• DocumentCode
    1938037
  • Title

    Resource Clustering Based Decentralized Resource Discovery Scheme in Computing Grid

  • Author

    Wang, Xuan ; Kong, Ling-Fu

  • Author_Institution
    Yanshan Univ., Qinhuangdao
  • Volume
    7
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    3859
  • Lastpage
    3863
  • Abstract
    Resource discovery is one of the basic services in grid. In large-scale grid environment, traditional centralized resource discovery approaches limit scalability and result performance bottleneck. Based on the peer-to-peer protocol and the idea of resource clustering, a decentralized resource discovery scheme is introduced to overcome the deficiencies of the centralized resource discovery mechanism. Resources with the same resource type and the similar resource performance get together with the resource clusters that are the minimum units of resource management. Based on the resource clusters, the whole resource space is mapped into two index sub-spaces. A hierarchical and P2P hybrid resource discovery framework is developed to make advantage of the centralized and distributed topologies of the Internet. The algorithm of resource discovery is described. Theoretic analysis and simulation result show that this approach discovers desired resource efficiently.
  • Keywords
    grid computing; pattern clustering; peer-to-peer computing; protocols; resource allocation; centralized topology; computing grid; decentralized resource discovery scheme; distributed topology; peer-to-peer protocol; resource clustering; Analytical models; Clustering algorithms; Grid computing; Internet; Large-scale systems; Peer to peer computing; Protocols; Resource management; Scalability; Topology; Grid; Peer-to-peer; Resource clustering; Resource discovery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370819
  • Filename
    4370819