architectures and implementation technologies. This heterogeneity poses a significant system management problem, and can limit the extent to which the benefits of cross-cloud resource utilization can be realized. We address this problem through the definition of an architecture to facilitate the management of compute resources from different cloud providers in an homogenous manner. This preserves the flexibility and adaptability promised by the cloud computing paradigm, whilst enabling the benefits of cross-cloud resource utilization to be realized. The practical efficacy of the architecture is demonstrated through an implementation utilizing compute resources managed through different interfaces on the Amazon Elastic Compute Cloud (EC2) service. Additionally, we provide empirical results highlighting the performance differential of these different interfaces, and discuss the impact of this performance differential on efficiency and profitability.

Polytopol computing for multi-core and distributed systems

NASA Astrophysics Data System (ADS)

Spaanenburg, Henk; Spaanenburg, Lambert; Ranefors, Johan

2009-05-01

Multi-core computing provides new challenges to software engineering. The paper addresses such issues in the general setting of polytopol computing, that takes multi-core problems in such widely differing areas as ambient intelligence sensor networks and cloud computing into account. It argues that the essence lies in a suitable allocation of free moving tasks. Where hardware is ubiquitous and pervasive, the network is virtualized into a connection of software snippets judiciously injected to such hardware that a system function looks as one again. The concept of polytopol computing provides a further formalization in terms of the partitioning of labor between collector and sensor nodes. Collectors provide functions such as a knowledge integrator, awareness collector, situation displayer/reporter, communicator of clues and an inquiry-interface provider. Sensors provide functions such as anomaly detection (only communicating singularities, not continuous observation), they are generally powered or self-powered, amorphous (not on a grid) with generation-and-attrition, field re-programmable, and sensor plug-and-play-able. Together the collector and the sensor are part of the skeleton injector mechanism, added to every node, and give the network the ability to organize itself into some of many topologies. Finally we will discuss a number of applications and indicate how a multi-core architecture supports the security aspects of the skeleton injector.

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.

Cloud computing security.

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

Shin, Dongwan; Claycomb, William R.; Urias, Vincent E.

Cloud computing is a paradigm rapidly being embraced by government and industry as a solution for cost-savings, scalability, and collaboration. While a multitude of applications and services are available commercially for cloud-based solutions, research in this area has yet to fully embrace the full spectrum of potential challenges facing cloud computing. This tutorial aims to provide researchers with a fundamental understanding of cloud computing, with the goals of identifying a broad range of potential research topics, and inspiring a new surge in research to address current issues. We will also discuss real implementations of research-oriented cloud computing systems for bothmore » academia and government, including configuration options, hardware issues, challenges, and solutions.« less

CLOUDCLOUD : general-purpose instrument monitoring and data managing software

NASA Astrophysics Data System (ADS)

Dias, António; Amorim, António; Tomé, António

2016-04-01

An effective experiment is dependent on the ability to store and deliver data and information to all participant parties regardless of their degree of involvement in the specific parts that make the experiment a whole. Having fast, efficient and ubiquitous access to data will increase visibility and discussion, such that the outcome will have already been reviewed several times, strengthening the conclusions. The CLOUD project aims at providing users with a general purpose data acquisition, management and instrument monitoring platform that is fast, easy to use, lightweight and accessible to all participants of an experiment. This work is now implemented in the CLOUD experiment at CERN and will be fully integrated with the experiment as of 2016. Despite being used in an experiment of the scale of CLOUD, this software can also be used in any size of experiment or monitoring station, from single computers to large networks of computers to monitor any sort of instrument output without influencing the individual instrument's DAQ. Instrument data and meta data is stored and accessed via a specially designed database architecture and any type of instrument output is accepted using our continuously growing parsing application. Multiple databases can be used to separate different data taking periods or a single database can be used if for instance an experiment is continuous. A simple web-based application gives the user total control over the monitored instruments and their data, allowing data visualization and download, upload of processed data and the ability to edit existing instruments or add new instruments to the experiment. When in a network, new computers are immediately recognized and added to the system and are able to monitor instruments connected to them. Automatic computer integration is achieved by a locally running python-based parsing agent that communicates with a main server application guaranteeing that all instruments assigned to that computer are monitored with parsing intervals as fast as milliseconds. This software (server+agents+interface+database) comes in easy and ready-to-use packages that can be installed in any operating system, including Android and iOS systems. This software is ideal for use in modular experiments or monitoring stations with large variability in instruments and measuring methods or in large collaborations, where data requires homogenization in order to be effectively transmitted to all involved parties. This work presents the software and provides performance comparison with previously used monitoring systems in the CLOUD experiment at CERN.

Maestro: an orchestration framework for large-scale WSN simulations.

PubMed

Riliskis, Laurynas; Osipov, Evgeny

2014-03-18

Contemporary wireless sensor networks (WSNs) have evolved into large and complex systems and are one of the main technologies used in cyber-physical systems and the Internet of Things. Extensive research on WSNs has led to the development of diverse solutions at all levels of software architecture, including protocol stacks for communications. This multitude of solutions is due to the limited computational power and restrictions on energy consumption that must be accounted for when designing typical WSN systems. It is therefore challenging to develop, test and validate even small WSN applications, and this process can easily consume significant resources. Simulations are inexpensive tools for testing, verifying and generally experimenting with new technologies in a repeatable fashion. Consequently, as the size of the systems to be tested increases, so does the need for large-scale simulations. This article describes a tool called Maestro for the automation of large-scale simulation and investigates the feasibility of using cloud computing facilities for such task. Using tools that are built into Maestro, we demonstrate a feasible approach for benchmarking cloud infrastructure in order to identify cloud Virtual Machine (VM)instances that provide an optimal balance of performance and cost for a given simulation.

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.

Maestro: An Orchestration Framework for Large-Scale WSN Simulations

PubMed Central

Riliskis, Laurynas; Osipov, Evgeny

2014-01-01

Contemporary wireless sensor networks (WSNs) have evolved into large and complex systems and are one of the main technologies used in cyber-physical systems and the Internet of Things. Extensive research on WSNs has led to the development of diverse solutions at all levels of software architecture, including protocol stacks for communications. This multitude of solutions is due to the limited computational power and restrictions on energy consumption that must be accounted for when designing typical WSN systems. It is therefore challenging to develop, test and validate even small WSN applications, and this process can easily consume significant resources. Simulations are inexpensive tools for testing, verifying and generally experimenting with new technologies in a repeatable fashion. Consequently, as the size of the systems to be tested increases, so does the need for large-scale simulations. This article describes a tool called Maestro for the automation of large-scale simulation and investigates the feasibility of using cloud computing facilities for such task. Using tools that are built into Maestro, we demonstrate a feasible approach for benchmarking cloud infrastructure in order to identify cloud Virtual Machine (VM)instances that provide an optimal balance of performance and cost for a given simulation. PMID:24647123

phpMs: A PHP-Based Mass Spectrometry Utilities Library.

PubMed

Collins, Andrew; Jones, Andrew R

2018-03-02

The recent establishment of cloud computing, high-throughput networking, and more versatile web standards and browsers has led to a renewed interest in web-based applications. While traditionally big data has been the domain of optimized desktop and server applications, it is now possible to store vast amounts of data and perform the necessary calculations offsite in cloud storage and computing providers, with the results visualized in a high-quality cross-platform interface via a web browser. There are number of emerging platforms for cloud-based mass spectrometry data analysis; however, there is limited pre-existing code accessible to web developers, especially for those that are constrained to a shared hosting environment where Java and C applications are often forbidden from use by the hosting provider. To remedy this, we provide an open-source mass spectrometry library for one of the most commonly used web development languages, PHP. Our new library, phpMs, provides objects for storing and manipulating spectra and identification data as well as utilities for file reading, file writing, calculations, peptide fragmentation, and protein digestion as well as a software interface for controlling search engines. We provide a working demonstration of some of the capabilities at http://pgb.liv.ac.uk/phpMs .

Challenges and Security in Cloud Computing

NASA Astrophysics Data System (ADS)

Chang, Hyokyung; Choi, Euiin

People who live in this world want to solve any problems as they happen then. An IT technology called Ubiquitous computing should help the situations easier and we call a technology which makes it even better and powerful cloud computing. Cloud computing, however, is at the stage of the beginning to implement and use and it faces a lot of challenges in technical matters and security issues. This paper looks at the cloud computing security.

Scaling predictive modeling in drug development with cloud computing.

PubMed

Moghadam, Behrooz Torabi; Alvarsson, Jonathan; Holm, Marcus; Eklund, Martin; Carlsson, Lars; Spjuth, Ola

2015-01-26

Growing data sets with increased time for analysis is hampering predictive modeling in drug discovery. Model building can be carried out on high-performance computer clusters, but these can be expensive to purchase and maintain. We have evaluated ligand-based modeling on cloud computing resources where computations are parallelized and run on the Amazon Elastic Cloud. We trained models on open data sets of varying sizes for the end points logP and Ames mutagenicity and compare with model building parallelized on a traditional high-performance computing cluster. We show that while high-performance computing results in faster model building, the use of cloud computing resources is feasible for large data sets and scales well within cloud instances. An additional advantage of cloud computing is that the costs of predictive models can be easily quantified, and a choice can be made between speed and economy. The easy access to computational resources with no up-front investments makes cloud computing an attractive alternative for scientists, especially for those without access to a supercomputer, and our study shows that it enables cost-efficient modeling of large data sets on demand within reasonable time.

Cloud-based large-scale air traffic flow optimization

NASA Astrophysics Data System (ADS)

Cao, Yi

The ever-increasing traffic demand makes the efficient use of airspace an imperative mission, and this paper presents an effort in response to this call. Firstly, a new aggregate model, called Link Transmission Model (LTM), is proposed, which models the nationwide traffic as a network of flight routes identified by origin-destination pairs. The traversal time of a flight route is assumed to be the mode of distribution of historical flight records, and the mode is estimated by using Kernel Density Estimation. As this simplification abstracts away physical trajectory details, the complexity of modeling is drastically decreased, resulting in efficient traffic forecasting. The predicative capability of LTM is validated against recorded traffic data. Secondly, a nationwide traffic flow optimization problem with airport and en route capacity constraints is formulated based on LTM. The optimization problem aims at alleviating traffic congestions with minimal global delays. This problem is intractable due to millions of variables. A dual decomposition method is applied to decompose the large-scale problem such that the subproblems are solvable. However, the whole problem is still computational expensive to solve since each subproblem is an smaller integer programming problem that pursues integer solutions. Solving an integer programing problem is known to be far more time-consuming than solving its linear relaxation. In addition, sequential execution on a standalone computer leads to linear runtime increase when the problem size increases. To address the computational efficiency problem, a parallel computing framework is designed which accommodates concurrent executions via multithreading programming. The multithreaded version is compared with its monolithic version to show decreased runtime. Finally, an open-source cloud computing framework, Hadoop MapReduce, is employed for better scalability and reliability. This framework is an "off-the-shelf" parallel computing model that can be used for both offline historical traffic data analysis and online traffic flow optimization. It provides an efficient and robust platform for easy deployment and implementation. A small cloud consisting of five workstations was configured and used to demonstrate the advantages of cloud computing in dealing with large-scale parallelizable traffic problems.

Big data mining analysis method based on cloud computing

NASA Astrophysics Data System (ADS)

Cai, Qing Qiu; Cui, Hong Gang; Tang, Hao

2017-08-01

Information explosion era, large data super-large, discrete and non-(semi) structured features have gone far beyond the traditional data management can carry the scope of the way. With the arrival of the cloud computing era, cloud computing provides a new technical way to analyze the massive data mining, which can effectively solve the problem that the traditional data mining method cannot adapt to massive data mining. This paper introduces the meaning and characteristics of cloud computing, analyzes the advantages of using cloud computing technology to realize data mining, designs the mining algorithm of association rules based on MapReduce parallel processing architecture, and carries out the experimental verification. The algorithm of parallel association rule mining based on cloud computing platform can greatly improve the execution speed of data mining.

Cloud archiving and data mining of High-Resolution Rapid Refresh forecast model output

NASA Astrophysics Data System (ADS)

Blaylock, Brian K.; Horel, John D.; Liston, Samuel T.

2017-12-01

Weather-related research often requires synthesizing vast amounts of data that need archival solutions that are both economical and viable during and past the lifetime of the project. Public cloud computing services (e.g., from Amazon, Microsoft, or Google) or private clouds managed by research institutions are providing object data storage systems potentially appropriate for long-term archives of such large geophysical data sets. We illustrate the use of a private cloud object store developed by the Center for High Performance Computing (CHPC) at the University of Utah. Since early 2015, we have been archiving thousands of two-dimensional gridded fields (each one containing over 1.9 million values over the contiguous United States) from the High-Resolution Rapid Refresh (HRRR) data assimilation and forecast modeling system. The archive is being used for retrospective analyses of meteorological conditions during high-impact weather events, assessing the accuracy of the HRRR forecasts, and providing initial and boundary conditions for research simulations. The archive is accessible interactively and through automated download procedures for researchers at other institutions that can be tailored by the user to extract individual two-dimensional grids from within the highly compressed files. Characteristics of the CHPC object storage system are summarized relative to network file system storage or tape storage solutions. The CHPC storage system is proving to be a scalable, reliable, extensible, affordable, and usable archive solution for our research.

Charting a Security Landscape in the Clouds: Data Protection and Collaboration in Cloud Storage

DTIC Science & Technology

2016-07-01

cloud computing is perhaps the most revolutionary force in the information technology industry today. This field encompasses many different domains...characteristic shared by all cloud computing tasks is that they involve storing data in the cloud . In this report, we therefore aim to describe and rank the...CONCLUSION The advent of cloud computing has caused government organizations to rethink their IT architectures so that they can take advantage of the

Introducing Cloud Computing Topics in Curricula

ERIC Educational Resources Information Center

Chen, Ling; Liu, Yang; Gallagher, Marcus; Pailthorpe, Bernard; Sadiq, Shazia; Shen, Heng Tao; Li, Xue

2012-01-01

The demand for graduates with exposure in Cloud Computing is on the rise. For many educational institutions, the challenge is to decide on how to incorporate appropriate cloud-based technologies into their curricula. In this paper, we describe our design and experiences of integrating Cloud Computing components into seven third/fourth-year…

Capturing and analyzing wheelchair maneuvering patterns with mobile cloud computing.

PubMed

Fu, Jicheng; Hao, Wei; White, Travis; Yan, Yuqing; Jones, Maria; Jan, Yih-Kuen

2013-01-01

Power wheelchairs have been widely used to provide independent mobility to people with disabilities. Despite great advancements in power wheelchair technology, research shows that wheelchair related accidents occur frequently. To ensure safe maneuverability, capturing wheelchair maneuvering patterns is fundamental to enable other research, such as safe robotic assistance for wheelchair users. In this study, we propose to record, store, and analyze wheelchair maneuvering data by means of mobile cloud computing. Specifically, the accelerometer and gyroscope sensors in smart phones are used to record wheelchair maneuvering data in real-time. Then, the recorded data are periodically transmitted to the cloud for storage and analysis. The analyzed results are then made available to various types of users, such as mobile phone users, traditional desktop users, etc. The combination of mobile computing and cloud computing leverages the advantages of both techniques and extends the smart phone's capabilities of computing and data storage via the Internet. We performed a case study to implement the mobile cloud computing framework using Android smart phones and Google App Engine, a popular cloud computing platform. Experimental results demonstrated the feasibility of the proposed mobile cloud computing framework.

Bootstrapping and Maintaining Trust in the Cloud

DTIC Science & Technology

2016-12-01

simultaneous cloud nodes. 1. INTRODUCTION The proliferation and popularity of infrastructure-as-a- service (IaaS) cloud computing services such as...Amazon Web Services and Google Compute Engine means more cloud tenants are hosting sensitive, private, and business critical data and applications in the...thousands of IaaS resources as they are elastically instantiated and terminated. Prior cloud trusted computing solutions address a subset of these features

Local storage federation through XRootD architecture for interactive distributed analysis

NASA Astrophysics Data System (ADS)

Colamaria, F.; Colella, D.; Donvito, G.; Elia, D.; Franco, A.; Luparello, G.; Maggi, G.; Miniello, G.; Vallero, S.; Vino, G.

2015-12-01

A cloud-based Virtual Analysis Facility (VAF) for the ALICE experiment at the LHC has been deployed in Bari. Similar facilities are currently running in other Italian sites with the aim to create a federation of interoperating farms able to provide their computing resources for interactive distributed analysis. The use of cloud technology, along with elastic provisioning of computing resources as an alternative to the grid for running data intensive analyses, is the main challenge of these facilities. One of the crucial aspects of the user-driven analysis execution is the data access. A local storage facility has the disadvantage that the stored data can be accessed only locally, i.e. from within the single VAF. To overcome such a limitation a federated infrastructure, which provides full access to all the data belonging to the federation independently from the site where they are stored, has been set up. The federation architecture exploits both cloud computing and XRootD technologies, in order to provide a dynamic, easy-to-use and well performing solution for data handling. It should allow the users to store the files and efficiently retrieve the data, since it implements a dynamic distributed cache among many datacenters in Italy connected to one another through the high-bandwidth national network. Details on the preliminary architecture implementation and performance studies are discussed.

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.

Study on the application of mobile internet cloud computing platform

NASA Astrophysics Data System (ADS)

Gong, Songchun; Fu, Songyin; Chen, Zheng

2012-04-01

The innovative development of computer technology promotes the application of the cloud computing platform, which actually is the substitution and exchange of a sort of resource service models and meets the needs of users on the utilization of different resources after changes and adjustments of multiple aspects. "Cloud computing" owns advantages in many aspects which not merely reduce the difficulties to apply the operating system and also make it easy for users to search, acquire and process the resources. In accordance with this point, the author takes the management of digital libraries as the research focus in this paper, and analyzes the key technologies of the mobile internet cloud computing platform in the operation process. The popularization and promotion of computer technology drive people to create the digital library models, and its core idea is to strengthen the optimal management of the library resource information through computers and construct an inquiry and search platform with high performance, allowing the users to access to the necessary information resources at any time. However, the cloud computing is able to promote the computations within the computers to distribute in a large number of distributed computers, and hence implement the connection service of multiple computers. The digital libraries, as a typical representative of the applications of the cloud computing, can be used to carry out an analysis on the key technologies of the cloud computing.

Marine Corps Private Cloud Computing Environment Strategy

DTIC Science & Technology

2012-05-15

leveraging economies of scale through the MCEITS PCCE, the Marine Corps will measure consumed IT resources more effectively, increase or decrease...flexible broad network access, resource pooling, elastic provisioning and measured services. By leveraging economies of scale the Marine Corps will be able...IaaS SaaS / IaaS 1 1 LCE I ACE Dets I I I I ------------------~ GIG / CJ Internet Security Boundary MCEN I DISN r :------------------ MCEN

Fingerprinting Reverse Proxies Using Timing Analysis of TCP Flows

DTIC Science & Technology

2013-09-01

bayes classifier,” in Cloud Computing Security , ser. CCSW ’09. New York City, NY: ACM, 2009, pp. 31–42. [30] J. Zhang, R. Perdisci, W. Lee, U. Sarfraz...FSM Finite State Machine HTML Hypertext Markup Language HTTP Hypertext Transfer Protocol HTTPS Hypertext Transfer Protocol Secure ICMP Internet Control...This hidden traffic concept supports network access control, security protection through obfuscation, and performance boosts at the Internet facing

A New User Interface for On-Demand Customizable Data Products for Sensors in a SensorWeb

NASA Technical Reports Server (NTRS)

Mandl, Daniel; Cappelaere, Pat; Frye, Stuart; Sohlberg, Rob; Ly, Vuong; Chien, Steve; Sullivan, Don

2011-01-01

A SensorWeb is a set of sensors, which can consist of ground, airborne and space-based sensors interoperating in an automated or autonomous collaborative manner. The NASA SensorWeb toolbox, developed at NASA/GSFC in collaboration with NASA/JPL, NASA/Ames and other partners, is a set of software and standards that (1) enables users to create virtual private networks of sensors over open networks; (2) provides the capability to orchestrate their actions; (3) provides the capability to customize the output data products and (4) enables automated delivery of the data products to the users desktop. A recent addition to the SensorWeb Toolbox is a new user interface, together with web services co-resident with the sensors, to enable rapid creation, loading and execution of new algorithms for processing sensor data. The web service along with the user interface follows the Open Geospatial Consortium (OGC) standard called Web Coverage Processing Service (WCPS). This presentation will detail the prototype that was built and how the WCPS was tested against a HyspIRI flight testbed and an elastic computation cloud on the ground with EO-1 data. HyspIRI is a future NASA decadal mission. The elastic computation cloud stores EO-1 data and runs software similar to Amazon online shopping.

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.

SPARCCS - Smartphone-Assisted Readiness, Command and Control System

DTIC Science & Technology

2012-06-01

and database needs. By doing this SPARCCS takes advantage of all the capabilities cloud computing has to offer, especially that of disbursed data...40092829/ Microsoft. (2011). Cloud Computing . Retrieved September 24, 2011, http ://www.microsoft.com/industry/government/guides/cloud_computing/2...Command, and Control System) to address these issues. We use smartphones in conjunction with cloud computing to extend the benefits of collaborative

The application of cloud computing to scientific workflows: a study of cost and performance.

PubMed

Berriman, G Bruce; Deelman, Ewa; Juve, Gideon; Rynge, Mats; Vöckler, Jens-S

2013-01-28

The current model of transferring data from data centres to desktops for analysis will soon be rendered impractical by the accelerating growth in the volume of science datasets. Processing will instead often take place on high-performance servers co-located with data. Evaluations of how new technologies such as cloud computing would support such a new distributed computing model are urgently needed. Cloud computing is a new way of purchasing computing and storage resources on demand through virtualization technologies. We report here the results of investigations of the applicability of commercial cloud computing to scientific computing, with an emphasis on astronomy, including investigations of what types of applications can be run cheaply and efficiently on the cloud, and an example of an application well suited to the cloud: processing a large dataset to create a new science product.

Use of cloud computing in biomedicine.

PubMed

Sobeslav, Vladimir; Maresova, Petra; Krejcar, Ondrej; Franca, Tanos C C; Kuca, Kamil

2016-12-01

Nowadays, biomedicine is characterised by a growing need for processing of large amounts of data in real time. This leads to new requirements for information and communication technologies (ICT). Cloud computing offers a solution to these requirements and provides many advantages, such as cost savings, elasticity and scalability of using ICT. The aim of this paper is to explore the concept of cloud computing and the related use of this concept in the area of biomedicine. Authors offer a comprehensive analysis of the implementation of the cloud computing approach in biomedical research, decomposed into infrastructure, platform and service layer, and a recommendation for processing large amounts of data in biomedicine. Firstly, the paper describes the appropriate forms and technological solutions of cloud computing. Secondly, the high-end computing paradigm of cloud computing aspects is analysed. Finally, the potential and current use of applications in scientific research of this technology in biomedicine is discussed.

High-Performance Compute Infrastructure in Astronomy: 2020 Is Only Months Away

NASA Astrophysics Data System (ADS)

Berriman, B.; Deelman, E.; Juve, G.; Rynge, M.; Vöckler, J. S.

2012-09-01

By 2020, astronomy will be awash with as much as 60 PB of public data. Full scientific exploitation of such massive volumes of data will require high-performance computing on server farms co-located with the data. Development of this computing model will be a community-wide enterprise that has profound cultural and technical implications. Astronomers must be prepared to develop environment-agnostic applications that support parallel processing. The community must investigate the applicability and cost-benefit of emerging technologies such as cloud computing to astronomy, and must engage the Computer Science community to develop science-driven cyberinfrastructure such as workflow schedulers and optimizers. We report here the results of collaborations between a science center, IPAC, and a Computer Science research institute, ISI. These collaborations may be considered pathfinders in developing a high-performance compute infrastructure in astronomy. These collaborations investigated two exemplar large-scale science-driver workflow applications: 1) Calculation of an infrared atlas of the Galactic Plane at 18 different wavelengths by placing data from multiple surveys on a common plate scale and co-registering all the pixels; 2) Calculation of an atlas of periodicities present in the public Kepler data sets, which currently contain 380,000 light curves. These products have been generated with two workflow applications, written in C for performance and designed to support parallel processing on multiple environments and platforms, but with different compute resource needs: the Montage image mosaic engine is I/O-bound, and the NASA Star and Exoplanet Database periodogram code is CPU-bound. Our presentation will report cost and performance metrics and lessons-learned for continuing development. Applicability of Cloud Computing: Commercial Cloud providers generally charge for all operations, including processing, transfer of input and output data, and for storage of data, and so the costs of running applications vary widely according to how they use resources. The cloud is well suited to processing CPU-bound (and memory bound) workflows such as the periodogram code, given the relatively low cost of processing in comparison with I/O operations. I/O-bound applications such as Montage perform best on high-performance clusters with fast networks and parallel file-systems. Science-driven Cyberinfrastructure: Montage has been widely used as a driver application to develop workflow management services, such as task scheduling in distributed environments, designing fault tolerance techniques for job schedulers, and developing workflow orchestration techniques. Running Parallel Applications Across Distributed Cloud Environments: Data processing will eventually take place in parallel distributed across cyber infrastructure environments having different architectures. We have used the Pegasus Work Management System (WMS) to successfully run applications across three very different environments: TeraGrid, OSG (Open Science Grid), and FutureGrid. Provisioning resources across different grids and clouds (also referred to as Sky Computing), involves establishing a distributed environment, where issues of, e.g, remote job submission, data management, and security need to be addressed. This environment also requires building virtual machine images that can run in different environments. Usually, each cloud provides basic images that can be customized with additional software and services. In most of our work, we provisioned compute resources using a custom application, called Wrangler. Pegasus WMS abstracts the architectures of the compute environments away from the end-user, and can be considered a first-generation tool suitable for scientists to run their applications on disparate environments.

Road Risk Modeling and Cloud-Aided Safety-Based Route Planning.

PubMed

Li, Zhaojian; Kolmanovsky, Ilya; Atkins, Ella; Lu, Jianbo; Filev, Dimitar P; Michelini, John

2016-11-01

This paper presents a safety-based route planner that exploits vehicle-to-cloud-to-vehicle (V2C2V) connectivity. Time and road risk index (RRI) are considered as metrics to be balanced based on user preference. To evaluate road segment risk, a road and accident database from the highway safety information system is mined with a hybrid neural network model to predict RRI. Real-time factors such as time of day, day of the week, and weather are included as correction factors to the static RRI prediction. With real-time RRI and expected travel time, route planning is formulated as a multiobjective network flow problem and further reduced to a mixed-integer programming problem. A V2C2V implementation of our safety-based route planning approach is proposed to facilitate access to real-time information and computing resources. A real-world case study, route planning through the city of Columbus, Ohio, is presented. Several scenarios illustrate how the "best" route can be adjusted to favor time versus safety metrics.

Design and Implementation of Website Information Disclosure Assessment System

PubMed Central

Cho, Ying-Chiang; Pan, Jen-Yi

2015-01-01

Internet application technologies, such as cloud computing and cloud storage, have increasingly changed people’s lives. Websites contain vast amounts of personal privacy information. In order to protect this information, network security technologies, such as database protection and data encryption, attract many researchers. The most serious problems concerning web vulnerability are e-mail address and network database leakages. These leakages have many causes. For example, malicious users can steal database contents, taking advantage of mistakes made by programmers and administrators. In order to mitigate this type of abuse, a website information disclosure assessment system is proposed in this study. This system utilizes a series of technologies, such as web crawler algorithms, SQL injection attack detection, and web vulnerability mining, to assess a website’s information disclosure. Thirty websites, randomly sampled from the top 50 world colleges, were used to collect leakage information. This testing showed the importance of increasing the security and privacy of website information for academic websites. PMID:25768434

COMBAT: mobile-Cloud-based cOmpute/coMmunications infrastructure for BATtlefield applications

NASA Astrophysics Data System (ADS)

Soyata, Tolga; Muraleedharan, Rajani; Langdon, Jonathan; Funai, Colin; Ames, Scott; Kwon, Minseok; Heinzelman, Wendi

2012-05-01

The amount of data processed annually over the Internet has crossed the zetabyte boundary, yet this Big Data cannot be efficiently processed or stored using today's mobile devices. Parallel to this explosive growth in data, a substantial increase in mobile compute-capability and the advances in cloud computing have brought the state-of-the- art in mobile-cloud computing to an inflection point, where the right architecture may allow mobile devices to run applications utilizing Big Data and intensive computing. In this paper, we propose the MObile Cloud-based Hybrid Architecture (MOCHA), which formulates a solution to permit mobile-cloud computing applications such as object recognition in the battlefield by introducing a mid-stage compute- and storage-layer, called the cloudlet. MOCHA is built on the key observation that many mobile-cloud applications have the following characteristics: 1) they are compute-intensive, requiring the compute-power of a supercomputer, and 2) they use Big Data, requiring a communications link to cloud-based database sources in near-real-time. In this paper, we describe the operation of MOCHA in battlefield applications, by formulating the aforementioned mobile and cloudlet to be housed within a soldier's vest and inside a military vehicle, respectively, and enabling access to the cloud through high latency satellite links. We provide simulations using the traditional mobile-cloud approach as well as utilizing MOCHA with a mid-stage cloudlet to quantify the utility of this architecture. We show that the MOCHA platform for mobile-cloud computing promises a future for critical battlefield applications that access Big Data, which is currently not possible using existing technology.

Hybrid cloud: bridging of private and public cloud computing

NASA Astrophysics Data System (ADS)

Aryotejo, Guruh; Kristiyanto, Daniel Y.; Mufadhol

2018-05-01

Cloud Computing is quickly emerging as a promising paradigm in the recent years especially for the business sector. In addition, through cloud service providers, cloud computing is widely used by Information Technology (IT) based startup company to grow their business. However, the level of most businesses awareness on data security issues is low, since some Cloud Service Provider (CSP) could decrypt their data. Hybrid Cloud Deployment Model (HCDM) has characteristic as open source, which is one of secure cloud computing model, thus HCDM may solve data security issues. The objective of this study is to design, deploy and evaluate a HCDM as Infrastructure as a Service (IaaS). In the implementation process, Metal as a Service (MAAS) engine was used as a base to build an actual server and node. Followed by installing the vsftpd application, which serves as FTP server. In comparison with HCDM, public cloud was adopted through public cloud interface. As a result, the design and deployment of HCDM was conducted successfully, instead of having good security, HCDM able to transfer data faster than public cloud significantly. To the best of our knowledge, Hybrid Cloud Deployment model is one of secure cloud computing model due to its characteristic as open source. Furthermore, this study will serve as a base for future studies about Hybrid Cloud Deployment model which may relevant for solving big security issues of IT-based startup companies especially in Indonesia.

Cloud Computing

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

Pete Beckman and Ian Foster

Chicago Matters: Beyond Burnham (WTTW). Chicago has become a world center of "cloud computing." Argonne experts Pete Beckman and Ian Foster explain what "cloud computing" is and how you probably already use it on a daily basis.

A Cloud Robotics Based Service for Managing RPAS in Emergency, Rescue and Hazardous Scenarios

NASA Astrophysics Data System (ADS)

Silvagni, Mario; Chiaberge, Marcello; Sanguedolce, Claudio; Dara, Gianluca

2016-04-01

Cloud robotics and cloud services are revolutionizing not only the ICT world but also the robotics industry, giving robots more computing capabilities, storage and connection bandwidth while opening new scenarios that blend the physical to the digital world. In this vision, new IT architectures are required to manage robots, retrieve data from them and create services to interact with users. Among all the robots this work is mainly focused on flying robots, better known as drones, UAV (Unmanned Aerial Vehicle) or RPAS (Remotely Piloted Aircraft Systems). The cloud robotics approach shifts the concept of having a single local "intelligence" for every single UAV, as a unique device that carries out onboard all the computation and storage processes, to a more powerful "centralized brain" located in the cloud. This breakthrough opens new scenarios where UAVs are agents, relying on remote servers for most of their computational load and data storage, creating a network of devices where they can share knowledge and information. Many applications, using UAVs, are growing as interesting and suitable devices for environment monitoring. Many services can be build fetching data from UAVs, such as telemetry, video streaming, pictures or sensors data; once. These services, part of the IT architecture, can be accessed via web by other devices or shared with other UAVs. As test cases of the proposed architecture, two examples are reported. In the first one a search and rescue or emergency management, where UAVs are required for monitoring intervention, is shown. In case of emergency or aggression, the user requests the emergency service from the IT architecture, providing GPS coordinates and an identification number. The IT architecture uses a UAV (choosing among the available one according to distance, service status, etc.) to reach him/her for monitoring and support operations. In the meantime, an officer will use the service to see the current position of the UAV, its telemetry and video streaming from its camera. Data are stored for further use and documentation and can be shared to all the involved personal or services. The second case refer to imaging survey. An investigation area is selected using a map or a set of coordinates by a user that can be on the field on in a management facility. The cloud system elaborate this data and automatically compute a flight plan that consider the survey data requirements (i.e: picture ground resolution, overlapping) but also several environment constraints (i.e: no fly zones, possible hazardous areas, known obstacles, etc). Once the flight plan is loaded in the selected UAV the mission starts. During the mission, if a suitable data network coverage is available, the UAV transmit acquired images (typically low quality image to limit bandwidth) and shooting pose in order to perform a preliminary check during the mission and minimize failing in survey; if not, all data are uploaded asynchronously after the mission. The cloud servers perform all the tasks related to image processing (mosaic, ortho-photo, geo-referencing, 3D models) and data management.

Transitioning ISR architecture into the cloud

NASA Astrophysics Data System (ADS)

Lash, Thomas D.

2012-06-01

Emerging cloud computing platforms offer an ideal opportunity for Intelligence, Surveillance, and Reconnaissance (ISR) intelligence analysis. Cloud computing platforms help overcome challenges and limitations of traditional ISR architectures. Modern ISR architectures can benefit from examining commercial cloud applications, especially as they relate to user experience, usage profiling, and transformational business models. This paper outlines legacy ISR architectures and their limitations, presents an overview of cloud technologies and their applications to the ISR intelligence mission, and presents an idealized ISR architecture implemented with cloud computing.

A Simple and Accurate Network for Hydrogen and Carbon Chemistry in the Interstellar Medium

NASA Astrophysics Data System (ADS)

Gong, Munan; Ostriker, Eve C.; Wolfire, Mark G.

2017-07-01

Chemistry plays an important role in the interstellar medium (ISM), regulating the heating and cooling of the gas and determining abundances of molecular species that trace gas properties in observations. Although solving the time-dependent equations is necessary for accurate abundances and temperature in the dynamic ISM, a full chemical network is too computationally expensive to incorporate into numerical simulations. In this paper, we propose a new simplified chemical network for hydrogen and carbon chemistry in the atomic and molecular ISM. We compare results from our chemical network in detail with results from a full photodissociation region (PDR) code, and also with the Nelson & Langer (NL99) network previously adopted in the simulation literature. We show that our chemical network gives similar results to the PDR code in the equilibrium abundances of all species over a wide range of densities, temperature, and metallicities, whereas the NL99 network shows significant disagreement. Applying our network to 1D models, we find that the CO-dominated regime delimits the coldest gas and that the corresponding temperature tracks the cosmic-ray ionization rate in molecular clouds. We provide a simple fit for the locus of CO-dominated regions as a function of gas density and column. We also compare with observations of diffuse and translucent clouds. We find that the CO, {{CH}}x, and {{OH}}x abundances are consistent with equilibrium predictions for densities n=100{--}1000 {{cm}}-3, but the predicted equilibrium C abundance is higher than that seen in observations, signaling the potential importance of non-equilibrium/dynamical effects.

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.

Libraries in the Cloud: Making a Case for Google and Amazon

ERIC Educational Resources Information Center

Buck, Stephanie

2009-01-01

As news outlets create headlines such as "A Cloud & A Prayer," "The Cloud Is the Computer," and "Leveraging Clouds to Make You More Efficient," many readers have been left with cloud confusion. Many definitions exist for cloud computing, and a uniform definition is hard to find. In its most basic form, cloud…

Studying the Relationship between High-Latitude Geomagnetic Activity and Parameters of Interplanetary Magnetic Clouds with the Use of Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Barkhatov, N. A.; Revunov, S. E.; Vorobjev, V. G.; Yagodkina, O. I.

2018-03-01

The cause-and-effect relations of the dynamics of high-latitude geomagnetic activity (in terms of the AL index) and the type of the magnetic cloud of the solar wind are studied with the use of artificial neural networks. A recurrent neural network model has been created based on the search for the optimal physically coupled input and output parameters characterizing the action of a plasma flux belonging to a certain magnetic cloud type on the magnetosphere. It has been shown that, with IMF components as input parameters of neural networks with allowance for a 90-min prehistory, it is possible to retrieve the AL sequence with an accuracy to 80%. The successful retrieval of the AL dynamics by the used data indicates the presence of a close nonlinear connection of the AL index with cloud parameters. The created neural network models can be applied with high efficiency to retrieve the AL index, both in periods of isolated magnetospheric substorms and in periods of the interaction between the Earth's magnetosphere and magnetic clouds of different types. The developed model of AL index retrieval can be used to detect magnetic clouds.

In the Clouds: The Implications of Cloud Computing for Higher Education Information Technology Governance and Decision Making

ERIC Educational Resources Information Center

Dulaney, Malik H.

2013-01-01

Emerging technologies challenge the management of information technology in organizations. Paradigm changing technologies, such as cloud computing, have the ability to reverse the norms in organizational management, decision making, and information technology governance. This study explores the effects of cloud computing on information technology…

Factors Influencing the Adoption of Cloud Computing by Decision Making Managers

ERIC Educational Resources Information Center

Ross, Virginia Watson

2010-01-01

Cloud computing is a growing field, addressing the market need for access to computing resources to meet organizational computing requirements. The purpose of this research is to evaluate the factors that influence an organization in their decision whether to adopt cloud computing as a part of their strategic information technology planning.…

A General Cross-Layer Cloud Scheduling Framework for Multiple IoT Computer Tasks.

PubMed

Wu, Guanlin; Bao, Weidong; Zhu, Xiaomin; Zhang, Xiongtao

2018-05-23

The diversity of IoT services and applications brings enormous challenges to improving the performance of multiple computer tasks' scheduling in cross-layer cloud computing systems. Unfortunately, the commonly-employed frameworks fail to adapt to the new patterns on the cross-layer cloud. To solve this issue, we design a new computer task scheduling framework for multiple IoT services in cross-layer cloud computing systems. Specifically, we first analyze the features of the cross-layer cloud and computer tasks. Then, we design the scheduling framework based on the analysis and present detailed models to illustrate the procedures of using the framework. With the proposed framework, the IoT services deployed in cross-layer cloud computing systems can dynamically select suitable algorithms and use resources more effectively to finish computer tasks with different objectives. Finally, the algorithms are given based on the framework, and extensive experiments are also given to validate its effectiveness, as well as its superiority.

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.

Secure open cloud in data transmission using reference pattern and identity with enhanced remote privacy checking

NASA Astrophysics Data System (ADS)

Vijay Singh, Ran; Agilandeeswari, L.

2017-11-01

To handle the large amount of client’s data in open cloud lots of security issues need to be address. Client’s privacy should not be known to other group members without data owner’s valid permission. Sometime clients are fended to have accessing with open cloud servers due to some restrictions. To overcome the security issues and these restrictions related to storing, data sharing in an inter domain network and privacy checking, we propose a model in this paper which is based on an identity based cryptography in data transmission and intermediate entity which have client’s reference with identity that will take control handling of data transmission in an open cloud environment and an extended remote privacy checking technique which will work at admin side. On behalf of data owner’s authority this proposed model will give best options to have secure cryptography in data transmission and remote privacy checking either as private or public or instructed. The hardness of Computational Diffie-Hellman assumption algorithm for key exchange makes this proposed model more secure than existing models which are being used for public cloud environment.

The cloud paradigm applied to e-Health.

PubMed

Vilaplana, Jordi; Solsona, Francesc; Abella; Filgueira, Rosa; Rius, Josep

2013-03-14

Cloud computing is a new paradigm that is changing how enterprises, institutions and people understand, perceive and use current software systems. With this paradigm, the organizations have no need to maintain their own servers, nor host their own software. Instead, everything is moved to the cloud and provided on demand, saving energy, physical space and technical staff. Cloud-based system architectures provide many advantages in terms of scalability, maintainability and massive data processing. We present the design of an e-health cloud system, modelled by an M/M/m queue with QoS capabilities, i.e. maximum waiting time of requests. Detailed results for the model formed by a Jackson network of two M/M/m queues from the queueing theory perspective are presented. These results show a significant performance improvement when the number of servers increases. Platform scalability becomes a critical issue since we aim to provide the system with high Quality of Service (QoS). In this paper we define an architecture capable of adapting itself to different diseases and growing numbers of patients. This platform could be applied to the medical field to greatly enhance the results of those therapies that have an important psychological component, such as addictions and chronic diseases.

Research on phone contacts online status based on mobile cloud computing

NASA Astrophysics Data System (ADS)

Wang, Wen-jinga; Ge, Weib

2013-03-01

Because the limited ability of storage space, CPU processing on mobile phone, it is difficult to realize complex applications on mobile phones, but along with the development of cloud computing, we can place the computing and storage in the clouds, provide users with rich cloud services, helping users complete various function through the browser has become the trend for future mobile communication. This article is taking the mobile phone contacts online status as an example to analysis the development and application of mobile cloud computing.

Bootstrapping and Maintaining Trust in the Cloud

DTIC Science & Technology

2016-12-01

proliferation and popularity of infrastructure-as-a- service (IaaS) cloud computing services such as Amazon Web Services and Google Compute Engine means...IaaS trusted computing system: • Secure Bootstrapping – the system should enable the tenant to securely install an initial root secret into each cloud ...elastically instantiated and terminated. Prior cloud trusted computing solutions address a subset of these features, but none achieve all. Excalibur [31] sup

Cloud Computing: An Overview

NASA Astrophysics Data System (ADS)

Qian, Ling; Luo, Zhiguo; Du, Yujian; Guo, Leitao

In order to support the maximum number of user and elastic service with the minimum resource, the Internet service provider invented the cloud computing. within a few years, emerging cloud computing has became the hottest technology. From the publication of core papers by Google since 2003 to the commercialization of Amazon EC2 in 2006, and to the service offering of AT&T Synaptic Hosting, the cloud computing has been evolved from internal IT system to public service, from cost-saving tools to revenue generator, and from ISP to telecom. This paper introduces the concept, history, pros and cons of cloud computing as well as the value chain and standardization effort.

Cloud Collaboration: Cloud-Based Instruction for Business Writing Class

ERIC Educational Resources Information Center

Lin, Charlie; Yu, Wei-Chieh Wayne; Wang, Jenny

2014-01-01

Cloud computing technologies, such as Google Docs, Adobe Creative Cloud, Dropbox, and Microsoft Windows Live, have become increasingly appreciated to the next generation digital learning tools. Cloud computing technologies encourage students' active engagement, collaboration, and participation in their learning, facilitate group work, and support…

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.

Security model for VM in cloud

NASA Astrophysics Data System (ADS)

Kanaparti, Venkataramana; Naveen K., R.; Rajani, S.; Padmvathamma, M.; Anitha, C.

2013-03-01

Cloud computing is a new approach emerged to meet ever-increasing demand for computing resources and to reduce operational costs and Capital Expenditure for IT services. As this new way of computation allows data and applications to be stored away from own corporate server, it brings more issues in security such as virtualization security, distributed computing, application security, identity management, access control and authentication. Even though Virtualization forms the basis for cloud computing it poses many threats in securing cloud. As most of Security threats lies at Virtualization layer in cloud we proposed this new Security Model for Virtual Machine in Cloud (SMVC) in which every process is authenticated by Trusted-Agent (TA) in Hypervisor as well as in VM. Our proposed model is designed to with-stand attacks by unauthorized process that pose threat to applications related to Data Mining, OLAP systems, Image processing which requires huge resources in cloud deployed on one or more VM's.

Internet-Based Solutions for a Secure and Efficient Seismic Network

NASA Astrophysics Data System (ADS)

Bhadha, R.; Black, M.; Bruton, C.; Hauksson, E.; Stubailo, I.; Watkins, M.; Alvarez, M.; Thomas, V.

2017-12-01

The Southern California Seismic Network (SCSN), operated by Caltech and USGS, leverages modern Internet-based computing technologies to provide timely earthquake early warning for damage reduction, event notification, ShakeMap, and other data products. Here we present recent and ongoing innovations in telemetry, security, cloud computing, virtualization, and data analysis that have allowed us to develop a network that runs securely and efficiently.Earthquake early warning systems must process seismic data within seconds of being recorded, and SCSN maintains a robust and resilient network of more than 350 digital strong motion and broadband seismic stations to achieve this goal. We have continued to improve the path diversity and fault tolerance within our network, and have also developed new tools for latency monitoring and archiving.Cyberattacks are in the news almost daily, and with most of our seismic data streams running over the Internet, it is only a matter of time before SCSN is targeted. To ensure system integrity and availability across our network, we have implemented strong security, including encryption and Virtual Private Networks (VPNs).SCSN operates its own data center at Caltech, but we have also installed real-time servers on Amazon Web Services (AWS), to provide an additional level of redundancy, and eventually to allow full off-site operations continuity for our network. Our AWS systems receive data from Caltech-based import servers and directly from field locations, and are able to process the seismic data, calculate earthquake locations and magnitudes, and distribute earthquake alerts, directly from the cloud.We have also begun a virtualization project at our Caltech data center, allowing us to serve data from Virtual Machines (VMs), making efficient use of high-performance hardware and increasing flexibility and scalability of our data processing systems.Finally, we have developed new monitoring of station average noise levels at most stations. Noise monitoring is effective at identifying anthropogenic noise sources and malfunctioning acquisition equipment. We have built a dynamic display of results with sorting and mapping capabilities that allow us to quickly identify problematic sites and areas with elevated noise.

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

Hameed, Abdul; Khoshkbarforoushha, Alireza; Ranjan, Rajiv

In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subjectmore » that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.« less

Secure data sharing in public cloud

NASA Astrophysics Data System (ADS)

Venkataramana, Kanaparti; Naveen Kumar, R.; Tatekalva, Sandhya; Padmavathamma, M.

2012-04-01

Secure multi-party protocols have been proposed for entities (organizations or individuals) that don't fully trust each other to share sensitive information. Many types of entities need to collect, analyze, and disseminate data rapidly and accurately, without exposing sensitive information to unauthorized or untrusted parties. Solutions based on secure multiparty computation guarantee privacy and correctness, at an extra communication (too costly in communication to be practical) and computation cost. The high overhead motivates us to extend this SMC to cloud environment which provides large computation and communication capacity which makes SMC to be used between multiple clouds (i.e., it may between private or public or hybrid clouds).Cloud may encompass many high capacity servers which acts as a hosts which participate in computation (IaaS and PaaS) for final result, which is controlled by Cloud Trusted Authority (CTA) for secret sharing within the cloud. The communication between two clouds is controlled by High Level Trusted Authority (HLTA) which is one of the hosts in a cloud which provides MgaaS (Management as a Service). Due to high risk for security in clouds, HLTA generates and distributes public keys and private keys by using Carmichael-R-Prime- RSA algorithm for exchange of private data in SMC between itself and clouds. In cloud, CTA creates Group key for Secure communication between the hosts in cloud based on keys sent by HLTA for exchange of Intermediate values and shares for computation of final result. Since this scheme is extended to be used in clouds( due to high availability and scalability to increase computation power) it is possible to implement SMC practically for privacy preserving in data mining at low cost for the clients.

Applications integration in a hybrid cloud computing environment: modelling and platform

NASA Astrophysics Data System (ADS)

Li, Qing; Wang, Ze-yuan; Li, Wei-hua; Li, Jun; Wang, Cheng; Du, Rui-yang

2013-08-01

With the development of application services providers and cloud computing, more and more small- and medium-sized business enterprises use software services and even infrastructure services provided by professional information service companies to replace all or part of their information systems (ISs). These information service companies provide applications, such as data storage, computing processes, document sharing and even management information system services as public resources to support the business process management of their customers. However, no cloud computing service vendor can satisfy the full functional IS requirements of an enterprise. As a result, enterprises often have to simultaneously use systems distributed in different clouds and their intra enterprise ISs. Thus, this article presents a framework to integrate applications deployed in public clouds and intra ISs. A run-time platform is developed and a cross-computing environment process modelling technique is also developed to improve the feasibility of ISs under hybrid cloud computing environments.

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…

Lidar-based individual tree species classification using convolutional neural network

NASA Astrophysics Data System (ADS)

Mizoguchi, Tomohiro; Ishii, Akira; Nakamura, Hiroyuki; Inoue, Tsuyoshi; Takamatsu, Hisashi

2017-06-01

Terrestrial lidar is commonly used for detailed documentation in the field of forest inventory investigation. Recent improvements of point cloud processing techniques enabled efficient and precise computation of an individual tree shape parameters, such as breast-height diameter, height, and volume. However, tree species are manually specified by skilled workers to date. Previous works for automatic tree species classification mainly focused on aerial or satellite images, and few works have been reported for classification techniques using ground-based sensor data. Several candidate sensors can be considered for classification, such as RGB or multi/hyper spectral cameras. Above all candidates, we use terrestrial lidar because it can obtain high resolution point cloud in the dark forest. We selected bark texture for the classification criteria, since they clearly represent unique characteristics of each tree and do not change their appearance under seasonable variation and aged deterioration. In this paper, we propose a new method for automatic individual tree species classification based on terrestrial lidar using Convolutional Neural Network (CNN). The key component is the creation step of a depth image which well describe the characteristics of each species from a point cloud. We focus on Japanese cedar and cypress which cover the large part of domestic forest. Our experimental results demonstrate the effectiveness of our proposed method.

Climbing the Slope of Enlightenment during NASA's Arctic Boreal Vulnerability Experiment

NASA Astrophysics Data System (ADS)

Griffith, P. C.; Hoy, E.; Duffy, D.; McInerney, M.

2015-12-01

The Arctic Boreal Vulnerability Experiment (ABoVE) is a new field campaign sponsored by NASA's Terrestrial Ecology Program and designed to improve understanding of the vulnerability and resilience of Arctic and boreal social-ecological systems to environmental change (http://above.nasa.gov). ABoVE is integrating field-based studies, modeling, and data from airborne and satellite remote sensing. The NASA Center for Climate Simulation (NCCS) has partnered with the NASA Carbon Cycle and Ecosystems Office (CCEO) to create a high performance science cloud for this field campaign. The ABoVE Science Cloud combines high performance computing with emerging technologies and data management with tools for analyzing and processing geographic information to create an environment specifically designed for large-scale modeling, analysis of remote sensing data, copious disk storage for "big data" with integrated data management, and integration of core variables from in-situ networks. The ABoVE Science Cloud is a collaboration that is accelerating the pace of new Arctic science for researchers participating in the field campaign. Specific examples of the utilization of the ABoVE Science Cloud by several funded projects will be presented.

A distributed cloud-based cyberinfrastructure framework for integrated bridge monitoring

NASA Astrophysics Data System (ADS)

Jeong, Seongwoon; Hou, Rui; Lynch, Jerome P.; Sohn, Hoon; Law, Kincho H.

2017-04-01

This paper describes a cloud-based cyberinfrastructure framework for the management of the diverse data involved in bridge monitoring. Bridge monitoring involves various hardware systems, software tools and laborious activities that include, for examples, a structural health monitoring (SHM), sensor network, engineering analysis programs and visual inspection. Very often, these monitoring systems, tools and activities are not coordinated, and the collected information are not shared. A well-designed integrated data management framework can support the effective use of the data and, thereby, enhance bridge management and maintenance operations. The cloud-based cyberinfrastructure framework presented herein is designed to manage not only sensor measurement data acquired from the SHM system, but also other relevant information, such as bridge engineering model and traffic videos, in an integrated manner. For the scalability and flexibility, cloud computing services and distributed database systems are employed. The information stored can be accessed through standard web interfaces. For demonstration, the cyberinfrastructure system is implemented for the monitoring of the bridges located along the I-275 Corridor in the state of Michigan.

A Comprehensive Toolset for General-Purpose Private Computing and Outsourcing

DTIC Science & Technology

2016-12-08

project and scientific advances made towards each of the research thrusts throughout the project duration. 1 Project Objectives Cloud computing enables...possibilities that the cloud enables is computation outsourcing, when the client can utilize any necessary computing resources for its computational task...Security considerations, however, stand on the way of harnessing the full benefits of cloud computing to the fullest extent and prevent clients from

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

An Offload NIC for NASA, NLR, and Grid Computing

NASA Technical Reports Server (NTRS)

Awrach, James

2013-01-01

This work addresses distributed data management and access dynamically configurable high-speed access to data distributed and shared over wide-area high-speed network environments. An offload engine NIC (network interface card) is proposed that scales at nX10-Gbps increments through 100-Gbps full duplex. The Globus de facto standard was used in projects requiring secure, robust, high-speed bulk data transport. Novel extension mechanisms were derived that will combine these technologies for use by GridFTP, bandwidth management resources, and host CPU (central processing unit) acceleration. The result will be wire-rate encrypted Globus grid data transactions through offload for splintering, encryption, and compression. As the need for greater network bandwidth increases, there is an inherent need for faster CPUs. The best way to accelerate CPUs is through a network acceleration engine. Grid computing data transfers for the Globus tool set did not have wire-rate encryption or compression. Existing technology cannot keep pace with the greater bandwidths of backplane and network connections. Present offload engines with ports to Ethernet are 32 to 40 Gbps f-d at best. The best of ultra-high-speed offload engines use expensive ASICs (application specific integrated circuits) or NPUs (network processing units). The present state of the art also includes bonding and the use of multiple NICs that are also in the planning stages for future portability to ASICs and software to accommodate data rates at 100 Gbps. The remaining industry solutions are for carrier-grade equipment manufacturers, with costly line cards having multiples of 10-Gbps ports, or 100-Gbps ports such as CFP modules that interface to costly ASICs and related circuitry. All of the existing solutions vary in configuration based on requirements of the host, motherboard, or carriergrade equipment. The purpose of the innovation is to eliminate data bottlenecks within cluster, grid, and cloud computing systems, and to add several more capabilities while reducing space consumption and cost. Provisions were designed for interoperability with systems used in the NASA HEC (High-End Computing) program. The new acceleration engine consists of state-ofthe- art FPGA (field-programmable gate array) core IP, C, and Verilog code; novel communication protocol; and extensions to the Globus structure. The engine provides the functions of network acceleration, encryption, compression, packet-ordering, and security added to Globus grid or for cloud data transfer. This system is scalable in nX10-Gbps increments through 100-Gbps f-d. It can be interfaced to industry-standard system-side or network-side devices or core IP in increments of 10 GigE, scaling to provide IEEE 40/100 GigE compliance.

CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing.

PubMed

Angiuoli, Samuel V; Matalka, Malcolm; Gussman, Aaron; Galens, Kevin; Vangala, Mahesh; Riley, David R; Arze, Cesar; White, James R; White, Owen; Fricke, W Florian

2011-08-30

Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.

Low latency network and distributed storage for next generation HPC systems: the ExaNeSt project

NASA Astrophysics Data System (ADS)

Ammendola, R.; Biagioni, A.; Cretaro, P.; Frezza, O.; Lo Cicero, F.; Lonardo, A.; Martinelli, M.; Paolucci, P. S.; Pastorelli, E.; Pisani, F.; Simula, F.; Vicini, P.; Navaridas, J.; Chaix, F.; Chrysos, N.; Katevenis, M.; Papaeustathiou, V.

2017-10-01

With processor architecture evolution, the HPC market has undergone a paradigm shift. The adoption of low-cost, Linux-based clusters extended the reach of HPC from its roots in modelling and simulation of complex physical systems to a broader range of industries, from biotechnology, cloud computing, computer analytics and big data challenges to manufacturing sectors. In this perspective, the near future HPC systems can be envisioned as composed of millions of low-power computing cores, densely packed — meaning cooling by appropriate technology — with a tightly interconnected, low latency and high performance network and equipped with a distributed storage architecture. Each of these features — dense packing, distributed storage and high performance interconnect — represents a challenge, made all the harder by the need to solve them at the same time. These challenges lie as stumbling blocks along the road towards Exascale-class systems; the ExaNeSt project acknowledges them and tasks itself with investigating ways around them.

Cloud Computing

DTIC Science & Technology

2010-04-01

delivery models: •  Software  as a  Service  ( SaaS ): The consumer uses an application, but does not control the operating system, hardware or network...suggestions for reducing this burden, to Washington Headquarters Services , Directorate for Information Operations and Reports, 1215 Jefferson Davis...AVAILABILITY STATEMENT Approved for public release; distribution unlimited 13. SUPPLEMENTARY NOTES Presented at the 22nd Systems and Software

NASA Briefing for Unidata

NASA Technical Reports Server (NTRS)

Lynnes, Christopher

2016-01-01

The NASA representative to the Unidata Strategic Committee presented a semiannual update on NASAs work with and use of Unidata technologies. The talk covered the program of cloud computing prototypes being undertaken for the Earth Observing System Data and Information System (EOSDIS). Also discussed were dataset interoperability recommendations ratified via the EOSDIS Standards Office and the HDF Product Designer tool with respect to its possible applicability to data in network Common Data Form (NetCDF) version 4.

The research and application of green computer room environmental monitoring system based on internet of things technology

NASA Astrophysics Data System (ADS)

Wei, Wang; Chongchao, Pan; Yikai, Liang; Gang, Li

2017-11-01

With the rapid development of information technology, the scale of data center increases quickly, and the energy consumption of computer room also increases rapidly, among which, energy consumption of air conditioning cooling makes up a large proportion. How to apply new technology to reduce the energy consumption of the computer room becomes an important topic of energy saving in the current research. This paper study internet of things technology, and design a kind of green computer room environmental monitoring system. In the system, we can get the real-time environment data from the application of wireless sensor network technology, which will be showed in a creative way of three-dimensional effect. In the environment monitor, we can get the computer room assets view, temperature cloud view, humidity cloud view, microenvironment view and so on. Thus according to the condition of the microenvironment, we can adjust the air volume, temperature and humidity parameters of the air conditioning for the individual equipment cabinet to realize the precise air conditioning refrigeration. And this can reduce the energy consumption of air conditioning, as a result, the overall energy consumption of the green computer room will reduce greatly. At the same time, we apply this project in the computer center of Weihai, and after a year of test and running, we find that it took a good energy saving effect, which fully verified the effectiveness of this project on the energy conservation of the computer room.

A high performance scientific cloud computing environment for materials simulations

NASA Astrophysics Data System (ADS)

Jorissen, K.; Vila, F. D.; Rehr, J. J.

2012-09-01

We describe the development of a scientific cloud computing (SCC) platform that offers high performance computation capability. The platform consists of a scientific virtual machine prototype containing a UNIX operating system and several materials science codes, together with essential interface tools (an SCC toolset) that offers functionality comparable to local compute clusters. In particular, our SCC toolset provides automatic creation of virtual clusters for parallel computing, including tools for execution and monitoring performance, as well as efficient I/O utilities that enable seamless connections to and from the cloud. Our SCC platform is optimized for the Amazon Elastic Compute Cloud (EC2). We present benchmarks for prototypical scientific applications and demonstrate performance comparable to local compute clusters. To facilitate code execution and provide user-friendly access, we have also integrated cloud computing capability in a JAVA-based GUI. Our SCC platform may be an alternative to traditional HPC resources for materials science or quantum chemistry applications.

A network approach to the geometric structure of shallow cloud fields

NASA Astrophysics Data System (ADS)

Glassmeier, F.; Feingold, G.

2017-12-01

The representation of shallow clouds and their radiative impact is one of the largest challenges for global climate models. While the bulk properties of cloud fields, including effects of organization, are a very active area of research, the potential of the geometric arrangement of cloud fields for the development of new parameterizations has hardly been explored. Self-organized patterns are particularly evident in the cellular structure of Stratocumulus (Sc) clouds so readily visible in satellite imagery. Inspired by similar patterns in biology and physics, we approach pattern formation in Sc fields from the perspective of natural cellular networks. Our network analysis is based on large-eddy simulations of open- and closed-cell Sc cases. We find the network structure to be neither random nor characteristic to natural convection. It is independent of macroscopic cloud fields properties like the Sc regime (open vs closed) and its typical length scale (boundary layer height). The latter is a consequence of entropy maximization (Lewis's Law with parameter 0.16). The cellular pattern is on average hexagonal, where non-6 sided cells occur according to a neighbor-number distribution variance of about 2. Reflecting the continuously renewing dynamics of Sc fields, large (many-sided) cells tend to neighbor small (few-sided) cells (Aboav-Weaire Law with parameter 0.9). These macroscopic network properties emerge independent of the Sc regime because the different processes governing the evolution of closed as compared to open cells correspond to topologically equivalent network dynamics. By developing a heuristic model, we show that open and closed cell dynamics can both be mimicked by versions of cell division and cell disappearance and are biased towards the expansion of smaller cells. This model offers for the first time a fundamental and universal explanation for the geometric pattern of Sc clouds. It may contribute to the development of advanced Sc parameterizations. As an outlook, we discuss how a similar network approach can be applied to describe and quantify the geometric structure of shallow cumulus cloud fields.

Application verification research of cloud computing technology in the field of real time aerospace experiment

NASA Astrophysics Data System (ADS)

Wan, Junwei; Chen, Hongyan; Zhao, Jing

2017-08-01

According to the requirements of real-time, reliability and safety for aerospace experiment, the single center cloud computing technology application verification platform is constructed. At the IAAS level, the feasibility of the cloud computing technology be applied to the field of aerospace experiment is tested and verified. Based on the analysis of the test results, a preliminary conclusion is obtained: Cloud computing platform can be applied to the aerospace experiment computing intensive business. For I/O intensive business, it is recommended to use the traditional physical machine.