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  • Online Resource  (3)
  • Katz, Daniel S.  (3)
  • Rana, Omer  (3)
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  • Online Resource  (3)
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  • 1
    Online Resource
    Online Resource
    Wiley ; 2017
    In:  Concurrency and Computation: Practice and Experience Vol. 29, No. 4 ( 2017-02-25)
    In: Concurrency and Computation: Practice and Experience, Wiley, Vol. 29, No. 4 ( 2017-02-25)
    Abstract: We are in the midst of a scientific data explosion in which the rate of data growth is rapidly increasing. While large‐scale research projects have developed sophisticated data distribution networks to share their data with researchers globally, there is no such support for the many millions of research projects generating data of interest to much smaller audiences (as exemplified by the long tail scientist). In data‐oriented research, every aspect of the research process is influenced by data access. However, sharing and accessing data efficiently as well as lowering access barriers are difficult. In the absence of dedicated large‐scale storage, many have noted that there is an enormous storage capacity available via connected peers, none more so than the storage resources of many research groups. With widespread usage of the content delivery network model for disseminating web content, we believe a similar model can be applied to distributing, sharing, and accessing long tail research data in an e‐Science context. We describe the vision and architecture of a social content delivery network – a model that leverages the social networks of researchers to automatically share and replicate data on peers' resources based upon shared interests and trust. Using this model, we describe a simulator and investigate how aspects such as user activity, geographic distribution, trust, and replica selection algorithms affect data access and storage performance. From these results, we show that socially informed replication strategies are comparable with more general strategies in terms of availability and outperform them in terms of spatial efficiency. Copyright © 2016 John Wiley & Sons, Ltd.
    Type of Medium: Online Resource
    ISSN: 1532-0626 , 1532-0634
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2017
    detail.hit.zdb_id: 2052606-4
    SSG: 11
    Location Call Number Limitation Availability
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  • 2
    Online Resource
    Online Resource
    Wiley ; 2017
    In:  Concurrency and Computation: Practice and Experience Vol. 29, No. 8 ( 2017-04-25)
    In: Concurrency and Computation: Practice and Experience, Wiley, Vol. 29, No. 8 ( 2017-04-25)
    Abstract: A common feature across many science and engineering applications is the amount and diversity of data and computation that must be integrated to yield insights. Datasets are growing larger and becoming distributed; their location, availability, and properties are often time‐dependent. Collectively, these characteristics give rise to dynamic distributed data‐intensive applications. While “static” data applications have received significant attention, the characteristics, requirements, and software systems for the analysis of large volumes of dynamic, distributed data, and data‐intensive applications have received relatively less attention. This paper surveys several representative dynamic distributed data‐intensive application scenarios, provides a common conceptual framework to understand them, and examines the infrastructure used in support of applications.
    Type of Medium: Online Resource
    ISSN: 1532-0626 , 1532-0634
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2017
    detail.hit.zdb_id: 2052606-4
    SSG: 11
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 3
    Online Resource
    Online Resource
    Wiley ; 2013
    In:  Concurrency and Computation: Practice and Experience Vol. 25, No. 11 ( 2013-08-10), p. 1559-1585
    In: Concurrency and Computation: Practice and Experience, Wiley, Vol. 25, No. 11 ( 2013-08-10), p. 1559-1585
    Abstract: It is generally accepted that the ability to develop large‐scale distributed applications has lagged seriously behind other developments in cyberinfrastructure. In this paper, we provide insight into how such applications have been developed and an understanding of why developing applications for distributed infrastructure is hard. Our approach is unique in the sense that it is centered around half a dozen existing scientific applications; we posit that these scientific applications are representative of the characteristics, requirements, as well as the challenges of the bulk of current distributed applications on production cyberinfrastructure (such as the US TeraGrid). We provide a novel and comprehensive analysis of such distributed scientific applications. Specifically, we survey existing models and methods for large‐scale distributed applications and identify commonalities, recurring structures, patterns and abstractions. We find that there are many ad hoc solutions employed to develop and execute distributed applications, which result in a lack of generality and the inability of distributed applications to be extensible and independent of infrastructure details. In our analysis, we introduce the notion of application vectors: a novel way of understanding the structure of distributed applications. Important contributions of this paper include identifying patterns that are derived from a wide range of real distributed applications, as well as an integrated approach to analyzing applications, programming systems and patterns, resulting in the ability to provide a critical assessment of the current practice of developing, deploying and executing distributed applications. Gaps and omissions in the state of the art are identified, and directions for future research are outlined. Copyright © 2012 John Wiley & Sons, Ltd.
    Type of Medium: Online Resource
    ISSN: 1532-0626 , 1532-0634
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2013
    detail.hit.zdb_id: 2052606-4
    SSG: 11
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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