• DocumentCode
    1628120
  • Title

    SPSI: A hybrid super-node election method based on information theory

  • Author

    Gao, Zhiwei ; Gu, Zhimin ; Wang, Wenbao

  • Author_Institution
    Dept. of Comput. Sci., Beijing Inst. of Technol., Beijing, China
  • fYear
    2012
  • Firstpage
    1076
  • Lastpage
    1081
  • Abstract
    By exploiting heterogeneity, the super-node paradigm can lead to improved efficiency, without compromising the decentralized nature of peer-to-peer (P2P) networks. So many relevant applications such as grids, cloud computings use super-node paradigm as the lower service. However, due to inherent decentralisation, scale, dynamism, and complexity of P2P environments, self-managing super-node selection is a challenging problem. This paper present a super-node election protocol based on self-information theory (SPSI). In SPSI, every node has a information vector (VI), and SPSI uses a weighted mean mechanism based on VI to promote the “best” nodes to super-node status. We are the first (to the best of our knowledge) to use self-information theory to select super-node. The paper also includes extensive simulation experiments to prove the efficiency, scalability and robustness of SPSI.
  • Keywords
    cloud computing; computer network management; grid computing; information theory; peer-to-peer computing; protocols; P2P network; cloud computing; grid computing; hybrid super-node election method; information vector; peer-to-peer network; self-information theory; self-managing super-node selection; super-node election protocol; super-node paradigm; super-node status; weighted mean mechanism; Binary trees; Convergence; Network topology; Nominations and elections; Peer to peer computing; Protocols; Topology; SPSI; scalability; self-information; super-node;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Communication Technology (ICACT), 2012 14th International Conference on
  • Conference_Location
    PyeongChang
  • ISSN
    1738-9445
  • Print_ISBN
    978-1-4673-0150-3
  • Type

    conf

  • Filename
    6174853