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Sample records for abstract cloud computing

  1. Cloud Computing

    SciTech Connect

    Pete Beckman and Ian Foster

    2009-12-04

    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.

  2. Cloud Computing

    DTIC Science & Technology

    2009-11-12

    Eucalyptus Systems • Provides an open-source application that can be used to implement a cloud computing environment on a datacenter • Trying to establish an...Summary Cloud Computing is in essence an economic model • It is a different way to acquire and manage IT resources There are multiple cloud providers...edgeplatform.html • Amazon Elastic Compute Cloud (EC2): http://aws.amazon.com/ec2/ • Amazon Simple Storage Solution (S3): http://aws.amazon.com/s3/ • Eucalyptus

  3. Computers in Abstract Algebra

    ERIC Educational Resources Information Center

    Nwabueze, Kenneth K.

    2004-01-01

    The current emphasis on flexible modes of mathematics delivery involving new information and communication technology (ICT) at the university level is perhaps a reaction to the recent change in the objectives of education. Abstract algebra seems to be one area of mathematics virtually crying out for computer instructional support because of the…

  4. 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.

  5. 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.

  6. Cloud Computing Explained

    ERIC Educational Resources Information Center

    Metz, Rosalyn

    2010-01-01

    While many talk about the cloud, few actually understand it. Three organizations' definitions come to the forefront when defining the cloud: Gartner, Forrester, and the National Institutes of Standards and Technology (NIST). Although both Gartner and Forrester provide definitions of cloud computing, the NIST definition is concise and uses…

  7. Computer animation of clouds

    SciTech Connect

    Max, N.

    1994-01-28

    Computer animation of outdoor scenes is enhanced by realistic clouds. I will discuss several different modeling and rendering schemes for clouds, and show how they evolved in my animation work. These include transparency-textured clouds on a 2-D plane, smooth shaded or textured 3-D clouds surfaces, and 3-D volume rendering. For the volume rendering, I will present various illumination schemes, including the density emitter, single scattering, and multiple scattering models.

  8. Cloud computing security.

    SciTech Connect

    Shin, Dongwan; Claycomb, William R.; Urias, Vincent E.

    2010-10-01

    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 both academia and government, including configuration options, hardware issues, challenges, and solutions.

  9. 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.

  10. 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.

  11. Computing in the Clouds

    ERIC Educational Resources Information Center

    Johnson, Doug

    2010-01-01

    Web-based applications offer teachers, students, and school districts a convenient way to accomplish a wide range of tasks, from accounting to word processing, for free. Cloud computing has the potential to offer staff and students better services at a lower cost than the technology deployment models they're using now. Saving money and improving…

  12. 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…

  13. 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.

  14. Cloud Computing Strategy

    DTIC Science & Technology

    2012-07-01

    the use of  available cloud and  shared   services .”     Federal Risk and Authorization Management Program (FedRAMP):  FedRAMP (See  Appendix B...governance processes will promote and enable the use of standardized SLAs  that facilitate the adoption of  shared   services  and virtual computing...Services,  shared   services  (cloud services offered by other  Components, the Federal Government, mission partners) and commercial vendors that meet

  15. Cloud Computing and Its Applications in GIS

    NASA Astrophysics Data System (ADS)

    Kang, Cao

    2011-12-01

    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.)

  16. The Ethics of Cloud Computing.

    PubMed

    de Bruin, Boudewijn; Floridi, Luciano

    2017-02-01

    Cloud computing is rapidly gaining traction in business. It offers businesses online services on demand (such as Gmail, iCloud and Salesforce) and allows them to cut costs on hardware and IT support. This is the first paper in business ethics dealing with this new technology. It analyzes the informational duties of hosting companies that own and operate cloud computing datacentres (e.g., Amazon). It considers the cloud services providers leasing 'space in the cloud' from hosting companies (e.g., Dropbox, Salesforce). And it examines the business and private 'clouders' using these services. The first part of the paper argues that hosting companies, services providers and clouders have mutual informational (epistemic) obligations to provide and seek information about relevant issues such as consumer privacy, reliability of services, data mining and data ownership. The concept of interlucency is developed as an epistemic virtue governing ethically effective communication. The second part considers potential forms of government restrictions on or proscriptions against the development and use of cloud computing technology. Referring to the concept of technology neutrality, it argues that interference with hosting companies and cloud services providers is hardly ever necessary or justified. It is argued, too, however, that businesses using cloud services (e.g., banks, law firms, hospitals etc. storing client data in the cloud) will have to follow rather more stringent regulations.

  17. Trusted computing strengthens cloud authentication.

    PubMed

    Ghazizadeh, Eghbal; Zamani, Mazdak; Ab Manan, Jamalul-lail; Alizadeh, Mojtaba

    2014-01-01

    Cloud computing is a new generation of technology which is designed to provide the commercial necessities, solve the IT management issues, and run the appropriate applications. Another entry on the list of cloud functions which has been handled internally is Identity Access Management (IAM). Companies encounter IAM as security challenges while adopting more technologies became apparent. Trust Multi-tenancy and trusted computing based on a Trusted Platform Module (TPM) are great technologies for solving the trust and security concerns in the cloud identity environment. Single sign-on (SSO) and OpenID have been released to solve security and privacy problems for cloud identity. This paper proposes the use of trusted computing, Federated Identity Management, and OpenID Web SSO to solve identity theft in the cloud. Besides, this proposed model has been simulated in .Net environment. Security analyzing, simulation, and BLP confidential model are three ways to evaluate and analyze our proposed model.

  18. Trusted Computing Strengthens Cloud Authentication

    PubMed Central

    2014-01-01

    Cloud computing is a new generation of technology which is designed to provide the commercial necessities, solve the IT management issues, and run the appropriate applications. Another entry on the list of cloud functions which has been handled internally is Identity Access Management (IAM). Companies encounter IAM as security challenges while adopting more technologies became apparent. Trust Multi-tenancy and trusted computing based on a Trusted Platform Module (TPM) are great technologies for solving the trust and security concerns in the cloud identity environment. Single sign-on (SSO) and OpenID have been released to solve security and privacy problems for cloud identity. This paper proposes the use of trusted computing, Federated Identity Management, and OpenID Web SSO to solve identity theft in the cloud. Besides, this proposed model has been simulated in .Net environment. Security analyzing, simulation, and BLP confidential model are three ways to evaluate and analyze our proposed model. PMID:24701149

  19. Architectural Implications of Cloud Computing

    DTIC Science & Technology

    2011-10-24

    Mellon University Final Thoughts 1 Cloud Computing is in essence an economic model • It is a different way to acquire and manage IT resources...Cloud (EC2): http://aws.amazon.com/ec2/ • Amazon Simple Storage Solution (S3): http://aws.amazon.com/s3/ • Eucalyptus Systems: http

  20. Cloud computing in medical imaging.

    PubMed

    Kagadis, George C; Kloukinas, Christos; Moore, Kevin; Philbin, Jim; Papadimitroulas, Panagiotis; Alexakos, Christos; Nagy, Paul G; Visvikis, Dimitris; Hendee, William R

    2013-07-01

    Over the past century technology has played a decisive role in defining, driving, and reinventing procedures, devices, and pharmaceuticals in healthcare. Cloud computing has been introduced only recently but is already one of the major topics of discussion in research and clinical settings. The provision of extensive, easily accessible, and reconfigurable resources such as virtual systems, platforms, and applications with low service cost has caught the attention of many researchers and clinicians. Healthcare researchers are moving their efforts to the cloud, because they need adequate resources to process, store, exchange, and use large quantities of medical data. This Vision 20/20 paper addresses major questions related to the applicability of advanced cloud computing in medical imaging. The paper also considers security and ethical issues that accompany cloud computing.

  1. Adopting Cloud Computing in the Pakistan Navy

    DTIC Science & Technology

    2015-06-01

    ABSTRACT (maximum 200 words) Pakistan’s proximity to the Strait of Hormuz, through which millions of barrels of oil is shipped per day, makes it a...As a flag bearer of protecting the country’s sea lines of communication and safeguarding its maritime territories, the Pakistan Navy is in the...information from anywhere around the globe. This thesis explores the peculiarities of cloud computing and its potential utility to the Pakistan Navy. After

  2. 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

  3. 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…

  4. 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.…

  5. 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.

  6. Abstract quantum computing machines and quantum computational logics

    NASA Astrophysics Data System (ADS)

    Chiara, Maria Luisa Dalla; Giuntini, Roberto; Sergioli, Giuseppe; Leporini, Roberto

    2016-06-01

    Classical and quantum parallelism are deeply different, although it is sometimes claimed that quantum Turing machines are nothing but special examples of classical probabilistic machines. We introduce the concepts of deterministic state machine, classical probabilistic state machine and quantum state machine. On this basis, we discuss the question: To what extent can quantum state machines be simulated by classical probabilistic state machines? Each state machine is devoted to a single task determined by its program. Real computers, however, behave differently, being able to solve different kinds of problems. This capacity can be modeled, in the quantum case, by the mathematical notion of abstract quantum computing machine, whose different programs determine different quantum state machines. The computations of abstract quantum computing machines can be linguistically described by the formulas of a particular form of quantum logic, termed quantum computational logic.

  7. 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…

  8. Research computing in a distributed cloud environment

    NASA Astrophysics Data System (ADS)

    Fransham, K.; Agarwal, A.; Armstrong, P.; Bishop, A.; Charbonneau, A.; Desmarais, R.; Hill, N.; Gable, I.; Gaudet, S.; Goliath, S.; Impey, R.; Leavett-Brown, C.; Ouellete, J.; Paterson, M.; Pritchet, C.; Penfold-Brown, D.; Podaima, W.; Schade, D.; Sobie, R. J.

    2010-11-01

    The recent increase in availability of Infrastructure-as-a-Service (IaaS) computing clouds provides a new way for researchers to run complex scientific applications. However, using cloud resources for a large number of research jobs requires significant effort and expertise. Furthermore, running jobs on many different clouds presents even more difficulty. In order to make it easy for researchers to deploy scientific applications across many cloud resources, we have developed a virtual machine resource manager (Cloud Scheduler) for distributed compute clouds. In response to a user's job submission to a batch system, the Cloud Scheduler manages the distribution and deployment of user-customized virtual machines across multiple clouds. We describe the motivation for and implementation of a distributed cloud using the Cloud Scheduler that is spread across both commercial and dedicated private sites, and present some early results of scientific data analysis using the system.

  9. The Advance of Computing from the Ground to the Cloud

    ERIC Educational Resources Information Center

    Breeding, Marshall

    2009-01-01

    A trend toward the abstraction of computing platforms that has been developing in the broader IT arena over the last few years is just beginning to make inroads into the library technology scene. Cloud computing offers for libraries many interesting possibilities that may help reduce technology costs and increase capacity, reliability, and…

  10. 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.

  11. 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.

  12. Airborne Cloud Computing Environment (ACCE)

    NASA Technical Reports Server (NTRS)

    Hardman, Sean; Freeborn, Dana; Crichton, Dan; Law, Emily; Kay-Im, Liz

    2011-01-01

    Airborne Cloud Computing Environment (ACCE) is JPL's internal investment to improve the return on airborne missions. Improve development performance of the data system. Improve return on the captured science data. The investment is to develop a common science data system capability for airborne instruments that encompasses the end-to-end lifecycle covering planning, provisioning of data system capabilities, and support for scientific analysis in order to improve the quality, cost effectiveness, and capabilities to enable new scientific discovery and research in earth observation.

  13. 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.

  14. 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.

  15. 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.

  16. The Evolution of Cloud Computing in ATLAS

    NASA Astrophysics Data System (ADS)

    Taylor, Ryan P.; Berghaus, Frank; Brasolin, Franco; Domingues Cordeiro, Cristovao Jose; Desmarais, Ron; Field, Laurence; Gable, Ian; Giordano, Domenico; Di Girolamo, Alessandro; Hover, John; LeBlanc, Matthew; Love, Peter; Paterson, Michael; Sobie, Randall; Zaytsev, Alexandr

    2015-12-01

    The ATLAS experiment at the LHC has successfully incorporated cloud computing technology and cloud resources into its primarily grid-based model of distributed computing. Cloud R&D activities continue to mature and transition into stable production systems, while ongoing evolutionary changes are still needed to adapt and refine the approaches used, in response to changes in prevailing cloud technology. In addition, completely new developments are needed to handle emerging requirements. This paper describes the overall evolution of cloud computing in ATLAS. The current status of the virtual machine (VM) management systems used for harnessing Infrastructure as a Service resources are discussed. Monitoring and accounting systems tailored for clouds are needed to complete the integration of cloud resources within ATLAS' distributed computing framework. We are developing and deploying new solutions to address the challenge of operation in a geographically distributed multi-cloud scenario, including a system for managing VM images across multiple clouds, a system for dynamic location-based discovery of caching proxy servers, and the usage of a data federation to unify the worldwide grid of storage elements into a single namespace and access point. The usage of the experiment's high level trigger farm for Monte Carlo production, in a specialized cloud environment, is presented. Finally, we evaluate and compare the performance of commercial clouds using several benchmarks.

  17. 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.

  18. Selected Translated Abstracts of Russian-Language Climate-Change Publications, II. Clouds

    SciTech Connect

    Ravina, C.B.

    1994-01-01

    This report presents abstracts (translated into English) of important Russian-language literature concerning clouds as they relate to climate change. In addition to the bibliographic citations and abstracts translated into English, this report presents the original citations and abstracts in Russian. Author and title indexes are included, to assist the reader in locating abstracts of particular interest.

  19. Selected translated abstracts of Russian-language climate-change publications: II, Clouds. Issue 159

    SciTech Connect

    Burtis, M.D.

    1994-01-01

    This report presents abstracts (translated into English) of important Russian-language literature concerning clouds as they relate to climate change. In addition to the bibliographic citations and abstracts translated into English, this report presents the original citations and abstracts in Russian. Author and title indexes are included to assist the reader in locating abstracts of particular interest.

  20. Cloud Computing Technologies and Applications

    NASA Astrophysics Data System (ADS)

    Zhu, Jinzy

    In a nutshell, the existing Internet provides to us content in the forms of videos, emails and information served up in web pages. With Cloud Computing, the next generation of Internet will allow us to "buy" IT services from a web portal, drastic expanding the types of merchandise available beyond those on e-commerce sites such as eBay and Taobao. We would be able to rent from a virtual storefront the basic necessities to build a virtual data center: such as CPU, memory, storage, and add on top of that the middleware necessary: web application servers, databases, enterprise server bus, etc. as the platform(s) to support the applications we would like to either rent from an Independent Software Vendor (ISV) or develop ourselves. Together this is what we call as "IT as a Service," or ITaaS, bundled to us the end users as a virtual data center.

  1. 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.

  2. 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

  3. Study on global cloud computing research trend

    NASA Astrophysics Data System (ADS)

    Ma, Feicheng; Zhan, Nan

    2014-01-01

    Since "cloud computing" was put forward by Google , it quickly became the most popular concept in IT industry and widely permeated into various areas promoted by IBM, Microsoft and other IT industry giants. In this paper the methods of bibliometric analysis were used to investigate the global cloud computing research trend based on Web of Science (WoS) database and the Engineering Index (EI) Compendex database. In this study, the publication, countries, institutes, keywords of the papers was deeply studied in methods of quantitative analysis, figures and tables are used to describe the production and the development trends of cloud computing.

  4. 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.

  5. Non-Determinism: An Abstract Concept in Computer Science Studies

    ERIC Educational Resources Information Center

    Armoni, Michal; Gal-Ezer, Judith

    2007-01-01

    Non-determinism is one of the most important, yet abstract, recurring concepts of Computer Science. It plays an important role in Computer Science areas such as formal language theory, computability theory, distributed computing, and operating systems. We conducted a series of studies on the perception of non-determinism. In the current research,…

  6. Notification: Audit of EPA's Cloud Computer Initiative

    EPA Pesticide Factsheets

    Project #OA-FY13-0095, December 17, 2012. The U.S. Environmental Protection Agency (EPA) Office of Inspector General plans to begin preliminary research on the audit of EPA’s cloud computer initiative.

  7. 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).

  8. Integrating Network Management for Cloud Computing Services

    DTIC Science & Technology

    2015-06-01

    Integrating Network Management For Cloud Computing Services Peng Sun A Dissertation Presented to the Faculty of Princeton University in Candidacy for...2015 2. REPORT TYPE 3. DATES COVERED 00-00-2015 to 00-00-2015 4. TITLE AND SUBTITLE Integrating Network Management for Cloud Computing Services... integrate the management of various network components. With commercial deployment, our operational experiences feed back into revision of the

  9. When STAR meets the Clouds - Virtualization & Cloud Computing Experiences

    NASA Astrophysics Data System (ADS)

    Lauret, J.; Walker, M.; Goasguen, S.; Stout, L.; Fenn, M.; Balewski, J.; Hajdu, L.; Keahey, K.

    2011-12-01

    In recent years, Cloud computing has become a very attractive paradigm and popular model for accessing distributed resources. The Cloud has emerged as the next big trend. The burst of platform and projects providing Cloud resources and interfaces at the very same time that Grid projects are entering a production phase in their life cycle has however raised the question of the best approach to handling distributed resources. Especially, are Cloud resources scaling at the levels shown by Grids? Are they performing at the same level? What is their overhead on the IT teams and infrastructure? Rather than seeing the two as orthogonal, the STAR experiment has viewed them as complimentary and has studied merging the best of the two worlds with Grid middleware providing the aggregation of both Cloud and traditional resources. Since its first use of Cloud resources on Amazon EC2 in 2008/2009 using a Nimbus/EC2 interface, the STAR software team has tested and experimented with many novel approaches: from a traditional, native EC2 approach to the Virtual Organization Cluster (VOC) at Clemson University and Condor/VM on the GLOW resources at the University of Wisconsin. The STAR team is also planning to run as part of the DOE/Magellan project. In this paper, we will present an overview of our findings from using truly opportunistic resources and scaling-out two orders of magnitude in both tests and practical usage.

  10. The Magellan Final Report on Cloud Computing

    SciTech Connect

    ,; Coghlan, Susan; Yelick, Katherine

    2011-12-21

    The goal of Magellan, a project funded through the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR), was to investigate the potential role of cloud computing in addressing the computing needs for the DOE Office of Science (SC), particularly related to serving the needs of mid- range computing and future data-intensive computing workloads. A set of research questions was formed to probe various aspects of cloud computing from performance, usability, and cost. To address these questions, a distributed testbed infrastructure was deployed at the Argonne Leadership Computing Facility (ALCF) and the National Energy Research Scientific Computing Center (NERSC). The testbed was designed to be flexible and capable enough to explore a variety of computing models and hardware design points in order to understand the impact for various scientific applications. During the project, the testbed also served as a valuable resource to application scientists. Applications from a diverse set of projects such as MG-RAST (a metagenomics analysis server), the Joint Genome Institute, the STAR experiment at the Relativistic Heavy Ion Collider, and the Laser Interferometer Gravitational Wave Observatory (LIGO), were used by the Magellan project for benchmarking within the cloud, but the project teams were also able to accomplish important production science utilizing the Magellan cloud resources.

  11. How language enables abstraction: a study in computational cultural psychology.

    PubMed

    Neuman, Yair; Turney, Peter; Cohen, Yohai

    2012-06-01

    The idea that language mediates our thoughts and enables abstract cognition has been a key idea in socio-cultural psychology. However, it is not clear what mechanisms support this process of abstraction. Peirce argued that one mechanism by which language enables abstract thought is hypostatic abstraction, the process through which a predicate (e.g., dark) turns into an object (e.g., darkness). By using novel computational tools we tested Peirce's idea. Analysis of the data provides empirical support for Peirce's mechanism and evidence of the way the use of signs enables abstraction. These conclusions are supported by the in-depth analysis of two case studies concerning the abstraction of sweet and dark. The paper concludes by discussing the findings from a broad and integrative theoretical perspective and by pointing to computational cultural psychology as a promising perspective for addressing long-lasting questions of the field.

  12. Searching for SNPs with cloud computing

    PubMed Central

    2009-01-01

    As DNA sequencing outpaces improvements in computer speed, there is a critical need to accelerate tasks like alignment and SNP calling. Crossbow is a cloud-computing software tool that combines the aligner Bowtie and the SNP caller SOAPsnp. Executing in parallel using Hadoop, Crossbow analyzes data comprising 38-fold coverage of the human genome in three hours using a 320-CPU cluster rented from a cloud computing service for about $85. Crossbow is available from http://bowtie-bio.sourceforge.net/crossbow/. PMID:19930550

  13. Argonne's Magellan Cloud Computing Research Project

    ScienceCinema

    Beckman, Pete

    2016-07-12

    Pete Beckman, head of Argonne's Leadership Computing Facility (ALCF), discusses the Department of Energy's new $32-million Magellan project, which designed to test how cloud computing can be used for scientific research. More information: http://www.anl.gov/Media_Center/News/2009/news091014a.html

  14. Argonne's Magellan Cloud Computing Research Project

    SciTech Connect

    Beckman, Pete

    2009-01-01

    Pete Beckman, head of Argonne's Leadership Computing Facility (ALCF), discusses the Department of Energy's new $32-million Magellan project, which designed to test how cloud computing can be used for scientific research. More information: http://www.anl.gov/Media_Center/News/2009/news091014a.html

  15. Abstraction/Representation Theory for heterotic physical computing.

    PubMed

    Horsman, D C

    2015-07-28

    We give a rigorous framework for the interaction of physical computing devices with abstract computation. Device and program are mediated by the non-logical representation relation; we give the conditions under which representation and device theory give rise to commuting diagrams between logical and physical domains, and the conditions for computation to occur. We give the interface of this new framework with currently existing formal methods, showing in particular its close relationship to refinement theory, and the implications for questions of meaning and reference in theoretical computer science. The case of hybrid computing is considered in detail, addressing in particular the example of an Internet-mediated social machine, and the abstraction/representation framework used to provide a formal distinction between heterotic and hybrid computing. This forms the basis for future use of the framework in formal treatments of non-standard physical computers.

  16. 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.

  17. Spontaneous Ad Hoc Mobile Cloud Computing Network

    PubMed Central

    Lacuesta, Raquel; Sendra, Sandra; Peñalver, Lourdes

    2014-01-01

    Cloud computing helps users and companies to share computing resources instead of having local servers or personal devices to handle the applications. Smart devices are becoming one of the main information processing devices. Their computing features are reaching levels that let them create a mobile cloud computing network. But sometimes they are not able to create it and collaborate actively in the cloud because it is difficult for them to build easily a spontaneous network and configure its parameters. For this reason, in this paper, we are going to present the design and deployment of a spontaneous ad hoc mobile cloud computing network. In order to perform it, we have developed a trusted algorithm that is able to manage the activity of the nodes when they join and leave the network. The paper shows the network procedures and classes that have been designed. Our simulation results using Castalia show that our proposal presents a good efficiency and network performance even by using high number of nodes. PMID:25202715

  18. Spontaneous ad hoc mobile cloud computing network.

    PubMed

    Lacuesta, Raquel; Lloret, Jaime; Sendra, Sandra; Peñalver, Lourdes

    2014-01-01

    Cloud computing helps users and companies to share computing resources instead of having local servers or personal devices to handle the applications. Smart devices are becoming one of the main information processing devices. Their computing features are reaching levels that let them create a mobile cloud computing network. But sometimes they are not able to create it and collaborate actively in the cloud because it is difficult for them to build easily a spontaneous network and configure its parameters. For this reason, in this paper, we are going to present the design and deployment of a spontaneous ad hoc mobile cloud computing network. In order to perform it, we have developed a trusted algorithm that is able to manage the activity of the nodes when they join and leave the network. The paper shows the network procedures and classes that have been designed. Our simulation results using Castalia show that our proposal presents a good efficiency and network performance even by using high number of nodes.

  19. 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.

  20. 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.

  1. Cloud Computing Based E-Learning System

    ERIC Educational Resources Information Center

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

    2010-01-01

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

  2. Assured Cloud Computing: The Odessa Monitoring System

    DTIC Science & Technology

    2011-07-11

    prototype and evaluate architectures – Design and optimize the performance of secure, timely, fault -tolerant, mission-oriented cloud computing...and Availability • Search & Analysis • Satellite Coverage UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN | ENGINEERING AT ILLINOIS INFORMATION TRUST...multiple organizations in real-time UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN | ENGINEERING AT ILLINOIS INFORMATION TRUST INSTITUTE Risk Analysis

  3. Web Solutions Inspire Cloud Computing Software

    NASA Technical Reports Server (NTRS)

    2013-01-01

    An effort at Ames Research Center to standardize NASA websites unexpectedly led to a breakthrough in open source cloud computing technology. With the help of Rackspace Inc. of San Antonio, Texas, the resulting product, OpenStack, has spurred the growth of an entire industry that is already employing hundreds of people and generating hundreds of millions in revenue.

  4. Green Cloud Computing: An Experimental Validation

    NASA Astrophysics Data System (ADS)

    Castellar Monteiro, Rogerio; Dantas, M. A. R.; Rodriguez, Martius Vicente Rodriguez y.

    2014-10-01

    Cloud configurations can be computational environment with interesting cost efficiency for several organizations sizes. However, the indiscriminate action of buying servers and network devices may not represent a correspondent performance number. In the academic and commercial literature, some researches highlight that these environments are idle for long periods. Therefore, energy management is an essential approach in any organization, because energy bills can causes remarkable negative impacts to these organizations in term of costs. In this paper, we present a research work that is characterized by an analysis of energy consumption in a private cloud computing environment, considering both computational resources and network devices. This study was motivated by a real case of a large organization. Therefore, the first part of the study we considered empirical experiments. In a second moment we used the GreenCloud simulator which was utilized to foresee some different configurations. The research reached a successful and differentiated goal in presenting key issues from computational resources and network, related to the energy consumption for real private cloud.

  5. High Assurance Challenges for Cloud Based Computing

    DTIC Science & Technology

    2011-10-01

    transactions to exploits for eaves dropping, ex-filtration, session high-jacking, data corruption, man-in-the-middle, masquerade, blocking or...technology correspondent, guardian.co.uk, Cloud computing is a trap, warns GNU founder Richard Stallman, 29 September 2008, http

  6. Exploring Cloud Computing for Distance Learning

    ERIC Educational Resources Information Center

    He, Wu; Cernusca, Dan; Abdous, M'hammed

    2011-01-01

    The use of distance courses in learning is growing exponentially. To better support faculty and students for teaching and learning, distance learning programs need to constantly innovate and optimize their IT infrastructures. The new IT paradigm called "cloud computing" has the potential to transform the way that IT resources are utilized and…

  7. 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.

  8. Cloud Computing for Mission Design and Operations

    NASA Technical Reports Server (NTRS)

    Arrieta, Juan; Attiyah, Amy; Beswick, Robert; Gerasimantos, Dimitrios

    2012-01-01

    The space mission design and operations community already recognizes the value of cloud computing and virtualization. However, natural and valid concerns, like security, privacy, up-time, and vendor lock-in, have prevented a more widespread and expedited adoption into official workflows. In the interest of alleviating these concerns, we propose a series of guidelines for internally deploying a resource-oriented hub of data and algorithms. These guidelines provide a roadmap for implementing an architecture inspired in the cloud computing model: associative, elastic, semantical, interconnected, and adaptive. The architecture can be summarized as exposing data and algorithms as resource-oriented Web services, coordinated via messaging, and running on virtual machines; it is simple, and based on widely adopted standards, protocols, and tools. The architecture may help reduce common sources of complexity intrinsic to data-driven, collaborative interactions and, most importantly, it may provide the means for teams and agencies to evaluate the cloud computing model in their specific context, with minimal infrastructure changes, and before committing to a specific cloud services provider.

  9. 75 FR 64258 - Cloud Computing Forum & Workshop II

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-19

    ... National Institute of Standards and Technology Cloud Computing Forum & Workshop II AGENCY: National... 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 an updated status on...

  10. Cloud Computing in Higher Education Sector for Sustainable Development

    ERIC Educational Resources Information Center

    Duan, Yuchao

    2016-01-01

    Cloud computing is considered a new frontier in the field of computing, as this technology comprises three major entities namely: software, hardware and network. The collective nature of all these entities is known as the Cloud. This research aims to examine the impacts of various aspects namely: cloud computing, sustainability, performance…

  11. 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…

  12. 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…

  13. Abstracts

    ERIC Educational Resources Information Center

    American Biology Teacher, 1977

    1977-01-01

    Included are over 50 abstracts of papers being presented at the 1977 National Association of Biology Teachers Convention. Included in each abstract are the title, author, and summary of the paper. Topics include photographic techniques environmental studies, and biological instruction. (MA)

  14. 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.

  15. Computing through Scientific Abstractions in SysBioPS

    SciTech Connect

    Chin, George; Stephan, Eric G.; Gracio, Deborah K.

    2004-10-13

    Today, biologists and bioinformaticists have a tremendous amount of computational power at their disposal. With the availability of supercomputers, burgeoning scientific databases and digital libraries such as GenBank and PubMed, and pervasive computational environments such as the Grid, biologists have access to a wealth of computational capabilities and scientific data at hand. Yet, the rapid development of computational technologies has far exceeded the typical biologist’s ability to effectively apply the technology in their research. Computational sciences research and development efforts such as the Biology Workbench, BioSPICE (Biological Simulation Program for Intra-Cellular Evaluation), and BioCoRE (Biological Collaborative Research Environment) are important in connecting biologists and their scientific problems to computational infrastructures. On the Computational Cell Environment and Heuristic Entity-Relationship Building Environment projects at the Pacific Northwest National Laboratory, we are jointly developing a new breed of scientific problem solving environment called SysBioPSE that will allow biologists to access and apply computational resources in the scientific research context. In contrast to other computational science environments, SysBioPSE operates as an abstraction layer above a computational infrastructure. The goal of SysBioPSE is to allow biologists to apply computational resources in the context of the scientific problems they are addressing and the scientific perspectives from which they conduct their research. More specifically, SysBioPSE allows biologists to capture and represent scientific concepts and theories and experimental processes, and to link these views to scientific applications, data repositories, and computer systems.

  16. 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.

  17. Evolving the Land Information System into a Cloud Computing Service

    SciTech Connect

    Houser, Paul R.

    2015-02-17

    The Land Information System (LIS) was developed to use advanced flexible land surface modeling and data assimilation frameworks to integrate extremely large satellite- and ground-based observations with advanced land surface models to produce continuous high-resolution fields of land surface states and fluxes. The resulting fields are extremely useful for drought and flood assessment, agricultural planning, disaster management, weather and climate forecasting, water resources assessment, and the like. We envisioned transforming the LIS modeling system into a scientific cloud computing-aware web and data service that would allow clients to easily setup and configure for use in addressing large water management issues. The focus of this Phase 1 project was to determine the scientific, technical, commercial merit and feasibility of the proposed LIS-cloud innovations that are currently barriers to broad LIS applicability. We (a) quantified the barriers to broad LIS utility and commercialization (high performance computing, big data, user interface, and licensing issues); (b) designed the proposed LIS-cloud web service, model-data interface, database services, and user interfaces; (c) constructed a prototype LIS user interface including abstractions for simulation control, visualization, and data interaction, (d) used the prototype to conduct a market analysis and survey to determine potential market size and competition, (e) identified LIS software licensing and copyright limitations and developed solutions, and (f) developed a business plan for development and marketing of the LIS-cloud innovation. While some significant feasibility issues were found in the LIS licensing, overall a high degree of LIS-cloud technical feasibility was found.

  18. 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

  19. 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

  20. Performing quantum computing experiments in the cloud

    NASA Astrophysics Data System (ADS)

    Devitt, Simon J.

    2016-09-01

    Quantum computing technology has reached a second renaissance in the past five years. Increased interest from both the private and public sector combined with extraordinary theoretical and experimental progress has solidified this technology as a major advancement in the 21st century. As anticipated my many, some of the first realizations of quantum computing technology has occured over the cloud, with users logging onto dedicated hardware over the classical internet. Recently, IBM has released the Quantum Experience, which allows users to access a five-qubit quantum processor. In this paper we take advantage of this online availability of actual quantum hardware and present four quantum information experiments. We utilize the IBM chip to realize protocols in quantum error correction, quantum arithmetic, quantum graph theory, and fault-tolerant quantum computation by accessing the device remotely through the cloud. While the results are subject to significant noise, the correct results are returned from the chip. This demonstrates the power of experimental groups opening up their technology to a wider audience and will hopefully allow for the next stage of development in quantum information technology.

  1. Secure medical information sharing in cloud computing.

    PubMed

    Shao, Zhiyi; Yang, Bo; Zhang, Wenzheng; Zhao, Yi; Wu, Zhenqiang; Miao, Meixia

    2015-01-01

    Medical information sharing is one of the most attractive applications of cloud computing, where searchable encryption is a fascinating solution for securely and conveniently sharing medical data among different medical organizers. However, almost all previous works are designed in symmetric key encryption environment. The only works in public key encryption do not support keyword trapdoor security, have long ciphertext related to the number of receivers, do not support receiver revocation without re-encrypting, and do not preserve the membership of receivers. In this paper, we propose a searchable encryption supporting multiple receivers for medical information sharing based on bilinear maps in public key encryption environment. In the proposed protocol, data owner stores only one copy of his encrypted file and its corresponding encrypted keywords on cloud for multiple designated receivers. The keyword ciphertext is significantly shorter and its length is constant without relation to the number of designated receivers, i.e., for n receivers the ciphertext length is only twice the element length in the group. Only the owner knows that with whom his data is shared, and the access to his data is still under control after having been put on the cloud. We formally prove the security of keyword ciphertext based on the intractability of Bilinear Diffie-Hellman problem and the keyword trapdoor based on Decisional Diffie-Hellman problem.

  2. 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.

  3. Modelling, abstraction, and computation in systems biology: A view from computer science.

    PubMed

    Melham, Tom

    2013-04-01

    Systems biology is centrally engaged with computational modelling across multiple scales and at many levels of abstraction. Formal modelling, precise and formalised abstraction relationships, and computation also lie at the heart of computer science--and over the past decade a growing number of computer scientists have been bringing their discipline's core intellectual and computational tools to bear on biology in fascinating new ways. This paper explores some of the apparent points of contact between the two fields, in the context of a multi-disciplinary discussion on conceptual foundations of systems biology.

  4. 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…

  5. '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.

  6. Evaluating open-source cloud computing solutions for geosciences

    NASA Astrophysics Data System (ADS)

    Huang, Qunying; Yang, Chaowei; Liu, Kai; Xia, Jizhe; Xu, Chen; Li, Jing; Gui, Zhipeng; Sun, Min; Li, Zhenglong

    2013-09-01

    Many organizations start to adopt cloud computing for better utilizing computing resources by taking advantage of its scalability, cost reduction, and easy to access characteristics. Many private or community cloud computing platforms are being built using open-source cloud solutions. However, little has been done to systematically compare and evaluate the features and performance of open-source solutions in supporting Geosciences. This paper provides a comprehensive study of three open-source cloud solutions, including OpenNebula, Eucalyptus, and CloudStack. We compared a variety of features, capabilities, technologies and performances including: (1) general features and supported services for cloud resource creation and management, (2) advanced capabilities for networking and security, and (3) the performance of the cloud solutions in provisioning and operating the cloud resources as well as the performance of virtual machines initiated and managed by the cloud solutions in supporting selected geoscience applications. Our study found that: (1) no significant performance differences in central processing unit (CPU), memory and I/O of virtual machines created and managed by different solutions, (2) OpenNebula has the fastest internal network while both Eucalyptus and CloudStack have better virtual machine isolation and security strategies, (3) Cloudstack has the fastest operations in handling virtual machines, images, snapshots, volumes and networking, followed by OpenNebula, and (4) the selected cloud computing solutions are capable for supporting concurrent intensive web applications, computing intensive applications, and small-scale model simulations without intensive data communication.

  7. 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.

  8. 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.

  9. Infrastructure Suitability Assessment Modeling for Cloud Computing Solutions

    DTIC Science & Technology

    2011-09-01

    implementations of the cloud com- puting paradigm, dissolving the need to co-locate user and computing power by providing desired services through the...increased imple- mentations of the cloud computing paradigm, dissolving the need to co-locate user and computing power by providing desired services...technologies, such as the widespread availability of fast computer networks, inexpensive computing power provided by small-form factor servers and

  10. Mission critical cloud computing in a week

    NASA Astrophysics Data System (ADS)

    George, B.; Shams, K.; Knight, D.; Kinney, J.

    NASA's vision is to “ reach for new heights and reveal the unknown so that what we do and learn will benefit all humankind.” While our missions provide large volumes of unique and invaluable data to the scientific community, they also serve to inspire and educate the next generation of engineers and scientists. One critical aspect of “ benefiting all humankind” is to make our missions as visible and accessible as possible to facilitate the transfer of scientific knowledge to the public. The recent successful landing of the Curiosity rover on Mars exemplified this vision: we shared the landing event via live video streaming and web experiences with millions of people around the world. The video stream on Curiosity's website was delivered by a highly scalable stack of computing resources in the cloud to cache and distribute the video stream to our viewers. While this work was done in the context of public outreach, it has extensive implications for the development of mission critical, highly available, and elastic applications in the cloud for a diverse set of use cases across NASA.

  11. Reducing Abstraction in High School Computer Science Education: The Case of Definition, Implementation, and Use of Abstract Data Types

    ERIC Educational Resources Information Center

    Sakhnini, Victoria; Hazzan, Orit

    2008-01-01

    The research presented in this article deals with the difficulties and mental processes involved in the definition, implementation, and use of abstract data types encountered by 12th grade advanced-level computer science students. Research findings are interpreted within the theoretical framework of "reducing abstraction" [Hazzan 1999]. The…

  12. Integrating Cloud-Computing-Specific Model into Aircraft Design

    NASA Astrophysics Data System (ADS)

    Zhimin, Tian; Qi, Lin; Guangwen, Yang

    Cloud Computing is becoming increasingly relevant, as it will enable companies involved in spreading this technology to open the door to Web 3.0. In the paper, the new categories of services introduced will slowly replace many types of computational resources currently used. In this perspective, grid computing, the basic element for the large scale supply of cloud services, will play a fundamental role in defining how those services will be provided. The paper tries to integrate cloud computing specific model into aircraft design. This work has acquired good results in sharing licenses of large scale and expensive software, such as CFD (Computational Fluid Dynamics), UG, CATIA, and so on.

  13. Information Security in the Age of Cloud Computing

    ERIC Educational Resources Information Center

    Sims, J. Eric

    2012-01-01

    Information security has been a particularly hot topic since the enhanced internal control requirements of Sarbanes-Oxley (SOX) were introduced in 2002. At about this same time, cloud computing started its explosive growth. Outsourcing of mission-critical functions has always been a gamble for managers, but the advantages of cloud computing are…

  14. A Semantic Based Policy Management Framework for Cloud Computing Environments

    ERIC Educational Resources Information Center

    Takabi, Hassan

    2013-01-01

    Cloud computing paradigm has gained tremendous momentum and generated intensive interest. Although security issues are delaying its fast adoption, cloud computing is an unstoppable force and we need to provide security mechanisms to ensure its secure adoption. In this dissertation, we mainly focus on issues related to policy management and access…

  15. Cloud Computing for Teaching Practice: A New Design?

    ERIC Educational Resources Information Center

    Saadatdoost, Robab; Sim, Alex Tze Hiang; Jafarkarimi, Hosein; Hee, Jee Mei; Saadatdoost, Leila

    2014-01-01

    Recently researchers have shown an increased interest in cloud computing technology. It is becoming increasingly difficult to ignore cloud computing technology in education context. However rapid changes in information technology are having a serious effect on teaching framework designs. So far, however, there has been little discussion about…

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. ProteoCloud: a full-featured open source proteomics cloud computing pipeline.

    PubMed

    Muth, Thilo; Peters, Julian; Blackburn, Jonathan; Rapp, Erdmann; Martens, Lennart

    2013-08-02

    We here present the ProteoCloud pipeline, a freely available, full-featured cloud-based platform to perform computationally intensive, exhaustive searches in a cloud environment using five different peptide identification algorithms. ProteoCloud is entirely open source, and is built around an easy to use and cross-platform software client with a rich graphical user interface. This client allows full control of the number of cloud instances to initiate and of the spectra to assign for identification. It also enables the user to track progress, and to visualize and interpret the results in detail. Source code, binaries and documentation are all available at http://proteocloud.googlecode.com.

  1. 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.

  2. Evaluating the Influence of the Client Behavior in Cloud Computing

    PubMed Central

    Centurion, Adriana Molina; Franco Eustáquio, Paulo Sérgio; Carlucci Santana, Regina Helena; Bruschi, Sarita Mazzini; Santana, Marcos José

    2016-01-01

    This paper proposes a novel approach for the implementation of simulation scenarios, providing a client entity for cloud computing systems. The client entity allows the creation of scenarios in which the client behavior has an influence on the simulation, making the results more realistic. The proposed client entity is based on several characteristics that affect the performance of a cloud computing system, including different modes of submission and their behavior when the waiting time between requests (think time) is considered. The proposed characterization of the client enables the sending of either individual requests or group of Web services to scenarios where the workload takes the form of bursts. The client entity is included in the CloudSim, a framework for modelling and simulation of cloud computing. Experimental results show the influence of the client behavior on the performance of the services executed in a cloud computing system. PMID:27441559

  3. 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

  4. 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.

  5. Evaluating the Influence of the Client Behavior in Cloud Computing.

    PubMed

    Souza Pardo, Mário Henrique; Centurion, Adriana Molina; Franco Eustáquio, Paulo Sérgio; Carlucci Santana, Regina Helena; Bruschi, Sarita Mazzini; Santana, Marcos José

    2016-01-01

    This paper proposes a novel approach for the implementation of simulation scenarios, providing a client entity for cloud computing systems. The client entity allows the creation of scenarios in which the client behavior has an influence on the simulation, making the results more realistic. The proposed client entity is based on several characteristics that affect the performance of a cloud computing system, including different modes of submission and their behavior when the waiting time between requests (think time) is considered. The proposed characterization of the client enables the sending of either individual requests or group of Web services to scenarios where the workload takes the form of bursts. The client entity is included in the CloudSim, a framework for modelling and simulation of cloud computing. Experimental results show the influence of the client behavior on the performance of the services executed in a cloud computing system.

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  8. Challenges and opportunities of cloud computing for atmospheric sciences

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Cloud computing is an emerging technological solution widely used in many fields. Initially developed as a flexible way of managing peak demand it has began to make its way in scientific research. One of the greatest advantages of cloud computing for scientific research is independence of having access to a large cyberinfrastructure to fund or perform a research project. Cloud computing can avoid maintenance expenses for large supercomputers and has the potential to 'democratize' the access to high-performance computing, giving flexibility to funding bodies for allocating budgets for the computational costs associated with a project. Two of the most challenging problems in atmospheric sciences are computational cost and uncertainty in meteorological forecasting and climate projections. Both problems are closely related. Usually uncertainty can be reduced with the availability of computational resources to better reproduce a phenomenon or to perform a larger number of experiments. Here we expose results of the application of cloud computing resources for climate modeling using cloud computing infrastructures of three major vendors and two climate models. We show how the cloud infrastructure compares in performance to traditional supercomputers and how it provides the capability to complete experiments in shorter periods of time. The monetary cost associated is also analyzed. Finally we discuss the future potential of this technology for meteorological and climatological applications, both from the point of view of operational use and research.

  9. 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.

  10. Combining the GRID with Cloud for Earth Science Computing

    NASA Astrophysics Data System (ADS)

    Mishin, Dmitry; Levchenko, Oleg; Groudnev, Andrei; Zhizhin, Mikhail

    2010-05-01

    Cloud computing is a new economic model of using large cluster computing resources which were earlier managed by GRID. Reusing existing GRID infrastructure gives an opportunity to combine the Cloud and GRID technologies on the same hardware and to provide GRID users with functionality for running high performance computing tasks inside virtual machines. In this case Cloud works "above" GRID, sharing computing power and utilizing unused processor time. We manage virtual machines with Eucalyptus elastic cloud and we use Torque system from gLite infrastructure for spreading Cloud jobs in GRID computing nodes to scale the parallel computing tasks on virtual machines created by elastic cloud. For this purpose we have added new types of tasks to the standard GRID task list: to run a virtual node and to run a job on a virtual node. This gives a possibility to seamlessly upscale the Cloud with the new tasks when needed and to shrink it when the tasks are completed. Using GRID components for managing the size of a virtual cloud simplifies building the billing system to charge the Cloud users for the processor time, disk space and outer traffic consumed. A list of Earth Science computing problems that can be solved by using the elastic Cloud include repetitive tasks of downloading, converting and storing in a database of large arrays of data (e.g. weather forecast); creating a pyramid of lower resolution images from a very large one for fast distributed browsing; processing and analyzing the large distributed amounts of data by running Earth Science numerical models.

  11. Facilitating NASA Earth Science Data Processing Using Nebula Cloud Computing

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  12. A study on strategic provisioning of cloud computing services.

    PubMed

    Whaiduzzaman, Md; Haque, Mohammad Nazmul; Rejaul Karim Chowdhury, Md; Gani, Abdullah

    2014-01-01

    Cloud computing is currently emerging as an ever-changing, growing paradigm that models "everything-as-a-service." Virtualised physical resources, infrastructure, and applications are supplied by service provisioning in the cloud. The evolution in the adoption of cloud computing is driven by clear and distinct promising features for both cloud users and cloud providers. However, the increasing number of cloud providers and the variety of service offerings have made it difficult for the customers to choose the best services. By employing successful service provisioning, the essential services required by customers, such as agility and availability, pricing, security and trust, and user metrics can be guaranteed by service provisioning. Hence, continuous service provisioning that satisfies the user requirements is a mandatory feature for the cloud user and vitally important in cloud computing service offerings. Therefore, we aim to review the state-of-the-art service provisioning objectives, essential services, topologies, user requirements, necessary metrics, and pricing mechanisms. We synthesize and summarize different provision techniques, approaches, and models through a comprehensive literature review. A thematic taxonomy of cloud service provisioning is presented after the systematic review. Finally, future research directions and open research issues are identified.

  13. A Study on Strategic Provisioning of Cloud Computing Services

    PubMed Central

    Rejaul Karim Chowdhury, Md

    2014-01-01

    Cloud computing is currently emerging as an ever-changing, growing paradigm that models “everything-as-a-service.” Virtualised physical resources, infrastructure, and applications are supplied by service provisioning in the cloud. The evolution in the adoption of cloud computing is driven by clear and distinct promising features for both cloud users and cloud providers. However, the increasing number of cloud providers and the variety of service offerings have made it difficult for the customers to choose the best services. By employing successful service provisioning, the essential services required by customers, such as agility and availability, pricing, security and trust, and user metrics can be guaranteed by service provisioning. Hence, continuous service provisioning that satisfies the user requirements is a mandatory feature for the cloud user and vitally important in cloud computing service offerings. Therefore, we aim to review the state-of-the-art service provisioning objectives, essential services, topologies, user requirements, necessary metrics, and pricing mechanisms. We synthesize and summarize different provision techniques, approaches, and models through a comprehensive literature review. A thematic taxonomy of cloud service provisioning is presented after the systematic review. Finally, future research directions and open research issues are identified. PMID:25032243

  14. An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing

    PubMed Central

    Han, Guangjie; Que, Wenhui; Jia, Gangyong; Shu, Lei

    2016-01-01

    Cloud computing has innovated the IT industry in recent years, as it can delivery subscription-based services to users in the pay-as-you-go model. Meanwhile, multimedia cloud computing is emerging based on cloud computing to provide a variety of media services on the Internet. However, with the growing popularity of multimedia cloud computing, its large energy consumption cannot only contribute to greenhouse gas emissions, but also result in the rising of cloud users’ costs. Therefore, the multimedia cloud providers should try to minimize its energy consumption as much as possible while satisfying the consumers’ resource requirements and guaranteeing quality of service (QoS). In this paper, we have proposed a remaining utilization-aware (RUA) algorithm for virtual machine (VM) placement, and a power-aware algorithm (PA) is proposed to find proper hosts to shut down for energy saving. These two algorithms have been combined and applied to cloud data centers for completing the process of VM consolidation. Simulation results have shown that there exists a trade-off between the cloud data center’s energy consumption and service-level agreement (SLA) violations. Besides, the RUA algorithm is able to deal with variable workload to prevent hosts from overloading after VM placement and to reduce the SLA violations dramatically. PMID:26901201

  15. Climate goals and computing the future of clouds

    NASA Astrophysics Data System (ADS)

    Schneider, Tapio; Teixeira, João; Bretherton, Christopher S.; Brient, Florent; Pressel, Kyle G.; Schär, Christoph; Siebesma, A. Pier

    2017-01-01

    How clouds respond to warming remains the greatest source of uncertainty in climate projections. Improved computational and observational tools can reduce this uncertainty. Here we discuss the need for research focusing on high-resolution atmosphere models and the representation of clouds and turbulence within them.

  16. Enhancing Instruction through Constructivism, Cooperative Learning, and Cloud Computing

    ERIC Educational Resources Information Center

    Denton, David W.

    2012-01-01

    Cloud computing technologies, such as Google Docs and Microsoft Office Live, have the potential to enhance instructional methods predicated on constructivism and cooperative learning. Cloud-based application features like file sharing and online publishing are prompting departments of education across the nation to adopt these technologies.…

  17. An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing.

    PubMed

    Han, Guangjie; Que, Wenhui; Jia, Gangyong; Shu, Lei

    2016-02-18

    Cloud computing has innovated the IT industry in recent years, as it can delivery subscription-based services to users in the pay-as-you-go model. Meanwhile, multimedia cloud computing is emerging based on cloud computing to provide a variety of media services on the Internet. However, with the growing popularity of multimedia cloud computing, its large energy consumption cannot only contribute to greenhouse gas emissions, but also result in the rising of cloud users' costs. Therefore, the multimedia cloud providers should try to minimize its energy consumption as much as possible while satisfying the consumers' resource requirements and guaranteeing quality of service (QoS). In this paper, we have proposed a remaining utilization-aware (RUA) algorithm for virtual machine (VM) placement, and a power-aware algorithm (PA) is proposed to find proper hosts to shut down for energy saving. These two algorithms have been combined and applied to cloud data centers for completing the process of VM consolidation. Simulation results have shown that there exists a trade-off between the cloud data center's energy consumption and service-level agreement (SLA) violations. Besides, the RUA algorithm is able to deal with variable workload to prevent hosts from overloading after VM placement and to reduce the SLA violations dramatically.

  18. On Teaching Abstraction in Computer Science to Novices

    ERIC Educational Resources Information Center

    Armoni, Michal

    2013-01-01

    Abstraction is a key concept in CS, one of the most fundamental ideas underlying CS and its practice. However, teaching this soft concept to novices is a very difficult task, as discussed by many CSE experts. This paper discusses this issue, and suggests a general framework for teaching abstraction in CS to novices, a framework that would fit into…

  19. 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.

  20. Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure

    NASA Astrophysics Data System (ADS)

    Wang, Henry; Ma, Yunzhi; Pratx, Guillem; Xing, Lei

    2011-09-01

    Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed. This work was presented in part at the 2010 Annual Meeting of the American Association of Physicists in Medicine (AAPM), Philadelphia, PA.

  1. Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure.

    PubMed

    Wang, Henry; Ma, Yunzhi; Pratx, Guillem; Xing, Lei

    2011-09-07

    Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed.

  2. Cloud computing and patient engagement: leveraging available technology.

    PubMed

    Noblin, Alice; Cortelyou-Ward, Kendall; Servan, Rosa M

    2014-01-01

    Cloud computing technology has the potential to transform medical practices and improve patient engagement and quality of care. However, issues such as privacy and security and "fit" can make incorporation of the cloud an intimidating decision for many physicians. This article summarizes the four most common types of clouds and discusses their ideal uses, how they engage patients, and how they improve the quality of care offered. This technology also can be used to meet Meaningful Use requirements 1 and 2; and, if speculation is correct, the cloud will provide the necessary support needed for Meaningful Use 3 as well.

  3. Predictive Control of Networked Multiagent Systems via Cloud Computing.

    PubMed

    Liu, Guo-Ping

    2017-01-18

    This paper studies the design and analysis of networked multiagent predictive control systems via cloud computing. A cloud predictive control scheme for networked multiagent systems (NMASs) is proposed to achieve consensus and stability simultaneously and to compensate for network delays actively. The design of the cloud predictive controller for NMASs is detailed. The analysis of the cloud predictive control scheme gives the necessary and sufficient conditions of stability and consensus of closed-loop networked multiagent control systems. The proposed scheme is verified to characterize the dynamical behavior and control performance of NMASs through simulations. The outcome provides a foundation for the development of cooperative and coordinative control of NMASs and its applications.

  4. 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.

  5. Cloud Computing Trace Characterization and Synthetic Workload Generation

    DTIC Science & Technology

    2013-03-01

    to design realistic cloud workloads, which drive the evaluation of Hadoop job schedulers and Hadoop shared storage system performance. The trace...synthesizing realistic workload traces for studying the hadoop ecosystem. Presented at Modeling, Analysis & Simulation of Computer and

  6. Hyrax: Cloud Computing on Mobile Devices using MapReduce

    DTIC Science & Technology

    2009-09-01

    and showing that it is feasible using today’s mobile technology . • Implement Hyrax, a mobile-cloud computing platform, by porting Hadoop to run on...of applications that a mobile-cloud computing platform would facilitate, and the feasibility of such a platform using today’s mobile technology . 3.3.1...an interactive experience via mobile technology such as YinzCam Media [2009]. YinzCam allows game attendants to view replays from various angles and

  7. Benefits of cloud computing for PACS and archiving.

    PubMed

    Koch, Patrick

    2012-01-01

    The goal of cloud-based services is to provide easy, scalable access to computing resources and IT services. The healthcare industry requires a private cloud that adheres to government mandates designed to ensure privacy and security of patient data while enabling access by authorized users. Cloud-based computing in the imaging market has evolved from a service that provided cost effective disaster recovery for archived data to fully featured PACS and vendor neutral archiving services that can address the needs of healthcare providers of all sizes. Healthcare providers worldwide are now using the cloud to distribute images to remote radiologists while supporting advanced reading tools, deliver radiology reports and imaging studies to referring physicians, and provide redundant data storage. Vendor managed cloud services eliminate large capital investments in equipment and maintenance, as well as staffing for the data center--creating a reduction in total cost of ownership for the healthcare provider.

  8. Cloud Computing: A Free Technology Option to Promote Collaborative Learning

    ERIC Educational Resources Information Center

    Siegle, Del

    2010-01-01

    In a time of budget cuts and limited funding, purchasing and installing the latest software on classroom computers can be prohibitive for schools. Many educators are unaware that a variety of free software options exist, and some of them do not actually require installing software on the user's computer. One such option is cloud computing. This…

  9. Mobile healthcare information management utilizing Cloud Computing and Android OS.

    PubMed

    Doukas, Charalampos; Pliakas, Thomas; Maglogiannis, Ilias

    2010-01-01

    Cloud Computing provides functionality for managing information data in a distributed, ubiquitous and pervasive manner supporting several platforms, systems and applications. This work presents the implementation of a mobile system that enables electronic healthcare data storage, update and retrieval using Cloud Computing. The mobile application is developed using Google's Android operating system and provides management of patient health records and medical images (supporting DICOM format and JPEG2000 coding). The developed system has been evaluated using the Amazon's S3 cloud service. This article summarizes the implementation details and presents initial results of the system in practice.

  10. CloudMC: a cloud computing application for Monte Carlo simulation.

    PubMed

    Miras, H; Jiménez, R; Miras, C; Gomà, C

    2013-04-21

    This work presents CloudMC, a cloud computing application-developed in Windows Azure®, the platform of the Microsoft® cloud-for the parallelization of Monte Carlo simulations in a dynamic virtual cluster. CloudMC is a web application designed to be independent of the Monte Carlo code in which the simulations are based-the simulations just need to be of the form: input files → executable → output files. To study the performance of CloudMC in Windows Azure®, Monte Carlo simulations with penelope were performed on different instance (virtual machine) sizes, and for different number of instances. The instance size was found to have no effect on the simulation runtime. It was also found that the decrease in time with the number of instances followed Amdahl's law, with a slight deviation due to the increase in the fraction of non-parallelizable time with increasing number of instances. A simulation that would have required 30 h of CPU on a single instance was completed in 48.6 min when executed on 64 instances in parallel (speedup of 37 ×). Furthermore, the use of cloud computing for parallel computing offers some advantages over conventional clusters: high accessibility, scalability and pay per usage. Therefore, it is strongly believed that cloud computing will play an important role in making Monte Carlo dose calculation a reality in future clinical practice.

  11. Cloud computing: a new business paradigm for biomedical information sharing.

    PubMed

    Rosenthal, Arnon; Mork, Peter; Li, Maya Hao; Stanford, Jean; Koester, David; Reynolds, Patti

    2010-04-01

    We examine how the biomedical informatics (BMI) community, especially consortia that share data and applications, can take advantage of a new resource called "cloud computing". Clouds generally offer resources on demand. In most clouds, charges are pay per use, based on large farms of inexpensive, dedicated servers, sometimes supporting parallel computing. Substantial economies of scale potentially yield costs much lower than dedicated laboratory systems or even institutional data centers. Overall, even with conservative assumptions, for applications that are not I/O intensive and do not demand a fully mature environment, the numbers suggested that clouds can sometimes provide major improvements, and should be seriously considered for BMI. Methodologically, it was very advantageous to formulate analyses in terms of component technologies; focusing on these specifics enabled us to bypass the cacophony of alternative definitions (e.g., exactly what does a cloud include) and to analyze alternatives that employ some of the component technologies (e.g., an institution's data center). Relative analyses were another great simplifier. Rather than listing the absolute strengths and weaknesses of cloud-based systems (e.g., for security or data preservation), we focus on the changes from a particular starting point, e.g., individual lab systems. We often find a rough parity (in principle), but one needs to examine individual acquisitions--is a loosely managed lab moving to a well managed cloud, or a tightly managed hospital data center moving to a poorly safeguarded cloud?

  12. Further developments in cloud statistics for computer simulations

    NASA Technical Reports Server (NTRS)

    Chang, D. T.; Willand, J. H.

    1972-01-01

    This study is a part of NASA's continued program to provide global statistics of cloud parameters for computer simulation. The primary emphasis was on the development of the data bank of the global statistical distributions of cloud types and cloud layers and their applications in the simulation of the vertical distributions of in-cloud parameters such as liquid water content. These statistics were compiled from actual surface observations as recorded in Standard WBAN forms. Data for a total of 19 stations were obtained and reduced. These stations were selected to be representative of the 19 primary cloud climatological regions defined in previous studies of cloud statistics. Using the data compiled in this study, a limited study was conducted of the hemogeneity of cloud regions, the latitudinal dependence of cloud-type distributions, the dependence of these statistics on sample size, and other factors in the statistics which are of significance to the problem of simulation. The application of the statistics in cloud simulation was investigated. In particular, the inclusion of the new statistics in an expanded multi-step Monte Carlo simulation scheme is suggested and briefly outlined.

  13. Cloud@Home: A New Enhanced Computing Paradigm

    NASA Astrophysics Data System (ADS)

    Distefano, Salvatore; Cunsolo, Vincenzo D.; Puliafito, Antonio; Scarpa, Marco

    Cloud computing is a distributed computing paradigm that mixes aspects of Grid computing, ("… hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities" (Foster, 2002)) Internet Computing ("…a computing platform geographically distributed across the Internet" (Milenkovic et al., 2003)), Utility computing ("a collection of technologies and business practices that enables computing to be delivered seamlessly and reliably across multiple computers, ... available as needed and billed according to usage, much like water and electricity are today" (Ross & Westerman, 2004)) Autonomic computing ("computing systems that can manage themselves given high-level objectives from administrators" (Kephart & Chess, 2003)), Edge computing ("… provides a generic template facility for any type of application to spread its execution across a dedicated grid, balancing the load …" Davis, Parikh, & Weihl, 2004) and Green computing (a new frontier of Ethical computing1 starting from the assumption that in next future energy costs will be related to the environment pollution).

  14. Cloud Computing for Geosciences--GeoCloud for standardized geospatial service platforms (Invited)

    NASA Astrophysics Data System (ADS)

    Nebert, D. D.; Huang, Q.; Yang, C.

    2013-12-01

    The 21st century geoscience faces challenges of Big Data, spike computing requirements (e.g., when natural disaster happens), and sharing resources through cyberinfrastructure across different organizations (Yang et al., 2011). With flexibility and cost-efficiency of computing resources a primary concern, cloud computing emerges as a promising solution to provide core capabilities to address these challenges. Many governmental and federal agencies are adopting cloud technologies to cut costs and to make federal IT operations more efficient (Huang et al., 2010). However, it is still difficult for geoscientists to take advantage of the benefits of cloud computing to facilitate the scientific research and discoveries. This presentation reports using GeoCloud to illustrate the process and strategies used in building a common platform for geoscience communities to enable the sharing, integration of geospatial data, information and knowledge across different domains. GeoCloud is an annual incubator project coordinated by the Federal Geographic Data Committee (FGDC) in collaboration with the U.S. General Services Administration (GSA) and the Department of Health and Human Services. It is designed as a staging environment to test and document the deployment of a common GeoCloud community platform that can be implemented by multiple agencies. With these standardized virtual geospatial servers, a variety of government geospatial applications can be quickly migrated to the cloud. In order to achieve this objective, multiple projects are nominated each year by federal agencies as existing public-facing geospatial data services. From the initial candidate projects, a set of common operating system and software requirements was identified as the baseline for platform as a service (PaaS) packages. Based on these developed common platform packages, each project deploys and monitors its web application, develops best practices, and documents cost and performance information. This

  15. GATE Monte Carlo simulation in a cloud computing environment

    NASA Astrophysics Data System (ADS)

    Rowedder, Blake Austin

    The GEANT4-based GATE is a unique and powerful Monte Carlo (MC) platform, which provides a single code library allowing the simulation of specific medical physics applications, e.g. PET, SPECT, CT, radiotherapy, and hadron therapy. However, this rigorous yet flexible platform is used only sparingly in the clinic due to its lengthy calculation time. By accessing the powerful computational resources of a cloud computing environment, GATE's runtime can be significantly reduced to clinically feasible levels without the sizable investment of a local high performance cluster. This study investigated a reliable and efficient execution of GATE MC simulations using a commercial cloud computing services. Amazon's Elastic Compute Cloud was used to launch several nodes equipped with GATE. Job data was initially broken up on the local computer, then uploaded to the worker nodes on the cloud. The results were automatically downloaded and aggregated on the local computer for display and analysis. Five simulations were repeated for every cluster size between 1 and 20 nodes. Ultimately, increasing cluster size resulted in a decrease in calculation time that could be expressed with an inverse power model. Comparing the benchmark results to the published values and error margins indicated that the simulation results were not affected by the cluster size and thus that integrity of a calculation is preserved in a cloud computing environment. The runtime of a 53 minute long simulation was decreased to 3.11 minutes when run on a 20-node cluster. The ability to improve the speed of simulation suggests that fast MC simulations are viable for imaging and radiotherapy applications. With high power computing continuing to lower in price and accessibility, implementing Monte Carlo techniques with cloud computing for clinical applications will continue to become more attractive.

  16. A hazy outlook for cloud computing.

    PubMed

    Perna, Gabriel

    2012-01-01

    Because of competing priorities as well as cost, security, and implementation concerns, cloud-based storage development has gotten off to a slow start in healthcare. CIOs, CTOs, and other healthcare IT leaders are adopting a variety of strategies in this area, based on their organizations' needs, resources, and priorities.

  17. (abstract) The Nest Generation of Space Flight Computers

    NASA Technical Reports Server (NTRS)

    Alkalaj, Leon; Panwar, Ramesh

    1993-01-01

    To meet new design objectives for drastic reductions in mass, size, and power consumption, the Flight Computer Development Group at JPL is participating in a design study and development of a light-weight, small-sized, low-power 3-D Space Flight Computer. In this paper, we will present a detailed design and tradeoff study of the proposed computer. We will also discuss a complete design of the multichip modules and their size, weight, and power consumption. Prelimimary thermal models will also be discussed.

  18. UFO (UnFold Operator) computer program abstract

    SciTech Connect

    Kissel, L.; Biggs, F.

    1982-11-01

    UFO (UnFold Operator) is an interactive user-oriented computer program designed to solve a wide range of problems commonly encountered in physical measurements. This document provides a summary of the capabilities of version 3A of UFO.

  19. Radiotherapy Monte Carlo simulation using cloud computing technology.

    PubMed

    Poole, C M; Cornelius, I; Trapp, J V; Langton, C M

    2012-12-01

    Cloud computing allows for vast computational resources to be leveraged quickly and easily in bursts as and when required. Here we describe a technique that allows for Monte Carlo radiotherapy dose calculations to be performed using GEANT4 and executed in the cloud, with relative simulation cost and completion time evaluated as a function of machine count. As expected, simulation completion time decreases as 1/n for n parallel machines, and relative simulation cost is found to be optimal where n is a factor of the total simulation time in hours. Using the technique, we demonstrate the potential usefulness of cloud computing as a solution for rapid Monte Carlo simulation for radiotherapy dose calculation without the need for dedicated local computer hardware as a proof of principal.

  20. Snore related signals processing in a private cloud computing system.

    PubMed

    Qian, Kun; Guo, Jian; Xu, Huijie; Zhu, Zhaomeng; Zhang, Gongxuan

    2014-09-01

    Snore related signals (SRS) have been demonstrated to carry important information about the obstruction site and degree in the upper airway of Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) patients in recent years. To make this acoustic signal analysis method more accurate and robust, big SRS data processing is inevitable. As an emerging concept and technology, cloud computing has motivated numerous researchers and engineers to exploit applications both in academic and industry field, which could have an ability to implement a huge blue print in biomedical engineering. Considering the security and transferring requirement of biomedical data, we designed a system based on private cloud computing to process SRS. Then we set the comparable experiments of processing a 5-hour audio recording of an OSAHS patient by a personal computer, a server and a private cloud computing system to demonstrate the efficiency of the infrastructure we proposed.

  1. Off the Shelf Cloud Robotics for the Smart Home: Empowering a Wireless Robot through Cloud Computing

    PubMed Central

    Ramírez De La Pinta, Javier; Maestre Torreblanca, José María; Jurado, Isabel; Reyes De Cozar, Sergio

    2017-01-01

    In this paper, we explore the possibilities offered by the integration of home automation systems and service robots. In particular, we examine how advanced computationally expensive services can be provided by using a cloud computing approach to overcome the limitations of the hardware available at the user’s home. To this end, we integrate two wireless low-cost, off-the-shelf systems in this work, namely, the service robot Rovio and the home automation system Z-wave. Cloud computing is used to enhance the capabilities of these systems so that advanced sensing and interaction services based on image processing and voice recognition can be offered. PMID:28272305

  2. Off the Shelf Cloud Robotics for the Smart Home: Empowering a Wireless Robot through Cloud Computing.

    PubMed

    Ramírez De La Pinta, Javier; Maestre Torreblanca, José María; Jurado, Isabel; Reyes De Cozar, Sergio

    2017-03-06

    In this paper, we explore the possibilities offered by the integration of home automation systems and service robots. In particular, we examine how advanced computationally expensive services can be provided by using a cloud computing approach to overcome the limitations of the hardware available at the user's home. To this end, we integrate two wireless low-cost, off-the-shelf systems in this work, namely, the service robot Rovio and the home automation system Z-wave. Cloud computing is used to enhance the capabilities of these systems so that advanced sensing and interaction services based on image processing and voice recognition can be offered.

  3. Quantitative Investigation of the Technologies That Support Cloud Computing

    ERIC Educational Resources Information Center

    Hu, Wenjin

    2014-01-01

    Cloud computing is dramatically shaping modern IT infrastructure. It virtualizes computing resources, provides elastic scalability, serves as a pay-as-you-use utility, simplifies the IT administrators' daily tasks, enhances the mobility and collaboration of data, and increases user productivity. We focus on providing generalized black-box…

  4. Optimizing Security of Cloud Computing within the DoD

    DTIC Science & Technology

    2010-12-01

    Denial of Service DRP Disaster Recovery Plan ENISA European Network and Information Security Agency FedRAMP Federal Risk and Authorization...federated identity management) 116 Lee Badger and Tim Grance, “Standards Acceleration to Jumpstart...computing-usage.html (accessed October 1, 2010). 119 Badger and Grance, “Standards Acceleration to Jumpstart Adoption of Cloud Computing.” 120

  5. Cloud computing for comparative genomics with windows azure platform.

    PubMed

    Kim, Insik; Jung, Jae-Yoon; Deluca, Todd F; Nelson, Tristan H; Wall, Dennis P

    2012-01-01

    Cloud computing services have emerged as a cost-effective alternative for cluster systems as the number of genomes and required computation power to analyze them increased in recent years. Here we introduce the Microsoft Azure platform with detailed execution steps and a cost comparison with Amazon Web Services.

  6. Cloud Computing for Comparative Genomics with Windows Azure Platform

    PubMed Central

    Kim, Insik; Jung, Jae-Yoon; DeLuca, Todd F.; Nelson, Tristan H.; Wall, Dennis P.

    2012-01-01

    Cloud computing services have emerged as a cost-effective alternative for cluster systems as the number of genomes and required computation power to analyze them increased in recent years. Here we introduce the Microsoft Azure platform with detailed execution steps and a cost comparison with Amazon Web Services. PMID:23032609

  7. Managing Laboratory Data Using Cloud Computing as an Organizational Tool

    ERIC Educational Resources Information Center

    Bennett, Jacqueline; Pence, Harry E.

    2011-01-01

    One of the most significant difficulties encountered when directing undergraduate research and developing new laboratory experiments is how to efficiently manage the data generated by a number of students. Cloud computing, where both software and computer files reside online, offers a solution to this data-management problem and allows researchers…

  8. 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.

  9. Design and Implementation of a Cloud Computing Adoption Decision Tool: Generating a Cloud Road.

    PubMed

    Bildosola, Iñaki; Río-Belver, Rosa; Cilleruelo, Ernesto; Garechana, Gaizka

    2015-01-01

    Migrating to cloud computing is one of the current enterprise challenges. This technology provides a new paradigm based on "on-demand payment" for information and communication technologies. In this sense, the small and medium enterprise is supposed to be the most interested, since initial investments are avoided and the technology allows gradual implementation. However, even if the characteristics and capacities have been widely discussed, entry into the cloud is still lacking in terms of practical, real frameworks. This paper aims at filling this gap, presenting a real tool already implemented and tested, which can be used as a cloud computing adoption decision tool. This tool uses diagnosis based on specific questions to gather the required information and subsequently provide the user with valuable information to deploy the business within the cloud, specifically in the form of Software as a Service (SaaS) solutions. This information allows the decision makers to generate their particular Cloud Road. A pilot study has been carried out with enterprises at a local level with a two-fold objective: to ascertain the degree of knowledge on cloud computing and to identify the most interesting business areas and their related tools for this technology. As expected, the results show high interest and low knowledge on this subject and the tool presented aims to readdress this mismatch, insofar as possible.

  10. Design and Implementation of a Cloud Computing Adoption Decision Tool: Generating a Cloud Road

    PubMed Central

    Bildosola, Iñaki; Río-Belver, Rosa; Cilleruelo, Ernesto; Garechana, Gaizka

    2015-01-01

    Migrating to cloud computing is one of the current enterprise challenges. This technology provides a new paradigm based on “on-demand payment” for information and communication technologies. In this sense, the small and medium enterprise is supposed to be the most interested, since initial investments are avoided and the technology allows gradual implementation. However, even if the characteristics and capacities have been widely discussed, entry into the cloud is still lacking in terms of practical, real frameworks. This paper aims at filling this gap, presenting a real tool already implemented and tested, which can be used as a cloud computing adoption decision tool. This tool uses diagnosis based on specific questions to gather the required information and subsequently provide the user with valuable information to deploy the business within the cloud, specifically in the form of Software as a Service (SaaS) solutions. This information allows the decision makers to generate their particular Cloud Road. A pilot study has been carried out with enterprises at a local level with a two-fold objective: to ascertain the degree of knowledge on cloud computing and to identify the most interesting business areas and their related tools for this technology. As expected, the results show high interest and low knowledge on this subject and the tool presented aims to readdress this mismatch, insofar as possible. PMID:26230400

  11. Cloud computing approaches to accelerate drug discovery value chain.

    PubMed

    Garg, Vibhav; Arora, Suchir; Gupta, Chitra

    2011-12-01

    Continued advancements in the area of technology have helped high throughput screening (HTS) evolve from a linear to parallel approach by performing system level screening. Advanced experimental methods used for HTS at various steps of drug discovery (i.e. target identification, target validation, lead identification and lead validation) can generate data of the order of terabytes. As a consequence, there is pressing need to store, manage, mine and analyze this data to identify informational tags. This need is again posing challenges to computer scientists to offer the matching hardware and software infrastructure, while managing the varying degree of desired computational power. Therefore, the potential of "On-Demand Hardware" and "Software as a Service (SAAS)" delivery mechanisms cannot be denied. This on-demand computing, largely referred to as Cloud Computing, is now transforming the drug discovery research. Also, integration of Cloud computing with parallel computing is certainly expanding its footprint in the life sciences community. The speed, efficiency and cost effectiveness have made cloud computing a 'good to have tool' for researchers, providing them significant flexibility, allowing them to focus on the 'what' of science and not the 'how'. Once reached to its maturity, Discovery-Cloud would fit best to manage drug discovery and clinical development data, generated using advanced HTS techniques, hence supporting the vision of personalized medicine.

  12. InSAR Scientific Computing Environment on the Cloud

    NASA Astrophysics Data System (ADS)

    Rosen, P. A.; Shams, K. S.; Gurrola, E. M.; George, B. A.; Knight, D. S.

    2012-12-01

    In response to the needs of the international scientific and operational Earth observation communities, spaceborne Synthetic Aperture Radar (SAR) systems are being tasked to produce enormous volumes of raw data daily, with availability to scientists to increase substantially as more satellites come online and data becomes more accessible through more open data policies. The availability of these unprecedentedly dense and rich datasets has led to the development of sophisticated algorithms that can take advantage of them. In particular, interferometric time series analysis of SAR data provides insights into the changing earth and requires substantial computational power to process data across large regions and over large time periods. This poses challenges for existing infrastructure, software, and techniques required to process, store, and deliver the results to the global community of scientists. The current state-of-the-art solutions employ traditional data storage and processing applications that require download of data to the local repositories before processing. This approach is becoming untenable in light of the enormous volume of data that must be processed in an iterative and collaborative manner. We have analyzed and tested new cloud computing and virtualization approaches to address these challenges within the context of InSAR in the earth science community. Cloud computing is democratizing computational and storage capabilities for science users across the world. The NASA Jet Propulsion Laboratory has been an early adopter of this technology, successfully integrating cloud computing in a variety of production applications ranging from mission operations to downlink data processing. We have ported a new InSAR processing suite called ISCE (InSAR Scientific Computing Environment) to a scalable distributed system running in the Amazon GovCloud to demonstrate the efficacy of cloud computing for this application. We have integrated ISCE with Polyphony to

  13. Proposing an Abstracted Interface and Protocol for Computer Systems.

    SciTech Connect

    Resnick, David Richard; Ignatowski, Mike

    2014-07-01

    While it made sense for historical reasons to develop different interfaces and protocols for memory channels, CPU to CPU interactions, and I/O devices, ongoing developments in the computer industry are leading to more converged requirements and physical implementations for these interconnects. As it becomes increasingly common for advanced components to contain a variety of computational devices as well as memory, the distinction between processors, memory, accelerators, and I/O devices become s increasingly blurred. As a result, the interface requirements among such components are converging. There is also a wide range of new disruptive technologies that will impact the computer market in the coming years , including 3D integration and emerging NVRAM memory. Optimal exploitation of these technologies cannot be done with the existing memory, storage, and I/O interface standards. The computer industry has historically made major advances when industry players have been able to add innovation behind a standard interface. The standard interface provides a large market for their products and enables relatively quick and widespread adoption. To enable a new wave of innovation in the form of advanced memory products and accelerators, we need a new standard interface explicitly designed to provide both the performance and flexibility to support new system integration solutions.

  14. Proposing an Abstracted Interface and Protocol for Computer Systems.

    SciTech Connect

    Resnick, David Richard; Ignatowski, Mike

    2014-07-01

    While it made sense for historical reasons to develop different interfaces and protocols for memory channels, CPU to CPU interactions, and I/O devices, ongoing developments in the computer industry are leading to more converged requirements and physical implementations for these interconnects. As it becomes increasingly common for advanced components to contain a variety of computational devices as well as memory, the distinction between processors, memory, accelerators, and I/O devices become s increasingly blur red. As a result, the interface requirements among such components are converging. There is also a wide range of new disruptive technologies that will impact the computer market in the coming years , including 3D integration and emerging NVRAM memory. Optimal exploitation of these technologies cannot be done with the existing memory , storage, and I/O interface standards. The computer industry has historically made major advances when industry players have been able to add innovation behind a standard interface. The standard interface provides a large market for their products and enable s relatively quick and widespread adoption. To enable a new wave of innovation in the form of advanced memory products and accelerators, we need a new standard interface explicitly design ed to provide both the performance and flexibility to support new system integration solutions.

  15. Cloud computing for protein-ligand binding site comparison.

    PubMed

    Hung, Che-Lun; Hua, Guan-Jie

    2013-01-01

    The proteome-wide analysis of protein-ligand binding sites and their interactions with ligands is important in structure-based drug design and in understanding ligand cross reactivity and toxicity. The well-known and commonly used software, SMAP, has been designed for 3D ligand binding site comparison and similarity searching of a structural proteome. SMAP can also predict drug side effects and reassign existing drugs to new indications. However, the computing scale of SMAP is limited. We have developed a high availability, high performance system that expands the comparison scale of SMAP. This cloud computing service, called Cloud-PLBS, combines the SMAP and Hadoop frameworks and is deployed on a virtual cloud computing platform. To handle the vast amount of experimental data on protein-ligand binding site pairs, Cloud-PLBS exploits the MapReduce paradigm as a management and parallelizing tool. Cloud-PLBS provides a web portal and scalability through which biologists can address a wide range of computer-intensive questions in biology and drug discovery.

  16. Genomic cloud computing: legal and ethical points to consider

    PubMed Central

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

    2015-01-01

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

  17. Genomic cloud computing: legal and ethical points to consider.

    PubMed

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

    2015-10-01

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

  18. Secure Dynamic access control scheme of PHR in cloud computing.

    PubMed

    Chen, Tzer-Shyong; Liu, Chia-Hui; Chen, Tzer-Long; Chen, Chin-Sheng; Bau, Jian-Guo; Lin, Tzu-Ching

    2012-12-01

    With the development of information technology and medical technology, medical information has been developed from traditional paper records into electronic medical records, which have now been widely applied. The new-style medical information exchange system "personal health records (PHR)" is gradually developed. PHR is a kind of health records maintained and recorded by individuals. An ideal personal health record could integrate personal medical information from different sources and provide complete and correct personal health and medical summary through the Internet or portable media under the requirements of security and privacy. A lot of personal health records are being utilized. The patient-centered PHR information exchange system allows the public autonomously maintain and manage personal health records. Such management is convenient for storing, accessing, and sharing personal medical records. With the emergence of Cloud computing, PHR service has been transferred to storing data into Cloud servers that the resources could be flexibly utilized and the operation cost can be reduced. Nevertheless, patients would face privacy problem when storing PHR data into Cloud. Besides, it requires a secure protection scheme to encrypt the medical records of each patient for storing PHR into Cloud server. In the encryption process, it would be a challenge to achieve accurately accessing to medical records and corresponding to flexibility and efficiency. A new PHR access control scheme under Cloud computing environments is proposed in this study. With Lagrange interpolation polynomial to establish a secure and effective PHR information access scheme, it allows to accurately access to PHR with security and is suitable for enormous multi-users. Moreover, this scheme also dynamically supports multi-users in Cloud computing environments with personal privacy and offers legal authorities to access to PHR. From security and effectiveness analyses, the proposed PHR access

  19. COMPUTATIONAL MODELING OF ELECTRON CLOUD FOR MEIC

    SciTech Connect

    S. Ahmed, B. Yunn, J. Dolph, T. Satogata, G.A. Krafft

    2012-07-01

    This work is the continuation of [4] our earlier studies on electron cloud (EC) simulations for the medium energy electron-ion collider (MEIC) envisioned at Jefferson Lab beyond the 12 GeV upgrade of CEBAF. In this paper, we study the EC saturation density with various MEIC operational parameters. The details of the study shows saturation of line density 1.7 nC/m and tune shift per unit length 4.9 x 10{sup -7} m{sup -1}.

  20. A European Federated Cloud: Innovative distributed computing solutions by EGI

    NASA Astrophysics Data System (ADS)

    Sipos, Gergely; Turilli, Matteo; Newhouse, Steven; Kacsuk, Peter

    2013-04-01

    The European Grid Infrastructure (EGI) is the result of pioneering work that has, over the last decade, built a collaborative production infrastructure of uniform services through the federation of national resource providers that supports multi-disciplinary science across Europe and around the world. This presentation will provide an overview of the recently established 'federated cloud computing services' that the National Grid Initiatives (NGIs), operators of EGI, offer to scientific communities. The presentation will explain the technical capabilities of the 'EGI Federated Cloud' and the processes whereby earth and space science researchers can engage with it. EGI's resource centres have been providing services for collaborative, compute- and data-intensive applications for over a decade. Besides the well-established 'grid services', several NGIs already offer privately run cloud services to their national researchers. Many of these researchers recently expressed the need to share these cloud capabilities within their international research collaborations - a model similar to the way the grid emerged through the federation of institutional batch computing and file storage servers. To facilitate the setup of a pan-European cloud service from the NGIs' resources, the EGI-InSPIRE project established a Federated Cloud Task Force in September 2011. The Task Force has a mandate to identify and test technologies for a multinational federated cloud that could be provisioned within EGI by the NGIs. A guiding principle for the EGI Federated Cloud is to remain technology neutral and flexible for both resource providers and users: • Resource providers are allowed to use any cloud hypervisor and management technology to join virtualised resources into the EGI Federated Cloud as long as the site is subscribed to the user-facing interfaces selected by the EGI community. • Users can integrate high level services - such as brokers, portals and customised Virtual Research

  1. Cloud CPFP: a shotgun proteomics data analysis pipeline using cloud and high performance computing.

    PubMed

    Trudgian, David C; Mirzaei, Hamid

    2012-12-07

    We have extended the functionality of the Central Proteomics Facilities Pipeline (CPFP) to allow use of remote cloud and high performance computing (HPC) resources for shotgun proteomics data processing. CPFP has been modified to include modular local and remote scheduling for data processing jobs. The pipeline can now be run on a single PC or server, a local cluster, a remote HPC cluster, and/or the Amazon Web Services (AWS) cloud. We provide public images that allow easy deployment of CPFP in its entirety in the AWS cloud. This significantly reduces the effort necessary to use the software, and allows proteomics laboratories to pay for compute time ad hoc, rather than obtaining and maintaining expensive local server clusters. Alternatively the Amazon cloud can be used to increase the throughput of a local installation of CPFP as necessary. We demonstrate that cloud CPFP allows users to process data at higher speed than local installations but with similar cost and lower staff requirements. In addition to the computational improvements, the web interface to CPFP is simplified, and other functionalities are enhanced. The software is under active development at two leading institutions and continues to be released under an open-source license at http://cpfp.sourceforge.net.

  2. A Scientific Cloud Computing Platform for Condensed Matter Physics

    NASA Astrophysics Data System (ADS)

    Jorissen, K.; Johnson, W.; Vila, F. D.; Rehr, J. J.

    2013-03-01

    Scientific Cloud Computing (SCC) makes possible calculations with high performance computational tools, without the need to purchase or maintain sophisticated hardware and software. We have recently developed an interface dubbed SC2IT that controls on-demand virtual Linux clusters within the Amazon EC2 cloud platform. Using this interface we have developed a more advanced, user-friendly SCC Platform configured especially for condensed matter calculations. This platform contains a GUI, based on a new Java version of SC2IT, that permits calculations of various materials properties. The cloud platform includes Virtual Machines preconfigured for parallel calculations and several precompiled and optimized materials science codes for electronic structure and x-ray and electron spectroscopy. Consequently this SCC makes state-of-the-art condensed matter calculations easy to access for general users. Proof-of-principle performance benchmarks show excellent parallelization and communication performance. Supported by NSF grant OCI-1048052

  3. Cloud Computing Boosts Business Intelligence of Telecommunication Industry

    NASA Astrophysics Data System (ADS)

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

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

  4. Towards an Abstraction-Friendly Programming Model for High Productivity and High Performance Computing

    SciTech Connect

    Liao, C; Quinlan, D; Panas, T

    2009-10-06

    General purpose languages, such as C++, permit the construction of various high level abstractions to hide redundant, low level details and accelerate programming productivity. Example abstractions include functions, data structures, classes, templates and so on. However, the use of abstractions significantly impedes static code analyses and optimizations, including parallelization, applied to the abstractions complex implementations. As a result, there is a common perception that performance is inversely proportional to the level of abstraction. On the other hand, programming large scale, possibly heterogeneous high-performance computing systems is notoriously difficult and programmers are less likely to abandon the help from high level abstractions when solving real-world, complex problems. Therefore, the need for programming models balancing both programming productivity and execution performance has reached a new level of criticality. We are exploring a novel abstraction-friendly programming model in order to support high productivity and high performance computing. We believe that standard or domain-specific semantics associated with high level abstractions can be exploited to aid compiler analyses and optimizations, thus helping achieving high performance without losing high productivity. We encode representative abstractions and their useful semantics into an abstraction specification file. In the meantime, an accessible, source-to-source compiler infrastructure (the ROSE compiler) is used to facilitate recognizing high level abstractions and utilizing their semantics for more optimization opportunities. Our initial work has shown that recognizing abstractions and knowing their semantics within a compiler can dramatically extend the applicability of existing optimizations, including automatic parallelization. Moreover, a new set of optimizations have become possible within an abstraction-friendly and semantics-aware programming model. In the future, we will

  5. Cloud Computing Techniques for Space Mission Design

    NASA Technical Reports Server (NTRS)

    Arrieta, Juan; Senent, Juan

    2014-01-01

    The overarching objective of space mission design is to tackle complex problems producing better results, and faster. In developing the methods and tools to fulfill this objective, the user interacts with the different layers of a computing system.

  6. Polyphony: A Workflow Orchestration Framework for Cloud Computing

    NASA Technical Reports Server (NTRS)

    Shams, Khawaja S.; Powell, Mark W.; Crockett, Tom M.; Norris, Jeffrey S.; Rossi, Ryan; Soderstrom, Tom

    2010-01-01

    Cloud Computing has delivered unprecedented compute capacity to NASA missions at affordable rates. Missions like the Mars Exploration Rovers (MER) and Mars Science Lab (MSL) are enjoying the elasticity that enables them to leverage hundreds, if not thousands, or machines for short durations without making any hardware procurements. In this paper, we describe Polyphony, a resilient, scalable, and modular framework that efficiently leverages a large set of computing resources to perform parallel computations. Polyphony can employ resources on the cloud, excess capacity on local machines, as well as spare resources on the supercomputing center, and it enables these resources to work in concert to accomplish a common goal. Polyphony is resilient to node failures, even if they occur in the middle of a transaction. We will conclude with an evaluation of a production-ready application built on top of Polyphony to perform image-processing operations of images from around the solar system, including Mars, Saturn, and Titan.

  7. Cloud computing strategic framework (FY13 - FY15).

    SciTech Connect

    Arellano, Lawrence R.; Arroyo, Steven C.; Giese, Gerald J.; Cox, Philip M.; Rogers, G. Kelly

    2012-11-01

    This document presents an architectural framework (plan) and roadmap for the implementation of a robust Cloud Computing capability at Sandia National Laboratories. It is intended to be a living document and serve as the basis for detailed implementation plans, project proposals and strategic investment requests.

  8. Cloud Computing Adoption and Usage in Community Colleges

    ERIC Educational Resources Information Center

    Behrend, Tara S.; Wiebe, Eric N.; London, Jennifer E.; Johnson, Emily C.

    2011-01-01

    Cloud computing is gaining popularity in higher education settings, but the costs and benefits of this tool have gone largely unexplored. The purpose of this study was to examine the factors that lead to technology adoption in a higher education setting. Specifically, we examined a range of predictors and outcomes relating to the acceptance of a…

  9. Factors Influencing Cloud-Computing Technology Adoption in Developing Countries

    ERIC Educational Resources Information Center

    Hailu, Alemayehu

    2012-01-01

    Adoption of new technology has complicating components both from the selection, as well as decision-making criteria and process. Although new technology such as cloud computing provides great benefits especially to the developing countries, it has challenges that may complicate the selection decision and subsequent adoption process. This study…

  10. Risk in Enterprise Cloud Computing: Re-Evaluated

    ERIC Educational Resources Information Center

    Funmilayo, Bolonduro, R.

    2016-01-01

    A quantitative study was conducted to get the perspectives of IT experts about risks in enterprise cloud computing. In businesses, these IT experts are often not in positions to prioritize business needs. The business experts commonly known as business managers mostly determine an organization's business needs. Even if an IT expert classified a…

  11. Above the cloud computing: applying cloud computing principles to create an orbital services model

    NASA Astrophysics Data System (ADS)

    Straub, Jeremy; Mohammad, Atif; Berk, Josh; Nervold, Anders K.

    2013-05-01

    Large satellites and exquisite planetary missions are generally self-contained. They have, onboard, all of the computational, communications and other capabilities required to perform their designated functions. Because of this, the satellite or spacecraft carries hardware that may be utilized only a fraction of the time; however, the full cost of development and launch are still bone by the program. Small satellites do not have this luxury. Due to mass and volume constraints, they cannot afford to carry numerous pieces of barely utilized equipment or large antennas. This paper proposes a cloud-computing model for exposing satellite services in an orbital environment. Under this approach, each satellite with available capabilities broadcasts a service description for each service that it can provide (e.g., general computing capacity, DSP capabilities, specialized sensing capabilities, transmission capabilities, etc.) and its orbital elements. Consumer spacecraft retain a cache of service providers and select one utilizing decision making heuristics (e.g., suitability of performance, opportunity to transmit instructions and receive results - based on the orbits of the two craft). The two craft negotiate service provisioning (e.g., when the service can be available and for how long) based on the operating rules prioritizing use of (and allowing access to) the service on the service provider craft, based on the credentials of the consumer. Service description, negotiation and sample service performance protocols are presented. The required components of each consumer or provider spacecraft are reviewed. These include fully autonomous control capabilities (for provider craft), a lightweight orbit determination routine (to determine when consumer and provider craft can see each other and, possibly, pointing requirements for craft with directional antennas) and an authentication and resource utilization priority-based access decision making subsystem (for provider craft

  12. Exploring the Universe with WISE and Cloud Computing

    NASA Technical Reports Server (NTRS)

    Benford, Dominic J.

    2011-01-01

    WISE is a recently-completed astronomical survey mission that has imaged the entire sky in four infrared wavelength bands. The large quantity of science images returned consists of 2,776,922 individual snapshots in various locations in each band which, along with ancillary data, totals around 110TB of raw, uncompressed data. Making the most use of this data requires advanced computing resources. I will discuss some initial attempts in the use of cloud computing to make this large problem tractable.

  13. Conference Abstracts: Fourth Annual World Conference on Computers in Education-Part II.

    ERIC Educational Resources Information Center

    Baird, William E.

    1986-01-01

    Presented are abstracts from volume two of the World Conference on Computers in Education, 1985. Four topics are: (1) cognitive and visual style; (2) computer graphics and descriptive geometry; (3) LOGO and educational research; and (4) algorithms, programing, and computer literacy. (JM)

  14. Abstract Proceedings of the Florida Instructional Computing Conference (Orlando, Florida, January 21-24, 1986).

    ERIC Educational Resources Information Center

    Roblyer, M. D., Ed.

    Current issues in educational uses for microcomputers are addressed in this collection of 139 abstracts of papers in which computer literacy and practical applications dominate. Topics discussed include factors related to computer use in the classroom, e.g., computer lab utilization; teaching geometry, science, math, and English via…

  15. Benchmarking undedicated cloud computing providers for analysis of genomic datasets.

    PubMed

    Yazar, Seyhan; Gooden, George E C; Mackey, David A; Hewitt, Alex W

    2014-01-01

    A major bottleneck in biological discovery is now emerging at the computational level. Cloud computing offers a dynamic means whereby small and medium-sized laboratories can rapidly adjust their computational capacity. We benchmarked two established cloud computing services, Amazon Web Services Elastic MapReduce (EMR) on Amazon EC2 instances and Google Compute Engine (GCE), using publicly available genomic datasets (E.coli CC102 strain and a Han Chinese male genome) and a standard bioinformatic pipeline on a Hadoop-based platform. Wall-clock time for complete assembly differed by 52.9% (95% CI: 27.5-78.2) for E.coli and 53.5% (95% CI: 34.4-72.6) for human genome, with GCE being more efficient than EMR. The cost of running this experiment on EMR and GCE differed significantly, with the costs on EMR being 257.3% (95% CI: 211.5-303.1) and 173.9% (95% CI: 134.6-213.1) more expensive for E.coli and human assemblies respectively. Thus, GCE was found to outperform EMR both in terms of cost and wall-clock time. Our findings confirm that cloud computing is an efficient and potentially cost-effective alternative for analysis of large genomic datasets. In addition to releasing our cost-effectiveness comparison, we present available ready-to-use scripts for establishing Hadoop instances with Ganglia monitoring on EC2 or GCE.

  16. Towards Dynamic Remote Data Auditing in Computational Clouds

    PubMed Central

    Khurram Khan, Muhammad; Anuar, Nor Badrul

    2014-01-01

    Cloud computing is a significant shift of computational paradigm where computing as a utility and storing data remotely have a great potential. Enterprise and businesses are now more interested in outsourcing their data to the cloud to lessen the burden of local data storage and maintenance. However, the outsourced data and the computation outcomes are not continuously trustworthy due to the lack of control and physical possession of the data owners. To better streamline this issue, researchers have now focused on designing remote data auditing (RDA) techniques. The majority of these techniques, however, are only applicable for static archive data and are not subject to audit the dynamically updated outsourced data. We propose an effectual RDA technique based on algebraic signature properties for cloud storage system and also present a new data structure capable of efficiently supporting dynamic data operations like append, insert, modify, and delete. Moreover, this data structure empowers our method to be applicable for large-scale data with minimum computation cost. The comparative analysis with the state-of-the-art RDA schemes shows that the proposed scheme is secure and highly efficient in terms of the computation and communication overhead on the auditor and server. PMID:25121114

  17. Towards dynamic remote data auditing in computational clouds.

    PubMed

    Sookhak, Mehdi; Akhunzada, Adnan; Gani, Abdullah; Khurram Khan, Muhammad; Anuar, Nor Badrul

    2014-01-01

    Cloud computing is a significant shift of computational paradigm where computing as a utility and storing data remotely have a great potential. Enterprise and businesses are now more interested in outsourcing their data to the cloud to lessen the burden of local data storage and maintenance. However, the outsourced data and the computation outcomes are not continuously trustworthy due to the lack of control and physical possession of the data owners. To better streamline this issue, researchers have now focused on designing remote data auditing (RDA) techniques. The majority of these techniques, however, are only applicable for static archive data and are not subject to audit the dynamically updated outsourced data. We propose an effectual RDA technique based on algebraic signature properties for cloud storage system and also present a new data structure capable of efficiently supporting dynamic data operations like append, insert, modify, and delete. Moreover, this data structure empowers our method to be applicable for large-scale data with minimum computation cost. The comparative analysis with the state-of-the-art RDA schemes shows that the proposed scheme is secure and highly efficient in terms of the computation and communication overhead on the auditor and server.

  18. Cloud Computing and the Power to Choose

    ERIC Educational Resources Information Center

    Bristow, Rob; Dodds, Ted; Northam, Richard; Plugge, Leo

    2010-01-01

    Some of the most significant changes in information technology are those that have given the individual user greater power to choose. The first of these changes was the development of the personal computer. The PC liberated the individual user from the limitations of the mainframe and minicomputers and from the rules and regulations of centralized…

  19. BOINC service for volunteer cloud computing

    NASA Astrophysics Data System (ADS)

    Høimyr, N.; Blomer, J.; Buncic, P.; Giovannozzi, M.; Gonzalez, A.; Harutyunyan, A.; Jones, P. L.; Karneyeu, A.; Marquina, M. A.; Mcintosh, E.; Segal, B.; Skands, P.; Grey, F.; Lombraña González, D.; Zacharov, I.

    2012-12-01

    Since a couple of years, a team at CERN and partners from the Citizen Cyberscience Centre (CCC) have been working on a project that enables general physics simulation programs to run in a virtual machine on volunteer PCs around the world. The project uses the Berkeley Open Infrastructure for Network Computing (BOINC) framework. Based on CERNVM and the job management framework Co-Pilot, this project was made available for public beta-testing in August 2011 with Monte Carlo simulations of LHC physics under the name “LHC@home 2.0” and the BOINC project: “Test4Theory”. At the same time, CERN's efforts on Volunteer Computing for LHC machine studies have been intensified; this project has previously been known as LHC@home, and has been running the “Sixtrack” beam dynamics application for the LHC accelerator, using a classic BOINC framework without virtual machines. CERN-IT has set up a BOINC server cluster, and has provided and supported the BOINC infrastructure for both projects. CERN intends to evolve the setup into a generic BOINC application service that will allow scientists and engineers at CERN to profit from volunteer computing. This paper describes the experience with the two different approaches to volunteer computing as well as the status and outlook of a general BOINC service.

  20. Cloud Computing Technologies Facilitate Earth Research

    NASA Technical Reports Server (NTRS)

    2015-01-01

    Under a Space Act Agreement, NASA partnered with Seattle-based Amazon Web Services to make the agency's climate and Earth science satellite data publicly available on the company's servers. Users can access the data for free, but they can also pay to use Amazon's computing services to analyze and visualize information using the same software available to NASA researchers.

  1. Computer tomography of large dust clouds in complex plasmas.

    PubMed

    Killer, Carsten; Himpel, Michael; Melzer, André

    2014-10-01

    The dust density is a central parameter of a dusty plasma. Here, a tomography setup for the determination of the three-dimensionally resolved density distribution of spatially extended dust clouds is presented. The dust clouds consist of micron-sized particles confined in a radio frequency argon plasma, where they fill almost the entire discharge volume. First, a line-of-sight integrated dust density is obtained from extinction measurements, where the incident light from an LED panel is scattered and absorbed by the dust. Performing these extinction measurements from many different angles allows the reconstruction of the 3D dust density distribution, analogous to a computer tomography in medical applications.

  2. Computer tomography of large dust clouds in complex plasmas

    SciTech Connect

    Killer, Carsten; Himpel, Michael; Melzer, André

    2014-10-15

    The dust density is a central parameter of a dusty plasma. Here, a tomography setup for the determination of the three-dimensionally resolved density distribution of spatially extended dust clouds is presented. The dust clouds consist of micron-sized particles confined in a radio frequency argon plasma, where they fill almost the entire discharge volume. First, a line-of-sight integrated dust density is obtained from extinction measurements, where the incident light from an LED panel is scattered and absorbed by the dust. Performing these extinction measurements from many different angles allows the reconstruction of the 3D dust density distribution, analogous to a computer tomography in medical applications.

  3. Facilitating NASA Earth Science Data Processing Using Nebula Cloud Computing

    NASA Astrophysics Data System (ADS)

    Chen, A.; Pham, L.; Kempler, S.; Theobald, M.; Esfandiari, A.; Campino, J.; Vollmer, B.; Lynnes, C.

    2011-12-01

    Cloud Computing technology has been used to offer high-performance and low-cost computing and storage resources for both scientific problems and business services. Several cloud computing services have been implemented in the commercial arena, e.g. Amazon's EC2 & S3, Microsoft's Azure, and Google App Engine. There are also some research and application programs being launched in academia and governments to utilize Cloud Computing. NASA launched the Nebula Cloud Computing platform in 2008, which is an Infrastructure as a Service (IaaS) to deliver on-demand distributed virtual computers. Nebula users can receive required computing resources as a fully outsourced service. NASA Goddard Earth Science Data and Information Service Center (GES DISC) migrated several GES DISC's applications to the Nebula as a proof of concept, including: a) The Simple, Scalable, Script-based Science Processor for Measurements (S4PM) for processing scientific data; b) the Atmospheric Infrared Sounder (AIRS) data process workflow for processing AIRS raw data; and c) the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (GIOVANNI) for online access to, analysis, and visualization of Earth science data. This work aims to evaluate the practicability and adaptability of the Nebula. The initial work focused on the AIRS data process workflow to evaluate the Nebula. The AIRS data process workflow consists of a series of algorithms being used to process raw AIRS level 0 data and output AIRS level 2 geophysical retrievals. Migrating the entire workflow to the Nebula platform is challenging, but practicable. After installing several supporting libraries and the processing code itself, the workflow is able to process AIRS data in a similar fashion to its current (non-cloud) configuration. We compared the performance of processing 2 days of AIRS level 0 data through level 2 using a Nebula virtual computer and a local Linux computer. The result shows that Nebula has significantly

  4. Smart learning services based on smart cloud computing.

    PubMed

    Kim, Svetlana; Song, Su-Mi; Yoon, Yong-Ik

    2011-01-01

    Context-aware technologies can make e-learning services smarter and more efficient since context-aware services are based on the user's behavior. To add those technologies into existing e-learning services, a service architecture model is needed to transform the existing e-learning environment, which is situation-aware, into the environment that understands context as well. The context-awareness in e-learning may include the awareness of user profile and terminal context. In this paper, we propose a new notion of service that provides context-awareness to smart learning content in a cloud computing environment. We suggest the elastic four smarts (E4S)--smart pull, smart prospect, smart content, and smart push--concept to the cloud services so smart learning services are possible. The E4S focuses on meeting the users' needs by collecting and analyzing users' behavior, prospecting future services, building corresponding contents, and delivering the contents through cloud computing environment. Users' behavior can be collected through mobile devices such as smart phones that have built-in sensors. As results, the proposed smart e-learning model in cloud computing environment provides personalized and customized learning services to its users.

  5. Cloud Computing Test Bed for NASA Earth Observation

    NASA Astrophysics Data System (ADS)

    Klene, S. A.; Murphy, K. J.; Fertetta, M.; Law, E.; Wilson, B. D.; Hua, H.; Huang, T.

    2014-12-01

    In order to develop a deeper understanding of utilizing cloud computing technologies for using earth observation data processing a test bed was created to ease access to the technology. Users had expressed concerns about accruing large compute bills by accident while they are learning to use the technology. The test bed is to support NASA efforts such as: Developing a Science Data Service platform to handle big earth data for supporting scalable time and space searches, on-the-fly climatologies, data extraction and data transformation such as data re-gridding. Multi-sensor climate data fusion where users can select, merge and cache variables from multiple sensors to compare data over multiple years. Facilitate rapid prototype efforts to provide an infrastructure so that new development efforts do not need to spend time and effort obtaining a platform. Once successful development is done the application could then scale to very large platform on larger or commercial clouds. Goals of the test bed are: To provide a greater understanding of cloud computing so informed choices can be made on future efforts to handle the over 15 Petabytes of NASA earth science data. Provide an environment where a set of science tools can be developed and reused by multiple earth science disciplines. Develop a Platform as a Service (PaaS) capability for general earth science use. This talk will present the lessons learned from building a community cloud for earth science data.

  6. Smart Learning Services Based on Smart Cloud Computing

    PubMed Central

    Kim, Svetlana; Song, Su-Mi; Yoon, Yong-Ik

    2011-01-01

    Context-aware technologies can make e-learning services smarter and more efficient since context-aware services are based on the user’s behavior. To add those technologies into existing e-learning services, a service architecture model is needed to transform the existing e-learning environment, which is situation-aware, into the environment that understands context as well. The context-awareness in e-learning may include the awareness of user profile and terminal context. In this paper, we propose a new notion of service that provides context-awareness to smart learning content in a cloud computing environment. We suggest the elastic four smarts (E4S)—smart pull, smart prospect, smart content, and smart push—concept to the cloud services so smart learning services are possible. The E4S focuses on meeting the users’ needs by collecting and analyzing users’ behavior, prospecting future services, building corresponding contents, and delivering the contents through cloud computing environment. Users’ behavior can be collected through mobile devices such as smart phones that have built-in sensors. As results, the proposed smart e-learning model in cloud computing environment provides personalized and customized learning services to its users. PMID:22164048

  7. 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.

  8. 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

    ... National Institute of Standards and Technology Notice of Public Meeting--Cloud Computing and Big Data Forum...) announces a Cloud Computing and Big Data Forum and Workshop to be held on Tuesday, January 15, Wednesday... workshop. The NIST Cloud Computing and Big Data Forum and Workshop will bring together leaders...

  9. 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…

  10. 76 FR 62373 - Notice of Public Meeting-Cloud Computing Forum & Workshop IV

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-07

    ... National Institute of Standards and Technology Notice of Public Meeting--Cloud Computing Forum & Workshop...: NIST announces the Cloud Computing Forum & Workshop IV to be held on November 2, 3 and 4, 2011. This workshop will provide information on the U.S. Government (USG) Cloud Computing Technology...

  11. 77 FR 26509 - Notice of Public Meeting-Cloud Computing Forum & Workshop V

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-05-04

    ... National Institute of Standards and Technology Notice of Public Meeting--Cloud Computing Forum & Workshop V... announces the Cloud Computing Forum & Workshop V to be held on Tuesday, Wednesday and Thursday, June 5, 6... provide information on the U.S. Government (USG) Cloud Computing Technology Roadmap initiative....

  12. 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…

  13. Hybrid cloud and cluster computing paradigms for life science applications

    PubMed Central

    2010-01-01

    Background Clouds and MapReduce have shown themselves to be a broadly useful approach to scientific computing especially for parallel data intensive applications. However they have limited applicability to some areas such as data mining because MapReduce has poor performance on problems with an iterative structure present in the linear algebra that underlies much data analysis. Such problems can be run efficiently on clusters using MPI leading to a hybrid cloud and cluster environment. This motivates the design and implementation of an open source Iterative MapReduce system Twister. Results Comparisons of Amazon, Azure, and traditional Linux and Windows environments on common applications have shown encouraging performance and usability comparisons in several important non iterative cases. These are linked to MPI applications for final stages of the data analysis. Further we have released the open source Twister Iterative MapReduce and benchmarked it against basic MapReduce (Hadoop) and MPI in information retrieval and life sciences applications. Conclusions The hybrid cloud (MapReduce) and cluster (MPI) approach offers an attractive production environment while Twister promises a uniform programming environment for many Life Sciences applications. Methods We used commercial clouds Amazon and Azure and the NSF resource FutureGrid to perform detailed comparisons and evaluations of different approaches to data intensive computing. Several applications were developed in MPI, MapReduce and Twister in these different environments. PMID:21210982

  14. A lightweight distributed framework for computational offloading in mobile cloud computing.

    PubMed

    Shiraz, Muhammad; Gani, Abdullah; Ahmad, Raja Wasim; Adeel Ali Shah, Syed; Karim, Ahmad; Rahman, Zulkanain Abdul

    2014-01-01

    The latest developments in mobile computing technology have enabled intensive applications on the modern Smartphones. However, such applications are still constrained by limitations in processing potentials, storage capacity and battery lifetime of the Smart Mobile Devices (SMDs). Therefore, Mobile Cloud Computing (MCC) leverages the application processing services of computational clouds for mitigating resources limitations in SMDs. Currently, a number of computational offloading frameworks are proposed for MCC wherein the intensive components of the application are outsourced to computational clouds. Nevertheless, such frameworks focus on runtime partitioning of the application for computational offloading, which is time consuming and resources intensive. The resource constraint nature of SMDs require lightweight procedures for leveraging computational clouds. Therefore, this paper presents a lightweight framework which focuses on minimizing additional resources utilization in computational offloading for MCC. The framework employs features of centralized monitoring, high availability and on demand access services of computational clouds for computational offloading. As a result, the turnaround time and execution cost of the application are reduced. The framework is evaluated by testing prototype application in the real MCC environment. The lightweight nature of the proposed framework is validated by employing computational offloading for the proposed framework and the latest existing frameworks. Analysis shows that by employing the proposed framework for computational offloading, the size of data transmission is reduced by 91%, energy consumption cost is minimized by 81% and turnaround time of the application is decreased by 83.5% as compared to the existing offloading frameworks. Hence, the proposed framework minimizes additional resources utilization and therefore offers lightweight solution for computational offloading in MCC.

  15. A Lightweight Distributed Framework for Computational Offloading in Mobile Cloud Computing

    PubMed Central

    Shiraz, Muhammad; Gani, Abdullah; Ahmad, Raja Wasim; Adeel Ali Shah, Syed; Karim, Ahmad; Rahman, Zulkanain Abdul

    2014-01-01

    The latest developments in mobile computing technology have enabled intensive applications on the modern Smartphones. However, such applications are still constrained by limitations in processing potentials, storage capacity and battery lifetime of the Smart Mobile Devices (SMDs). Therefore, Mobile Cloud Computing (MCC) leverages the application processing services of computational clouds for mitigating resources limitations in SMDs. Currently, a number of computational offloading frameworks are proposed for MCC wherein the intensive components of the application are outsourced to computational clouds. Nevertheless, such frameworks focus on runtime partitioning of the application for computational offloading, which is time consuming and resources intensive. The resource constraint nature of SMDs require lightweight procedures for leveraging computational clouds. Therefore, this paper presents a lightweight framework which focuses on minimizing additional resources utilization in computational offloading for MCC. The framework employs features of centralized monitoring, high availability and on demand access services of computational clouds for computational offloading. As a result, the turnaround time and execution cost of the application are reduced. The framework is evaluated by testing prototype application in the real MCC environment. The lightweight nature of the proposed framework is validated by employing computational offloading for the proposed framework and the latest existing frameworks. Analysis shows that by employing the proposed framework for computational offloading, the size of data transmission is reduced by 91%, energy consumption cost is minimized by 81% and turnaround time of the application is decreased by 83.5% as compared to the existing offloading frameworks. Hence, the proposed framework minimizes additional resources utilization and therefore offers lightweight solution for computational offloading in MCC. PMID:25127245

  16. A Computer-Assisted Instruction in Teaching Abstract Statistics to Public Affairs Undergraduates

    ERIC Educational Resources Information Center

    Ozturk, Ali Osman

    2012-01-01

    This article attempts to demonstrate the applicability of a computer-assisted instruction supported with simulated data in teaching abstract statistical concepts to political science and public affairs students in an introductory research methods course. The software is called the Elaboration Model Computer Exercise (EMCE) in that it takes a great…

  17. Abstracts of computer programs and data libraries pertaining to photon production data

    SciTech Connect

    White, J.E.; Manneschmidt, J.B.; Finch, S.Y.; Dickens, J.K.

    1998-06-01

    Abstracts, or descriptions, of computer programs and data libraries pertaining to Photon Production Data (Measurements, Evaluations and Calculations) maintained in the collections of the Radiation Safety Information Computational Center, Oak Ridge, Tennessee USA and at the OECD/NEA Data Bank, Paris, are collected in this document.

  18. Two-Cloud-Servers-Assisted Secure Outsourcing Multiparty Computation

    PubMed Central

    Wen, Qiaoyan; Zhang, Hua; Jin, Zhengping; Li, Wenmin

    2014-01-01

    We focus on how to securely outsource computation task to the cloud and propose a secure outsourcing multiparty computation protocol on lattice-based encrypted data in two-cloud-servers scenario. Our main idea is to transform the outsourced data respectively encrypted by different users' public keys to the ones that are encrypted by the same two private keys of the two assisted servers so that it is feasible to operate on the transformed ciphertexts to compute an encrypted result following the function to be computed. In order to keep the privacy of the result, the two servers cooperatively produce a custom-made result for each user that is authorized to get the result so that all authorized users can recover the desired result while other unauthorized ones including the two servers cannot. Compared with previous research, our protocol is completely noninteractive between any users, and both of the computation and the communication complexities of each user in our solution are independent of the computing function. PMID:24982949

  19. Two-cloud-servers-assisted secure outsourcing multiparty computation.

    PubMed

    Sun, Yi; Wen, Qiaoyan; Zhang, Yudong; Zhang, Hua; Jin, Zhengping; Li, Wenmin

    2014-01-01

    We focus on how to securely outsource computation task to the cloud and propose a secure outsourcing multiparty computation protocol on lattice-based encrypted data in two-cloud-servers scenario. Our main idea is to transform the outsourced data respectively encrypted by different users' public keys to the ones that are encrypted by the same two private keys of the two assisted servers so that it is feasible to operate on the transformed ciphertexts to compute an encrypted result following the function to be computed. In order to keep the privacy of the result, the two servers cooperatively produce a custom-made result for each user that is authorized to get the result so that all authorized users can recover the desired result while other unauthorized ones including the two servers cannot. Compared with previous research, our protocol is completely noninteractive between any users, and both of the computation and the communication complexities of each user in our solution are independent of the computing function.

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

    DTIC Science & Technology

    2010-09-01

    Provides developers with tools to build their own cloud computing infrastructures [3tera 2010] Eucalyptus Systems: Provides an open-source...for cloud computing [ Eucalyptus 2010]. 5 The National Institute of Standards and Technology (NIST) defines two additional types of cloud...40 | CMU/SEI-2010-TN-009 5 Conclusions and Open Questions Cloud computing is in essence an economic model—a different way to acquire and manage

  1. Energy Conservation Using Dynamic Voltage Frequency Scaling for Computational Cloud

    PubMed Central

    Florence, A. Paulin; Shanthi, V.; Simon, C. B. Sunil

    2016-01-01

    Cloud computing is a new technology which supports resource sharing on a “Pay as you go” basis around the world. It provides various services such as SaaS, IaaS, and PaaS. Computation is a part of IaaS and the entire computational requests are to be served efficiently with optimal power utilization in the cloud. Recently, various algorithms are developed to reduce power consumption and even Dynamic Voltage and Frequency Scaling (DVFS) scheme is also used in this perspective. In this paper we have devised methodology which analyzes the behavior of the given cloud request and identifies the associated type of algorithm. Once the type of algorithm is identified, using their asymptotic notations, its time complexity is calculated. Using best fit strategy the appropriate host is identified and the incoming job is allocated to the victimized host. Using the measured time complexity the required clock frequency of the host is measured. According to that CPU frequency is scaled up or down using DVFS scheme, enabling energy to be saved up to 55% of total Watts consumption. PMID:27239551

  2. Energy Conservation Using Dynamic Voltage Frequency Scaling for Computational Cloud.

    PubMed

    Florence, A Paulin; Shanthi, V; Simon, C B Sunil

    2016-01-01

    Cloud computing is a new technology which supports resource sharing on a "Pay as you go" basis around the world. It provides various services such as SaaS, IaaS, and PaaS. Computation is a part of IaaS and the entire computational requests are to be served efficiently with optimal power utilization in the cloud. Recently, various algorithms are developed to reduce power consumption and even Dynamic Voltage and Frequency Scaling (DVFS) scheme is also used in this perspective. In this paper we have devised methodology which analyzes the behavior of the given cloud request and identifies the associated type of algorithm. Once the type of algorithm is identified, using their asymptotic notations, its time complexity is calculated. Using best fit strategy the appropriate host is identified and the incoming job is allocated to the victimized host. Using the measured time complexity the required clock frequency of the host is measured. According to that CPU frequency is scaled up or down using DVFS scheme, enabling energy to be saved up to 55% of total Watts consumption.

  3. 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.

  4. Tavaxy: Integrating Taverna and Galaxy workflows with cloud computing support

    PubMed Central

    2012-01-01

    Background Over the past decade the workflow system paradigm has evolved as an efficient and user-friendly approach for developing complex bioinformatics applications. Two popular workflow systems that have gained acceptance by the bioinformatics community are Taverna and Galaxy. Each system has a large user-base and supports an ever-growing repository of application workflows. However, workflows developed for one system cannot be imported and executed easily on the other. The lack of interoperability is due to differences in the models of computation, workflow languages, and architectures of both systems. This lack of interoperability limits sharing of workflows between the user communities and leads to duplication of development efforts. Results In this paper, we present Tavaxy, a stand-alone system for creating and executing workflows based on using an extensible set of re-usable workflow patterns. Tavaxy offers a set of new features that simplify and enhance the development of sequence analysis applications: It allows the integration of existing Taverna and Galaxy workflows in a single environment, and supports the use of cloud computing capabilities. The integration of existing Taverna and Galaxy workflows is supported seamlessly at both run-time and design-time levels, based on the concepts of hierarchical workflows and workflow patterns. The use of cloud computing in Tavaxy is flexible, where the users can either instantiate the whole system on the cloud, or delegate the execution of certain sub-workflows to the cloud infrastructure. Conclusions Tavaxy reduces the workflow development cycle by introducing the use of workflow patterns to simplify workflow creation. It enables the re-use and integration of existing (sub-) workflows from Taverna and Galaxy, and allows the creation of hybrid workflows. Its additional features exploit recent advances in high performance cloud computing to cope with the increasing data size and complexity of analysis. The system

  5. A Cloud Computing Platform for Large-Scale Forensic Computing

    NASA Astrophysics Data System (ADS)

    Roussev, Vassil; Wang, Liqiang; Richard, Golden; Marziale, Lodovico

    The timely processing of massive digital forensic collections demands the use of large-scale distributed computing resources and the flexibility to customize the processing performed on the collections. This paper describes MPI MapReduce (MMR), an open implementation of the MapReduce processing model that outperforms traditional forensic computing techniques. MMR provides linear scaling for CPU-intensive processing and super-linear scaling for indexing-related workloads.

  6. Computer Education and Instructional Technology Teacher Trainees' Opinions about Cloud Computing Technology

    ERIC Educational Resources Information Center

    Karamete, Aysen

    2015-01-01

    This study aims to show the present conditions about the usage of cloud computing in the department of Computer Education and Instructional Technology (CEIT) amongst teacher trainees in School of Necatibey Education, Balikesir University, Turkey. In this study, a questionnaire with open-ended questions was used. 17 CEIT teacher trainees…

  7. cloudPEST - A python module for cloud-computing deployment of PEST, a program for parameter estimation

    USGS Publications Warehouse

    Fienen, Michael N.; Kunicki, Thomas C.; Kester, Daniel E.

    2011-01-01

    This report documents cloudPEST-a Python module with functions to facilitate deployment of the model-independent parameter estimation code PEST on a cloud-computing environment. cloudPEST makes use of low-level, freely available command-line tools that interface with the Amazon Elastic Compute Cloud (EC2(TradeMark)) that are unlikely to change dramatically. This report describes the preliminary setup for both Python and EC2 tools and subsequently describes the functions themselves. The code and guidelines have been tested primarily on the Windows(Registered) operating system but are extensible to Linux(Registered).

  8. 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.

  9. 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.

  10. Providing Assistive Technology Applications as a Service Through Cloud Computing.

    PubMed

    Mulfari, Davide; Celesti, Antonio; Villari, Massimo; Puliafito, Antonio

    2015-01-01

    Users with disabilities interact with Personal Computers (PCs) using Assistive Technology (AT) software solutions. Such applications run on a PC that a person with a disability commonly uses. However the configuration of AT applications is not trivial at all, especially whenever the user needs to work on a PC that does not allow him/her to rely on his / her AT tools (e.g., at work, at university, in an Internet point). In this paper, we discuss how cloud computing provides a valid technological solution to enhance such a scenario.With the emergence of cloud computing, many applications are executed on top of virtual machines (VMs). Virtualization allows us to achieve a software implementation of a real computer able to execute a standard operating system and any kind of application. In this paper we propose to build personalized VMs running AT programs and settings. By using the remote desktop technology, our solution enables users to control their customized virtual desktop environment by means of an HTML5-based web interface running on any computer equipped with a browser, whenever they are.

  11. SC2IT: a cloud computing interface that makes computational science available to non-specialists

    NASA Astrophysics Data System (ADS)

    Jorissen, Kevin; Vila, Fernando; Rehr, John

    2012-10-01

    Computational work is a vital part of much scientific research. In materials science research in particular, theoretical models are usually needed to understand measurements. There is currently a double barrier that keeps a broad class of researchers from using state-of-the-art materials science (MS) codes: the software typically lacks user-friendliness, and the hardware requirements can demand a significant investment, e.g. the purchase of a Beowulf cluster. Scientific Cloud Computing (SCC) has the potential to breach this barrier and make computational science accessible to a wide class of non-specialists scientists. We present a platform, SC2IT, that enables seamless control of virtual compute clusters in the Amazon EC2 cloud and is designed to be embedded in user-friendly Java GUIs. Thus users can create powerful High-Performance Computing systems with preconfigured MS codes in the cloud with a single mouse click. We present applications of our SCC platform to the materials science codes FEFF9, WIEN2k, and MEEP-mpi. SC2IT and the paradigm described here are applicable to other fields of research beyond materials science, although the computational performance of Cloud Computing may vary with the characteristics of the calculations.

  12. 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,…

  13. Performance Evaluation of Resource Management in Cloud Computing Environments.

    PubMed

    Batista, Bruno Guazzelli; Estrella, Julio Cezar; Ferreira, Carlos Henrique Gomes; Filho, Dionisio Machado Leite; Nakamura, Luis Hideo Vasconcelos; Reiff-Marganiec, Stephan; Santana, Marcos José; Santana, Regina Helena Carlucci

    2015-01-01

    Cloud computing is a computational model in which resource providers can offer on-demand services to clients in a transparent way. However, to be able to guarantee quality of service without limiting the number of accepted requests, providers must be able to dynamically manage the available resources so that they can be optimized. This dynamic resource management is not a trivial task, since it involves meeting several challenges related to workload modeling, virtualization, performance modeling, deployment and monitoring of applications on virtualized resources. This paper carries out a performance evaluation of a module for resource management in a cloud environment that includes handling available resources during execution time and ensuring the quality of service defined in the service level agreement. An analysis was conducted of different resource configurations to define which dimension of resource scaling has a real influence on client requests. The results were used to model and implement a simulated cloud system, in which the allocated resource can be changed on-the-fly, with a corresponding change in price. In this way, the proposed module seeks to satisfy both the client by ensuring quality of service, and the provider by ensuring the best use of resources at a fair price.

  14. DoD Cloud Computing Strategy Needs Implementation Plan and Detailed Waiver Process

    DTIC Science & Technology

    2014-12-04

    specialists to use when acquiring cloud services. The matrix contains 21 issues specific to cloud computing that should be addressed in cloud computing...No. DODIG-2015-045 D E C E M B E R 4 , 2 0 1 4 DoD Cloud Computing Strategy Needs Implementation Plan and Detailed Waiver Process Report...REPORT TYPE 3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE DoD Cloud Computing Strategy Needs Implementation Plan and Detailed

  15. Cloud computing geospatial application for water resources based on free and open source software and open standards - a prototype

    NASA Astrophysics Data System (ADS)

    Delipetrev, Blagoj

    2016-04-01

    Presently, most of the existing software is desktop-based, designed to work on a single computer, which represents a major limitation in many ways, starting from limited computer processing, storage power, accessibility, availability, etc. The only feasible solution lies in the web and cloud. This abstract presents research and development of a cloud computing geospatial application for water resources based on free and open source software and open standards using hybrid deployment model of public - private cloud, running on two separate virtual machines (VMs). The first one (VM1) is running on Amazon web services (AWS) and the second one (VM2) is running on a Xen cloud platform. The presented cloud application is developed using free and open source software, open standards and prototype code. The cloud application presents a framework how to develop specialized cloud geospatial application that needs only a web browser to be used. This cloud application is the ultimate collaboration geospatial platform because multiple users across the globe with internet connection and browser can jointly model geospatial objects, enter attribute data and information, execute algorithms, and visualize results. The presented cloud application is: available all the time, accessible from everywhere, it is scalable, works in a distributed computer environment, it creates a real-time multiuser collaboration platform, the programing languages code and components are interoperable, and it is flexible in including additional components. The cloud geospatial application is implemented as a specialized water resources application with three web services for 1) data infrastructure (DI), 2) support for water resources modelling (WRM), 3) user management. The web services are running on two VMs that are communicating over the internet providing services to users. The application was tested on the Zletovica river basin case study with concurrent multiple users. The application is a state

  16. 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.…

  17. Change Detection of Mobile LIDAR Data Using Cloud Computing

    NASA Astrophysics Data System (ADS)

    Liu, Kun; Boehm, Jan; Alis, Christian

    2016-06-01

    Change detection has long been a challenging problem although a lot of research has been conducted in different fields such as remote sensing and photogrammetry, computer vision, and robotics. In this paper, we blend voxel grid and Apache Spark together to propose an efficient method to address the problem in the context of big data. Voxel grid is a regular geometry representation consisting of the voxels with the same size, which fairly suites parallel computation. Apache Spark is a popular distributed parallel computing platform which allows fault tolerance and memory cache. These features can significantly enhance the performance of Apache Spark and results in an efficient and robust implementation. In our experiments, both synthetic and real point cloud data are employed to demonstrate the quality of our method.

  18. Cloud identification using genetic algorithms and massively parallel computation

    NASA Technical Reports Server (NTRS)

    Buckles, Bill P.; Petry, Frederick E.

    1996-01-01

    As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMS) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here the results were mixed (60% to 80% accuracy). Given that one is willing to run the experiment several times (say 10), then it is acceptable to claim the higher accuracy rating. This problem has never been successfully automated. Therefore, these results are encouraging even though less impressive than the cloud experiment. Successful conclusion of an automated ocean current detection system would impact coastal fishing, naval tactics, and the study of micro-climates. Finally we contributed to the basic knowledge of GA (genetic algorithm) behavior in parallel environments. We developed better knowledge of the use of subpopulations in the context of shared breeding pools and the migration of individuals. Rigorous experiments were conducted based on quantifiable performance criteria. While much of the work confirmed current wisdom, for the first time we were able to submit conclusive evidence. The software developed under this grant was placed in the public domain. An extensive user

  19. Assessing the Amazon Cloud Suitability for CLARREO's Computational Needs

    NASA Technical Reports Server (NTRS)

    Goldin, Daniel; Vakhnin, Andrei A.; Currey, Jon C.

    2015-01-01

    In this document we compare the performance of the Amazon Web Services (AWS), also known as Amazon Cloud, with the CLARREO (Climate Absolute Radiance and Refractivity Observatory) cluster and assess its suitability for computational needs of the CLARREO mission. A benchmark executable to process one month and one year of PARASOL (Polarization and Anistropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) data was used. With the optimal AWS configuration, adequate data-processing times, comparable to the CLARREO cluster, were found. The assessment of alternatives to the CLARREO cluster continues and several options, such as a NASA-based cluster, are being considered.

  20. Computational biology in the cloud: methods and new insights from computing at scale.

    PubMed

    Kasson, Peter M

    2013-01-01

    The past few years have seen both explosions in the size of biological data sets and the proliferation of new, highly flexible on-demand computing capabilities. The sheer amount of information available from genomic and metagenomic sequencing, high-throughput proteomics, experimental and simulation datasets on molecular structure and dynamics affords an opportunity for greatly expanded insight, but it creates new challenges of scale for computation, storage, and interpretation of petascale data. Cloud computing resources have the potential to help solve these problems by offering a utility model of computing and storage: near-unlimited capacity, the ability to burst usage, and cheap and flexible payment models. Effective use of cloud computing on large biological datasets requires dealing with non-trivial problems of scale and robustness, since performance-limiting factors can change substantially when a dataset grows by a factor of 10,000 or more. New computing paradigms are thus often needed. The use of cloud platforms also creates new opportunities to share data, reduce duplication, and to provide easy reproducibility by making the datasets and computational methods easily available.

  1. Teaching, Learning, and Collaborating in the Cloud: Applications of Cloud Computing for Educators in Post-Secondary Institutions

    ERIC Educational Resources Information Center

    Aaron, Lynn S.; Roche, Catherine M.

    2012-01-01

    "Cloud computing" refers to the use of computing resources on the Internet instead of on individual personal computers. The field is expanding and has significant potential value for educators. This is discussed with a focus on four main functions: file storage, file synchronization, document creation, and collaboration--each of which has…

  2. 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

  3. 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.

  4. Easy, Collaborative and Engaging--The Use of Cloud Computing in the Design of Management Classrooms

    ERIC Educational Resources Information Center

    Schneckenberg, Dirk

    2014-01-01

    Background: Cloud computing has recently received interest in information systems research and practice as a new way to organise information with the help of an increasingly ubiquitous computer infrastructure. However, the use of cloud computing in higher education institutions and business schools, as well as its potential to create novel…

  5. Migrating Educational Data and Services to Cloud Computing: Exploring Benefits and Challenges

    ERIC Educational Resources Information Center

    Lahiri, Minakshi; Moseley, James L.

    2013-01-01

    "Cloud computing" is currently the "buzzword" in the Information Technology field. Cloud computing facilitates convenient access to information and software resources as well as easy storage and sharing of files and data, without the end users being aware of the details of the computing technology behind the process. This…

  6. 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.

  7. Indoor scene classification of robot vision based on cloud computing

    NASA Astrophysics Data System (ADS)

    Hu, Tao; Qi, Yuxiao; Li, Shipeng

    2016-07-01

    For intelligent service robots, indoor scene classification is an important issue. To overcome the weak real-time performance of conventional algorithms, a new method based on Cloud computing is proposed for global image features in indoor scene classification. With MapReduce method, global PHOG feature of indoor scene image is extracted in parallel. And, feature eigenvector is used to train the decision classifier through SVM concurrently. Then, the indoor scene is validly classified by decision classifier. To verify the algorithm performance, we carried out an experiment with 350 typical indoor scene images from MIT LabelMe image library. Experimental results show that the proposed algorithm can attain better real-time performance. Generally, it is 1.4 2.1 times faster than traditional classification methods which rely on single computation, while keeping stable classification correct rate as 70%.

  8. A hierarchical method for molecular docking using cloud computing.

    PubMed

    Kang, Ling; Guo, Quan; Wang, Xicheng

    2012-11-01

    Discovering small molecules that interact with protein targets will be a key part of future drug discovery efforts. Molecular docking of drug-like molecules is likely to be valuable in this field; however, the great number of such molecules makes the potential size of this task enormous. In this paper, a method to screen small molecular databases using cloud computing is proposed. This method is called the hierarchical method for molecular docking and can be completed in a relatively short period of time. In this method, the optimization of molecular docking is divided into two subproblems based on the different effects on the protein-ligand interaction energy. An adaptive genetic algorithm is developed to solve the optimization problem and a new docking program (FlexGAsDock) based on the hierarchical docking method has been developed. The implementation of docking on a cloud computing platform is then discussed. The docking results show that this method can be conveniently used for the efficient molecular design of drugs.

  9. Data Sets, Ensemble Cloud Computing, and the University Library (Invited)

    NASA Astrophysics Data System (ADS)

    Plale, B. A.

    2013-12-01

    The environmental researcher at the public university has new resources at their disposal to aid in research and publishing. Cloud computing provides compute cycles on demand for analysis and modeling scenarios. Cloud computing is attractive for e-Science because of the ease with which cores can be accessed on demand, and because the virtual machine implementation that underlies cloud computing reduces the cost of porting a numeric or analysis code to a new platform. At the university, many libraries at larger universities are developing the e-Science skills to serve as repositories of record for publishable data sets. But these are confusing times for the publication of data sets from environmental research. The large publishers of scientific literature are advocating a process whereby data sets are tightly tied to a publication. In other words, a paper published in the scientific literature that gives results based on data, must have an associated data set accessible that backs up the results. This approach supports reproducibility of results in that publishers maintain a repository for the papers they publish, and the data sets that the papers used. Does such a solution that maps one data set (or subset) to one paper fit the needs of the environmental researcher who among other things uses complex models, mines longitudinal data bases, and generates observational results? The second school of thought has emerged out of NSF, NOAA, and NASA funded efforts over time: data sets exist coherent at a location, such as occurs at National Snow and Ice Data Center (NSIDC). But when a collection is coherent, reproducibility of individual results is more challenging. We argue for a third complementary option: the university repository as a location for data sets produced as a result of university-based research. This location for a repository relies on the expertise developing in the university libraries across the country, and leverages tools, such as are being developed

  10. Computational study on SiH4 dissociation channels and H abstraction reactions

    NASA Astrophysics Data System (ADS)

    Hayashi, Toshio; Ishikawa, Kenji; Sekine, Makoto; Hori, Masaru

    2016-07-01

    The primary dissociation channels of SiH4 were investigated using computational chemistry. The results showed properties very similar to those of CH4. The main dissociation product was SiH2 and the second dissociation product was SiH3. SiH was produced through SiH3 to SiH + H2 dissociation by electronic excitation. H abstraction reactions by H and SiH3 were also calculated for SiH4, Si2H6, Si3H8, and Si9H14(100) cluster models. The energy barriers of H abstraction reactions were lower than those of SiH3 abstraction reactions. This result is considerably important for deposition in SiH4/H2 process plasma.

  11. The Role of Standards in Cloud-Computing Interoperability

    DTIC Science & Technology

    2012-10-01

    Ahronovitz 2010, Harding 2010, Badger 2011, Kundra 2011]. Risks of vendor lock-in include reduced negotiation power in reaction to price increases and...use cases classified into three groups: cloud management, cloud interoperability, and cloud security [ Badger 2010]. These use cases are listed below... Badger 2010]: • Cloud Management Use Cases − Open an Account − Close an Account − Terminate an Account − Copy Data Objects into a Cloud − Copy

  12. 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.

  13. Geometric data perturbation-based personal health record transactions in cloud computing.

    PubMed

    Balasubramaniam, S; Kavitha, V

    2015-01-01

    Cloud computing is a new delivery model for information technology services and it typically involves the provision of dynamically scalable and often virtualized resources over the Internet. However, cloud computing raises concerns on how cloud service providers, user organizations, and governments should handle such information and interactions. Personal health records represent an emerging patient-centric model for health information exchange, and they are outsourced for storage by third parties, such as cloud providers. With these records, it is necessary for each patient to encrypt their own personal health data before uploading them to cloud servers. Current techniques for encryption primarily rely on conventional cryptographic approaches. However, key management issues remain largely unsolved with these cryptographic-based encryption techniques. We propose that personal health record transactions be managed using geometric data perturbation in cloud computing. In our proposed scheme, the personal health record database is perturbed using geometric data perturbation and outsourced to the Amazon EC2 cloud.

  14. Geometric Data Perturbation-Based Personal Health Record Transactions in Cloud Computing

    PubMed Central

    Balasubramaniam, S.; Kavitha, V.

    2015-01-01

    Cloud computing is a new delivery model for information technology services and it typically involves the provision of dynamically scalable and often virtualized resources over the Internet. However, cloud computing raises concerns on how cloud service providers, user organizations, and governments should handle such information and interactions. Personal health records represent an emerging patient-centric model for health information exchange, and they are outsourced for storage by third parties, such as cloud providers. With these records, it is necessary for each patient to encrypt their own personal health data before uploading them to cloud servers. Current techniques for encryption primarily rely on conventional cryptographic approaches. However, key management issues remain largely unsolved with these cryptographic-based encryption techniques. We propose that personal health record transactions be managed using geometric data perturbation in cloud computing. In our proposed scheme, the personal health record database is perturbed using geometric data perturbation and outsourced to the Amazon EC2 cloud. PMID:25767826

  15. Redefining Tactical Operations for MER Using Cloud Computing

    NASA Technical Reports Server (NTRS)

    Joswig, Joseph C.; Shams, Khawaja S.

    2011-01-01

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

  16. 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.

  17. 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.

  18. 'Big data', Hadoop and cloud computing in genomics.

    PubMed

    O'Driscoll, Aisling; Daugelaite, Jurate; Sleator, Roy D

    2013-10-01

    Since the completion of the Human Genome project at the turn of the Century, there has been an unprecedented proliferation of genomic sequence data. A consequence of this is that the medical discoveries of the future will largely depend on our ability to process and analyse large genomic data sets, which continue to expand as the cost of sequencing decreases. Herein, we provide an overview of cloud computing and big data technologies, and discuss how such expertise can be used to deal with biology's big data sets. In particular, big data technologies such as the Apache Hadoop project, which provides distributed and parallelised data processing and analysis of petabyte (PB) scale data sets will be discussed, together with an overview of the current usage of Hadoop within the bioinformatics community.

  19. Simple computation of reaction-diffusion processes on point clouds.

    PubMed

    Macdonald, Colin B; Merriman, Barry; Ruuth, Steven J

    2013-06-04

    The study of reaction-diffusion processes is much more complicated on general curved surfaces than on standard Cartesian coordinate spaces. Here we show how to formulate and solve systems of reaction-diffusion equations on surfaces in an extremely simple way, using only the standard Cartesian form of differential operators, and a discrete unorganized point set to represent the surface. Our method decouples surface geometry from the underlying differential operators. As a consequence, it becomes possible to formulate and solve rather general reaction-diffusion equations on general surfaces without having to consider the complexities of differential geometry or sophisticated numerical analysis. To illustrate the generality of the method, computations for surface diffusion, pattern formation, excitable media, and bulk-surface coupling are provided for a variety of complex point cloud surfaces.

  20. A Cloud Computing Based Patient Centric Medical Information System

    NASA Astrophysics Data System (ADS)

    Agarwal, Ankur; Henehan, Nathan; Somashekarappa, Vivek; Pandya, A. S.; Kalva, Hari; Furht, Borko

    This chapter discusses an emerging concept of a cloud computing based Patient Centric Medical Information System framework that will allow various authorized users to securely access patient records from various Care Delivery Organizations (CDOs) such as hospitals, urgent care centers, doctors, laboratories, imaging centers among others, from any location. Such a system must seamlessly integrate all patient records including images such as CT-SCANS and MRI'S which can easily be accessed from any location and reviewed by any authorized user. In such a scenario the storage and transmission of medical records will have be conducted in a totally secure and safe environment with a very high standard of data integrity, protecting patient privacy and complying with all Health Insurance Portability and Accountability Act (HIPAA) regulations.

  1. Taking the High Ground: A Case for Department of Defense Application of Public Cloud Computing

    DTIC Science & Technology

    2011-06-01

    maintain pace with advances in commercial IT. As Waxer observes, private infras - tructures can rarely match the service levels offered by public cloud...hypervisor (See Figure 3) runs directly on the host’s hardware and guest operating systems are installed one layer above it. VMWare ESXi and Microsoft Hyper ...cio.gov/documents/Federal-Cloud-Computing-Strategy.pdf. 8. D. Linthicum, Cloud Computing and SOA Convergence in Your Enterprise: A Step-by-Step Guide

  2. 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

  3. Does Cloud Computing in the Atmospheric Sciences Make Sense? A case study of hybrid cloud computing at NASA Langley Research Center

    NASA Astrophysics Data System (ADS)

    Nguyen, L.; Chee, T.; Minnis, P.; Spangenberg, D.; Ayers, J. K.; Palikonda, R.; Vakhnin, A.; Dubois, R.; Murphy, P. R.

    2014-12-01

    The processing, storage and dissemination of satellite cloud and radiation products produced at NASA Langley Research Center are key activities for the Climate Science Branch. A constellation of systems operates in sync to accomplish these goals. Because of the complexity involved with operating such intricate systems, there are both high failure rates and high costs for hardware and system maintenance. Cloud computing has the potential to ameliorate cost and complexity issues. Over time, the cloud computing model has evolved and hybrid systems comprising off-site as well as on-site resources are now common. Towards our mission of providing the highest quality research products to the widest audience, we have explored the use of the Amazon Web Services (AWS) Cloud and Storage and present a case study of our results and efforts. This project builds upon NASA Langley Cloud and Radiation Group's experience with operating large and complex computing infrastructures in a reliable and cost effective manner to explore novel ways to leverage cloud computing resources in the atmospheric science environment. Our case study presents the project requirements and then examines the fit of AWS with the LaRC computing model. We also discuss the evaluation metrics, feasibility, and outcomes and close the case study with the lessons we learned that would apply to others interested in exploring the implementation of the AWS system in their own atmospheric science computing environments.

  4. An Efficient Cloud Computing-Based Architecture for Freight System Application in China Railway

    NASA Astrophysics Data System (ADS)

    Zhang, Baopeng; Zhang, Ning; Li, Honghui; Liu, Feng; Miao, Kai

    Cloud computing is a new network computing paradigm of distributed application environment. It utilizes the computing resource and storage resource to dynamically provide on-demand service for users. The distribution and parallel characters of cloud computing can leverage the railway freight system. We implement a cloud computing-based architecture for freight system application, which explores the Tashi and Hadoop for virtual resource management and MapReduce-based search technology. We propose the semantic model and setup configuration parameter by experiment, and develop the prototype system for freight search and tracking.

  5. Assessing Affordances of Selected Cloud Computing Tools for Language Teacher Education in Nigeria

    ERIC Educational Resources Information Center

    Ofemile, Abdulmalik Yusuf

    2015-01-01

    This paper reports part of a study that hoped to understand Teacher Educators' (TE) assessment of the affordances of selected cloud computing tools ranked among the top 100 for the year 2010. Research has shown that ICT and by extension cloud computing has positive impacts on daily life and this informed the Nigerian government's policy to…

  6. WE-B-BRD-01: Innovation in Radiation Therapy Planning II: Cloud Computing in RT

    SciTech Connect

    Moore, K; Kagadis, G; Xing, L; McNutt, T

    2014-06-15

    As defined by the National Institute of Standards and Technology, cloud computing is “a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.” Despite the omnipresent role of computers in radiotherapy, cloud computing has yet to achieve widespread adoption in clinical or research applications, though the transition to such “on-demand” access is underway. As this transition proceeds, new opportunities for aggregate studies and efficient use of computational resources are set against new challenges in patient privacy protection, data integrity, and management of clinical informatics systems. In this Session, current and future applications of cloud computing and distributed computational resources will be discussed in the context of medical imaging, radiotherapy research, and clinical radiation oncology applications. Learning Objectives: Understand basic concepts of cloud computing. Understand how cloud computing could be used for medical imaging applications. Understand how cloud computing could be employed for radiotherapy research.4. Understand how clinical radiotherapy software applications would function in the cloud.

  7. State of the Art of Network Security Perspectives in Cloud Computing

    NASA Astrophysics Data System (ADS)

    Oh, Tae Hwan; Lim, Shinyoung; Choi, Young B.; Park, Kwang-Roh; Lee, Heejo; Choi, Hyunsang

    Cloud computing is now regarded as one of social phenomenon that satisfy customers' needs. It is possible that the customers' needs and the primary principle of economy - gain maximum benefits from minimum investment - reflects realization of cloud computing. We are living in the connected society with flood of information and without connected computers to the Internet, our activities and work of daily living will be impossible. Cloud computing is able to provide customers with custom-tailored features of application software and user's environment based on the customer's needs by adopting on-demand outsourcing of computing resources through the Internet. It also provides cloud computing users with high-end computing power and expensive application software package, and accordingly the users will access their data and the application software where they are located at the remote system. As the cloud computing system is connected to the Internet, network security issues of cloud computing are considered as mandatory prior to real world service. In this paper, survey and issues on the network security in cloud computing are discussed from the perspective of real world service environments.

  8. 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.

  9. Cloud-Based Computational Tools for Earth Science Applications

    NASA Astrophysics Data System (ADS)

    Arendt, A. A.; Fatland, R.; Howe, B.

    2015-12-01

    Earth scientists are increasingly required to think across disciplines and utilize a wide range of datasets in order to solve complex environmental challenges. Although significant progress has been made in distributing data, researchers must still invest heavily in developing computational tools to accommodate their specific domain. Here we document our development of lightweight computational data systems aimed at enabling rapid data distribution, analytics and problem solving tools for Earth science applications. Our goal is for these systems to be easily deployable, scalable and flexible to accommodate new research directions. As an example we describe "Ice2Ocean", a software system aimed at predicting runoff from snow and ice in the Gulf of Alaska region. Our backend components include relational database software to handle tabular and vector datasets, Python tools (NumPy, pandas and xray) for rapid querying of gridded climate data, and an energy and mass balance hydrological simulation model (SnowModel). These components are hosted in a cloud environment for direct access across research teams, and can also be accessed via API web services using a REST interface. This API is a vital component of our system architecture, as it enables quick integration of our analytical tools across disciplines, and can be accessed by any existing data distribution centers. We will showcase several data integration and visualization examples to illustrate how our system has expanded our ability to conduct cross-disciplinary research.

  10. Reconciliation of the cloud computing model with US federal electronic health record regulations.

    PubMed

    Schweitzer, Eugene J

    2012-01-01

    Cloud computing refers to subscription-based, fee-for-service utilization of computer hardware and software over the Internet. The model is gaining acceptance for business information technology (IT) applications because it allows capacity and functionality to increase on the fly without major investment in infrastructure, personnel or licensing fees. Large IT investments can be converted to a series of smaller operating expenses. Cloud architectures could potentially be superior to traditional electronic health record (EHR) designs in terms of economy, efficiency and utility. A central issue for EHR developers in the US is that these systems are constrained by federal regulatory legislation and oversight. These laws focus on security and privacy, which are well-recognized challenges for cloud computing systems in general. EHRs built with the cloud computing model can achieve acceptable privacy and security through business associate contracts with cloud providers that specify compliance requirements, performance metrics and liability sharing.

  11. Reconciliation of the cloud computing model with US federal electronic health record regulations

    PubMed Central

    2011-01-01

    Cloud computing refers to subscription-based, fee-for-service utilization of computer hardware and software over the Internet. The model is gaining acceptance for business information technology (IT) applications because it allows capacity and functionality to increase on the fly without major investment in infrastructure, personnel or licensing fees. Large IT investments can be converted to a series of smaller operating expenses. Cloud architectures could potentially be superior to traditional electronic health record (EHR) designs in terms of economy, efficiency and utility. A central issue for EHR developers in the US is that these systems are constrained by federal regulatory legislation and oversight. These laws focus on security and privacy, which are well-recognized challenges for cloud computing systems in general. EHRs built with the cloud computing model can achieve acceptable privacy and security through business associate contracts with cloud providers that specify compliance requirements, performance metrics and liability sharing. PMID:21727204

  12. Understanding the Performance and Potential of Cloud Computing for Scientific Applications

    SciTech Connect

    Sadooghi, Iman; Hernandez Martin, Jesus; Li, Tonglin; Brandstatter, Kevin; Zhao, Yong; Maheshwari, Ketan; Pais Pitta de Lacerda Ruivo, Tiago; Timm, Steven; Garzoglio, Gabriele; Raicu, Ioan

    2015-01-01

    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 to 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.

  13. Exploring the factors influencing the cloud computing adoption: a systematic study on cloud migration.

    PubMed

    Rai, Rashmi; Sahoo, Gadadhar; Mehfuz, Shabana

    2015-01-01

    Today, most of the organizations trust on their age old legacy applications, to support their business-critical systems. However, there are several critical concerns, as maintainability and scalability issues, associated with the legacy system. In this background, cloud services offer a more agile and cost effective platform, to support business applications and IT infrastructure. As the adoption of cloud services has been increasing recently and so has been the academic research in cloud migration. However, there is a genuine need of secondary study to further strengthen this research. The primary objective of this paper is to scientifically and systematically identify, categorize and compare the existing research work in the area of legacy to cloud migration. The paper has also endeavored to consolidate the research on Security issues, which is prime factor hindering the adoption of cloud through classifying the studies on secure cloud migration. SLR (Systematic Literature Review) of thirty selected papers, published from 2009 to 2014 was conducted to properly understand the nuances of the security framework. To categorize the selected studies, authors have proposed a conceptual model for cloud migration which has resulted in a resource base of existing solutions for cloud migration. This study concludes that cloud migration research is in seminal stage but simultaneously it is also evolving and maturing, with increasing participation from academics and industry alike. The paper also identifies the need for a secure migration model, which can fortify organization's trust into cloud migration and facilitate necessary tool support to automate the migration process.

  14. 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

    ... National Institute of Standards and Technology Notice of Public Meeting--Intersection of Cloud Computing...-mobility.cfm . SUPPLEMENTARY INFORMATION: NIST hosted six prior Cloud Computing Forum & Workshop events in..., portability, and security, discuss the Federal Government's experience with cloud computing, report on...

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

    SciTech Connect

    Echeverria, Victor T.; Metral, Michael David; Leger, Michelle A.; Gabert, Kasimir Georg; Edgett, Patrick Garrett; Thai, Tan Q.

    2010-09-01

    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 Elastic 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.

  16. Use of Cloud Computing to Calibrate a Highly Parameterized Model

    NASA Astrophysics Data System (ADS)

    Hayley, K. H.; Schumacher, J.; MacMillan, G.; Boutin, L.

    2012-12-01

    We present a case study using cloud computing to facilitate the calibration of a complex and highly parameterized model of regional groundwater flow. The calibration dataset consisted of many (~1500) measurements or estimates of static hydraulic head, a high resolution time series of groundwater extraction and disposal rates at 42 locations and pressure monitoring at 147 locations with a total of more than one million raw measurements collected over a ten year pumping history, and base flow estimates at 5 surface water monitoring locations. This modeling project was undertaken to assess the sustainability of groundwater withdrawal and disposal plans for insitu heavy oil extraction in Northeast Alberta, Canada. The geological interpretations used for model construction were based on more than 5,000 wireline logs collected throughout the 30,865 km2 regional study area (RSA), and resulted in a model with 28 slices, and 28 hydro stratigraphic units (average model thickness of 700 m, with aquifers ranging from a depth of 50 to 500 m below ground surface). The finite element FEFLOW model constructed on this geological interpretation had 331,408 nodes and required 265 time steps to simulate the ten year transient calibration period. This numerical model of groundwater flow required 3 hours to run on a on a server with two, 2.8 GHz processers and 16 Gb. RAM. Calibration was completed using PEST. Horizontal and vertical hydraulic conductivity as well as specific storage for each unit were independent parameters. For the recharge and the horizontal hydraulic conductivity in the three aquifers with the most transient groundwater use, a pilot point parameterization was adopted. A 7*7 grid of pilot points was defined over the RSA that defined a spatially variable horizontal hydraulic conductivity or recharge field. A 7*7 grid of multiplier pilot points that perturbed the more regional field was then superimposed over the 3,600 km2 local study area (LSA). The pilot point

  17. Above the cloud computing orbital services distributed data model

    NASA Astrophysics Data System (ADS)

    Straub, Jeremy

    2014-05-01

    Technology miniaturization and system architecture advancements have created an opportunity to significantly lower the cost of many types of space missions by sharing capabilities between multiple spacecraft. Historically, most spacecraft have been atomic entities that (aside from their communications with and tasking by ground controllers) operate in isolation. Several notable example exist; however, these are purpose-designed systems that collaborate to perform a single goal. The above the cloud computing (ATCC) concept aims to create ad-hoc collaboration between service provider and consumer craft. Consumer craft can procure processing, data transmission, storage, imaging and other capabilities from provider craft. Because of onboard storage limitations, communications link capability limitations and limited windows of communication, data relevant to or required for various operations may span multiple craft. This paper presents a model for the identification, storage and accessing of this data. This model includes appropriate identification features for this highly distributed environment. It also deals with business model constraints such as data ownership, retention and the rights of the storing craft to access, resell, transmit or discard the data in its possession. The model ensures data integrity and confidentiality (to the extent applicable to a given data item), deals with unique constraints of the orbital environment and tags data with business model (contractual) obligation data.

  18. Emergency healthcare process automation using mobile computing and cloud services.

    PubMed

    Poulymenopoulou, M; Malamateniou, F; Vassilacopoulos, G

    2012-10-01

    Emergency care is basically concerned with the provision of pre-hospital and in-hospital medical and/or paramedical services and it typically involves a wide variety of interdependent and distributed activities that can be interconnected to form emergency care processes within and between Emergency Medical Service (EMS) agencies and hospitals. Hence, in developing an information system for emergency care processes, it is essential to support individual process activities and to satisfy collaboration and coordination needs by providing readily access to patient and operational information regardless of location and time. Filling this information gap by enabling the provision of the right information, to the right people, at the right time fosters new challenges, including the specification of a common information format, the interoperability among heterogeneous institutional information systems or the development of new, ubiquitous trans-institutional systems. This paper is concerned with the development of an integrated computer support to emergency care processes by evolving and cross-linking institutional healthcare systems. To this end, an integrated EMS cloud-based architecture has been developed that allows authorized users to access emergency case information in standardized document form, as proposed by the Integrating the Healthcare Enterprise (IHE) profile, uses the Organization for the Advancement of Structured Information Standards (OASIS) standard Emergency Data Exchange Language (EDXL) Hospital Availability Exchange (HAVE) for exchanging operational data with hospitals and incorporates an intelligent module that supports triaging and selecting the most appropriate ambulances and hospitals for each case.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  20. Cloud Computing for the Grid: GridControl: A Software Platform to Support the Smart Grid

    SciTech Connect

    2012-02-08

    GENI Project: Cornell University is creating a new software platform for grid operators called GridControl that will utilize cloud computing to more efficiently control the grid. In a cloud computing system, there are minimal hardware and software demands on users. The user can tap into a network of computers that is housed elsewhere (the cloud) and the network runs computer applications for the user. The user only needs interface software to access all of the cloud’s data resources, which can be as simple as a web browser. Cloud computing can reduce costs, facilitate innovation through sharing, empower users, and improve the overall reliability of a dispersed system. Cornell’s GridControl will focus on 4 elements: delivering the state of the grid to users quickly and reliably; building networked, scalable grid-control software; tailoring services to emerging smart grid uses; and simulating smart grid behavior under various conditions.

  1. The performance of low-cost commercial cloud computing as an alternative in computational chemistry.

    PubMed

    Thackston, Russell; Fortenberry, Ryan C

    2015-05-05

    The growth of commercial cloud computing (CCC) as a viable means of computational infrastructure is largely unexplored for the purposes of quantum chemistry. In this work, the PSI4 suite of computational chemistry programs is installed on five different types of Amazon World Services CCC platforms. The performance for a set of electronically excited state single-point energies is compared between these CCC platforms and typical, "in-house" physical machines. Further considerations are made for the number of cores or virtual CPUs (vCPUs, for the CCC platforms), but no considerations are made for full parallelization of the program (even though parallelization of the BLAS library is implemented), complete high-performance computing cluster utilization, or steal time. Even with this most pessimistic view of the computations, CCC resources are shown to be more cost effective for significant numbers of typical quantum chemistry computations. Large numbers of large computations are still best utilized by more traditional means, but smaller-scale research may be more effectively undertaken through CCC services.

  2. 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

  3. Identifying the impact of G-quadruplexes on Affymetrix 3' arrays using cloud computing.

    PubMed

    Memon, Farhat N; Owen, Anne M; Sanchez-Graillet, Olivia; Upton, Graham J G; Harrison, Andrew P

    2010-01-15

    A tetramer quadruplex structure is formed by four parallel strands of DNA/ RNA containing runs of guanine. These quadruplexes are able to form because guanine can Hoogsteen hydrogen bond to other guanines, and a tetrad of guanines can form a stable arrangement. Recently we have discovered that probes on Affymetrix GeneChips that contain runs of guanine do not measure gene expression reliably. We associate this finding with the likelihood that quadruplexes are forming on the surface of GeneChips. In order to cope with the rapidly expanding size of GeneChip array datasets in the public domain, we are exploring the use of cloud computing to replicate our experiments on 3' arrays to look at the effect of the location of G-spots (runs of guanines). Cloud computing is a recently introduced high-performance solution that takes advantage of the computational infrastructure of large organisations such as Amazon and Google. We expect that cloud computing will become widely adopted because it enables bioinformaticians to avoid capital expenditure on expensive computing resources and to only pay a cloud computing provider for what is used. Moreover, as well as financial efficiency, cloud computing is an ecologically-friendly technology, it enables efficient data-sharing and we expect it to be faster for development purposes. Here we propose the advantageous use of cloud computing to perform a large data-mining analysis of public domain 3' arrays.

  4. Now and next-generation sequencing techniques: future of sequence analysis using cloud computing.

    PubMed

    Thakur, Radhe Shyam; Bandopadhyay, Rajib; Chaudhary, Bratati; Chatterjee, Sourav

    2012-01-01

    Advances in the field of sequencing techniques have resulted in the greatly accelerated production of huge sequence datasets. This presents immediate challenges in database maintenance at datacenters. It provides additional computational challenges in data mining and sequence analysis. Together these represent a significant overburden on traditional stand-alone computer resources, and to reach effective conclusions quickly and efficiently, the virtualization of the resources and computation on a pay-as-you-go concept (together termed "cloud computing") has recently appeared. The collective resources of the datacenter, including both hardware and software, can be available publicly, being then termed a public cloud, the resources being provided in a virtual mode to the clients who pay according to the resources they employ. Examples of public companies providing these resources include Amazon, Google, and Joyent. The computational workload is shifted to the provider, which also implements required hardware and software upgrades over time. A virtual environment is created in the cloud corresponding to the computational and data storage needs of the user via the internet. The task is then performed, the results transmitted to the user, and the environment finally deleted after all tasks are completed. In this discussion, we focus on the basics of cloud computing, and go on to analyze the prerequisites and overall working of clouds. Finally, the applications of cloud computing in biological systems, particularly in comparative genomics, genome informatics, and SNP detection are discussed with reference to traditional workflows.

  5. Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing

    PubMed Central

    Shatil, Anwar S.; Younas, Sohail; Pourreza, Hossein; Figley, Chase R.

    2015-01-01

    With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications. PMID:27279746

  6. Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing.

    PubMed

    Shatil, Anwar S; Younas, Sohail; Pourreza, Hossein; Figley, Chase R

    2015-01-01

    With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications.

  7. Science in the clouds: UAVs and cloud computing methods for spatial diffuse pollution risk assessment (Invited)

    NASA Astrophysics Data System (ADS)

    Reaney, S. M.

    2010-12-01

    . For example, information on changes in the direction of plough lines and the timing of canopy closure will give extra insight into the export of nutrients from the landscape. The extraction of the amount of vegetation cover from the images has been done through the use of a custom web based image processing service. Basing the analysis in a cloud computing framework enables greater collaboration within the project consortium and the effective dissemination of images and results to stakeholders. This presentation will discuss the results of the first four months of the UAV helicopter images and how the information has been extracted from the images. This work is part of the Defra Demonstration Test Catchments project and the NERC Pilot Virtual Observatory project.

  8. 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.

  9. Evaluating the Acceptance of Cloud-Based Productivity Computer Solutions in Small and Medium Enterprises

    ERIC Educational Resources Information Center

    Dominguez, Alfredo

    2013-01-01

    Cloud computing has emerged as a new paradigm for on-demand delivery and consumption of shared IT resources over the Internet. Research has predicted that small and medium organizations (SMEs) would be among the earliest adopters of cloud solutions; however, this projection has not materialized. This study set out to investigate if behavior…

  10. 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…

  11. Open Science in the Cloud: Towards a Universal Platform for Scientific and Statistical Computing

    NASA Astrophysics Data System (ADS)

    Chine, Karim

    The UK, through the e-Science program, the US through the NSF-funded cyber infrastructure and the European Union through the ICT Calls aimed to provide "the technological solution to the problem of efficiently connecting data, computers, and people with the goal of enabling derivation of novel scientific theories and knowledge".1 The Grid (Foster, 2002; Foster; Kesselman, Nick, & Tuecke, 2002), foreseen as a major accelerator of discovery, didn't meet the expectations it had excited at its beginnings and was not adopted by the broad population of research professionals. The Grid is a good tool for particle physicists and it has allowed them to tackle the tremendous computational challenges inherent to their field. However, as a technology and paradigm for delivering computing on demand, it doesn't work and it can't be fixed. On one hand, "the abstractions that Grids expose - to the end-user, to the deployers and to application developers - are inappropriate and they need to be higher level" (Jha, Merzky, & Fox), and on the other hand, academic Grids are inherently economically unsustainable. They can't compete with a service outsourced to the Industry whose quality and price would be driven by market forces. The virtualization technologies and their corollary, the Infrastructure-as-a-Service (IaaS) style cloud, hold the promise to enable what the Grid failed to deliver: a sustainable environment for computational sciences that would lower the barriers for accessing federated computational resources, software tools and data; enable collaboration and resources sharing and provide the building blocks of a ubiquitous platform for traceable and reproducible computational research.

  12. High-performance computational condensed-matter physics in the cloud

    NASA Astrophysics Data System (ADS)

    Rehr, J. J.; Svec, L.; Gardner, J. P.; Prange, M. P.

    2009-03-01

    We demonstrate the feasibility of high performance scientific computation in condensed-matter physics using cloud computers as an alternative to traditional computational tools. The availability of these large, virtualized pools of compute resources raises the possibility of a new compute paradigm for scientific research with many advantages. For research groups, cloud computing provides convenient access to reliable, high performance clusters and storage, without the need to purchase and maintain sophisticated hardware. For developers, virtualization allows scientific codes to be pre-installed on machine images, facilitating control over the computational environment. Detailed tests are presented for the parallelized versions of the electronic structure code SIESTA ootnotetextJ. Soler et al., J. Phys.: Condens. Matter 14, 2745 (2002). and for the x-ray spectroscopy code FEFF ootnotetextA. Ankudinov et al., Phys. Rev. B 65, 104107 (2002). including CPU, network, and I/O performance, using the the Amazon EC2 Elastic Cloud.

  13. Now and Next-Generation Sequencing Techniques: Future of Sequence Analysis Using Cloud Computing

    PubMed Central

    Thakur, Radhe Shyam; Bandopadhyay, Rajib; Chaudhary, Bratati; Chatterjee, Sourav

    2012-01-01

    Advances in the field of sequencing techniques have resulted in the greatly accelerated production of huge sequence datasets. This presents immediate challenges in database maintenance at datacenters. It provides additional computational challenges in data mining and sequence analysis. Together these represent a significant overburden on traditional stand-alone computer resources, and to reach effective conclusions quickly and efficiently, the virtualization of the resources and computation on a pay-as-you-go concept (together termed “cloud computing”) has recently appeared. The collective resources of the datacenter, including both hardware and software, can be available publicly, being then termed a public cloud, the resources being provided in a virtual mode to the clients who pay according to the resources they employ. Examples of public companies providing these resources include Amazon, Google, and Joyent. The computational workload is shifted to the provider, which also implements required hardware and software upgrades over time. A virtual environment is created in the cloud corresponding to the computational and data storage needs of the user via the internet. The task is then performed, the results transmitted to the user, and the environment finally deleted after all tasks are completed. In this discussion, we focus on the basics of cloud computing, and go on to analyze the prerequisites and overall working of clouds. Finally, the applications of cloud computing in biological systems, particularly in comparative genomics, genome informatics, and SNP detection are discussed with reference to traditional workflows. PMID:23248640

  14. Performance, Agility and Cost of Cloud Computing Services for NASA GES DISC Giovanni Application

    NASA Astrophysics Data System (ADS)

    Pham, L.; Chen, A.; Wharton, S.; Winter, E. L.; Lynnes, C.

    2013-12-01

    The NASA Goddard Earth Science Data and Information Services Center (GES DISC) is investigating the performance, agility and cost of Cloud computing for GES DISC applications. Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure), one of the core applications at the GES DISC for online climate-related Earth science data access, subsetting, analysis, visualization, and downloading, was used to evaluate the feasibility and effort of porting an application to the Amazon Cloud Services platform. The performance and the cost of running Giovanni on the Amazon Cloud were compared to similar parameters for the GES DISC local operational system. A Giovanni Time-Series analysis of aerosol absorption optical depth (388nm) from OMI (Ozone Monitoring Instrument)/Aura was selected for these comparisons. All required data were pre-cached in both the Cloud and local system to avoid data transfer delays. The 3-, 6-, 12-, and 24-month data were used for analysis on the Cloud and local system respectively, and the processing times for the analysis were used to evaluate system performance. To investigate application agility, Giovanni was installed and tested on multiple Cloud platforms. The cost of using a Cloud computing platform mainly consists of: computing, storage, data requests, and data transfer in/out. The Cloud computing cost is calculated based on the hourly rate, and the storage cost is calculated based on the rate of Gigabytes per month. Cost for incoming data transfer is free, and for data transfer out, the cost is based on the rate in Gigabytes. The costs for a local server system consist of buying hardware/software, system maintenance/updating, and operating cost. The results showed that the Cloud platform had a 38% better performance and cost 36% less than the local system. This investigation shows the potential of cloud computing to increase system performance and lower the overall cost of system management.

  15. AceCloud: Molecular Dynamics Simulations in the Cloud.

    PubMed

    Harvey, M J; De Fabritiis, G

    2015-05-26

    We present AceCloud, an on-demand service for molecular dynamics simulations. AceCloud is designed to facilitate the secure execution of large ensembles of simulations on an external cloud computing service (currently Amazon Web Services). The AceCloud client, integrated into the ACEMD molecular dynamics package, provides an easy-to-use interface that abstracts all aspects of interaction with the cloud services. This gives the user the experience that all simulations are running on their local machine, minimizing the learning curve typically associated with the transition to using high performance computing services.

  16. 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

  17. 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.

  18. The Department of Defense and the Power of Cloud Computing: Weighing Acceptable Cost Versus Acceptable Risk

    DTIC Science & Technology

    2016-04-01

    DISA is leading the way for the development of a private DOD cloud computing environment in conjunction with the Army. Operational in 2008, DISA...significant opportunities and security challenges when implementing a cloud computing environment . The transformation of DOD information technology...is this shared pool of resources, espe- cially shared resources in a commercial environment , that also creates numerous risks not usually seen in

  19. Building a Cloud Computing and Big Data Infrastructure for Cybersecurity Research and Education

    DTIC Science & Technology

    2015-04-17

    switch provides 4 x 40GbE + 48 x 10 Gb Base-T  Data Nodes (x12): Dell PowerEdge R720xd each w/  2 Intel Xeon Processors each with 6 Cores  64 GB...cloud computing and big data infrastructure to support the cybersecurity research, education, and outreach programs at Norfolk State University...2014 31-Jan-2015 Approved for Public Release; Distribution Unlimited Final Report: Building a Cloud Computing and Big Data Infrastructure for

  20. 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.

  1. Computation of Concentric Shell Particle Scattering Effects in Jovian Clouds

    NASA Astrophysics Data System (ADS)

    Fry, Patrick M.; Sromovsky, Lawrence A.

    2014-11-01

    From analysis of NIMS and ISO spectra of Jupiter Sromovsky and Fry (2010, Icarus 210, 211-229; 2010, Icarus 210, 230-257) concluded that both NH3 and NH4SH were present near the visible cloud tops, probably in the form of composite particles. Composite particles were also suggested from analysis of VIMS spectra of Saturn's Great Storm of 2010-2011 by Sromovsky et al. (2013, Icarus 226, 402-418), in this case concentric shells of H2O, NH4SH, and NH3. These results and suggestions that coatings of various materials might be capable of hiding NH3 spectral features on Jupiter, such as by Atreya et al. (2005, Planet. Space Sci. 53, 498-507), have raised interest in and a need for modeling of scattering properties of complex composite particles. Since many of the particle sizes inferred for composite particles are below or close to the range near 1 μm where particle shape has less impact on near IR spectral features (Clapp and Miller, 1993, Icarus 105, 529-536), concentric shell codes have considerable relevance to modeling of composite particles. Here we report on two codes: one fast code (Toon and Ackerman, 1981, Applied Optics 20, No. 20, 3657-3660) that is capable of handling a core and shell of different materials, and a slower code (Pena and Pal, 2009, Computer Physics Comm., 180, 2348-2354) that can handle an arbitrary number of layers. Typical times to calculate a phase function for a wide size distribution (gamma distribution with normalized variance of 0.1) for the faster core/shell code are about 0.75 seconds per wavelength. The newer slower, but more versatile, code runs about 10X slower, and will typically double or triple the execution time of our multiple scattering code when it is incorporated. Optimizing integration over particle size distributions to achieve suitable accuracy can minimize computational costs; we have therefore determined a rule for the number of intervals in the size distribution. Sample calculations will be presented to show effects

  2. Applying analytic hierarchy process to assess healthcare-oriented cloud computing service systems.

    PubMed

    Liao, Wen-Hwa; Qiu, Wan-Li

    2016-01-01

    Numerous differences exist between the healthcare industry and other industries. Difficulties in the business operation of the healthcare industry have continually increased because of the volatility and importance of health care, changes to and requirements of health insurance policies, and the statuses of healthcare providers, which are typically considered not-for-profit organizations. Moreover, because of the financial risks associated with constant changes in healthcare payment methods and constantly evolving information technology, healthcare organizations must continually adjust their business operation objectives; therefore, cloud computing presents both a challenge and an opportunity. As a response to aging populations and the prevalence of the Internet in fast-paced contemporary societies, cloud computing can be used to facilitate the task of balancing the quality and costs of health care. To evaluate cloud computing service systems for use in health care, providing decision makers with a comprehensive assessment method for prioritizing decision-making factors is highly beneficial. Hence, this study applied the analytic hierarchy process, compared items related to cloud computing and health care, executed a questionnaire survey, and then classified the critical factors influencing healthcare cloud computing service systems on the basis of statistical analyses of the questionnaire results. The results indicate that the primary factor affecting the design or implementation of optimal cloud computing healthcare service systems is cost effectiveness, with the secondary factors being practical considerations such as software design and system architecture.

  3. Cloud computing for energy management in smart grid - an application survey

    NASA Astrophysics Data System (ADS)

    Naveen, P.; Kiing Ing, Wong; Kobina Danquah, Michael; Sidhu, Amandeep S.; Abu-Siada, Ahmed

    2016-03-01

    The smart grid is the emerging energy system wherein the application of information technology, tools and techniques that make the grid run more efficiently. It possesses demand response capacity to help balance electrical consumption with supply. The challenges and opportunities of emerging and future smart grids can be addressed by cloud computing. To focus on these requirements, we provide an in-depth survey on different cloud computing applications for energy management in the smart grid architecture. In this survey, we present an outline of the current state of research on smart grid development. We also propose a model of cloud based economic power dispatch for smart grid.

  4. A computational- And storage-cloud for integration of biodiversity collections

    USGS Publications Warehouse

    Matsunaga, A.; Thompson, A.; Figueiredo, R. J.; Germain-Aubrey, C.C; Collins, M.; Beeman, R.S; Macfadden, B.J.; Riccardi, G.; Soltis, P.S; Page, L. M.; Fortes, J.A.B

    2013-01-01

    A core mission of the Integrated Digitized Biocollections (iDigBio) project is the building and deployment of a cloud computing environment customized to support the digitization workflow and integration of data from all U.S. nonfederal biocollections. iDigBio chose to use cloud computing technologies to deliver a cyberinfrastructure that is flexible, agile, resilient, and scalable to meet the needs of the biodiversity community. In this context, this paper describes the integration of open source cloud middleware, applications, and third party services using standard formats, protocols, and services. In addition, this paper demonstrates the value of the digitized information from collections in a broader scenario involving multiple disciplines.

  5. 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

  6. 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.

  7. The monitoring and managing application of cloud computing based on Internet of Things.

    PubMed

    Luo, Shiliang; Ren, Bin

    2016-07-01

    Cloud computing and the Internet of Things are the two hot points in the Internet application field. The application of the two new technologies is in hot discussion and research, but quite less on the field of medical monitoring and managing application. Thus, in this paper, we study and analyze the application of cloud computing and the Internet of Things on the medical field. And we manage to make a combination of the two techniques in the medical monitoring and managing field. The model architecture for remote monitoring cloud platform of healthcare information (RMCPHI) was established firstly. Then the RMCPHI architecture was analyzed. Finally an efficient PSOSAA algorithm was proposed for the medical monitoring and managing application of cloud computing. Simulation results showed that our proposed scheme can improve the efficiency about 50%.

  8. Confidentiality Protection of Digital Health Records in Cloud Computing.

    PubMed

    Chen, Shyh-Wei; Chiang, Dai Lun; Liu, Chia-Hui; Chen, Tzer-Shyong; Lai, Feipei; Wang, Huihui; Wei, Wei

    2016-05-01

    Electronic medical records containing confidential information were uploaded to the cloud. The cloud allows medical crews to access and manage the data and integration of medical records easily. This data system provides relevant information to medical personnel and facilitates and improve electronic medical record management and data transmission. A structure of cloud-based and patient-centered personal health record (PHR) is proposed in this study. This technique helps patients to manage their health information, such as appointment date with doctor, health reports, and a completed understanding of their own health conditions. It will create patients a positive attitudes to maintain the health. The patients make decision on their own for those whom has access to their records over a specific span of time specified by the patients. Storing data in the cloud environment can reduce costs and enhance the share of information, but the potential threat of information security should be taken into consideration. This study is proposing the cloud-based secure transmission mechanism is suitable for multiple users (like nurse aides, patients, and family members).

  9. CloudLCA: finding the lowest common ancestor in metagenome analysis using cloud computing.

    PubMed

    Zhao, Guoguang; Bu, Dechao; Liu, Changning; Li, Jing; Yang, Jian; Liu, Zhiyong; Zhao, Yi; Chen, Runsheng

    2012-02-01

    Estimating taxonomic content constitutes a key problem in metagenomic sequencing data analysis. However, extracting such content from high-throughput data of next-generation sequencing is very time-consuming with the currently available software. Here, we present CloudLCA, a parallel LCA algorithm that significantly improves the efficiency of determining taxonomic composition in metagenomic data analysis. Results show that CloudLCA (1) has a running time nearly linear with the increase of dataset magnitude, (2) displays linear speedup as the number of processors grows, especially for large datasets, and (3) reaches a speed of nearly 215 million reads each minute on a cluster with ten thin nodes. In comparison with MEGAN, a well-known metagenome analyzer, the speed of CloudLCA is up to 5 more times faster, and its peak memory usage is approximately 18.5% that of MEGAN, running on a fat node. CloudLCA can be run on one multiprocessor node or a cluster. It is expected to be part of MEGAN to accelerate analyzing reads, with the same output generated as MEGAN, which can be import into MEGAN in a direct way to finish the following analysis. Moreover, CloudLCA is a universal solution for finding the lowest common ancestor, and it can be applied in other fields requiring an LCA algorithm.

  10. Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  11. An Interactive Web-Based Analysis Framework for Remote Sensing Cloud Computing

    NASA Astrophysics Data System (ADS)

    Wang, X. Z.; Zhang, H. M.; Zhao, J. H.; Lin, Q. H.; Zhou, Y. C.; Li, J. H.

    2015-07-01

    Spatiotemporal data, especially remote sensing data, are widely used in ecological, geographical, agriculture, and military research and applications. With the development of remote sensing technology, more and more remote sensing data are accumulated and stored in the cloud. An effective way for cloud users to access and analyse these massive spatiotemporal data in the web clients becomes an urgent issue. In this paper, we proposed a new scalable, interactive and web-based cloud computing solution for massive remote sensing data analysis. We build a spatiotemporal analysis platform to provide the end-user with a safe and convenient way to access massive remote sensing data stored in the cloud. The lightweight cloud storage system used to store public data and users' private data is constructed based on open source distributed file system. In it, massive remote sensing data are stored as public data, while the intermediate and input data are stored as private data. The elastic, scalable, and flexible cloud computing environment is built using Docker, which is a technology of open-source lightweight cloud computing container in the Linux operating system. In the Docker container, open-source software such as IPython, NumPy, GDAL, and Grass GIS etc., are deployed. Users can write scripts in the IPython Notebook web page through the web browser to process data, and the scripts will be submitted to IPython kernel to be executed. By comparing the performance of remote sensing data analysis tasks executed in Docker container, KVM virtual machines and physical machines respectively, we can conclude that the cloud computing environment built by Docker makes the greatest use of the host system resources, and can handle more concurrent spatial-temporal computing tasks. Docker technology provides resource isolation mechanism in aspects of IO, CPU, and memory etc., which offers security guarantee when processing remote sensing data in the IPython Notebook. Users can write

  12. Dynamic partitioning as a way to exploit new computing paradigms: the cloud use case.

    NASA Astrophysics Data System (ADS)

    Ciaschini, Vincenzo; Dal Pra, Stefano; dell'Agnello, Luca

    2015-12-01

    The WLCG community and many groups in the HEP community have based their computing strategy on the Grid paradigm, which proved successful and still ensures its goals. However, Grid technology has not spread much over other communities; in the commercial world, the cloud paradigm is the emerging way to provide computing services. WLCG experiments aim to achieve integration of their existing current computing model with cloud deployments and take advantage of the so-called opportunistic resources (including HPC facilities) which are usually not Grid compliant. One missing feature in the most common cloud frameworks, is the concept of job scheduler, which plays a key role in a traditional computing centre, by enabling a fairshare based access at the resources to the experiments in a scenario where demand greatly outstrips availability. At CNAF we are investigating the possibility to access the Tier-1 computing resources as an OpenStack based cloud service. The system, exploiting the dynamic partitioning mechanism already being used to enable Multicore computing, allowed us to avoid a static splitting of the computing resources in the Tier-1 farm, while permitting a share friendly approach. The hosts in a dynamically partitioned farm may be moved to or from the partition, according to suitable policies for request and release of computing resources. Nodes being requested in the partition switch their role and become available to play a different one. In the cloud use case hosts may switch from acting as Worker Node in the Batch system farm to cloud compute node member, made available to tenants. In this paper we describe the dynamic partitioning concept, its implementation and integration with our current batch system, LSF.

  13. Parallel optimization of pixel purity index algorithm for massive hyperspectral images in cloud computing environment

    NASA Astrophysics Data System (ADS)

    Chen, Yufeng; Wu, Zebin; Sun, Le; Wei, Zhihui; Li, Yonglong

    2016-04-01

    With the gradual increase in the spatial and spectral resolution of hyperspectral images, the size of image data becomes larger and larger, and the complexity of processing algorithms is growing, which poses a big challenge to efficient massive hyperspectral image processing. Cloud computing technologies distribute computing tasks to a large number of computing resources for handling large data sets without the limitation of memory and computing resource of a single machine. This paper proposes a parallel pixel purity index (PPI) algorithm for unmixing massive hyperspectral images based on a MapReduce programming model for the first time in the literature. According to the characteristics of hyperspectral images, we describe the design principle of the algorithm, illustrate the main cloud unmixing processes of PPI, and analyze the time complexity of serial and parallel algorithms. Experimental results demonstrate that the parallel implementation of the PPI algorithm on the cloud can effectively process big hyperspectral data and accelerate the algorithm.

  14. Opportunities and Challenges of Cloud Computing to Improve Health Care Services

    PubMed Central

    2011-01-01

    Cloud computing is a new way of delivering computing resources and services. Many managers and experts believe that it can improve health care services, benefit health care research, and change the face of health information technology. However, as with any innovation, cloud computing should be rigorously evaluated before its widespread adoption. This paper discusses the concept and its current place in health care, and uses 4 aspects (management, technology, security, and legal) to evaluate the opportunities and challenges of this computing model. Strategic planning that could be used by a health organization to determine its direction, strategy, and resource allocation when it has decided to migrate from traditional to cloud-based health services is also discussed. PMID:21937354

  15. Opportunities and challenges of cloud computing to improve health care services.

    PubMed

    Kuo, Alex Mu-Hsing

    2011-09-21

    Cloud computing is a new way of delivering computing resources and services. Many managers and experts believe that it can improve health care services, benefit health care research, and change the face of health information technology. However, as with any innovation, cloud computing should be rigorously evaluated before its widespread adoption. This paper discusses the concept and its current place in health care, and uses 4 aspects (management, technology, security, and legal) to evaluate the opportunities and challenges of this computing model. Strategic planning that could be used by a health organization to determine its direction, strategy, and resource allocation when it has decided to migrate from traditional to cloud-based health services is also discussed.

  16. Development and clinical study of mobile 12-lead electrocardiography based on cloud computing for cardiac emergency.

    PubMed

    Fujita, Hideo; Uchimura, Yuji; Waki, Kayo; Omae, Koji; Takeuchi, Ichiro; Ohe, Kazuhiko

    2013-01-01

    To improve emergency services for accurate diagnosis of cardiac emergency, we developed a low-cost new mobile electrocardiography system "Cloud Cardiology®" based upon cloud computing for prehospital diagnosis. This comprises a compact 12-lead ECG unit equipped with Bluetooth and Android Smartphone with an application for transmission. Cloud server enables us to share ECG simultaneously inside and outside the hospital. We evaluated the clinical effectiveness by conducting a clinical trial with historical comparison to evaluate this system in a rapid response car in the real emergency service settings. We found that this system has an ability to shorten the onset to balloon time of patients with acute myocardial infarction, resulting in better clinical outcome. Here we propose that cloud-computing based simultaneous data sharing could be powerful solution for emergency service for cardiology, along with its significant clinical outcome.

  17. Accelerating statistical image reconstruction algorithms for fan-beam x-ray CT using cloud computing

    NASA Astrophysics Data System (ADS)

    Srivastava, Somesh; Rao, A. Ravishankar; Sheinin, Vadim

    2011-03-01

    Statistical image reconstruction algorithms potentially offer many advantages to x-ray computed tomography (CT), e.g. lower radiation dose. But, their adoption in practical CT scanners requires extra computation power, which is traditionally provided by incorporating additional computing hardware (e.g. CPU-clusters, GPUs, FPGAs etc.) into a scanner. An alternative solution is to access the required computation power over the internet from a cloud computing service, which is orders-of-magnitude more cost-effective. This is because users only pay a small pay-as-you-go fee for the computation resources used (i.e. CPU time, storage etc.), and completely avoid purchase, maintenance and upgrade costs. In this paper, we investigate the benefits and shortcomings of using cloud computing for statistical image reconstruction. We parallelized the most time-consuming parts of our application, the forward and back projectors, using MapReduce, the standard parallelization library on clouds. From preliminary investigations, we found that a large speedup is possible at a very low cost. But, communication overheads inside MapReduce can limit the maximum speedup, and a better MapReduce implementation might become necessary in the future. All the experiments for this paper, including development and testing, were completed on the Amazon Elastic Compute Cloud (EC2) for less than $20.

  18. Above-Campus Services: Shaping the Promise of Cloud Computing for Higher Education

    ERIC Educational Resources Information Center

    Wheeler, Brad; Waggener, Shelton

    2009-01-01

    The concept of today's cloud computing may date back to 1961, when John McCarthy, retired Stanford professor and Turing Award winner, delivered a speech at MIT's Centennial. In that speech, he predicted that in the future, computing would become a "public utility." Yet for colleges and universities, the recent growth of pervasive, very high speed…

  19. Investigating the Structural Relationship for the Determinants of Cloud Computing Adoption in Education

    ERIC Educational Resources Information Center

    Bhatiasevi, Veera; Naglis, Michael

    2016-01-01

    This research is one of the first few to investigate the adoption and usage of cloud computing in higher education in the context of developing countries, in this case Thailand. It proposes extending the technology acceptance model to integrate subjective norm, perceived convenience, trust, computer self-efficacy, and software functionality in…

  20. Distance Learning and Cloud Computing: "Just Another Buzzword or a Major E-Learning Breakthrough?"

    ERIC Educational Resources Information Center

    Romiszowski, Alexander J.

    2012-01-01

    "Cloud computing is a model for the enabling of ubiquitous, convenient, and on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and other services) that can be rapidly provisioned and released with minimal management effort or service provider interaction." This…

  1. Directly executable formal models of middleware for MANET and Cloud Networking and Computing

    NASA Astrophysics Data System (ADS)

    Pashchenko, D. V.; Sadeq Jaafar, Mustafa; Zinkin, S. A.; Trokoz, D. A.; Pashchenko, T. U.; Sinev, M. P.

    2016-04-01

    The article considers some “directly executable” formal models that are suitable for the specification of computing and networking in the cloud environment and other networks which are similar to wireless networks MANET. These models can be easily programmed and implemented on computer networks.

  2. An Analysis of the Use of Cloud Computing among University Lecturers: A Case Study in Zimbabwe

    ERIC Educational Resources Information Center

    Musungwini, Samuel; Mugoniwa, Beauty; Furusa, Samuel Simbarashe; Rebanowako, Taurai George

    2016-01-01

    Cloud computing is a novel model of computing that may bring extensive benefits to users, institutions, businesses and academics, while at the same time also giving rise to new risks and challenges. This study looked at the benefits of using Google docs by researchers and academics and analysing the factors affecting the adoption and use of the…

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

    SciTech Connect

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  5. A novel cost based model for energy consumption in cloud computing.

    PubMed

    Horri, A; Dastghaibyfard, Gh

    2015-01-01

    Cloud data centers consume enormous amounts of electrical energy. To support green cloud computing, providers also need to minimize cloud infrastructure energy consumption while conducting the QoS. In this study, for cloud environments an energy consumption model is proposed for time-shared policy in virtualization layer. The cost and energy usage of time-shared policy were modeled in the CloudSim simulator based upon the results obtained from the real system and then proposed model was evaluated by different scenarios. In the proposed model, the cache interference costs were considered. These costs were based upon the size of data. The proposed model was implemented in the CloudSim simulator and the related simulation results indicate that the energy consumption may be considerable and that it can vary with different parameters such as the quantum parameter, data size, and the number of VMs on a host. Measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment. Also, measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment.

  6. Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm.

    PubMed

    Abdulhamid, Shafi'i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

    2016-01-01

    Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques.

  7. Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm

    PubMed Central

    Abdulhamid, Shafi’i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

    2016-01-01

    Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques. PMID:27384239

  8. U.S. Geological Survey national computer technology meeting; program and abstracts, New Orleans, Louisiana, April 10-15, 1994

    USGS Publications Warehouse

    Balthrop, B. H.; Baker, E.G.

    1994-01-01

    This report contains some of the abstracts of papers that were presented at the National Computer Technology Meeting that was held in April 1994. This meeting was sponsored by the Water Resources Division of the U.S. Geological Survey, and was attended by more than 200 technical and managerial personnel representing all the Divisions of the U.S. Geological Survey. Computer-related information from all Divisions of the U.S. Geological Survey are discussed in this compilation of abstracts. Some of the topics addressed are data transfer, data-base management, hydrologic applications, national water information systems, and geographic information systems applications and techniques.

  9. U.S. Geological Survey National Computer Technology Meeting; Program and abstracts, May 7-11, 1990

    USGS Publications Warehouse

    Balthrop, B. H.; Baker, E.G.

    1990-01-01

    Computer-related information from all Divisions of the U.S. Geological Survey are discussed in this compilation of abstracts. Some of the topics addressed are system administration; distributed information systems and data bases, both current (1990) and proposed; hydrologic applications; national water information systems; geographic information systems applications and techniques. The report contains some of the abstracts that were presented at the National Computer Technology Meeting that was held in May 1990. The meeting was sponsored by the Water Resources Division and was attended by more than 200 technical and managerial personnel representing all the Divisions of the U.S. Geological Survey. (USGS)

  10. Cloud Computing and Virtual Desktop Infrastructures in Afloat Environments

    DTIC Science & Technology

    2012-06-01

    INTENTIONALLY LEFT BLANK xiii LIST OF ACRONYMS AND ABBREVIATIONS AOR Area of Responsibility API Application Programming Interface BGAN ...Global Area Network The Broadband Global Area Network, or BGAN , is a global satellite Internet network system. The system utilizes the Internet...transfer, and remote surveillance, among others. [38] BGAN is a viable and suitable solution to linking nodes in an afloat cloud infrastructure for several

  11. A Fast Synthetic Aperture Radar Raw Data Simulation Using Cloud Computing.

    PubMed

    Li, Zhixin; Su, Dandan; Zhu, Haijiang; Li, Wei; Zhang, Fan; Li, Ruirui

    2017-01-08

    Synthetic Aperture Radar (SAR) raw data simulation is a fundamental problem in radar system design and imaging algorithm research. The growth of surveying swath and resolution results in a significant increase in data volume and simulation period, which can be considered to be a comprehensive data intensive and computing intensive issue. Although several high performance computing (HPC) methods have demonstrated their potential for accelerating simulation, the input/output (I/O) bottleneck of huge raw data has not been eased. In this paper, we propose a cloud computing based SAR raw data simulation algorithm, which employs the MapReduce model to accelerate the raw data computing and the Hadoop distributed file system (HDFS) for fast I/O access. The MapReduce model is designed for the irregular parallel accumulation of raw data simulation, which greatly reduces the parallel efficiency of graphics processing unit (GPU) based simulation methods. In addition, three kinds of optimization strategies are put forward from the aspects of programming model, HDFS configuration and scheduling. The experimental results show that the cloud computing based algorithm achieves 4_ speedup over the baseline serial approach in an 8-node cloud environment, and each optimization strategy can improve about 20%. This work proves that the proposed cloud algorithm is capable of solving the computing intensive and data intensive issues in SAR raw data simulation, and is easily extended to large scale computing to achieve higher acceleration.

  12. A Fast Synthetic Aperture Radar Raw Data Simulation Using Cloud Computing

    PubMed Central

    Li, Zhixin; Su, Dandan; Zhu, Haijiang; Li, Wei; Zhang, Fan; Li, Ruirui

    2017-01-01

    Synthetic Aperture Radar (SAR) raw data simulation is a fundamental problem in radar system design and imaging algorithm research. The growth of surveying swath and resolution results in a significant increase in data volume and simulation period, which can be considered to be a comprehensive data intensive and computing intensive issue. Although several high performance computing (HPC) methods have demonstrated their potential for accelerating simulation, the input/output (I/O) bottleneck of huge raw data has not been eased. In this paper, we propose a cloud computing based SAR raw data simulation algorithm, which employs the MapReduce model to accelerate the raw data computing and the Hadoop distributed file system (HDFS) for fast I/O access. The MapReduce model is designed for the irregular parallel accumulation of raw data simulation, which greatly reduces the parallel efficiency of graphics processing unit (GPU) based simulation methods. In addition, three kinds of optimization strategies are put forward from the aspects of programming model, HDFS configuration and scheduling. The experimental results show that the cloud computing based algorithm achieves 4× speedup over the baseline serial approach in an 8-node cloud environment, and each optimization strategy can improve about 20%. This work proves that the proposed cloud algorithm is capable of solving the computing intensive and data intensive issues in SAR raw data simulation, and is easily extended to large scale computing to achieve higher acceleration. PMID:28075343

  13. Threshold-based queuing system for performance analysis of cloud computing system with dynamic scaling

    SciTech Connect

    Shorgin, Sergey Ya.; Pechinkin, Alexander V.; Samouylov, Konstantin E.; Gaidamaka, Yuliya V.; Gudkova, Irina A.; Sopin, Eduard S.

    2015-03-10

    Cloud computing is promising technology to manage and improve utilization of computing center resources to deliver various computing and IT services. For the purpose of energy saving there is no need to unnecessarily operate many servers under light loads, and they are switched off. On the other hand, some servers should be switched on in heavy load cases to prevent very long delays. Thus, waiting times and system operating cost can be maintained on acceptable level by dynamically adding or removing servers. One more fact that should be taken into account is significant server setup costs and activation times. For better energy efficiency, cloud computing system should not react on instantaneous increase or instantaneous decrease of load. That is the main motivation for using queuing systems with hysteresis for cloud computing system modelling. In the paper, we provide a model of cloud computing system in terms of multiple server threshold-based infinite capacity queuing system with hysteresis and noninstantanuous server activation. For proposed model, we develop a method for computing steady-state probabilities that allow to estimate a number of performance measures.

  14. Large-Scale, Multi-Sensor Atmospheric Data Fusion Using Hybrid Cloud Computing

    NASA Astrophysics Data System (ADS)

    Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

    2015-12-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, MODIS, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. HySDS is a Hybrid-Cloud Science Data System that has been developed and applied under NASA AIST, MEaSUREs, and ACCESS grants. HySDS uses the SciFlow workflow engine to partition analysis workflows into parallel tasks (e.g. segmenting by time or space) that are pushed into a durable job queue. The tasks are "pulled" from the queue by worker Virtual Machines (VM's) and executed in an on-premise Cloud (Eucalyptus or OpenStack) or at Amazon in the public Cloud or govCloud. In this way, years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the transferred data. We are using HySDS to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a MEASURES grant. We will present the architecture of HySDS, describe the achieved "clock time" speedups in fusing datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. Our system demonstrates how one can pull A-Train variables (Levels 2 & 3) on-demand into the Amazon Cloud, and cache only those variables that are heavily used, so that any number of compute jobs can be

  15. 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.

  16. Implementation of a solution Cloud Computing with MapReduce model

    NASA Astrophysics Data System (ADS)

    Baya, Chalabi

    2014-10-01

    In recent years, large scale computer systems have emerged to meet the demands of high storage, supercomputing, and applications using very large data sets. The emergence of Cloud Computing offers the potentiel for analysis and processing of large data sets. Mapreduce is the most popular programming model which is used to support the development of such applications. It was initially designed by Google for building large datacenters on a large scale, to provide Web search services with rapid response and high availability. In this paper we will test the clustering algorithm K-means Clustering in a Cloud Computing. This algorithm is implemented on MapReduce. It has been chosen for its characteristics that are representative of many iterative data analysis algorithms. Then, we modify the framework CloudSim to simulate the MapReduce execution of K-means Clustering on different Cloud Computing, depending on their size and characteristics of target platforms. The experiment show that the implementation of K-means Clustering gives good results especially for large data set and the Cloud infrastructure has an influence on these results.

  17. Information Security: Federal Guidance Needed to Address Control Issues With Implementing Cloud Computing

    DTIC Science & Technology

    2010-05-01

    Figure 2: Cloud Computing Deployment Models 13 Figure 3: NIST Essential Characteristics 14 Figure 4: NASA Nebula Container 37...Access Computing Environment (RACE) program, the National Aeronautics and Space Administration’s (NASA) Nebula program, and the Department of...computing programs: the DOD’s RACE program; NASA’s Nebula program; and Department of Transportation’s CARS program, including lessons learned related

  18. Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment

    PubMed Central

    Abdullahi, Mohammed; Ngadi, Md Asri

    2016-01-01

    Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS) has been shown to perform competitively with Particle Swarm Optimization (PSO). The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA) based SOS (SASOS) in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs) which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan. PMID:27348127

  19. Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment.

    PubMed

    Abdullahi, Mohammed; Ngadi, Md Asri

    2016-01-01

    Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS) has been shown to perform competitively with Particle Swarm Optimization (PSO). The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA) based SOS (SASOS) in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs) which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.

  20. Agile Development of Various Computational Power Adaptive Web-Based Mobile-Learning Software Using Mobile Cloud Computing

    ERIC Educational Resources Information Center

    Zadahmad, Manouchehr; Yousefzadehfard, Parisa

    2016-01-01

    Mobile Cloud Computing (MCC) aims to improve all mobile applications such as m-learning systems. This study presents an innovative method to use web technology and software engineering's best practices to provide m-learning functionalities hosted in a MCC-learning system as service. Components hosted by MCC are used to empower developers to create…

  1. Secure encapsulation and publication of biological services in the cloud computing environment.

    PubMed

    Zhang, Weizhe; Wang, Xuehui; Lu, Bo; Kim, Tai-hoon

    2013-01-01

    Secure encapsulation and publication for bioinformatics software products based on web service are presented, and the basic function of biological information is realized in the cloud computing environment. In the encapsulation phase, the workflow and function of bioinformatics software are conducted, the encapsulation interfaces are designed, and the runtime interaction between users and computers is simulated. In the publication phase, the execution and management mechanisms and principles of the GRAM components are analyzed. The functions such as remote user job submission and job status query are implemented by using the GRAM components. The services of bioinformatics software are published to remote users. Finally the basic prototype system of the biological cloud is achieved.

  2. Enabling Water Quality Management Decision Support and Public Outreach Using Cloud-Computing Services

    NASA Astrophysics Data System (ADS)

    Sun, A. Y.; Scanlon, B. R.; Uhlman, K.

    2013-12-01

    Watershed management is a participatory process that requires collaboration among multiple groups of people. Environmental decision support systems (EDSS) have long been used to support such co-management and co-learning processes in watershed management. However, implementing and maintaining EDSS in-house can be a significant burden to many water agencies because of budget, technical, and policy constraints. Basing on experiences from several web-GIS environmental management projects in Texas, we showcase how cloud-computing services can help shift the design and hosting of EDSS from the traditional client-server-based platforms to be simple clients of cloud-computing services.

  3. Annual Report and Abstracts of Research of the Department of Computer and Information Science, July 1976-June 1977.

    ERIC Educational Resources Information Center

    Ohio State Univ., Columbus. Computer and Information Science Research Center.

    The annual report of the Department of Computer and Information Science includes abstracts of research carried out during the 1976-77 academic year with support from grants by governmental agencies and industry, as well as The Ohio State University. The report covers the department's organizational structure, objectives, highlights of department…

  4. COMPUTER-AIDED INDEXING OF A SCIENTIFIC ABSTRACTS JOURNAL BY THE UDC WITH UNIDEK--A CASE STUDY.

    ERIC Educational Resources Information Center

    FREEMAN, ROBERT R.; RUSSELL, MARTIN

    THIS PAPER IS A CASE STUDY OF THE ADOPTION BY GEOSCIENCE ABSTRACTS OF UNIDEK, A COMPUTER-COMPILED SYSTEMATIC SUBJECT INDEX BASED ON THE UNIVERSAL DECIMAL CLASSIFICATION (UDC). EVENTS LEADING TO A DECISION TO ADOPT THE SYSTEM, SOME THEORY OF INDEXES, PROBLEMS INVOLVED IN CONVERSION, AND SOME OF THE RESULTS ACHIEVED ARE REVIEWED. UNIDEK MAKES…

  5. Computer generated hologram from point cloud using graphics processor.

    PubMed

    Chen, Rick H-Y; Wilkinson, Timothy D

    2009-12-20

    Computer generated holography is an extremely demanding and complex task when it comes to providing realistic reconstructions with full parallax, occlusion, and shadowing. We present an algorithm designed for data-parallel computing on modern graphics processing units to alleviate the computational burden. We apply Gaussian interpolation to create a continuous surface representation from discrete input object points. The algorithm maintains a potential occluder list for each individual hologram plane sample to keep the number of visibility tests to a minimum. We experimented with two approximations that simplify and accelerate occlusion computation. It is observed that letting several neighboring hologram plane samples share visibility information on object points leads to significantly faster computation without causing noticeable artifacts in the reconstructed images. Computing a reduced sample set via nonuniform sampling is also found to be an effective acceleration technique.

  6. Behavior life style analysis for mobile sensory data in cloud computing through MapReduce.

    PubMed

    Hussain, Shujaat; Bang, Jae Hun; Han, Manhyung; Ahmed, Muhammad Idris; Amin, Muhammad Bilal; Lee, Sungyoung; Nugent, Chris; McClean, Sally; Scotney, Bryan; Parr, Gerard

    2014-11-20

    Cloud computing has revolutionized healthcare in today's world as it can be seamlessly integrated into a mobile application and sensor devices. The sensory data is then transferred from these devices to the public and private clouds. In this paper, a hybrid and distributed environment is built which is capable of collecting data from the mobile phone application and store it in the cloud. We developed an activity recognition application and transfer the data to the cloud for further processing. Big data technology Hadoop MapReduce is employed to analyze the data and create user timeline of user's activities. These activities are visualized to find useful health analytics and trends. In this paper a big data solution is proposed to analyze the sensory data and give insights into user behavior and lifestyle trends.

  7. Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduce

    PubMed Central

    Hussain, Shujaat; Bang, Jae Hun; Han, Manhyung; Ahmed, Muhammad Idris; Amin, Muhammad Bilal; Lee, Sungyoung; Nugent, Chris; McClean, Sally; Scotney, Bryan; Parr, Gerard

    2014-01-01

    Cloud computing has revolutionized healthcare in today's world as it can be seamlessly integrated into a mobile application and sensor devices. The sensory data is then transferred from these devices to the public and private clouds. In this paper, a hybrid and distributed environment is built which is capable of collecting data from the mobile phone application and store it in the cloud. We developed an activity recognition application and transfer the data to the cloud for further processing. Big data technology Hadoop MapReduce is employed to analyze the data and create user timeline of user's activities. These activities are visualized to find useful health analytics and trends. In this paper a big data solution is proposed to analyze the sensory data and give insights into user behavior and lifestyle trends. PMID:25420151

  8. 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.

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

    PubMed

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

    2016-09-01

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

  10. 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

  11. APFA: Asynchronous Parallel Finite Automaton for Deep Packet Inspection in Cloud Computing

    NASA Astrophysics Data System (ADS)

    Li, Yang; Li, Zheng; Yu, Nenghai; Ma, Ke

    Security in cloud computing is getting more and more important recently. Besides passive defense such as encryption, it is necessary to implement real-time active monitoring, detection and defense in the cloud. According to the published researches, DPI (deep packet inspection) is the most effective technology to realize active inspection and defense. However, most recent works of DPI aim at space reduction but could not meet the demands of high speed and stability in the cloud. So, it is important to improve regular methods of DPI, making it more suitable for cloud computing. In this paper, an asynchronous parallel finite automaton named APFA is proposed, by introducing the asynchronous parallelization and the heuristically forecast mechanism, which significantly decreases the time consumed in matching while still keeps reducing the memory required. What is more, APFA is immune to the overlapping problem so that the stability is also enhanced. The evaluation results show that APFA achieves higher stability, better performance on time and memory. In short, APFA is more suitable for cloud computing.

  12. A Medical Image Backup Architecture Based on a NoSQL Database and Cloud Computing Services.

    PubMed

    Santos Simões de Almeida, Luan Henrique; Costa Oliveira, Marcelo

    2015-01-01

    The use of digital systems for storing medical images generates a huge volume of data. Digital images are commonly stored and managed on a Picture Archiving and Communication System (PACS), under the DICOM standard. However, PACS is limited because it is strongly dependent on the server's physical space. Alternatively, Cloud Computing arises as an extensive, low cost, and reconfigurable resource. However, medical images contain patient information that can not be made available in a public cloud. Therefore, a mechanism to anonymize these images is needed. This poster presents a solution for this issue by taking digital images from PACS, converting the information contained in each image file to a NoSQL database, and using cloud computing to store digital images.

  13. Cloud computing in pharmaceutical R&D: business risks and mitigations.

    PubMed

    Geiger, Karl

    2010-05-01

    Cloud computing provides information processing power and business services, delivering these services over the Internet from centrally hosted locations. Major technology corporations aim to supply these services to every sector of the economy. Deploying business processes 'in the cloud' requires special attention to the regulatory and business risks assumed when running on both hardware and software that are outside the direct control of a company. The identification of risks at the correct service level allows a good mitigation strategy to be selected. The pharmaceutical industry can take advantage of existing risk management strategies that have already been tested in the finance and electronic commerce sectors. In this review, the business risks associated with the use of cloud computing are discussed, and mitigations achieved through knowledge from securing services for electronic commerce and from good IT practice are highlighted.

  14. Privacy and Data Security under Cloud Computing Arrangements: The Legal Framework and Practical Do's and Don'ts

    ERIC Educational Resources Information Center

    Buckman, Joel; Gold, Stephanie

    2012-01-01

    This article outlines privacy and data security compliance issues facing postsecondary education institutions when they utilize cloud computing and concludes with a practical list of do's and dont's. Cloud computing does not change an institution's privacy and data security obligations. It does involve reliance on a third party, which requires an…

  15. Large-Scale, Multi-Sensor Atmospheric Data Fusion Using Hybrid Cloud Computing

    NASA Astrophysics Data System (ADS)

    Wilson, Brian; Manipon, Gerald; Hua, Hook; Fetzer, Eric

    2014-05-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map-reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in a hybrid Cloud (private eucalyptus & public Amazon). Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Multi-year datasets are automatically "sharded" by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will present the architecture of SciReduce, describe the

  16. Cloud object store for archive storage of high performance computing data using decoupling middleware

    DOEpatents

    Bent, John M.; Faibish, Sorin; Grider, Gary

    2015-06-30

    Cloud object storage is enabled for archived data, such as checkpoints and results, of high performance computing applications using a middleware process. A plurality of archived files, such as checkpoint files and results, generated by a plurality of processes in a parallel computing system are stored by obtaining the plurality of archived files from the parallel computing system; converting the plurality of archived files to objects using a log structured file system middleware process; and providing the objects for storage in a cloud object storage system. The plurality of processes may run, for example, on a plurality of compute nodes. The log structured file system middleware process may be embodied, for example, as a Parallel Log-Structured File System (PLFS). The log structured file system middleware process optionally executes on a burst buffer node.

  17. Cloud object store for checkpoints of high performance computing applications using decoupling middleware

    DOEpatents

    Bent, John M.; Faibish, Sorin; Grider, Gary

    2016-04-19

    Cloud object storage is enabled for checkpoints of high performance computing applications using a middleware process. A plurality of files, such as checkpoint files, generated by a plurality of processes in a parallel computing system are stored by obtaining said plurality of files from said parallel computing system; converting said plurality of files to objects using a log structured file system middleware process; and providing said objects for storage in a cloud object storage system. The plurality of processes may run, for example, on a plurality of compute nodes. The log structured file system middleware process may be embodied, for example, as a Parallel Log-Structured File System (PLFS). The log structured file system middleware process optionally executes on a burst buffer node.

  18. Process virtualization of large-scale lidar data in a cloud computing environment

    NASA Astrophysics Data System (ADS)

    Guan, Haiyan; Li, Jonathan; Zhong, Liang; Yongtao, Yu; Chapman, Michael

    2013-10-01

    Light detection and ranging (lidar) technologies have proven to be the most powerful tools to collect, within a short time, three-dimensional (3-D) point clouds with high-density, high-accuracy and significantly detailed surface information pertaining to terrain and objects. However, in terms of feature extraction and 3-D reconstruction in a computer-aided drawing (CAD) format, most of the existing stand-alone lidar data processing software packages are unable to process a large volume of lidar data in an effective and efficient fashion. To break this technical bottleneck, through the design of a Condor-based process virtualization platform, we presented in this paper a novel strategy that uses network-related computational resources to process, manage, and distribute vast quantities of lidar data in a cloud computing environment. Three extensive experiments with and without a cloud computing environment were compared. The experiment results demonstrated that the proposed process virtualization approach is promisingly applicable and effective in the management of large-scale lidar point clouds.

  19. Mitigating Cloud Computing Security Risks Using a Self-Monitoring Defensive Scheme

    DTIC Science & Technology

    2011-07-01

    intelligent multi - agent system , dynamic ontology I. INTRODUCTION Cloud Computing (CC) has been described a number of ways: network...leverages intelligent multi - agent systems and network data ontologies to provide automated defense for both known and some unknown malware security...protocols. Modeling and Simulation has also benefited significantly from the use of multi - agent systems . Agent-oriented modeling and simulation for

  20. Cloud Computing and Validated Learning for Accelerating Innovation in IoT

    ERIC Educational Resources Information Center

    Suciu, George; Todoran, Gyorgy; Vulpe, Alexandru; Suciu, Victor; Bulca, Cristina; Cheveresan, Romulus

    2015-01-01

    Innovation in Internet of Things (IoT) requires more than just creation of technology and use of cloud computing or big data platforms. It requires accelerated commercialization or aptly called go-to-market processes. To successfully accelerate, companies need a new type of product development, the so-called validated learning process.…

  1. A Quantitative Study of the Relationship between Leadership Practice and Strategic Intentions to Use Cloud Computing

    ERIC Educational Resources Information Center

    Castillo, Alan F.

    2014-01-01

    The purpose of this quantitative correlational cross-sectional research study was to examine a theoretical model consisting of leadership practice, attitudes of business process outsourcing, and strategic intentions of leaders to use cloud computing and to examine the relationships between each of the variables respectively. This study…

  2. 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…

  3. Risks and Crises for Healthcare Providers: The Impact of Cloud Computing

    PubMed Central

    Glasberg, Ronald; Hartmann, Michael; Tamm, Gerrit

    2014-01-01

    We analyze risks and crises for healthcare providers and discuss the impact of cloud computing in such scenarios. The analysis is conducted in a holistic way, taking into account organizational and human aspects, clinical, IT-related, and utilities-related risks as well as incorporating the view of the overall risk management. PMID:24707207

  4. A City Parking Integration System Combined with Cloud Computing Technologies and Smart Mobile Devices

    ERIC Educational Resources Information Center

    Yeh, Her-Tyan; Chen, Bing-Chang; Wang, Bo-Xun

    2016-01-01

    The current study applied cloud computing technology and smart mobile devices combined with a streaming server for parking lots to plan a city parking integration system. It is also equipped with a parking search system, parking navigation system, parking reservation service, and car retrieval service. With this system, users can quickly find…

  5. The Benefits & Drawbacks of Integrating Cloud Computing and Interactive Whiteboards in Teacher Preparation

    ERIC Educational Resources Information Center

    Blue, Elfreda; Tirotta, Rose

    2011-01-01

    Twenty-first century technology has changed the way tools are used to support and enhance learning and instruction. Cloud computing and interactive white boards, make it possible for learners to interact, simulate, collaborate, and document learning experiences and real world problem-solving. This article discusses how various technologies (blogs,…

  6. Selecting a Suitable Cloud Computing Technology Deployment Model for an Academic Institute : A Case Study

    ERIC Educational Resources Information Center

    Ramachandran, N.; Sivaprakasam, P.; Thangamani, G.; Anand, G.

    2014-01-01

    Purpose: Cloud Computing (CC) technology is getting implemented rapidly in the educational sector to improve learning, research and other administrative process. As evident from the literature review, most of these implementations are happening in the western countries such as USA, UK, while the level of implementation of CC in developing…

  7. Factors Influencing F/OSS Cloud Computing Software Product Success: A Quantitative Study

    ERIC Educational Resources Information Center

    Letort, D. Brian

    2012-01-01

    Cloud Computing introduces a new business operational model that allows an organization to shift information technology consumption from traditional capital expenditure to operational expenditure. This shift introduces challenges from both the adoption and creation vantage. This study evaluates factors that influence Free/Open Source Software…

  8. Factors Affecting University Students' Intention to Use Cloud Computing in Jordan

    ERIC Educational Resources Information Center

    Rababah, Khalid Ali; Khasawneh, Mohammad; Nassar, Bilal

    2017-01-01

    The aim of this study is to examine the factors affecting students' intention to use cloud computing in the Jordanian universities. To achieve this purpose, a quantitative research approach which is a survey-based was deployed. Around 400 questionnaires were distributed randomly to Information Technology (IT) students at four universities in…

  9. Application of Cloud Computing at KTU: MS Live@Edu Case

    ERIC Educational Resources Information Center

    Miseviciene, Regina; Budnikas, Germanas; Ambraziene, Danute

    2011-01-01

    Cloud computing is a significant alternative in today's educational perspective. The technology gives the students and teachers the opportunity to quickly access various application platforms and resources through the web pages on-demand. Unfortunately, not all educational institutions often have an ability to take full advantages of the newest…

  10. 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…

  11. Programming the Navier-Stokes computer: An abstract machine model and a visual editor

    NASA Technical Reports Server (NTRS)

    Middleton, David; Crockett, Tom; Tomboulian, Sherry

    1988-01-01

    The Navier-Stokes computer is a parallel computer designed to solve Computational Fluid Dynamics problems. Each processor contains several floating point units which can be configured under program control to implement a vector pipeline with several inputs and outputs. Since the development of an effective compiler for this computer appears to be very difficult, machine level programming seems necessary and support tools for this process have been studied. These support tools are organized into a graphical program editor. A programming process is described by which appropriate computations may be efficiently implemented on the Navier-Stokes computer. The graphical editor would support this programming process, verifying various programmer choices for correctness and deducing values such as pipeline delays and network configurations. Step by step details are provided and demonstrated with two example programs.

  12. Computer Simulations and the Transition from Concrete Manipulation of Objects to Abstract Thinking.

    ERIC Educational Resources Information Center

    Berlin, Donna F.; White, Arthur L.

    This study explores a learning model which suggests that a concept is acquired first through manipulation of concrete objects followed by transformation of the concrete objects into semi-concrete representations, followed by internalization of the concept through abstract representations. Microcomputer simulations of manipulative activities were…

  13. An Analysis of Cloud Computing with Amazon Web Services for the Atmospheric Science Data Center

    NASA Astrophysics Data System (ADS)

    Gleason, J. L.; Little, M. M.

    2013-12-01

    NASA science and engineering efforts rely heavily on compute and data handling systems. The nature of NASA science data is such that it is not restricted to NASA users, instead it is widely shared across a globally distributed user community including scientists, educators, policy decision makers, and the public. Therefore NASA science computing is a candidate use case for cloud computing where compute resources are outsourced to an external vendor. Amazon Web Services (AWS) is a commercial cloud computing service developed to use excess computing capacity at Amazon, and potentially provides an alternative to costly and potentially underutilized dedicated acquisitions whenever NASA scientists or engineers require additional data processing. AWS desires to provide a simplified avenue for NASA scientists and researchers to share large, complex data sets with external partners and the public. AWS has been extensively used by JPL for a wide range of computing needs and was previously tested on a NASA Agency basis during the Nebula testing program. Its ability to support the Langley Science Directorate needs to be evaluated by integrating it with real world operational needs across NASA and the associated maturity that would come with that. The strengths and weaknesses of this architecture and its ability to support general science and engineering applications has been demonstrated during the previous testing. The Langley Office of the Chief Information Officer in partnership with the Atmospheric Sciences Data Center (ASDC) has established a pilot business interface to utilize AWS cloud computing resources on a organization and project level pay per use model. This poster discusses an effort to evaluate the feasibility of the pilot business interface from a project level perspective by specifically using a processing scenario involving the Clouds and Earth's Radiant Energy System (CERES) project.

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

    ERIC Educational Resources Information Center

    Vaquero, L. M.

    2011-01-01

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

  15. Speech recognition by computer. 1964-September 1981 (a bibliography with abstracts)

    SciTech Connect

    Not Available

    1983-02-01

    The cited reports present investigations on the recognition, synthesis, and processing of speech by computer. The research includes the acoustical, phonological, and linguistic processes necessary in the conversion of the various waveforms by computers. (This updated bibliography contains 294 citations, none of which are new entries to the previous edition.)

  16. Speech recognition by computer. October 1981-1982 (a bibliography with abstracts)

    SciTech Connect

    Not Available

    1983-02-01

    The cited reports present investigations on the recognition, synthesis, and processing of speech by computer. The research includes the acoustical, phonological, and linguistic processes necessary in the conversion of the various waveforms by computers. (This updated bibliography contains 33 citations, all of which are new entries to the previous edition.)

  17. Novel Techniques for Secure Use of Public Cloud Computing Resources

    DTIC Science & Technology

    2015-09-17

    SIGCOMM Computer Communication Review, volume 43, 513–514. ACM, 2013. [61] Jeong, Ik Rae and Jeong Ok Kwon. “Analysis of some keyword search schemes in...Government’s Information Infrastruc- ture”, 1993. URL http://govinfo.library.unt.edu/npr/library/reports/it09.html. [92] Rhee, Hyun Sook, Ik Rae Jeong

  18. Computer graphics for management: An abstract of capabilities and applications of the EIS system

    NASA Technical Reports Server (NTRS)

    Solem, B. J.

    1975-01-01

    The Executive Information Services (EIS) system, developed as a computer-based, time-sharing tool for making and implementing management decisions, and including computer graphics capabilities, was described. The following resources are available through the EIS languages: centralized corporate/gov't data base, customized and working data bases, report writing, general computational capability, specialized routines, modeling/programming capability, and graphics. Nearly all EIS graphs can be created by a single, on-line instruction. A large number of options are available, such as selection of graphic form, line control, shading, placement on the page, multiple images on a page, control of scaling and labeling, plotting of cum data sets, optical grid lines, and stack charts. The following are examples of areas in which the EIS system may be used: research, estimating services, planning, budgeting, and performance measurement, national computer hook-up negotiations.

  19. Formal Specification and Analysis of Cloud Computing Management

    DTIC Science & Technology

    2012-01-24

    QoS) Management in Service-Oriented Enterprise Architectures. IEEE International Enterprise Distributed Object Computing Conference, 0: 21 –32, 2004...Prof. Dr. Alexander Knapp Betreuer: Prof. Dr. José Meseguer Abgabe: 24. Januar 2012 Hiermit versichere ich, dass ich diese Masterarbeit selbständig...system [75]. Deduction in rewriting logic consists of the concurrent application of the rewriting rules in R modulo the equations in E ∪A. 3.2. The

  20. Dynamic resource allocation engine for cloud-based real-time video transcoding in mobile cloud computing environments

    NASA Astrophysics Data System (ADS)

    Adedayo, Bada; Wang, Qi; Alcaraz Calero, Jose M.; Grecos, Christos

    2015-02-01

    The recent explosion in video-related Internet traffic has been driven by the widespread use of smart mobile devices, particularly smartphones with advanced cameras that are able to record high-quality videos. Although many of these devices offer the facility to record videos at different spatial and temporal resolutions, primarily with local storage considerations in mind, most users only ever use the highest quality settings. The vast majority of these devices are optimised for compressing the acquired video using a single built-in codec and have neither the computational resources nor battery reserves to transcode the video to alternative formats. This paper proposes a new low-complexity dynamic resource allocation engine for cloud-based video transcoding services that are both scalable and capable of being delivered in real-time. Firstly, through extensive experimentation, we establish resource requirement benchmarks for a wide range of transcoding tasks. The set of tasks investigated covers the most widely used input formats (encoder type, resolution, amount of motion and frame rate) associated with mobile devices and the most popular output formats derived from a comprehensive set of use cases, e.g. a mobile news reporter directly transmitting videos to the TV audience of various video format requirements, with minimal usage of resources both at the reporter's end and at the cloud infrastructure end for transcoding services.

  1. Research Abstracts.

    ERIC Educational Resources Information Center

    Plotnik, Eric

    2001-01-01

    Presents six research abstracts from the ERIC (Educational Resources Information Center) database. Topics include: effectiveness of distance versus traditional on-campus education; improved attribution recall from diversification of environmental context during computer-based instruction; qualitative analysis of situated Web-based learning;…

  2. Large-Scale, Parallel, Multi-Sensor Atmospheric Data Fusion Using Cloud Computing

    NASA Astrophysics Data System (ADS)

    Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

    2013-12-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the 'A-Train' platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (MERRA), stratify the comparisons using a classification of the 'cloud scenes' from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Figure 1 shows the architecture of the full computational system, with SciReduce at the core. Multi-year datasets are automatically 'sharded' by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will

  3. 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.

  4. Fusion Render Cloud System for 3D Contents Using a Super Computer

    NASA Astrophysics Data System (ADS)

    Choi, E.-Jung; Kim, Seoksoo

    This study develops a SOHO RenderFarm system suitable for a lab environment through data collection and professional education, implements a user environment which is the same as a super computer, analyzes rendering problems that may arise from use of a super computer and then designs a FRC(Fusion Render Cloud) system. Also, clients can access the SOHO RenderFarm system through networks, and the FRC system completed in a test environment can be interlinked with external networks of a super computer.

  5. Fourth SIAM conference on mathematical and computational issues in the geosciences: Final program and abstracts

    SciTech Connect

    1997-12-31

    The conference focused on computational and modeling issues in the geosciences. Of the geosciences, problems associated with phenomena occurring in the earth`s subsurface were best represented. Topics in this area included petroleum recovery, ground water contamination and remediation, seismic imaging, parameter estimation, upscaling, geostatistical heterogeneity, reservoir and aquifer characterization, optimal well placement and pumping strategies, and geochemistry. Additional sessions were devoted to the atmosphere, surface water and oceans. The central mathematical themes included computational algorithms and numerical analysis, parallel computing, mathematical analysis of partial differential equations, statistical and stochastic methods, optimization, inversion, homogenization and renormalization. The problem areas discussed at this conference are of considerable national importance, with the increasing importance of environmental issues, global change, remediation of waste sites, declining domestic energy sources and an increasing reliance on producing the most out of established oil reservoirs.

  6. Large-Scale, Parallel, Multi-Sensor Atmospheric Data Fusion Using Cloud Computing

    NASA Astrophysics Data System (ADS)

    Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E.

    2013-05-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Figure 1 shows the architecture of the full computational system, with SciReduce at the core. Multi-year datasets are automatically "sharded" by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will

  7. 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

  8. Journal of Chemical Education: Software: Abstract of "The Computer-Based Laboratory."

    ERIC Educational Resources Information Center

    Krause, Daniel C.; Divis, Lynne M., Ed.

    1988-01-01

    Describes a chemistry laboratory software package for interfacing the Apple IIe for high school and introductory college courses. Topics include: thermistor calibration, phase change, heat of reaction, freezing point depression, Beer's law, and color decay in crystal violet. Explains the computer interface and the tools needed. (MVL)

  9. The symbolic computation of series solutions to ordinary differential equations using trees (extended abstract)

    NASA Technical Reports Server (NTRS)

    Grossman, Robert

    1991-01-01

    Algorithms previously developed by the author give formulas which can be used for the efficient symbolic computation of series expansions to solutions of nonlinear systems of ordinary differential equations. As a by product of this analysis, formulas are derived which relate to trees to the coefficients of the series expansions, similar to the work of Leroux and Viennot, and Lamnabhi, Leroux and Viennot.

  10. Beyond the Clock--Using the Computer to Teach the Abstract Concept of Time.

    ERIC Educational Resources Information Center

    Drysdale, Julie

    1993-01-01

    Discusses several projects to help teach and reinforce the concept of time, using the books "The Very Hungry Caterpillar" (by Eric Carle) and "Charlotte's Web (by E. B. White) as well as the computer software program "Timeliner" (by Tom Snyder). (SR)

  11. Uncertainty quantification through the Monte Carlo method in a cloud computing setting

    NASA Astrophysics Data System (ADS)

    Cunha, Americo; Nasser, Rafael; Sampaio, Rubens; Lopes, Hélio; Breitman, Karin

    2014-05-01

    The Monte Carlo (MC) method is the most common technique used for uncertainty quantification, due to its simplicity and good statistical results. However, its computational cost is extremely high, and, in many cases, prohibitive. Fortunately, the MC algorithm is easily parallelizable, which allows its use in simulations where the computation of a single realization is very costly. This work presents a methodology for the parallelization of the MC method, in the context of cloud computing. This strategy is based on the MapReduce paradigm, and allows an efficient distribution of tasks in the cloud. This methodology is illustrated on a problem of structural dynamics that is subject to uncertainties. The results show that the technique is capable of producing good results concerning statistical moments of low order. It is shown that even a simple problem may require many realizations for convergence of histograms, which makes the cloud computing strategy very attractive (due to its high scalability capacity and low-cost). Additionally, the results regarding the time of processing and storage space usage allow one to qualify this new methodology as a solution for simulations that require a number of MC realizations beyond the standard.

  12. Compute unified device architecture (CUDA)-based parallelization of WRF Kessler cloud microphysics scheme

    NASA Astrophysics Data System (ADS)

    Mielikainen, Jarno; Huang, Bormin; Wang, Jun; Allen Huang, H.-L.; Goldberg, Mitchell D.

    2013-03-01

    In recent years, graphics processing units (GPUs) have emerged as a low-cost, low-power and a very high performance alternative to conventional central processing units (CPUs). The latest GPUs offer a speedup of two-to-three orders of magnitude over CPU for various science and engineering applications. The Weather Research and Forecasting (WRF) model is the latest-generation numerical weather prediction model. It has been designed to serve both operational forecasting and atmospheric research needs. It proves useful for a broad spectrum of applications for domain scales ranging from meters to hundreds of kilometers. WRF computes an approximate solution to the differential equations which govern the air motion of the whole atmosphere. Kessler microphysics module in WRF is a simple warm cloud scheme that includes water vapor, cloud water and rain. Microphysics processes which are modeled are rain production, fall and evaporation. The accretion and auto-conversion of cloud water processes are also included along with the production of cloud water from condensation. In this paper, we develop an efficient WRF Kessler microphysics scheme which runs on Graphics Processing Units (GPUs) using the NVIDIA Compute Unified Device Architecture (CUDA). The GPU-based implementation of Kessler microphysics scheme achieves a significant speedup of 70× over its CPU based single-threaded counterpart. When a 4 GPU system is used, we achieve an overall speedup of 132× as compared to the single thread CPU version.

  13. USL NASA/RECON project presentations at the 1985 ACM Computer Science Conference: Abstracts and visuals

    NASA Technical Reports Server (NTRS)

    Dominick, Wayne D. (Editor); Chum, Frank Y.; Gallagher, Suzy; Granier, Martin; Hall, Philip P.; Moreau, Dennis R.; Triantafyllopoulos, Spiros

    1985-01-01

    This Working Paper Series entry represents the abstracts and visuals associated with presentations delivered by six USL NASA/RECON research team members at the above named conference. The presentations highlight various aspects of NASA contract activities pursued by the participants as they relate to individual research projects. The titles of the six presentations are as follows: (1) The Specification and Design of a Distributed Workstation; (2) An Innovative, Multidisciplinary Educational Program in Interactive Information Storage and Retrieval; (3) Critical Comparative Analysis of the Major Commercial IS and R Systems; (4) Design Criteria for a PC-Based Common User Interface to Remote Information Systems; (5) The Design of an Object-Oriented Graphics Interface; and (6) Knowledge-Based Information Retrieval: Techniques and Applications.

  14. A Cloud-Computing Service for Environmental Geophysics and Seismic Data Processing

    NASA Astrophysics Data System (ADS)

    Heilmann, B. Z.; Maggi, P.; Piras, A.; Satta, G.; Deidda, G. P.; Bonomi, E.

    2012-04-01

    Cloud computing is establishing worldwide as a new high performance computing paradigm that offers formidable possibilities to industry and science. The presented cloud-computing portal, part of the Grida3 project, provides an innovative approach to seismic data processing by combining open-source state-of-the-art processing software and cloud-computing technology, making possible the effective use of distributed computation and data management with administratively distant resources. We substituted the user-side demanding hardware and software requirements by remote access to high-performance grid-computing facilities. As a result, data processing can be done quasi in real-time being ubiquitously controlled via Internet by a user-friendly web-browser interface. Besides the obvious advantages over locally installed seismic-processing packages, the presented cloud-computing solution creates completely new possibilities for scientific education, collaboration, and presentation of reproducible results. The web-browser interface of our portal is based on the commercially supported grid portal EnginFrame, an open framework based on Java, XML, and Web Services. We selected the hosted applications with the objective to allow the construction of typical 2D time-domain seismic-imaging workflows as used for environmental studies and, originally, for hydrocarbon exploration. For data visualization and pre-processing, we chose the free software package Seismic Un*x. We ported tools for trace balancing, amplitude gaining, muting, frequency filtering, dip filtering, deconvolution and rendering, with a customized choice of options as services onto the cloud-computing portal. For structural imaging and velocity-model building, we developed a grid version of the Common-Reflection-Surface stack, a data-driven imaging method that requires no user interaction at run time such as manual picking in prestack volumes or velocity spectra. Due to its high level of automation, CRS stacking

  15. Abstracts of digital computer code packages assembled by the Radiation Shielding Information Center

    SciTech Connect

    Carter, B.J.; Maskewitz, B.F.

    1985-04-01

    This publication, ORNL/RSIC-13, Volumes I to III Revised, has resulted from an internal audit of the first 168 packages of computing technology in the Computer Codes Collection (CCC) of the Radiation Shielding Information Center (RSIC). It replaces the earlier three documents published as single volumes between 1966 to 1972. A significant number of the early code packages were considered to be obsolete and were removed from the collection in the audit process and the CCC numbers were not reassigned. Others not currently being used by the nuclear R and D community were retained in the collection to preserve technology not replaced by newer methods, or were considered of potential value for reference purposes. Much of the early technology, however, has improved through developer/RSIC/user interaction and continues at the forefront of the advancing state-of-the-art.

  16. Eighth SIAM conference on parallel processing for scientific computing: Final program and abstracts

    SciTech Connect

    1997-12-31

    This SIAM conference is the premier forum for developments in parallel numerical algorithms, a field that has seen very lively and fruitful developments over the past decade, and whose health is still robust. Themes for this conference were: combinatorial optimization; data-parallel languages; large-scale parallel applications; message-passing; molecular modeling; parallel I/O; parallel libraries; parallel software tools; parallel compilers; particle simulations; problem-solving environments; and sparse matrix computations.

  17. CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing

    PubMed Central

    2011-01-01

    Background 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. Results 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. Conclusion 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. PMID:21878105

  18. Monte Carlo simulation of photon migration in a cloud computing environment with MapReduce.

    PubMed

    Pratx, Guillem; Xing, Lei

    2011-12-01

    Monte Carlo simulation is considered the most reliable method for modeling photon migration in heterogeneous media. However, its widespread use is hindered by the high computational cost. The purpose of this work is to report on our implementation of a simple MapReduce method for performing fault-tolerant Monte Carlo computations in a massively-parallel cloud computing environment. We ported the MC321 Monte Carlo package to Hadoop, an open-source MapReduce framework. In this implementation, Map tasks compute photon histories in parallel while a Reduce task scores photon absorption. The distributed implementation was evaluated on a commercial compute cloud. The simulation time was found to be linearly dependent on the number of photons and inversely proportional to the number of nodes. For a cluster size of 240 nodes, the simulation of 100 billion photon histories took 22 min, a 1258 × speed-up compared to the single-threaded Monte Carlo program. The overall computational throughput was 85,178 photon histories per node per second, with a latency of 100 s. The distributed simulation produced the same output as the original implementation and was resilient to hardware failure: the correctness of the simulation was unaffected by the shutdown of 50% of the nodes.

  19. Monte Carlo simulation of photon migration in a cloud computing environment with MapReduce

    PubMed Central

    Pratx, Guillem; Xing, Lei

    2011-01-01

    Monte Carlo simulation is considered the most reliable method for modeling photon migration in heterogeneous media. However, its widespread use is hindered by the high computational cost. The purpose of this work is to report on our implementation of a simple MapReduce method for performing fault-tolerant Monte Carlo computations in a massively-parallel cloud computing environment. We ported the MC321 Monte Carlo package to Hadoop, an open-source MapReduce framework. In this implementation, Map tasks compute photon histories in parallel while a Reduce task scores photon absorption. The distributed implementation was evaluated on a commercial compute cloud. The simulation time was found to be linearly dependent on the number of photons and inversely proportional to the number of nodes. For a cluster size of 240 nodes, the simulation of 100 billion photon histories took 22 min, a 1258 × speed-up compared to the single-threaded Monte Carlo program. The overall computational throughput was 85,178 photon histories per node per second, with a latency of 100 s. The distributed simulation produced the same output as the original implementation and was resilient to hardware failure: the correctness of the simulation was unaffected by the shutdown of 50% of the nodes. PMID:22191916

  20. 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.

  1. 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.

  2. 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.

  3. Load Balancing in Cloud Computing Environment Using Improved Weighted Round Robin Algorithm for Nonpreemptive Dependent Tasks.

    PubMed

    Devi, D Chitra; Uthariaraj, V Rhymend

    2016-01-01

    Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple interdependent tasks and they may execute the independent tasks in multiple VMs or in the same VM's multiple cores. Also, the jobs arrive during the run time of the server in varying random intervals under various load conditions. The participating heterogeneous resources are managed by allocating the tasks to appropriate resources by static or dynamic scheduling to make the cloud computing more efficient and thus it improves the user satisfaction. Objective of this work is to introduce and evaluate the proposed scheduling and load balancing algorithm by considering the capabilities of each virtual machine (VM), the task length of each requested job, and the interdependency of multiple tasks. Performance of the proposed algorithm is studied by comparing with the existing methods.

  4. Load Balancing in Cloud Computing Environment Using Improved Weighted Round Robin Algorithm for Nonpreemptive Dependent Tasks

    PubMed Central

    Devi, D. Chitra; Uthariaraj, V. Rhymend

    2016-01-01

    Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple interdependent tasks and they may execute the independent tasks in multiple VMs or in the same VM's multiple cores. Also, the jobs arrive during the run time of the server in varying random intervals under various load conditions. The participating heterogeneous resources are managed by allocating the tasks to appropriate resources by static or dynamic scheduling to make the cloud computing more efficient and thus it improves the user satisfaction. Objective of this work is to introduce and evaluate the proposed scheduling and load balancing algorithm by considering the capabilities of each virtual machine (VM), the task length of each requested job, and the interdependency of multiple tasks. Performance of the proposed algorithm is studied by comparing with the existing methods. PMID:26955656

  5. 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

  6. Computational materials science aided design of glass ceramics and crystal properties (abstract only).

    PubMed

    Mannstadt, Wolfgang

    2008-02-13

    Today's high tech materials have in many cases highly specialized properties and designed functionalities. Materials parameters like high temperature stability, high stiffness and certain optical properties have to be optimized and in many cases an adaptation to given processes is necessary. Many materials are compounds or layered structures. Thus, surface and interface properties need to be considered as well. At the same time to some extent just a few atomic layers sometimes determine the properties of the material, as is well known in semiconductor and other thin film technologies. Therefore, a detailed understanding of the materials properties at the atomic scale becomes more and more important. In addition many high tech materials have to be of high purity or selective dopant concentrations have to be adjusted to fulfill the desired functionality. Modern materials developments successfully use computational materials science to achieve that goal. Improved software tools and continuously growing computational power allow us to predict macroscopic properties of materials on the basis of microscopic/atomic ab initio simulation approaches. At Schott, special materials, in particular glasses and glass ceramics, are produced for a variety of applications. For a glass ceramic all the above mentioned difficulties for materials development arise. The properties of a glass ceramic are determined by the interplay of crystalline phases embedded in an amorphous glass matrix. For materials development the understanding of crystal structures and their properties, surfaces and interface phenomena, and amorphous systems are necessary, likewise. Each by itself is already a challenging problem. Many crystal phases that are grown within the glass matrix do not exist as single crystals or are difficult to grow in reasonable amounts for experimental investigations. The only way to obtain the properties of these crystalline phases is through 'ab initio' simulations in the computer

  7. Abstract Computation in Schizophrenia Detection through Artificial Neural Network Based Systems

    PubMed Central

    Cardoso, L.; Marins, F.; Magalhães, R.; Marins, N.; Oliveira, T.; Vicente, H.; Abelha, A.; Machado, J.; Neves, J.

    2015-01-01

    Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information. PMID:25834836

  8. Scientific Services on the Cloud

    NASA Astrophysics Data System (ADS)

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

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

  9. 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

  10. 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.

  11. 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.

  12. Computer numerically controlled (CNC) aspheric shaping with toroidal Wheels (Abstract Only)

    NASA Astrophysics Data System (ADS)

    Ketelsen, D.; Kittrell, W. C.; Kuhn, W. M.; Parks, R. E.; Lamb, George L.; Baker, Lynn

    1987-01-01

    Contouring with computer numerically controlled (CNC) machines can be accomplished with several different tool geometries and coordinated machine axes. To minimize the number of coordinated axes for nonsymmetric work to three, it is common practice to use a spherically shaped tool such as a ball-end mill. However, to minimize grooving due to the feed and ball radius, it is desirable to use a long ball radius, but there is clearly a practical limit to ball diameter with the spherical tool. We have found that the use of commercially available toroidal wheels permits long effective cutting radii, which in turn improve finish and minimize grooving for a set feed. In addition, toroidal wheels are easier than spherical wheels to center accurately. Cutting parameters are also easier to control because the feed rate past the tool does not change as the slope of the work changes. The drawback to the toroidal wheel is the more complex calculation of the tool path. Of course, once the algorithm is worked out, the tool path is as easily calculated as for a spherical tool. We have performed two experiments with the Large Optical Generator (LOG) that were ideally suited to three-axis contouring--surfaces that have no axis of rotational symmetry. By oscillating the cutting head horizontally or vertically (in addition to the motions required to generate the power of the surface) , and carefully coordinating those motions with table rotation, the mostly astigmatic departure for these surfaces is produced. The first experiment was a pair of reflector molds that together correct the spherical aberration of the Arecibo radio telescope. The larger of these was 5 m in diameter and had a 12 cm departure from the best-fit sphere. The second experiment was the generation of a purely astigmatic surface to demonstrate the feasibility of producing axially symmetric asphe.rics while mounted and rotated about any off-axis point. Measurements of the latter (the first experiment had relatively

  13. SU-E-T-222: Computational Optimization of Monte Carlo Simulation On 4D Treatment Planning Using the Cloud Computing Technology

    SciTech Connect

    Chow, J

    2015-06-15

    Purpose: This study evaluated the efficiency of 4D lung radiation treatment planning using Monte Carlo simulation on the cloud. The EGSnrc Monte Carlo code was used in dose calculation on the 4D-CT image set. Methods: 4D lung radiation treatment plan was created by the DOSCTP linked to the cloud, based on the Amazon elastic compute cloud platform. Dose calculation was carried out by Monte Carlo simulation on the 4D-CT image set on the cloud, and results were sent to the FFD4D image deformation program for dose reconstruction. The dependence of computing time for treatment plan on the number of compute node was optimized with variations of the number of CT image set in the breathing cycle and dose reconstruction time of the FFD4D. Results: It is found that the dependence of computing time on the number of compute node was affected by the diminishing return of the number of node used in Monte Carlo simulation. Moreover, the performance of the 4D treatment planning could be optimized by using smaller than 10 compute nodes on the cloud. The effects of the number of image set and dose reconstruction time on the dependence of computing time on the number of node were not significant, as more than 15 compute nodes were used in Monte Carlo simulations. Conclusion: The issue of long computing time in 4D treatment plan, requiring Monte Carlo dose calculations in all CT image sets in the breathing cycle, can be solved using the cloud computing technology. It is concluded that the optimized number of compute node selected in simulation should be between 5 and 15, as the dependence of computing time on the number of node is significant.

  14. Two-Level Verification of Data Integrity for Data Storage in Cloud Computing

    NASA Astrophysics Data System (ADS)

    Xu, Guangwei; Chen, Chunlin; Wang, Hongya; Zang, Zhuping; Pang, Mugen; Jiang, Ping

    Data storage in cloud computing can save capital expenditure and relive burden of storage management for users. As the lose or corruption of files stored may happen, many researchers focus on the verification of data integrity. However, massive users often bring large numbers of verifying tasks for the auditor. Moreover, users also need to pay extra fee for these verifying tasks beyond storage fee. Therefore, we propose a two-level verification of data integrity to alleviate these problems. The key idea is to routinely verify the data integrity by users and arbitrate the challenge between the user and cloud provider by the auditor according to the MACs and ϕ values. The extensive performance simulations show that the proposed scheme obviously decreases auditor's verifying tasks and the ratio of wrong arbitration.

  15. A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path.

    PubMed

    Xie, Zhiqiang; Shao, Xia; Xin, Yu

    2016-01-01

    To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective.

  16. A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path

    PubMed Central

    Xie, Zhiqiang; Shao, Xia; Xin, Yu

    2016-01-01

    To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective. PMID:27490901

  17. An Assessment of Security Vulnerabilities Comprehension of Cloud Computing Environments: A Quantitative Study Using the Unified Theory of Acceptance and Use

    ERIC Educational Resources Information Center

    Venkatesh, Vijay P.

    2013-01-01

    The current computing landscape owes its roots to the birth of hardware and software technologies from the 1940s and 1950s. Since then, the advent of mainframes, miniaturized computing, and internetworking has given rise to the now prevalent cloud computing era. In the past few months just after 2010, cloud computing adoption has picked up pace…

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

    PubMed Central

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

    2011-01-01

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

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

    PubMed

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

    2011-01-01

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

  20. Cloud Computing: Short Term Impacts of 1:1 Computing in the Sixth Grade

    ERIC Educational Resources Information Center

    Bebell, Damian; Clarkson, Apryl; Burraston, James

    2014-01-01

    Many parents, educators, and policy makers see great potential for leveraging tools like laptop computers, tablets, and smartphones in the classrooms of the world. Under budget constraints and shared access to equipment for students and teachers, the impacts have been irregular but hint at greater possibilities in 1:1 student computing settings.…

  1. 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

  2. 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.

  3. A Telemetric system for electromagnetic measurements based on Internet technologies and cloud computing

    NASA Astrophysics Data System (ADS)

    Tassoulas, E.; Vereses, A.; Agiakatsikas, D.; Koulouras, Gr.; Nomicos, C.

    2010-05-01

    A few years ago, real time communication, data collection and transmission from a field station measuring electromagnetic variations in the middle of nowhere, was a very expensive accomplishment. Nowadays, wireless communications and Internet access reach end users much easier and they are less expensive. WIFI, GPRS, 3G or Satellite Internet connections enable this to come true even at the most detached areas of our world where no cables can easily reach at a low cost. Except for the effective potential range, these communication technologies can also give high speed, constant and low cost Internet access. As the Internet access speeds grow, a new term is coming to the foreground. Cloud Computing. The terminology of Cloud Computing refers to a wide subset of Internet technologies usage that the clients: A)Do not need to store any valuable information in any physical infrastructure owned by themselves. B)Consume on-line resources from a third party provider, enabling them to focus on their productivity without having to worry about their data or any other possible local hardware failure. C)Collaborate and share between associates faster and easier, as they can access their work from anywhere, just with the existence of Internet access. This telemetric system, relies on Cloud Computing for the delivery of collected data from the field station to an on-line storage. Collaborators and scientists, can be synchronized with the on-line storage, make changes and synchronize vice versa. Local storage at the field station end, is only needed in the case of an Internet connection failure, so that the data can be stored until the Internet connection is regained. Local storage at the user's side is optional, however desirable thus giving the ability to work off-line and synchronize again the changes when one goes on-line.

  4. AGM: A DSL for mobile cloud computing based on directed graph

    NASA Astrophysics Data System (ADS)

    Tanković, Nikola; Grbac, Tihana Galinac

    2016-06-01

    This paper summarizes a novel approach for consuming a domain specific language (DSL) by transforming it to a directed graph representation persisted by a graph database. Using such specialized database enables advanced navigation trough the stored model exposing only relevant subsets of meta-data to different involved services and components. We applied this approach in a mobile cloud computing system and used it to model several mobile applications in retail, supply chain management and merchandising domain. These application are distributed in a Software-as-a-Service (SaaS) fashion and used by thousands of customers in Croatia. We report on lessons learned and propose further research on this topic.

  5. The method of a joint intraday security check system based on cloud computing

    NASA Astrophysics Data System (ADS)

    Dong, Wei; Feng, Changyou; Zhou, Caiqi; Cai, Zhi; Dan, Xu; Dai, Sai; Zhang, Chuancheng

    2017-01-01

    The intraday security check is the core application in the dispatching control system. The existing security check calculation only uses the dispatch center’s local model and data as the functional margin. This paper introduces the design of all-grid intraday joint security check system based on cloud computing and its implementation. To reduce the effect of subarea bad data on the all-grid security check, a new power flow algorithm basing on comparison and adjustment with inter-provincial tie-line plan is presented. And the numerical example illustrated the effectiveness and feasibility of the proposed method.

  6. Ion Clouds in the Inductively Coupled Plasma Torch: A Closer Look through Computations.

    PubMed

    Aghaei, Maryam; Lindner, Helmut; Bogaerts, Annemie

    2016-08-16

    We have computationally investigated the introduction of copper elemental particles in an inductively coupled plasma torch connected to a sampling cone, including for the first time the ionization of the sample. The sample is inserted as liquid particles, which are followed inside the entire torch, i.e., from the injector inlet up to the ionization and reaching the sampler. The spatial position of the ion clouds inside the torch as well as detailed information on the copper species fluxes at the position of the sampler orifice and the exhausts of the torch are provided. The effect of on- and off-axis injection is studied. We clearly show that the ion clouds of on-axis injected material are located closer to the sampler with less radial diffusion. This guarantees a higher transport efficiency through the sampler cone. Moreover, our model reveals the optimum ranges of applied power and flow rates, which ensure the proper position of ion clouds inside the torch, i.e., close enough to the sampler to increase the fraction that can enter the mass spectrometer and with minimum loss of material toward the exhausts as well as a sufficiently high plasma temperature for efficient ionization.

  7. Predicting Cloud Computing Technology Adoption by Organizations: An Empirical Integration of Technology Acceptance Model and Theory of Planned Behavior

    ERIC Educational Resources Information Center

    Ekufu, ThankGod K.

    2012-01-01

    Organizations are finding it difficult in today's economy to implement the vast information technology infrastructure required to effectively conduct their business operations. Despite the fact that some of these organizations are leveraging on the computational powers and the cost-saving benefits of computing on the Internet cloud, others…

  8. Cloud Computing Applications in Support of Earth Science Activities at Marshall Space Flight Center

    NASA Astrophysics Data System (ADS)

    Molthan, A.; Limaye, A. S.

    2011-12-01

    Currently, the NASA Nebula Cloud Computing Platform is available to Agency personnel in a pre-release status as the system undergoes a formal operational readiness review. Over the past year, two projects within the Earth Science Office at NASA Marshall Space Flight Center have been investigating the performance and value of Nebula's "Infrastructure as a Service", or "IaaS" concept and applying cloud computing concepts to advance their respective mission goals. The Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique NASA satellite observations and weather forecasting capabilities for use within the operational forecasting community through partnerships with NOAA's National Weather Service (NWS). SPoRT has evaluated the performance of the Weather Research and Forecasting (WRF) model on virtual machines deployed within Nebula and used Nebula instances to simulate local forecasts in support of regional forecast studies of interest to select NWS forecast offices. In addition to weather forecasting applications, rapidly deployable Nebula virtual machines have supported the processing of high resolution NASA satellite imagery to support disaster assessment following the historic severe weather and tornado outbreak of April 27, 2011. Other modeling and satellite analysis activities are underway in support of NASA's SERVIR program, which integrates satellite observations, ground-based data and forecast models to monitor environmental change and improve disaster response in Central America, the Caribbean, Africa, and the Himalayas. Leveraging SPoRT's experience, SERVIR is working to establish a real-time weather forecasting model for Central America. Other modeling efforts include hydrologic forecasts for Kenya, driven by NASA satellite observations and reanalysis data sets provided by the broader meteorological community. Forecast modeling efforts are supplemented by short-term forecasts of convective initiation, determined by

  9. A Power Efficient Exaflop Computer Design for Global Cloud System Resolving Climate Models.

    NASA Astrophysics Data System (ADS)

    Wehner, M. F.; Oliker, L.; Shalf, J.

    2008-12-01

    Exascale computers would allow routine ensemble modeling of the global climate system at the cloud system resolving scale. Power and cost requirements of traditional architecture systems are likely to delay such capability for many years. We present an alternative route to the exascale using embedded processor technology to design a system optimized for ultra high resolution climate modeling. These power efficient processors, used in consumer electronic devices such as mobile phones, portable music players, cameras, etc., can be tailored to the specific needs of scientific computing. We project that a system capable of integrating a kilometer scale climate model a thousand times faster than real time could be designed and built in a five year time scale for US$75M with a power consumption of 3MW. This is cheaper, more power efficient and sooner than any other existing technology.

  10. An improved clustering algorithm of tunnel monitoring data for cloud computing.

    PubMed

    Zhong, Luo; Tang, KunHao; Li, Lin; Yang, Guang; Ye, JingJing

    2014-01-01

    With the rapid development of urban construction, the number of urban tunnels is increasing and the data they produce become more and more complex. It results in the fact that the traditional clustering algorithm cannot handle the mass data of the tunnel. To solve this problem, an improved parallel clustering algorithm based on k-means has been proposed. It is a clustering algorithm using the MapReduce within cloud computing that deals with data. It not only has the advantage of being used to deal with mass data but also is more efficient. Moreover, it is able to compute the average dissimilarity degree of each cluster in order to clean the abnormal data.

  11. Elucidating Ligand-Modulated Conformational Landscape of GPCRs Using Cloud-Computing Approaches.

    PubMed

    Shukla, Diwakar; Lawrenz, Morgan; Pande, Vijay S

    2015-01-01

    G-protein-coupled receptors (GPCRs) are a versatile family of membrane-bound signaling proteins. Despite the recent successes in obtaining crystal structures of GPCRs, much needs to be learned about the conformational changes associated with their activation. Furthermore, the mechanism by which ligands modulate the activation of GPCRs has remained elusive. Molecular simulations provide a way of obtaining detailed an atomistic description of GPCR activation dynamics. However, simulating GPCR activation is challenging due to the long timescales involved and the associated challenge of gaining insights from the "Big" simulation datasets. Here, we demonstrate how cloud-computing approaches have been used to tackle these challenges and obtain insights into the activation mechanism of GPCRs. In particular, we review the use of Markov state model (MSM)-based sampling algorithms for sampling milliseconds of dynamics of a major drug target, the G-protein-coupled receptor β2-AR. MSMs of agonist and inverse agonist-bound β2-AR reveal multiple activation pathways and how ligands function via modulation of the ensemble of activation pathways. We target this ensemble of conformations with computer-aided drug design approaches, with the goal of designing drugs that interact more closely with diverse receptor states, for overall increased efficacy and specificity. We conclude by discussing how cloud-based approaches present a powerful and broadly available tool for studying the complex biological systems routinely.

  12. An innovative privacy preserving technique for incremental datasets on cloud computing.

    PubMed

    Aldeen, Yousra Abdul Alsahib S; Salleh, Mazleena; Aljeroudi, Yazan

    2016-08-01

    Cloud computing (CC) is a magnificent service-based delivery with gigantic computer processing power and data storage across connected communications channels. It imparted overwhelming technological impetus in the internet (web) mediated IT industry, where users can easily share private data for further analysis and mining. Furthermore, user affable CC services enable to deploy sundry applications economically. Meanwhile, simple data sharing impelled various phishing attacks and malware assisted security threats. Some privacy sensitive applications like health services on cloud that are built with several economic and operational benefits necessitate enhanced security. Thus, absolute cyberspace security and mitigation against phishing blitz became mandatory to protect overall data privacy. Typically, diverse applications datasets are anonymized with better privacy to owners without providing all secrecy requirements to the newly added records. Some proposed techniques emphasized this issue by re-anonymizing the datasets from the scratch. The utmost privacy protection over incremental datasets on CC is far from being achieved. Certainly, the distribution of huge datasets volume across multiple storage nodes limits the privacy preservation. In this view, we propose a new anonymization technique to attain better privacy protection with high data utility over distributed and incremental datasets on CC. The proficiency of data privacy preservation and improved confidentiality requirements is demonstrated through performance evaluation.

  13. Running climate model in the commercial cloud computing environment: A case study using Community Earth System Model (CESM)

    NASA Astrophysics Data System (ADS)

    Chen, X.; Huang, X.; Jiao, C.; Flanner, M.; Raeker, T.; Palen, B.

    2015-12-01

    Numerical model is the major tool used in the studies of climate change and climate projection. Because of the enormous complexity involved in such climate models, they are usually run on supercomputing centers or at least high-performance computing clusters. The cloud computing environment, however, offers an alternative option for running climate models. Compared to traditional supercomputing environment, cloud computing offers more flexibility yet also extra technical challenges. Using the CESM (community earth system model) as a case study, we test the feasibility of running the climate model in the cloud-based virtual computing environment. Using the cloud computing resources offered by Amazon Web Service (AWS) Elastic Compute Cloud (EC2) and an open-source software, StarCluster, which can set up virtual cluster, we investigate how to run the CESM on AWS EC2 and the efficiency of parallelization of CESM on the AWS virtual cluster. We created virtual computing cluster using StarCluster on the AWS EC2 instances and carried out CESM simulations on such virtual cluster. We then compared the wall-clock time for one year of CESM simulation on the virtual cluster with that on a local high-performance computing (HPC) cluster with infiniband connections and operated by the University of Michigan. The results show that the CESM model can be efficiently scaled with number of CPUs on the AWS EC2 virtual computer cluster, and the parallelization efficiency is comparable to that on local HPC cluster. For standard configuration of the CESM at a spatial resolution of 1.9-degree latitude and 2.5-degree longitude, increasing the number of CPUs from 16 to 64 leads to a more than twice reduction in wall-clock running time and the scaling is nearly linear. Beyond 64 CPUs, the communication latency starts to overweight the saving of distributed computing and the parallelization efficiency becomes nearly level off.

  14. Resources and Costs for Microbial Sequence Analysis Evaluated Using Virtual Machines and Cloud Computing

    PubMed Central

    Angiuoli, Samuel V.; White, James R.; Matalka, Malcolm; White, Owen; Fricke, W. Florian

    2011-01-01

    Background The widespread popularity of genomic applications is threatened by the “bioinformatics bottleneck” resulting from uncertainty about the cost and infrastructure needed to meet increasing demands for next-generation sequence analysis. Cloud computing services have been discussed as potential new bioinformatics support systems but have not been evaluated thoroughly. Results We present benchmark costs and runtimes for common microbial genomics applications, including 16S rRNA analysis, microbial whole-genome shotgun (WGS) sequence assembly and annotation, WGS metagenomics and large-scale BLAST. Sequence dataset types and sizes were selected to correspond to outputs typically generated by small- to midsize facilities equipped with 454 and Illumina platforms, except for WGS metagenomics where sampling of Illumina data was used. Automated analysis pipelines, as implemented in the CloVR virtual machine, were used in order to guarantee transparency, reproducibility and portability across different operating systems, including the commercial Amazon Elastic Compute Cloud (EC2), which was used to attach real dollar costs to each analysis type. We found considerable differences in computational requirements, runtimes and costs associated with different microbial genomics applications. While all 16S analyses completed on a single-CPU desktop in under three hours, microbial genome and metagenome analyses utilized multi-CPU support of up to 120 CPUs on Amazon EC2, where each analysis completed in under 24 hours for less than $60. Representative datasets were used to estimate maximum data throughput on different cluster sizes and to compare costs between EC2 and comparable local grid servers. Conclusions Although bioinformatics requirements for microbial genomics depend on dataset characteristics and the analysis protocols applied, our results suggests that smaller sequencing facilities (up to three Roche/454 or one Illumina GAIIx sequencer) invested in 16S r

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

    SciTech Connect

    Hasenkamp, Daren; Sim, Alexander; Wehner, Michael; Wu, Kesheng

    2010-09-30

    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, while 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.

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

    NASA Astrophysics Data System (ADS)

    Ball, N. M.

    2013-10-01

    To-date, computing systems have allowed either sophisticated analysis of small datasets, as exemplified by most astronomy software, or simple analysis of large datasets, such as database queries. At the Canadian Astronomy Data Centre, we have combined our cloud computing system, the Canadian Advanced Network for Astronomical Research (CANFAR), with the world's most advanced machine learning software, Skytree, to create the world's first cloud computing system for data mining in astronomy. CANFAR provides a generic environment for the storage and processing of large datasets, removing the requirement for an individual or project to set up and maintain a computing system when implementing an extensive undertaking such as a survey pipeline. 500 processor cores and several hundred terabytes of persistent storage are currently available to users, and both the storage and processing infrastructure are expandable. The storage is implemented via the International Virtual Observatory Alliance's VOSpace protocol, and is available as a mounted filesystem accessible both interactively, and to all processing jobs. The user interacts with CANFAR by utilizing virtual machines, which appear to them as equivalent to a desktop. Each machine is replicated as desired to perform large-scale parallel processing. Such an arrangement enables the user to immediately install and run the same astronomy code that they already utilize, in the same way as on a desktop. In addition, unlike many cloud systems, batch job scheduling is handled for the user on multiple virtual machines by the Condor job queueing system. Skytree is installed and run just as any other software on the system, and thus acts as a library of command line data mining functions that can be integrated into one's wider analysis. Thus we have created a generic environment for large-scale analysis by data mining, in the same way that CANFAR itself has done for storage and processing. Because Skytree scales to large data in

  17. Rainbow: a tool for large-scale whole-genome sequencing data analysis using cloud computing

    PubMed Central

    2013-01-01

    Background Technical improvements have decreased sequencing costs and, as a result, the size and number of genomic datasets have increased rapidly. Because of the lower cost, large amounts of sequence data are now being produced by small to midsize research groups. Crossbow is a software tool that can detect single nucleotide polymorphisms (SNPs) in whole-genome sequencing (WGS) data from a single subject; however, Crossbow has a number of limitations when applied to multiple subjects from large-scale WGS projects. The data storage and CPU resources that are required for large-scale whole genome sequencing data analyses are too large for many core facilities and individual laboratories to provide. To help meet these challenges, we have developed Rainbow, a cloud-based software package that can assist in the automation of large-scale WGS data analyses. Results Here, we evaluated the performance of Rainbow by analyzing 44 different whole-genome-sequenced subjects. Rainbow has the capacity to process genomic data from more than 500 subjects in two weeks using cloud computing provided by the Amazon Web Service. The time includes the import and export of the data using Amazon Import/Export service. The average cost of processing a single sample in the cloud was less than 120 US dollars. Compared with Crossbow, the main improvements incorporated into Rainbow include the ability: (1) to handle BAM as well as FASTQ input files; (2) to split large sequence files for better load balance downstream; (3) to log the running metrics in data processing and monitoring multiple Amazon Elastic Compute Cloud (EC2) instances; and (4) to merge SOAPsnp outputs for multiple individuals into a single file to facilitate downstream genome-wide association studies. Conclusions Rainbow is a scalable, cost-effective, and open-source tool for large-scale WGS data analysis. For human WGS data sequenced by either the Illumina HiSeq 2000 or HiSeq 2500 platforms, Rainbow can be used straight out of

  18. Optimizing the Use of Storage Systems Provided by Cloud Computing Environments

    NASA Astrophysics Data System (ADS)

    Gallagher, J. H.; Potter, N.; Byrne, D. A.; Ogata, J.; Relph, J.

    2013-12-01

    Cloud computing systems present a set of features that include familiar computing resources (albeit augmented to support dynamic scaling of processing power) bundled with a mix of conventional and unconventional storage systems. The linux base on which many Cloud environments (e.g., Amazon) are based make it tempting to assume that any Unix software will run efficiently in this environment efficiently without change. OPeNDAP and NODC collaborated on a short project to explore how the S3 and Glacier storage systems provided by the Amazon Cloud Computing infrastructure could be used with a data server developed primarily to access data stored in a traditional Unix file system. Our work used the Amazon cloud system, but we strived for designs that could be adapted easily to other systems like OpenStack. Lastly, we evaluated different architectures from a computer security perspective. We found that there are considerable issues associated with treating S3 as if it is a traditional file system, even though doing so is conceptually simple. These issues include performance penalties because using a software tool that emulates a traditional file system to store data in S3 performs poorly when compared to a storing data directly in S3. We also found there are important benefits beyond performance to ensuring that data written to S3 can directly accessed without relying on a specific software tool. To provide a hierarchical organization to the data stored in S3, we wrote 'catalog' files, using XML. These catalog files map discrete files to S3 access keys. Like a traditional file system's directories, the catalogs can also contain references to other catalogs, providing a simple but effective hierarchy overlaid on top of S3's flat storage space. An added benefit to these catalogs is that they can be viewed in a web browser; our storage scheme provides both efficient access for the data server and access via a web browser. We also looked at the Glacier storage system and

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

    PubMed

    Yokohama, Noriya

    2013-07-01

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

  20. 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.

  1. Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering

    PubMed Central

    2014-01-01

    Backgroud Taking the advan tage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. Results In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Conclusions Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS. PMID:24717145

  2. A security-awareness virtual machine management scheme based on Chinese wall policy in cloud computing.

    PubMed

    Yu, Si; Gui, Xiaolin; Lin, Jiancai; Tian, Feng; Zhao, Jianqiang; Dai, Min

    2014-01-01

    Cloud computing gets increasing attention for its capacity to leverage developers from infrastructure management tasks. However, recent works reveal that side channel attacks can lead to privacy leakage in the cloud. Enhancing isolation between users is an effective solution to eliminate the attack. In this paper, to eliminate side channel attacks, we investigate the isolation enhancement scheme from the aspect of virtual machine (VM) management. The security-awareness VMs management scheme (SVMS), a VMs isolation enhancement scheme to defend against side channel attacks, is proposed. First, we use the aggressive conflict of interest relation (ACIR) and aggressive in ally with relation (AIAR) to describe user constraint relations. Second, based on the Chinese wall policy, we put forward four isolation rules. Third, the VMs placement and migration algorithms are designed to enforce VMs isolation between the conflict users. Finally, based on the normal distribution, we conduct a series of experiments to evaluate SVMS. The experimental results show that SVMS is efficient in guaranteeing isolation between VMs owned by conflict users, while the resource utilization rate decreases but not by much.

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

    SciTech Connect

    Hameed, Abdul; Khoshkbarforoushha, Alireza; Ranjan, Rajiv; Jayaraman, Prem Prakash; Kolodziej, Joanna; Balaji, Pavan; Zeadally, Sherali; Malluhi, Qutaibah Marwan; Tziritas, Nikos; Vishnu, Abhinav; Khan, Samee U.; Zomaya, Albert

    2014-06-06

    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 subject 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.

  4. Leveraging Cloud Computing to Address Public Health Disparities: An Analysis of the SPHPS.

    PubMed

    Jalali, Arash; Olabode, Olusegun A; Bell, Christopher M

    2012-01-01

    As the use of certified electronic health record technology (CEHRT) has continued to gain prominence in hospitals and physician practices, public health agencies and health professionals have the ability to access health data through health information exchanges (HIE). With such knowledge health providers are well positioned to positively affect population health, and enhance health status or quality-of-life outcomes in at-risk populations. Through big data analytics, predictive analytics and cloud computing, public health agencies have the opportunity to observe emerging public health threats in real-time and provide more effective interventions addressing health disparities in our communities. The Smarter Public Health Prevention System (SPHPS) provides real-time reporting of potential public health threats to public health leaders through the use of a simple and efficient dashboard and links people with needed personal health services through mobile platforms for smartphones and tablets to promote and encourage healthy behaviors in our communities. The purpose of this working paper is to evaluate how a secure virtual private cloud (VPC) solution could facilitate the implementation of the SPHPS in order to address public health disparities.

  5. A Security-Awareness Virtual Machine Management Scheme Based on Chinese Wall Policy in Cloud Computing

    PubMed Central

    Gui, Xiaolin; Lin, Jiancai; Tian, Feng; Zhao, Jianqiang; Dai, Min

    2014-01-01

    Cloud computing gets increasing attention for its capacity to leverage developers from infrastructure management tasks. However, recent works reveal that side channel attacks can lead to privacy leakage in the cloud. Enhancing isolation between users is an effective solution to eliminate the attack. In this paper, to eliminate side channel attacks, we investigate the isolation enhancement scheme from the aspect of virtual machine (VM) management. The security-awareness VMs management scheme (SVMS), a VMs isolation enhancement scheme to defend against side channel attacks, is proposed. First, we use the aggressive conflict of interest relation (ACIR) and aggressive in ally with relation (AIAR) to describe user constraint relations. Second, based on the Chinese wall policy, we put forward four isolation rules. Third, the VMs placement and migration algorithms are designed to enforce VMs isolation between the conflict users. Finally, based on the normal distribution, we conduct a series of experiments to evaluate SVMS. The experimental results show that SVMS is efficient in guaranteeing isolation between VMs owned by conflict users, while the resource utilization rate decreases but not by much. PMID:24688434

  6. Evaluating Cloud Computing in the Proposed NASA DESDynI Ground Data System

    NASA Technical Reports Server (NTRS)

    Tran, John J.; Cinquini, Luca; Mattmann, Chris A.; Zimdars, Paul A.; Cuddy, David T.; Leung, Kon S.; Kwoun, Oh-Ig; Crichton, Dan; Freeborn, Dana

    2011-01-01

    The proposed NASA Deformation, Ecosystem Structure and Dynamics of Ice (DESDynI) mission would be a first-of-breed endeavor that would fundamentally change the paradigm by which Earth Science data systems at NASA are built. DESDynI is evaluating a distributed architecture where expert science nodes around the country all engage in some form of mission processing and data archiving. This is compared to the traditional NASA Earth Science missions where the science processing is typically centralized. What's more, DESDynI is poised to profoundly increase the amount of data collection and processing well into the 5 terabyte/day and tens of thousands of job range, both of which comprise a tremendous challenge to DESDynI's proposed distributed data system architecture. In this paper, we report on a set of architectural trade studies and benchmarks meant to inform the DESDynI mission and the broader community of the impacts of these unprecedented requirements. In particular, we evaluate the benefits of cloud computing and its integration with our existing NASA ground data system software called Apache Object Oriented Data Technology (OODT). The preliminary conclusions of our study suggest that the use of the cloud and OODT together synergistically form an effective, efficient and extensible combination that could meet the challenges of NASA science missions requiring DESDynI-like data collection and processing volumes at reduced costs.

  7. Bio-signal analysis system design with support vector machines based on cloud computing service architecture.

    PubMed

    Shen, Chia-Ping; Chen, Wei-Hsin; Chen, Jia-Ming; Hsu, Kai-Ping; Lin, Jeng-Wei; Chiu, Ming-Jang; Chen, Chi-Huang; Lai, Feipei

    2010-01-01

    Today, many bio-signals such as Electroencephalography (EEG) are recorded in digital format. It is an emerging research area of analyzing these digital bio-signals to extract useful health information in biomedical engineering. In this paper, a bio-signal analyzing cloud computing architecture, called BACCA, is proposed. The system has been designed with the purpose of seamless integration into the National Taiwan University Health Information System. Based on the concept of. NET Service Oriented Architecture, the system integrates heterogeneous platforms, protocols, as well as applications. In this system, we add modern analytic functions such as approximated entropy and adaptive support vector machine (SVM). It is shown that the overall accuracy of EEG bio-signal analysis has increased to nearly 98% for different data sets, including open-source and clinical data sets.

  8. BioPig: Developing Cloud Computing Applications for Next-Generation Sequence Analysis

    SciTech Connect

    Bhatia, Karan; Wang, Zhong

    2011-03-22

    Next Generation sequencing is producing ever larger data sizes with a growth rate outpacing Moore's Law. The data deluge has made many of the current sequenceanalysis tools obsolete because they do not scale with data. Here we present BioPig, a collection of cloud computing tools to scale data analysis and management. Pig is aflexible data scripting language that uses Apache's Hadoop data structure and map reduce framework to process very large data files in parallel and combine the results.BioPig extends Pig with capability with sequence analysis. We will show the performance of BioPig on a variety of bioinformatics tasks, including screeningsequence contaminants, Illumina QA/QC, and gene discovery from metagenome data sets using the Rumen metagenome as an example.

  9. Cloud Computing Application for Hotspot Clustering Using Recursive Density Based Clustering (RDBC)

    NASA Astrophysics Data System (ADS)

    Santoso, Aries; Khiyarin Nisa, Karlina

    2016-01-01

    Indonesia has vast areas of tropical forest, but are often burned which causes extensive damage to property and human life. Monitoring hotspots can be one of the forest fire management. Each hotspot is recorded in dataset so that it can be processed and analyzed. This research aims to build a cloud computing application which visualizes hotspots clustering. This application uses the R programming language with Shiny web framework and implements Recursive Density Based Clustering (RDBC) algorithm. Clustering is done on hotspot dataset of the Kalimantan Island and South Sumatra Province to find the spread pattern of hotspots. The clustering results are evaluated using the Silhouette's Coefficient (SC) which yield best value 0.3220798 for Kalimantan dataset. Clustering pattern are displayed in the form of web pages so that it can be widely accessed and become the reference for fire occurrence prediction.

  10. Public-Private Partnerships in Cloud-Computing Services in the Context of Genomic Research.

    PubMed

    Granados Moreno, Palmira; Joly, Yann; Knoppers, Bartha Maria

    2017-01-01

    Public-private partnerships (PPPs) have been increasingly used to spur and facilitate innovation in a number of fields. In healthcare, the purpose of using a PPP is commonly to develop and/or provide vaccines and drugs against communicable diseases, mainly in developing or underdeveloped countries. With the advancement of technology and of the area of genomics, these partnerships also focus on large-scale genomic research projects that aim to advance the understanding of diseases that have a genetic component and to develop personalized treatments. This new focus has created new forms of PPPs that involve information technology companies, which provide computing infrastructure and services to store, analyze, and share the massive amounts of data genomic-related projects produce. In this article, we explore models of PPPs proposed to handle, protect, and share the genomic data collected and to further develop genomic-based medical products. We also identify the reasons that make these models suitable and the challenges they have yet to overcome. To achieve this, we describe the details and complexities of MSSNG, International Cancer Genome Consortium, and 100,000 Genomes Project, the three PPPs that focus on large-scale genomic research to better understand the genetic components of autism, cancer, rare diseases, and infectious diseases with the intention to find appropriate treatments. Organized as PPP and employing cloud-computing services, the three projects have advanced quickly and are likely to be important sources of research and development for future personalized medicine. However, there still are unresolved matters relating to conflicts of interest, commercialization, and data control. Learning from the challenges encountered by past PPPs allowed us to establish that developing guidelines to adequately manage personal health information stored in clouds and ensuring the protection of data integrity and privacy would be critical steps in the development of

  11. Cloud Computing Applications in Support of Earth Science Activities at Marshall Space Flight Center

    NASA Technical Reports Server (NTRS)

    Molthan, Andrew L.; Limaye, Ashutosh S.; Srikishen, Jayanthi

    2011-01-01

    Currently, the NASA Nebula Cloud Computing Platform is available to Agency personnel in a pre-release status as the system undergoes a formal operational readiness review. Over the past year, two projects within the Earth Science Office at NASA Marshall Space Flight Center have been investigating the performance and value of Nebula s "Infrastructure as a Service", or "IaaS" concept and applying cloud computing concepts to advance their respective mission goals. The Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique NASA satellite observations and weather forecasting capabilities for use within the operational forecasting community through partnerships with NOAA s National Weather Service (NWS). SPoRT has evaluated the performance of the Weather Research and Forecasting (WRF) model on virtual machines deployed within Nebula and used Nebula instances to simulate local forecasts in support of regional forecast studies of interest to select NWS forecast offices. In addition to weather forecasting applications, rapidly deployable Nebula virtual machines have supported the processing of high resolution NASA satellite imagery to support disaster assessment following the historic severe weather and tornado outbreak of April 27, 2011. Other modeling and satellite analysis activities are underway in support of NASA s SERVIR program, which integrates satellite observations, ground-based data and forecast models to monitor environmental change and improve disaster response in Central America, the Caribbean, Africa, and the Himalayas. Leveraging SPoRT s experience, SERVIR is working to establish a real-time weather forecasting model for Central America. Other modeling efforts include hydrologic forecasts for Kenya, driven by NASA satellite observations and reanalysis data sets provided by the broader meteorological community. Forecast modeling efforts are supplemented by short-term forecasts of convective initiation, determined by

  12. Elastic Extension of a CMS Computing Centre Resources on External Clouds

    NASA Astrophysics Data System (ADS)

    Codispoti, G.; Di Maria, R.; Aiftimiei, C.; Bonacorsi, D.; Calligola, P.; Ciaschini, V.; Costantini, A.; Dal Pra, S.; DeGirolamo, D.; Grandi, C.; Michelotto, D.; Panella, M.; Peco, G.; Sapunenko, V.; Sgaravatto, M.; Taneja, S.; Zizzi, G.

    2016-10-01

    After the successful LHC data taking in Run-I and in view of the future runs, the LHC experiments are facing new challenges in the design and operation of the computing facilities. The computing infrastructure for Run-II is dimensioned to cope at most with the average amount of data recorded. The usage peaks, as already observed in Run-I, may however originate large backlogs, thus delaying the completion of the data reconstruction and ultimately the data availability for physics analysis. In order to cope with the production peaks, CMS - along the lines followed by other LHC experiments - is exploring the opportunity to access Cloud resources provided by external partners or commercial providers. Specific use cases have already been explored and successfully exploited during Long Shutdown 1 (LS1) and the first part of Run 2. In this work we present the proof of concept of the elastic extension of a CMS site, specifically the Bologna Tier-3, on an external OpenStack infrastructure. We focus on the “Cloud Bursting” of a CMS Grid site using a newly designed LSF configuration that allows the dynamic registration of new worker nodes to LSF. In this approach, the dynamically added worker nodes instantiated on the OpenStack infrastructure are transparently accessed by the LHC Grid tools and at the same time they serve as an extension of the farm for the local usage. The amount of resources allocated thus can be elastically modeled to cope up with the needs of CMS experiment and local users. Moreover, a direct access/integration of OpenStack resources to the CMS workload management system is explored. In this paper we present this approach, we report on the performances of the on-demand allocated resources, and we discuss the lessons learned and the next steps.

  13. Public–Private Partnerships in Cloud-Computing Services in the Context of Genomic Research

    PubMed Central

    Granados Moreno, Palmira; Joly, Yann; Knoppers, Bartha Maria

    2017-01-01

    Public–private partnerships (PPPs) have been increasingly used to spur and facilitate innovation in a number of fields. In healthcare, the purpose of using a PPP is commonly to develop and/or provide vaccines and drugs against communicable diseases, mainly in developing or underdeveloped countries. With the advancement of technology and of the area of genomics, these partnerships also focus on large-scale genomic research projects that aim to advance the understanding of diseases that have a genetic component and to develop personalized treatments. This new focus has created new forms of PPPs that involve information technology companies, which provide computing infrastructure and services to store, analyze, and share the massive amounts of data genomic-related projects produce. In this article, we explore models of PPPs proposed to handle, protect, and share the genomic data collected and to further develop genomic-based medical products. We also identify the reasons that make these models suitable and the challenges they have yet to overcome. To achieve this, we describe the details and complexities of MSSNG, International Cancer Genome Consortium, and 100,000 Genomes Project, the three PPPs that focus on large-scale genomic research to better understand the genetic components of autism, cancer, rare diseases, and infectious diseases with the intention to find appropriate treatments. Organized as PPP and employing cloud-computing services, the three projects have advanced quickly and are likely to be important sources of research and development for future personalized medicine. However, there still are unresolved matters relating to conflicts of interest, commercialization, and data control. Learning from the challenges encountered by past PPPs allowed us to establish that developing guidelines to adequately manage personal health information stored in clouds and ensuring the protection of data integrity and privacy would be critical steps in the development

  14. Classification of large-scale fundus image data sets: a cloud-computing framework.

    PubMed

    Roychowdhury, Sohini; Roychowdhury, Sohini; Roychowdhury, Sohini

    2016-08-01

    Large medical image data sets with high dimensionality require substantial amount of computation time for data creation and data processing. This paper presents a novel generalized method that finds optimal image-based feature sets that reduce computational time complexity while maximizing overall classification accuracy for detection of diabetic retinopathy (DR). First, region-based and pixel-based features are extracted from fundus images for classification of DR lesions and vessel-like structures. Next, feature ranking strategies are used to distinguish the optimal classification feature sets. DR lesion and vessel classification accuracies are computed using the boosted decision tree and decision forest classifiers in the Microsoft Azure Machine Learning Studio platform, respectively. For images from the DIARETDB1 data set, 40 of its highest-ranked features are used to classify four DR lesion types with an average classification accuracy of 90.1% in 792 seconds. Also, for classification of red lesion regions and hemorrhages from microaneurysms, accuracies of 85% and 72% are observed, respectively. For images from STARE data set, 40 high-ranked features can classify minor blood vessels with an accuracy of 83.5% in 326 seconds. Such cloud-based fundus image analysis systems can significantly enhance the borderline classification performances in automated screening systems.

  15. Dynamic Voltage Frequency Scaling Simulator for Real Workflows Energy-Aware Management in Green Cloud Computing

    PubMed Central

    Cotes-Ruiz, Iván Tomás; Prado, Rocío P.; García-Galán, Sebastián; Muñoz-Expósito, José Enrique; Ruiz-Reyes, Nicolás

    2017-01-01

    Nowadays, the growing computational capabilities of Cloud systems rely on the reduction of the consumed power of their data centers to make them sustainable and economically profitable. The efficient management of computing resources is at the heart of any energy-aware data center and of special relevance is the adaptation of its performance to workload. Intensive computing applications in diverse areas of science generate complex workload called workflows, whose successful management in terms of energy saving is still at its beginning. WorkflowSim is currently one of the most advanced simulators for research on workflows processing, offering advanced features such as task clustering and failure policies. In this work, an expected power-aware extension of WorkflowSim is presented. This new tool integrates a power model based on a computing-plus-communication design to allow the optimization of new management strategies in energy saving considering computing, reconfiguration and networks costs as well as quality of service, and it incorporates the preeminent strategy for on host energy saving: Dynamic Voltage Frequency Scaling (DVFS). The simulator is designed to be consistent in different real scenarios and to include a wide repertory of DVFS governors. Results showing the validity of the simulator in terms of resources utilization, frequency and voltage scaling, power, energy and time saving are presented. Also, results achieved by the intra-host DVFS strategy with different governors are compared to those of the data center using a recent and successful DVFS-based inter-host scheduling strategy as overlapped mechanism to the DVFS intra-host technique. PMID:28085932

  16. Dynamic Voltage Frequency Scaling Simulator for Real Workflows Energy-Aware Management in Green Cloud Computing.

    PubMed

    Cotes-Ruiz, Iván Tomás; Prado, Rocío P; García-Galán, Sebastián; Muñoz-Expósito, José Enrique; Ruiz-Reyes, Nicolás

    2017-01-01

    Nowadays, the growing computational capabilities of Cloud systems rely on the reduction of the consumed power of their data centers to make them sustainable and economically profitable. The efficient management of computing resources is at the heart of any energy-aware data center and of special relevance is the adaptation of its performance to workload. Intensive computing applications in diverse areas of science generate complex workload called workflows, whose successful management in terms of energy saving is still at its beginning. WorkflowSim is currently one of the most advanced simulators for research on workflows processing, offering advanced features such as task clustering and failure policies. In this work, an expected power-aware extension of WorkflowSim is presented. This new tool integrates a power model based on a computing-plus-communication design to allow the optimization of new management strategies in energy saving considering computing, reconfiguration and networks costs as well as quality of service, and it incorporates the preeminent strategy for on host energy saving: Dynamic Voltage Frequency Scaling (DVFS). The simulator is designed to be consistent in different real scenarios and to include a wide repertory of DVFS governors. Results showing the validity of the simulator in terms of resources utilization, frequency and voltage scaling, power, energy and time saving are presented. Also, results achieved by the intra-host DVFS strategy with different governors are compared to those of the data center using a recent and successful DVFS-based inter-host scheduling strategy as overlapped mechanism to the DVFS intra-host technique.

  17. A collaborative computing framework of cloud network and WBSN applied to fall detection and 3-D motion reconstruction.

    PubMed

    Lai, Chin-Feng; Chen, Min; Pan, Jeng-Shyang; Youn, Chan-Hyun; Chao, Han-Chieh

    2014-03-01

    As cloud computing and wireless body sensor network technologies become gradually developed, ubiquitous healthcare services prevent accidents instantly and effectively, as well as provides relevant information to reduce related processing time and cost. This study proposes a co-processing intermediary framework integrated cloud and wireless body sensor networks, which is mainly applied to fall detection and 3-D motion reconstruction. In this study, the main focuses includes distributed computing and resource allocation of processing sensing data over the computing architecture, network conditions and performance evaluation. Through this framework, the transmissions and computing time of sensing data are reduced to enhance overall performance for the services of fall events detection and 3-D motion reconstruction.

  18. 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

    ... debate of topics generally believed to be true to determine to what extent that claim is warranted. The... positive impact on our cyber security posture. The fourth topic to be explored in this series is cloud computing. The workshop on this topic will be held in Gaithersburg, MD on October 21, 2011....

  19. Examining the Fundamental Obstructs of Adopting Cloud Computing for 9-1-1 Dispatch Centers in the USA

    ERIC Educational Resources Information Center

    Osman, Abdulaziz

    2016-01-01

    The purpose of this research study was to examine the unknown fears of embracing cloud computing which stretches across measurements like fear of change from leaders and the complexity of the technology in 9-1-1 dispatch centers in USA. The problem that was addressed in the study was that many 9-1-1 dispatch centers in USA are still using old…

  20. Using Cloud-Computing Applications to Support Collaborative Scientific Inquiry: Examining Pre-Service Teachers' Perceived Barriers to Integration

    ERIC Educational Resources Information Center

    Donna, Joel D.; Miller, Brant G.

    2013-01-01

    Technology plays a crucial role in facilitating collaboration within the scientific community. Cloud-computing applications, such as Google Drive, can be used to model such collaboration and support inquiry within the secondary science classroom. Little is known about pre-service teachers' beliefs related to the envisioned use of collaborative,…

  1. 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

    ... has been developed through a transparent working group process, which included five NIST Cloud Computing Working Groups that were established in November 2010. DATES: Comments must be received on or... management effort or service provider interaction.'' Special Publication 800-145 (Draft). \\2\\ Office...

  2. Consumer Security Perceptions and the Perceived Influence on Adopting Cloud Computing: A Quantitative Study Using the Technology Acceptance Model

    ERIC Educational Resources Information Center

    Paquet, Katherine G.

    2013-01-01

    Cloud computing may provide cost benefits for organizations by eliminating the overhead costs of software, hardware, and maintenance (e.g., license renewals, upgrading software, servers and their physical storage space, administration along with funding a large IT department). In addition to the promised savings, the organization may require…

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

    PubMed

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

    2013-09-21

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

  4. Ultrafast and scalable cone-beam CT reconstruction using MapReduce in a cloud computing environment

    PubMed Central

    Meng, Bowen; Pratx, Guillem; Xing, Lei

    2011-01-01

    Purpose: Four-dimensional CT (4DCT) and cone beam CT (CBCT) are widely used in radiation therapy for accurate tumor target definition and localization. However, high-resolution and dynamic image reconstruction is computationally demanding because of the large amount of data processed. Efficient use of these imaging techniques in the clinic requires high-performance computing. The purpose of this work is to develop a novel ultrafast, scalable and reliable image reconstruction technique for 4D CBCT/CT using a parallel computing framework called MapReduce. We show the utility of MapReduce for solving large-scale medical physics problems in a cloud computing environment. Methods: In this work, we accelerated the Feldcamp–Davis–Kress (FDK) algorithm by porting it to Hadoop, an open-source MapReduce implementation. Gated phases from a 4DCT scans were reconstructed independently. Following the MapReduce formalism, Map functions were used to filter and backproject subsets of projections, and Reduce function to aggregate those partial backprojection into the whole volume. MapReduce automatically parallelized the reconstruction process on a large cluster of computer nodes. As a validation, reconstruction of a digital phantom and an acquired CatPhan 600 phantom was performed on a commercial cloud computing environment using the proposed 4D CBCT/CT reconstruction algorithm. Results: Speedup of reconstruction time is found to be roughly linear with the number of nodes employed. For instance, greater than 10 times speedup was achieved using 200 nodes for all cases, compared to the same code executed on a single machine. Without modifying the code, faster reconstruction is readily achievable by allocating more nodes in the cloud computing environment. Root mean square error between the images obtained using MapReduce and a single-threaded reference implementation was on the order of 10−7. Our study also proved that cloud computing with MapReduce is fault tolerant: the

  5. Efficient Nash Equilibrium Resource Allocation Based on Game Theory Mechanism in Cloud Computing by Using Auction.

    PubMed

    Nezarat, Amin; Dastghaibifard, G H

    2015-01-01

    One of the most complex issues in the cloud computing environment is the problem of resource allocation so that, on one hand, the cloud provider expects the most profitability and, on the other hand, users also expect to have the best resources at their disposal considering the budget constraints and time. In most previous work conducted, heuristic and evolutionary approaches have been used to solve this problem. Nevertheless, since the nature of this environment is based on economic methods, using such methods can decrease response time and reducing the complexity of the problem. In this paper, an auction-based method is proposed which determines the auction winner by applying game theory mechanism and holding a repetitive game with incomplete information in a non-cooperative environment. In this method, users calculate suitable price bid with their objective function during several round and repetitions and send it to the auctioneer; and the auctioneer chooses the winning player based the suggested utility function. In the proposed method, the end point of the game is the Nash equilibrium point where players are no longer inclined to alter their bid for that resource and the final bid also satisfies the auctioneer's utility function. To prove the response space convexity, the Lagrange method is used and the proposed model is simulated in the cloudsim and the results are compared with previous work. At the end, it is concluded that this method converges to a response in a shorter time, provides the lowest service level agreement violations and the most utility to the provider.

  6. Efficient Nash Equilibrium Resource Allocation Based on Game Theory Mechanism in Cloud Computing by Using Auction

    PubMed Central

    Nezarat, Amin; Dastghaibifard, GH

    2015-01-01

    One of the most complex issues in the cloud computing environment is the problem of resource allocation so that, on one hand, the cloud provider expects the most profitability and, on the other hand, users also expect to have the best resources at their disposal considering the budget constraints and time. In most previous work conducted, heuristic and evolutionary approaches have been used to solve this problem. Nevertheless, since the nature of this environment is based on economic methods, using such methods can decrease response time and reducing the complexity of the problem. In this paper, an auction-based method is proposed which determines the auction winner by applying game theory mechanism and holding a repetitive game with incomplete information in a non-cooperative environment. In this method, users calculate suitable price bid with their objective function during several round and repetitions and send it to the auctioneer; and the auctioneer chooses the winning player based the suggested utility function. In the proposed method, the end point of the game is the Nash equilibrium point where players are no longer inclined to alter their bid for that resource and the final bid also satisfies the auctioneer’s utility function. To prove the response space convexity, the Lagrange method is used and the proposed model is simulated in the cloudsim and the results are compared with previous work. At the end, it is concluded that this method converges to a response in a shorter time, provides the lowest service level agreement violations and the most utility to the provider. PMID:26431035

  7. iSPHERE - A New Approach to Collaborative Research and Cloud Computing

    NASA Astrophysics Data System (ADS)

    Al-Ubaidi, T.; Khodachenko, M. L.; Kallio, E. J.; Harry, A.; Alexeev, I. I.; Vázquez-Poletti, J. L.; Enke, H.; Magin, T.; Mair, M.; Scherf, M.; Poedts, S.; De Causmaecker, P.; Heynderickx, D.; Congedo, P.; Manolescu, I.; Esser, B.; Webb, S.; Ruja, C.

    2015-10-01

    The project iSPHERE (integrated Scientific Platform for HEterogeneous Research and Engineering) that has been proposed for Horizon 2020 (EINFRA-9- 2015, [1]) aims at creating a next generation Virtual Research Environment (VRE) that embraces existing and emerging technologies and standards in order to provide a versatile platform for scientific investigations and collaboration. The presentation will introduce the large project consortium, provide a comprehensive overview of iSPHERE's basic concepts and approaches and outline general user requirements that the VRE will strive to satisfy. An overview of the envisioned architecture will be given, focusing on the adapted Service Bus concept, i.e. the "Scientific Service Bus" as it is called in iSPHERE. The bus will act as a central hub for all communication and user access, and will be implemented in the course of the project. The agile approach [2] that has been chosen for detailed elaboration and documentation of user requirements, as well as for the actual implementation of the system, will be outlined and its motivation and basic structure will be discussed. The presentation will show which user communities will benefit and which concrete problems, scientific investigations are facing today, will be tackled by the system. Another focus of the presentation is iSPHERE's seamless integration of cloud computing resources and how these will benefit scientific modeling teams by providing a reliable and web based environment for cloud based model execution, storage of results, and comparison with measurements, including fully web based tools for data mining, analysis and visualization. Also the envisioned creation of a dedicated data model for experimental plasma physics will be discussed. It will be shown why the Scientific Service Bus provides an ideal basis to integrate a number of data models and communication protocols and to provide mechanisms for data exchange across multiple and even multidisciplinary platforms.

  8. Towards large-scale data analysis: challenges in the design of portable systems and use of Cloud computing.

    PubMed

    Diaz, Javier; Arrizabalaga, Saioa; Bustamante, Paul; Mesa, Iker; Añorga, Javier; Goya, Jon

    2013-01-01

    Portable systems and global communications open a broad spectrum for new health applications. In the framework of electrophysiological applications, several challenges are faced when developing portable systems embedded in Cloud computing services. In order to facilitate new developers in this area based on our experience, five areas of interest are presented in this paper where strategies can be applied for improving the performance of portable systems: transducer and conditioning, processing, wireless communications, battery and power management. Likewise, for Cloud services, scalability, portability, privacy and security guidelines have been highlighted.

  9. Computer Simulations and the Transition from Concrete Manipulation of Objects to Abstract Thinking in Elementary School Mathematics.

    ERIC Educational Resources Information Center

    Berlin, Donna; White, Arthur

    1986-01-01

    This study investigated the effects of combining interactive microcomputer simulations and concrete activities on the development of abstract thinking in elementary school mathematics. Students in grades 2-4 were assessed on tasks involving designs and patterns. (MNS)

  10. Bioinformatics clouds for big data manipulation

    PubMed Central

    2012-01-01

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

  11. [Construction and analysis of a monitoring system with remote real-time multiple physiological parameters based on cloud computing].

    PubMed

    Zhu, Lingyun; Li, Lianjie; Meng, Chunyan

    2014-12-01

    There have been problems in the existing multiple physiological parameter real-time monitoring system, such as insufficient server capacity for physiological data storage and analysis so that data consistency can not be guaranteed, poor performance in real-time, and other issues caused by the growing scale of data. We therefore pro posed a new solution which was with multiple physiological parameters and could calculate clustered background data storage and processing based on cloud computing. Through our studies, a batch processing for longitudinal analysis of patients' historical data was introduced. The process included the resource virtualization of IaaS layer for cloud platform, the construction of real-time computing platform of PaaS layer, the reception and analysis of data stream of SaaS layer, and the bottleneck problem of multi-parameter data transmission, etc. The results were to achieve in real-time physiological information transmission, storage and analysis of a large amount of data. The simulation test results showed that the remote multiple physiological parameter monitoring system based on cloud platform had obvious advantages in processing time and load balancing over the traditional server model. This architecture solved the problems including long turnaround time, poor performance of real-time analysis, lack of extensibility and other issues, which exist in the traditional remote medical services. Technical support was provided in order to facilitate a "wearable wireless sensor plus mobile wireless transmission plus cloud computing service" mode moving towards home health monitoring for multiple physiological parameter wireless monitoring.

  12. MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME

    PubMed Central

    Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

    2017-01-01

    Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments. PMID:28190948

  13. MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

    PubMed

    Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

    2016-01-01

    Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

  14. Astroinformatics, Cloud Computing, and New Science at the Canadian Astronomy Data Centre

    NASA Astrophysics Data System (ADS)

    Ball, Nicholas M.

    2012-01-01

    With a collection of over 0.5 petabytes of information, and serving nearly 3000 astronomers worldwide, CADC is one of the world's largest astronomy data centres. Its unique blend of astronomers and computer specialists results in a rich interaction between world experts that is ideal for the fostering of developments within astroinformatics. CADC retains science drivers as the primary motivator at each step of the process, from the receipt of raw data from telescopes to its release and use by scientists. Developments are therefore guided by maximal benefit to the astronomy community. The Canadian Advanced Network for Astronomical Research (CANFAR) is a University of Victoria and CADC project that builds on the existing CADC infrastructure to provide storage, processing, and analysis tools needed to enable astronomers to perform data-intensive astronomy on current and next generation datasets, using their existing codes. CANFAR provides a Virtual Cluster, accessed via a Virtual Machine environment, over which the user has complete control, and access to Cloud Computing on the Compute Canada Grid. Its services are compliant with the International Virtual Observatory Alliance standards. Hence, rather than build a new infrastructure for a project such as a sky survey, an individual or collaboration may utilize CANFAR. CANFAR's main focus is on the storage and processing of data. By analogy to the argument that CANFAR can provide the generic hardware portions of a data processing pipeline, we implement fast, scalable, data mining algorithms that simplify the generic portions of knowledge discovery in databases within current and future datasets. This is a necessary step in further enabling practical data-intensive astronomy. We show an example of the use of the SkyTree software to perform K-means clustering to determine which galaxies in the Next Generation Virgo Cluster Survey (NGVS) are cluster members. This problem is unsolved within the survey.

  15. Three-dimensional rendering of computer-generated holograms acquired from point-clouds on light field displays

    NASA Astrophysics Data System (ADS)

    Symeonidou, Athanasia; Blinder, David; Ceulemans, Beerend; Munteanu, Adrian; Schelkens, Peter

    2016-09-01

    Holograms, either optically acquired or simulated numerically from 3D datasets, such as point clouds, have special rendering requirements for display. Evaluating the quality of hologram generation techniques is not straightforward, since high-quality holographic display technologies are still immature, In this paper we present a framework for three-dimensional rendering of colour computer-generated holograms (CGHs) acquired from point-clouds, on high-end light field displays. This allows for the rendering of holographic content with horizontal parallax and wide viewing angle. We deploy prior work, namely a fast CGH method that inherently handles occlusion problems to acquire high quality colour holograms from point clouds. Our experiments showed that rendering holograms with the proposed framework provides 3D effect with depth disparity and horizontal-only with wide viewing angle. Therefore, it allows for the evaluation of CGH techniques regarding functional properties such as depth cues and efficient occlusion handling.

  16. SciServer Compute brings Analysis to Big Data in the Cloud

    NASA Astrophysics Data System (ADS)

    Raddick, Jordan; Medvedev, Dmitry; Lemson, Gerard; Souter, Barbara

    2016-06-01

    SciServer Compute uses Jupyter Notebooks running within server-side Docker containers attached to big data collections to bring advanced analysis to big data "in the cloud." SciServer Compute is a component in the SciServer Big-Data ecosystem under development at JHU, which will provide a stable, reproducible, sharable virtual research environment.SciServer builds on the popular CasJobs and SkyServer systems that made the Sloan Digital Sky Survey (SDSS) archive one of the most-used astronomical instruments. SciServer extends those systems with server-side computational capabilities and very large scratch storage space, and further extends their functions to a range of other scientific disciplines.Although big datasets like SDSS have revolutionized astronomy research, for further analysis, users are still restricted to downloading the selected data sets locally - but increasing data sizes make this local approach impractical. Instead, researchers need online tools that are co-located with data in a virtual research environment, enabling them to bring their analysis to the data.SciServer supports this using the popular Jupyter notebooks, which allow users to write their own Python and R scripts and execute them on the server with the data (extensions to Matlab and other languages are planned). We have written special-purpose libraries that enable querying the databases and other persistent datasets. Intermediate results can be stored in large scratch space (hundreds of TBs) and analyzed directly from within Python or R with state-of-the-art visualization and machine learning libraries. Users can store science-ready results in their permanent allocation on SciDrive, a Dropbox-like system for sharing and publishing files. Communication between the various components of the SciServer system is managed through SciServer‘s new Single Sign-on Portal.We have created a number of demos to illustrate the capabilities of SciServer Compute, including Python and R scripts

  17. SU-E-T-314: The Application of Cloud Computing in Pencil Beam Scanning Proton Therapy Monte Carlo Simulation

    SciTech Connect

    Wang, Z; Gao, M

    2014-06-01

    Purpose: Monte Carlo simulation plays an important role for proton Pencil Beam Scanning (PBS) technique. However, MC simulation demands high computing power and is limited to few large proton centers that can afford a computer cluster. We study the feasibility of utilizing cloud computing in the MC simulation of PBS beams. Methods: A GATE/GEANT4 based MC simulation software was installed on a commercial cloud computing virtual machine (Linux 64-bits, Amazon EC2). Single spot Integral Depth Dose (IDD) curves and in-air transverse profiles were used to tune the source parameters to simulate an IBA machine. With the use of StarCluster software developed at MIT, a Linux cluster with 2–100 nodes can be conveniently launched in the cloud. A proton PBS plan was then exported to the cloud where the MC simulation was run. Results: The simulated PBS plan has a field size of 10×10cm{sup 2}, 20cm range, 10cm modulation, and contains over 10,000 beam spots. EC2 instance type m1.medium was selected considering the CPU/memory requirement and 40 instances were used to form a Linux cluster. To minimize cost, master node was created with on-demand instance and worker nodes were created with spot-instance. The hourly cost for the 40-node cluster was $0.63 and the projected cost for a 100-node cluster was $1.41. Ten million events were simulated to plot PDD and profile, with each job containing 500k events. The simulation completed within 1 hour and an overall statistical uncertainty of < 2% was achieved. Good agreement between MC simulation and measurement was observed. Conclusion: Cloud computing is a cost-effective and easy to maintain platform to run proton PBS MC simulation. When proton MC packages such as GATE and TOPAS are combined with cloud computing, it will greatly facilitate the pursuing of PBS MC studies, especially for newly established proton centers or individual researchers.

  18. Automatic segmentation of coronary arteries from computed tomography angiography data cloud using optimal thresholding

    NASA Astrophysics Data System (ADS)

    Ansari, Muhammad Ahsan; Zai, Sammer; Moon, Young Shik

    2017-01-01

    Manual analysis of the bulk data generated by computed tomography angiography (CTA) is time consuming, and interpretation of such data requires previous knowledge and expertise of the radiologist. Therefore, an automatic method that can isolate the coronary arteries from a given CTA dataset is required. We present an automatic yet effective segmentation method to delineate the coronary arteries from a three-dimensional CTA data cloud. Instead of a region growing process, which is usually time consuming and prone to leakages, the method is based on the optimal thresholding, which is applied globally on the Hessian-based vesselness measure in a localized way (slice by slice) to track the coronaries carefully to their distal ends. Moreover, to make the process automatic, we detect the aorta using the Hough transform technique. The proposed segmentation method is independent of the starting point to initiate its process and is fast in the sense that coronary arteries are obtained without any preprocessing or postprocessing steps. We used 12 real clinical datasets to show the efficiency and accuracy of the presented method. Experimental results reveal that the proposed method achieves 95% average accuracy.

  19. Advancing global marine biogeography research with open-source GIS software and cloud-computing

    USGS Publications Warehouse

    Fujioka, Ei; Vanden Berghe, Edward; Donnelly, Ben; Castillo, Julio; Cleary, Jesse; Holmes, Chris; McKnight, Sean; Halpin, patrick

    2012-01-01

    Across many scientific domains, the ability to aggregate disparate datasets enables more meaningful global analyses. Within marine biology, the Census of Marine Life served as the catalyst for such a global data aggregation effort. Under the Census framework, the Ocean Biogeographic Information System was established to coordinate an unprecedented aggregation of global marine biogeography data. The OBIS data system now contains 31.3 million observations, freely accessible through a geospatial portal. The challenges of storing, querying, disseminating, and mapping a global data collection of this complexity and magnitude are significant. In the face of declining performance and expanding feature requests, a redevelopment of the OBIS data system was undertaken. Following an Open Source philosophy, the OBIS technology stack was rebuilt using PostgreSQL, PostGIS, GeoServer and OpenLayers. This approach has markedly improved the performance and online user experience while maintaining a standards-compliant and interoperable framework. Due to the distributed nature of the project and increasing needs for storage, scalability and deployment flexibility, the entire hardware and software stack was built on a Cloud Computing environment. The flexibility of the platform, combined with the power of the application stack, enabled rapid re-development of the OBIS infrastructure, and ensured complete standards-compliance.

  20. Conference Abstracts: AEDS '84.

    ERIC Educational Resources Information Center

    Baird, William E.

    1985-01-01

    The Association of Educational Data Systems (AEDS) conference included 102 presentations. Abstracts of seven of these presentations are provided. Topic areas considered include LOGO, teaching probability through a computer game, writing effective computer assisted instructional materials, computer literacy, research on instructional…

  1. Cloud Based Applications and Platforms (Presentation)

    SciTech Connect

    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.

  2. The computation of cloud base height from paired whole-sky imaging cameras

    SciTech Connect

    Allmen, M.C.; Kegelmeyer, W.P. Jr.

    1994-03-01

    A major goal for global change studies is to improve the accuracy of general circulation models (GCMs) capable of predicting the timing and magnitude of greenhouse gas-induced global warming. Research has shown that cloud radiative feedback is the single most important effect determining the magnitude of possible climate responses to human activity. Of particular value to reducing the uncertainties associated with cloud-radiation interactions is the measurement of cloud base height (CBH), both because it is a dominant factor in determining the infrared radiative properties of clouds with respect to the earth`s surface and lower atmosphere and because CBHs are essential to measuring cloud cover fraction. We have developed a novel approach to the extraction of cloud base height from pairs of whole sky imaging (WSI) cameras. The core problem is to spatially register cloud fields from widely separated WSI cameras; this complete, triangulation provides the CBH measurements. The wide camera separation (necessary to cover the desired observation area) and the self-similarity of clouds defeats all standard matching algorithms when applied to static views of the sky. To address this, our approach is based on optical flow methods that exploit the fact that modern WSIs provide sequences of images. We will describe the algorithm and present its performance as evaluated both on real data validated by ceilometer measurements and on a variety of simulated cases.

  3. Cloud Cover

    ERIC Educational Resources Information Center

    Schaffhauser, Dian

    2012-01-01

    This article features a major statewide initiative in North Carolina that is showing how a consortium model can minimize risks for districts and help them exploit the advantages of cloud computing. Edgecombe County Public Schools in Tarboro, North Carolina, intends to exploit a major cloud initiative being refined in the state and involving every…

  4. Fast methods of computing bulk radiative properties of inhomogeneous clouds illuminated by solar radiation

    SciTech Connect

    Gabriel, P.

    1995-09-01

    The use of cloud fraction as a means of incorporating horizontal cloud inhomogeneity in radiative transfer calculations is widespread in the atmospheric science community. This research attempts to bypass the use of cloud fraction in radiative transfer modeling for two-dimensional media. Gabriel describes two approximation techniques useful in calculating the domain averaged bulk radiative properties such as albedo, flux divergence and mean radiance that dispense with the need to use cloud fraction as a specifier of cloud inhomogeneity. The results suggest that the variability of the medium can largely be accounted for through the pseudo-source term, offering hope of parameterizing the equation of transfer in terms of the statistical properties of the medium. 1 fig.

  5. A Cloud Computing Approach to Personal Risk Management: The Open Hazards Group

    NASA Astrophysics Data System (ADS)

    Graves, W. R.; Holliday, J. R.; Rundle, J. B.

    2010-12-01

    According to the California Earthquake Authority, only about 12% of current California residences are covered by any form of earthquake insurance, down from about 30% in 1996 following the 1994, M6.7 Northridge earthquake. Part of the reason for this decreasing rate of insurance uptake is the high deductible, either 10% or 15% of the value of the structure, and the relatively high cost of the premiums, as much as thousands of dollars per year. The earthquake insurance industry is composed of the CEA, a public-private partnership; modeling companies that produce damage and loss models similar to the FEMA HAZUS model; and financial companies such as the insurance, reinsurance, and investment banking companies in New York, London, the Cayman Islands, Zurich, Dubai, Singapore, and elsewhere. In setting earthquake insurance rates, financial companies rely on models like HAZUS, that calculate on risk and exposure. In California, the process begins with an official earthquake forecast by the Working Group on California Earthquake Probabilities. Modeling companies use these 30 year earthquake probabilities as inputs to their attenuation and damage models to estimate the possible damage factors from scenario earthquakes. Economic loss is then estimated from processes such as structural failure, lost economic activity, demand surge, and fire following the earthquake. Once the potential losses are known, rates can be set so that a target ruin probability of less than 1% or so can be assured. Open Hazards Group was founded with the idea that the global public might be interested in a personal estimate of earthquake risk, computed using data supplied by the public, with models running in a cloud computing environment. These models process data from the ANSS catalog, updated at least daily, to produce rupture forecasts that are backtested with standard Reliability/Attributes and Receiver Operating Characteristic tests, among others. Models for attenuation and structural damage

  6. Towards a Low-Cost Real-Time Photogrammetric Landslide Monitoring System Utilising Mobile and Cloud Computing Technology

    NASA Astrophysics Data System (ADS)

    Chidburee, P.; Mills, J. P.; Miller, P. E.; Fieber, K. D.

    2016-06-01

    Close-range photogrammetric techniques offer a potentially low-cost approach in terms of implementation and operation for initial assessment and monitoring of landslide processes over small areas. In particular, the Structure-from-Motion (SfM) pipeline is now extensively used to help overcome many constraints of traditional digital photogrammetry, offering increased user-friendliness to nonexperts, as well as lower costs. However, a landslide monitoring approach based on the SfM technique also presents some potential drawbacks due to the difficulty in managing and processing a large volume of data in real-time. This research addresses the aforementioned issues by attempting to combine a mobile device with cloud computing technology to develop a photogrammetric measurement solution as part of a monitoring system for landslide hazard analysis. The research presented here focusses on (i) the development of an Android mobile application; (ii) the implementation of SfM-based open-source software in the Amazon cloud computing web service, and (iii) performance assessment through a simulated environment using data collected at a recognized landslide test site in North Yorkshire, UK. Whilst the landslide monitoring mobile application is under development, this paper describes experiments carried out to ensure effective performance of the system in the future. Investigations presented here describe the initial assessment of a cloud-implemented approach, which is developed around the well-known VisualSFM algorithm. Results are compared to point clouds obtained from alternative SfM 3D reconstruction approaches considering a commercial software solution (Agisoft PhotoScan) and a web-based system (Autodesk 123D Catch). Investigations demonstrate that the cloud-based photogrammetric measurement system is capable of providing results of centimeter-level accuracy, evidencing its potential to provide an effective approach for quantifying and analyzing landslide hazard at a local-scale.

  7. Thunderstorm-associated cloud motions as computed from 5-minute SMS pictures. [Synchronous Meteorological Satellite

    NASA Technical Reports Server (NTRS)

    Tecson, J. J.; Umenhofer, T. A.; Fujita, T. T.

    1977-01-01

    The five-minute rapid-scan imagery from the Synchronous Meteorological Satellite is employed to study cloud motions associated with the Omaha tornado of May 6, 1975. Cloud-motion vectors derived from automated and man-machine interactive systems provide an account of the mesoscale phenomena. In addition to the geostationary satellite data, aerial photography obtained during a cloud-truth mission is used in the severe storm investigation. For tracking overland cumuli with short half-lives, a three-minute scan interval appears necessary for the satellite imagery.

  8. Cloud glaciation temperature estimation from passive remote sensing data with evolutionary computing

    NASA Astrophysics Data System (ADS)

    Carro-Calvo, L.; Hoose, C.; Stengel, M.; Salcedo-Sanz, S.

    2016-11-01

    The phase partitioning between supercooled liquid water and ice in clouds in the temperature range between 0 and -37°C influences their optical properties and the efficiency of precipitation formation. Passive remote sensing observations provide long-term records of the cloud top phase at a high spatial resolution. Based on the assumption of a cumulative Gaussian distribution of the ice cloud fraction as a function of temperature, we quantify the cloud glaciation temperature (CGT) as the 50th percentile of the fitted distribution function and its variance for different cloud top pressure intervals, obtained by applying an evolutionary algorithm (EA). EAs are metaheuristics approaches for optimization, used in difficult problems where standard approaches are either not applicable or show poor performance. In this case, the proposed EA is applied to 4 years of Pathfinder Atmospheres-Extended (PATMOS-x) data, aggregated into boxes of 1° × 1° and vertical layers of 5.5 hPa. The resulting vertical profile of CGT shows a characteristic sickle shape, indicating low CGTs close to homogeneous freezing in the upper troposphere and significantly higher values in the midtroposphere. In winter, a pronounced land-sea contrast is found at midlatitudes, with lower CGTs over land. Among this and previous studies, there is disagreement on the sign of the land-sea difference in CGT, suggesting that it is strongly sensitive to the detected and analyzed cloud types, the time of the day, and the phase retrieval method.

  9. 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.

  10. Leveraging Cloud Technology to Provide a Responsive, Reliable and Scalable Backend for the Virtual Ice Sheet Laboratory Using the Ice Sheet System Model and Amazon's Elastic Compute Cloud

    NASA Astrophysics Data System (ADS)

    Perez, G. L.; Larour, E. Y.; Halkides, D. J.; Cheng, D. L. C.

    2015-12-01

    The Virtual Ice Sheet Laboratory(VISL) is a Cryosphere outreach effort byscientists at the Jet Propulsion Laboratory(JPL) in Pasadena, CA, Earth and SpaceResearch(ESR) in Seattle, WA, and the University of California at Irvine (UCI), with the goal of providing interactive lessons for K-12 and college level students,while conforming to STEM guidelines. At the core of VISL is the Ice Sheet System Model(ISSM), an open-source project developed jointlyat JPL and UCI whose main purpose is to model the evolution of the polar ice caps in Greenland and Antarctica. By using ISSM, VISL students have access tostate-of-the-art modeling software that is being used to conduct scientificresearch by users all over the world. However, providing this functionality isby no means simple. The modeling of ice sheets in response to sea and atmospheric temperatures, among many other possible parameters, requiressignificant computational resources. Furthermore, this service needs to beresponsive and capable of handling burst requests produced by classrooms ofstudents. Cloud computing providers represent a burgeoning industry. With majorinvestments by tech giants like Amazon, Google and Microsoft, it has never beeneasier or more affordable to deploy computational elements on-demand. This isexactly what VISL needs and ISSM is capable of. Moreover, this is a promisingalternative to investing in expensive and rapidly devaluing hardware.

  11. A method of extracting ontology module using concept relations for sharing knowledge in mobile cloud computing environment.

    PubMed

    Lee, Keonsoo; Rho, Seungmin; Lee, Seok-Won

    2014-01-01

    In mobile cloud computing environment, the cooperation of distributed computing objects is one of the most important requirements for providing successful cloud services. To satisfy this requirement, all the members, who are employed in the cooperation group, need to share the knowledge for mutual understanding. Even if ontology can be the right tool for this goal, there are several issues to make a right ontology. As the cost and complexity of managing knowledge increase according to the scale of the knowledge, reducing the size of ontology is one of the critical issues. In this paper, we propose a method of extracting ontology module to increase the utility of knowledge. For the given signature, this method extracts the ontology module, which is semantically self-contained to fulfill the needs of the service, by considering the syntactic structure and semantic relation of concepts. By employing this module, instead of the original ontology, the cooperation of computing objects can be performed with less computing load and complexity. In particular, when multiple external ontologies need to be combined for more complex services, this method can be used to optimize the size of shared knowledge.

  12. 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

  13. 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.

  14. A Cloud Computing Workflow for Scalable Integration of Remote Sensing and Social Media Data in Urban Studies

    NASA Astrophysics Data System (ADS)

    Soliman, A.; Soltani, K.; Yin, J.; Subramaniam, B.; Liu, Y.; Padmanabhan, A.; Riteau, P.; Keahey, K.; Wang, S. W.

    2015-12-01

    Urban ecosystems are unique earth environments because both their physical and social components contribute to the overall dynamics of the system. Up-to-date, remote sensing data (e.g. optical and LiDAR) allowed researchers to monitor the development of impervious surfaces however, it was not adequate to detect associated social dynamics. Geo-located social media (e.g. Twitter) provides a data source to detect population dynamics and understand the interaction of people with their physical environment. Although, integrating social media with remote sensing data has been hindered by large volumes of data and the lack of models for integrating remote sensing products with unstructured social media data. In this research work, we leveraged the NSF chameleon cloud computing platform to provide virtual clusters and elastic auto-scaling of resources that are needed for the synthesis of landuse and geo-located Twitter data. In this context, data synthesis was used to address research questions related to population dynamics in major metropolitan areas. We provide an overview of a cloud computing workflow comprised of a set of coupled scalable synthesis modules for: a) preprocessing data, which includes storage and query of heterogeneous data streams, b) spatial data integration, which matches geo-located Twitter data with user defined landuse maps based on a conceptual model of human mobility and c) visualization of urban mobility patterns. Our results demonstrate the flexibility to connect data, synthesis methods and computing resources using cloud computing, which would be otherwise very difficult for untrained scientists to setup and control. Furthermore, we demonstrate the capabilities of CyberGIS-based workflow using the case study of comparing commuting distances across major US cities from 2013 through the present. We demonstrate how our workflow will support discoveries in urban ecological studies as well as linking human and physical dimensions in environmental

  15. Yabi: An online research environment for grid, high performance and cloud computing

    PubMed Central

    2012-01-01

    Background There is a significant demand for creating pipelines or workflows in the life science discipline that chain a number of discrete compute and data intensive analysis tasks into sophisticated analysis procedures. This need has led to the development of general as well as domain-specific workflow environments that are either complex desktop applications or Internet-based applications. Complexities can arise when configuring these applications in heterogeneous compute and storage environments if the execution and data access models are not designed appropriately. These complexities manifest themselves through limited access to available HPC resources, significant overhead required to configure tools and inability for users to simply manage files across heterogenous HPC storage infrastructure. Results In this paper, we describe the architecture of a software system that is adaptable to a range of both pluggable execution and data backends in an open source implementation called Yabi. Enabling seamless and transparent access to heterogenous HPC environments at its core, Yabi then provides an analysis workflow environment that can create and reuse workflows as well as manage large amounts of both raw and processed data in a secure and flexible way across geographically distributed compute resources. Yabi can be used via a web-based environment to drag-and-drop tools to create sophisticated workflows. Yabi can also be accessed through the Yabi command line which is designed for users that are more comfortable with writing scripts or for enabling external workflow environments to leverage the features in Yabi. Configuring tools can be a significant overhead in workflow environments. Yabi greatly simplifies this task by enabling system administrators to configure as well as manage running tools via a web-based environment and without the need to write or edit software programs or scripts. In this paper, we highlight Yabi's capabilities through a range of

  16. Computation of the Effects of Inhomogeneous Clouds on Retrieval of Remotely Sensed Properties

    NASA Technical Reports Server (NTRS)

    Chambers, Lin H.

    1998-01-01

    Current and future earth observation programs depend on satellite measurements of radiance to retrieve the properties of clouds on a global basis. At present, this retrieval is made assuming that the clouds in the instrument field of view are plane parallel and independent of adjacent pixels. While this assumption is known to be false except in very limited cases, its impact can be evaluated, and if possible corrected, based on emerging theoretical techniques. In this study, the Spherical Harmonic Discrete Ordinate Method (SHDOM, Evans, 1996) has been used to assess the sensitivity of the retrieval to a variety of cloud parameters. SHDOM allows the plane parallel assumption to be relaxed and makes 2D and even 3D radiative solutions practical. A previous study (Chambers et al., 1996) assessed the effect of horizontal inhomogeneity in 45 LANDSAT scenes of boundary layer clouds over ocean. The four scenes studied here represent overcast, broken, scattered and strongly thermally forced cloud fields and are used to perform sensitivity studies to a wider variety of parameters. Comparisons are made at three solar zenith angles (theta (sub 0) = 0, 49, and 63 degrees) to avoid ambiguity in the results due to solar zenith angle.

  17. Research Abstracts.

    ERIC Educational Resources Information Center

    Plotnick, Eric

    2001-01-01

    Presents research abstracts from the ERIC Clearinghouse on Information and Technology. Topics include: classroom communication apprehension and distance education; outcomes of a distance-delivered science course; the NASA/Kennedy Space Center Virtual Science Mentor program; survey of traditional and distance learning higher education members;…

  18. Abstract Constructions.

    ERIC Educational Resources Information Center

    Pietropola, Anne

    1998-01-01

    Describes a lesson designed to culminate a year of eighth-grade art classes in which students explore elements of design and space by creating 3-D abstract constructions. Outlines the process of using foam board and markers to create various shapes and optical effects. (DSK)

  19. Automatic Cloud Bursting under FermiCloud

    SciTech Connect

    Wu, Hao; Shangping, Ren; Garzoglio, Gabriele; Timm, Steven; Bernabeu, Gerard; Kim, Hyun Woo; Chadwick, Keith; Jang, Haengjin; Noh, Seo-Young

    2013-01-01

    Cloud computing is changing the infrastructure upon which scientific computing depends from supercomputers and distributed computing clusters to a more elastic cloud-based structure. The service-oriented focus and elasticity of clouds can not only facilitate technology needs of emerging business but also shorten response time and reduce operational costs of traditional scientific applications. Fermi National Accelerator Laboratory (Fermilab) is currently in the process of building its own private cloud, FermiCloud, which allows the existing grid infrastructure to use dynamically provisioned resources on FermiCloud to accommodate increased but dynamic computation demand from scientists in the domains of High Energy Physics (HEP) and other research areas. Cloud infrastructure also allows to increase a private cloud’s resource capacity through “bursting” by borrowing or renting resources from other community or commercial clouds when needed. This paper introduces a joint project on building a cloud federation to support HEP applications between Fermi National Accelerator Laboratory and Korea Institution of Science and Technology Information, with technical contributions from the Illinois Institute of Technology. In particular, this paper presents two recent accomplishments of the joint project: (a) cloud bursting automation and (b) load balancer. Automatic cloud bursting allows computer resources to be dynamically reconfigured to meet users’ demands. The load balance algorithm which the cloud bursting depends on decides when and where new resources need to be allocated. Our preliminary prototyping and experiments have shown promising success, yet, they also have opened new challenges to be studied

  20. Applications for Three-Dimensional Computer Graphic Cloud Representations Produced from Satellite Imagery

    DTIC Science & Technology

    1985-01-01

    Pueblo, Colorado (PLB) to Ourango, Colorado (DRO). * Figtvre 7-8 shows that this route-crosses two mountain ranges, the Sangre de Cristo Mountains to...D cloud-topography model. Inside the boxed-off 3rea, tv.o bands of orographically induned clouds can be seen which have formed cver tht Sangre de...shown in Figure 7-10. This view is valid for poPrt A (labeled in Figure 7-10). In Figure 7-11, a portion of the Sangre de Cristo Mountains is seen in

  1. Google Earth Engine: a new cloud-computing platform for global-scale earth observation data and analysis

    NASA Astrophysics Data System (ADS)

    Moore, R. T.; Hansen, M. C.

    2011-12-01

    Google Earth Engine is a new technology platform that enables monitoring and measurement of changes in the earth's environment, at planetary scale, on a large catalog of earth observation data. The platform offers intrinsically-parallel computational access to thousands of computers in Google's data centers. Initial efforts have focused primarily on global forest monitoring and measurement, in support of REDD+ activities in the developing world. The intent is to put this platform into the hands of scientists and developing world nations, in order to advance the broader operational deployment of existing scientific methods, and strengthen the ability for public institutions and civil society to better understand, manage and report on the state of their natural resources. Earth Engine currently hosts online nearly the complete historical Landsat archive of L5 and L7 data collected over more than twenty-five years. Newly-collected Landsat imagery is downloaded from USGS EROS Center into Earth Engine on a daily basis. Earth Engine also includes a set of historical and current MODIS data products. The platform supports generation, on-demand, of spatial and temporal mosaics, "best-pixel" composites (for example to remove clouds and gaps in satellite imagery), as well as a variety of spectral indices. Supervised learning methods are available over the Landsat data catalog. The platform also includes a new application programming framework, or "API", that allows scientists access to these computational and data resources, to scale their current algorithms or develop new ones. Under the covers of the Google Earth Engine API is an intrinsically-parallel image-processing system. Several forest monitoring applications powered by this API are currently in development and expected to be operational in 2011. Combining science with massive data and technology resources in a cloud-computing framework can offer advantages of computational speed, ease-of-use and collaboration, as

  2. Automated cropland mapping of continental Africa using Google Earth Engine cloud computing

    NASA Astrophysics Data System (ADS)

    Xiong, Jun; Thenkabail, Prasad S.; Gumma, Murali K.; Teluguntla, Pardhasaradhi; Poehnelt, Justin; Congalton, Russell G.; Yadav, Kamini; Thau, David

    2017-04-01

    's population, but only about 6% of world's irrigation. Net cropland area distribution was 95 Mha during season 1, 117 Mha during season 2, and 84 Mha continuous. About 58% of the rainfed and 39% of the irrigated were single crops (net cropland area without cropland fallows) cropped during either season 1 (January-May) or season 2 (June-September). The ACMA algorithm was deployed on Google Earth Engine (GEE) cloud computing platform and applied on MODIS time-series data from 2003 through 2014 to obtain ACMA-derived cropland layers for these years (ACL2003 to ACL2014). The results indicated that over these twelve years, on average: (a) croplands increased by 1 Mha/yr, and (b) cropland fallows decreased by 1 Mha/year. Cropland areas computed from ACL2014 for the 55 African countries were largely underestimated when compared with an independent source of census-based cropland data, with a root-mean-square error (RMSE) of 3.5 Mha. ACMA demonstrated the ability to hind-cast (past years), now-cast (present year), and forecast (future years) cropland products using MODIS 250-m time-series data rapidly, but currently, insufficient reference data exist to rigorously report trends from these results.

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

    DTIC Science & Technology

    2012-01-31

    4 Sources of Information for this Report .................................................................................... 5 ...50 A. 5 Metrics for Cloud-Based Systems...Number: H98230-08-D-0171 DO 001 TO 002 RT 039 Report No. SERC-2012-TR-023 January 31, 2012 UNCLASSIFIED 5 of 58

  4. Implementing a New Cloud Computing Library Management Service: A Symbiotic Approach

    ERIC Educational Resources Information Center

    Dula, Michael; Jacobsen, Lynne; Ferguson, Tyler; Ross, Rob

    2012-01-01

    This article presents the story of how Pepperdine University migrated its library management functions to the cloud using what is now known as OCLC's WorldShare Management Services (WMS). The story of implementing this new service is told from two vantage points: (1) that of the library; and (2) that of the service provider. The authors were the…

  5. A Cloud-Based Mobile Computing Applications Platform for First Responders

    DTIC Science & Technology

    2013-01-15

    mobile apps eco-system; core services; mobile command and control; situational awareness; smartphones; cloud based delivery 16. SECURITY ... Security perspective including a large international border with three major freight crossing points, a large coastline, and the presence of three...the Homeland Security Council (HSC) in partnership with the Department of Homeland Security . These high consequence scenarios represent threats or

  6. Cloud Modeling

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Moncrieff, Mitchell; Einaud, Franco (Technical Monitor)

    2001-01-01

    Numerical cloud models have been developed and applied extensively to study cloud-scale and mesoscale processes during the past four decades. The distinctive aspect of these cloud models is their ability to treat explicitly (or resolve) cloud-scale dynamics. This requires the cloud models to be formulated from the non-hydrostatic equations of motion that explicitly include the vertical acceleration terms since the vertical and horizontal scales of convection are similar. Such models are also necessary in order to allow gravity waves, such as those triggered by clouds, to be resolved explicitly. In contrast, the hydrostatic approximation, usually applied in global or regional models, does allow the presence of gravity waves. In addition, the availability of exponentially increasing computer capabilities has resulted in time integrations increasing from hours to days, domain grids boxes (points) increasing from less than 2000 to more than 2,500,000 grid points with 500 to 1000 m resolution, and 3-D models becoming increasingly prevalent. The cloud resolving model is now at a stage where it can provide reasonably accurate statistical information of the sub-grid, cloud-resolving processes poorly parameterized in climate models and numerical prediction models.

  7. Computer-science guest-lecture series at Langston University sponsored by the U.S. Geological Survey; abstracts, 1992-93

    USGS Publications Warehouse

    Steele, K. S.

    1994-01-01

    Langston University, a Historically Black University located at Langston, Oklahoma, has a computing and information science program within the Langston University Division of Business. Since 1984, Langston University has participated in the Historically Black College and University program of the U.S. Department of Interior, which provided education, training, and funding through a combined earth-science and computer-technology cooperative program with the U.S. Geological Survey (USGS). USGS personnel have presented guest lectures at Langston University since 1984. Students have been enthusiastic about the lectures, and as a result of this program, 13 Langston University students have been hired by the USGS on a part-time basis while they continued their education at the University. The USGS expanded the offering of guest lectures in 1992 by increasing the number of visits to Langston University, and by inviting participation of speakers from throughout the country. The objectives of the guest-lecture series are to assist Langston University in offering state-of-the-art education in the computer sciences, to provide students with an opportunity to learn from and interact with skilled computer-science professionals, and to develop a pool of potential future employees for part-time and full-time employment. This report includes abstracts for guest-lecture presentations during 1992-93 school year.

  8. Development of a High Resolution Weather Forecast Model for Mesoamerica Using the NASA Nebula Cloud Computing Environment

    NASA Technical Reports Server (NTRS)

    Molthan, Andrew L.; Case, Jonathan L.; Venner, Jason; Moreno-Madrinan, Max. J.; Delgado, Francisco

    2012-01-01

    Over the past two years, scientists in the Earth Science Office at NASA fs Marshall Space Flight Center (MSFC) have explored opportunities to apply cloud computing concepts to support near real ]time weather forecast modeling via the Weather Research and Forecasting (WRF) model. Collaborators at NASA fs Short ]term Prediction Research and Transition (SPoRT) Center and the SERVIR project at Marshall Space Flight Center have established a framework that provides high resolution, daily weather forecasts over Mesoamerica through use of the NASA Nebula Cloud Computing Platform at Ames Research Center. Supported by experts at Ames, staff at SPoRT and SERVIR have established daily forecasts complete with web graphics and a user interface that allows SERVIR partners access to high resolution depictions of weather in the next 48 hours, useful for monitoring and mitigating meteorological hazards such as thunderstorms, heavy precipitation, and tropical weather that can lead to other disasters such as flooding and landslides. This presentation will describe the framework for establishing and providing WRF forecasts, example applications of output provided via the SERVIR web portal, and early results of forecast model verification against available surface ] and satellite ]based observations.

  9. The application of data mining and cloud computing techniques in data-driven models for structural health monitoring

    NASA Astrophysics Data System (ADS)

    Khazaeli, S.; Ravandi, A. G.; Banerji, S.; Bagchi, A.

    2016-04-01

    Recently, data-driven models for Structural Health Monitoring (SHM) have been of great interest among many researchers. In data-driven models, the sensed data are processed to determine the structural performance and evaluate the damages of an instrumented structure without necessitating the mathematical modeling of the structure. A framework of data-driven models for online assessment of the condition of a structure has been developed here. The developed framework is intended for automated evaluation of the monitoring data and structural performance by the Internet technology and resources. The main challenges in developing such framework include: (a) utilizing the sensor measurements to estimate and localize the induced damage in a structure by means of signal processing and data mining techniques, and (b) optimizing the computing and storage resources with the aid of cloud services. The main focus in this paper is to demonstrate the efficiency of the proposed framework for real-time damage detection of a multi-story shear-building structure in two damage scenarios (change in mass and stiffness) in various locations. Several features are extracted from the sensed data by signal processing techniques and statistical methods. Machine learning algorithms are deployed to select damage-sensitive features as well as classifying the data to trace the anomaly in the response of the structure. Here, the cloud computing resources from Amazon Web Services (AWS) have been used to implement the proposed framework.

  10. Reaching for the cloud: on the lessons learned from grid computing technology transfer process to the biomedical community.

    PubMed

    Mohammed, Yassene; Dickmann, Frank; Sax, Ulrich; von Voigt, Gabriele; Smith, Matthew; Rienhoff, Otto

    2010-01-01

    Natural scientists such as physicists pioneered the sharing of computing resources, which led to the creation of the Grid. The inter domain transfer process of this technology has hitherto been an intuitive process without in depth analysis. Some difficulties facing the life science community in this transfer can be understood using the Bozeman's "Effectiveness Model of Technology Transfer". Bozeman's and classical technology transfer approaches deal with technologies which have achieved certain stability. Grid and Cloud solutions are technologies, which are still in flux. We show how Grid computing creates new difficulties in the transfer process that are not considered in Bozeman's model. We show why the success of healthgrids should be measured by the qualified scientific human capital and the opportunities created, and not primarily by the market impact. We conclude with recommendations that can help improve the adoption of Grid and Cloud solutions into the biomedical community. These results give a more concise explanation of the difficulties many life science IT projects are facing in the late funding periods, and show leveraging steps that can help overcoming the "vale of tears".

  11. Department of Defense Use of Commercial Cloud Computing Capabilities and Services

    DTIC Science & Technology

    2015-11-01

    provider. (NIST, 2011) Consumers acquire capabilities such as server time and network space through a web -based control panel or Application Programming...any location via a simple web -based access point. (The Open Group, 2013) A popular example of this characteristic is a consumer’s ability to access... web -based email, such as Gmail and Yahoo, from any device. Administrators can also access and provision cloud resources from outside a specialized

  12. Towards Monitoring-as-a-service for Scientific Computing Cloud applications using the ElasticSearch ecosystem

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    The INFN computing centre in Torino hosts a private Cloud, which is managed with the OpenNebula cloud controller. The infrastructure offers Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) services to different scientific computing applications. The main stakeholders of the facility are a grid Tier-2 site for the ALICE collaboration at LHC, an interactive analysis facility for the same experiment and a grid Tier-2 site for the BESIII collaboration, plus an increasing number of other small tenants. The dynamic allocation of resources to tenants is partially automated. This feature requires detailed monitoring and accounting of the resource usage. We set up a monitoring framework to inspect the site activities both in terms of IaaS and applications running on the hosted virtual instances. For this purpose we used the ElasticSearch, Logstash and Kibana (ELK) stack. The infrastructure relies on a MySQL database back-end for data preservation and to ensure flexibility to choose a different monitoring solution if needed. The heterogeneous accounting information is transferred from the database to the ElasticSearch engine via a custom Logstash plugin. Each use-case is indexed separately in ElasticSearch and we setup a set of Kibana dashboards with pre-defined queries in order to monitor the relevant information in each case. For the IaaS metering, we developed sensors for the OpenNebula API. The IaaS level information gathered through the API is sent to the MySQL database through an ad-hoc developed RESTful web service. Moreover, we have developed a billing system for our private Cloud, which relies on the RabbitMQ message queue for asynchronous communication to the database and on the ELK stack for its graphical interface. The Italian Grid accounting framework is also migrating to a similar set-up. Concerning the application level, we used the Root plugin TProofMonSenderSQL to collect accounting data from the interactive analysis facility. The BESIII

  13. Annual Conference Abstracts

    ERIC Educational Resources Information Center

    Journal of Engineering Education, 1972

    1972-01-01

    Includes abstracts of papers presented at the 80th Annual Conference of the American Society for Engineering Education. The broad areas include aerospace, affiliate and associate member council, agricultural engineering, biomedical engineering, continuing engineering studies, chemical engineering, civil engineering, computers, cooperative…

  14. Annual Conference Abstracts

    ERIC Educational Resources Information Center

    Engineering Education, 1976

    1976-01-01

    Presents the abstracts of 158 papers presented at the American Society for Engineering Education's annual conference at Knoxville, Tennessee, June 14-17, 1976. Included are engineering topics covering education, aerospace, agriculture, biomedicine, chemistry, computers, electricity, acoustics, environment, mechanics, and women. (SL)

  15. Abstraction through Game Play

    ERIC Educational Resources Information Center

    Avraamidou, Antri; Monaghan, John; Walker, Aisha

    2012-01-01

    This paper examines the computer game play of an 11-year-old boy. In the course of building a virtual house he developed and used, without assistance, an artefact and an accompanying strategy to ensure that his house was symmetric. We argue that the creation and use of this artefact-strategy is a mathematical abstraction. The discussion…

  16. Stacking Cans: Abstracting from Computation

    ERIC Educational Resources Information Center

    Roy, George J.; Safi, Farshid; Graul, LuAnn

    2015-01-01

    As current mathematics standards, such as the Common Core, are being implemented throughout the United States, it has become evident that teachers need support to enact the tenets of those standards. To help in this endeavor, this article was published as a guideline to emphasize to mathematics education stakeholders that "effective teaching…

  17. Abstract Machines for Polymorphous Computing

    DTIC Science & Technology

    2007-12-01

    In this paper , the scope of the word “configuration” is expanded to include also the mapping of the application onto the reconfigurable...optimization. The focus of this paper is thus on the on-line refinement component and its interaction with the configuration store. For a given instance...Mattson, J. Namkoong, J. D. Owens, B. Towles , and A. Chang., “Imagine: Media Processing with Streams,” IEEE Micro, March/April 2001, pp. 35-46. [27

  18. (abstract) Supernova Remnant and Molecular Clouds

    NASA Technical Reports Server (NTRS)

    Wang, Zhong

    1993-01-01

    Upon impact of the shockwaves generated by a supernova remnant, molecular gas and the associated dust grains are substantially excited and become prominent sources of infrared emission. Recent studies of such interactions, utilizing the infrared data and information from other wavelengths, have revealed many details of the physical processes in the interstellar medium. In particluar, the understanding of the temperature and ionization structures in the postshock material is helpful in modeling the star-gas cycles in the Galaxy, and probing the circumstances of star formation.

  19. An Automatic Prediction of Epileptic Seizures Using Cloud Computing and Wireless Sensor Networks.

    PubMed

    Sareen, Sanjay; Sood, Sandeep K; Gupta, Sunil Kumar

    2016-11-01

    Epilepsy is one of the most common neurological disorders which is characterized by the spontaneous and unforeseeable occurrence of seizures. An automatic prediction of seizure can protect the patients from accidents and save their life. In this article, we proposed a mobile-based framework that automatically predict seizures using the information contained in electroencephalography (EEG) signals. The wireless sensor technology is used to capture the EEG signals of patients. The cloud-based services are used to collect and analyze the EEG data from the patient's mobile phone. The features from the EEG signal are extracted using the fast Walsh-Hadamard transform (FWHT). The Higher Order Spectral Analysis (HOSA) is applied to FWHT coefficients in order to select the features set relevant to normal, preictal and ictal states of seizure. We subsequently exploit the selected features as input to a k-means classifier to detect epileptic seizure states in a reasonable time. The performance of the proposed model is tested on Amazon EC2 cloud and compared in terms of execution time and accuracy. The findings show that with selected HOS based features, we were able to achieve a classification accuracy of 94.6 %.

  20. Technical Challenges and Lessons from the Migration of the GLOBE Data and Information System to Utilize Cloud Computing Service

    NASA Technical Reports Server (NTRS)

    Moses, John F.; Memarsadeghi, Nargess; Overoye, David; Littlefield, Brain

    2017-01-01

    The Global Learning and Observation to Benefit the Environment (GLOBE) Data and Information System supports an international science and education program with capabilities to accept local environment observations, archive, display and visualize them along with global satellite observations. Since its inception twenty years ago, the Web and database system has been upgraded periodically to accommodate the changes in technology and the steady growth of GLOBEs education community and collection of observations. Recently, near the end-of-life of the system hardware, new commercial computer platform options were explored and a decision made to utilize Cloud services. Now the GLOBE DIS has been fully deployed and maintained using Amazon Cloud services for over two years now. This paper reviews the early risks, actual challenges, and some unexpected findings as a result of the GLOBE DIS migration. We describe the plans, cost drivers and estimates, highlight adjustments that were made and suggest improvements. We present the trade studies for provisioning, for load balancing, networks, processing, storage, as well as production, staging and backup systems. We outline the migration teams skills and required level of effort for transition, and resulting changes in the overall maintenance and operations activities. Examples include incremental adjustments to processing capacity and frequency of backups, and efforts previously expended on hardware maintenance that were refocused onto application-specific enhancements.