• DocumentCode
    1796502
  • Title

    Using client-side access partitioning for data clustering in big data applications

  • Author

    Dapeng Liu ; Shaochun Xu ; Zengdi Cui

  • Author_Institution
    GradientX, Santa Monica, CA, USA
  • fYear
    2014
  • fDate
    June 30 2014-July 2 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Big data has been playing a critical role in modern information technology. In some big data management systems, to simplify client design, data requests from clients are even distributed to all nodes and then are routed to the final correct data storage inside the data cluster. After performing analysis on this working mechanism, we point out some design problems and advocate the client-side access partitioning, i.e., clients know precisely which node of the cluster should be accessed for sought information. This approach could provide a fast access. We also implement a first-stage application based on client-side access partitioning for evaluation purpose and the result demonstrates our approach is effective.
  • Keywords
    Big Data; pattern clustering; storage management; very large databases; big data management systems; client-side access partitioning; data clustering; data requests; data storage; information technology; Big data; Computers; Distributed databases; Educational institutions; Partitioning algorithms; Telecommunication traffic; Client-Side Partitioning; data clustering; data security; load balance; performance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2014 15th IEEE/ACIS International Conference on
  • Conference_Location
    Las Vegas, NV
  • Type

    conf

  • DOI
    10.1109/SNPD.2014.6888697
  • Filename
    6888697