• DocumentCode
    2017466
  • Title

    Towards a Cluster Based Incentive Mechanism for P2P Networks

  • Author

    Zhang, Kan ; Antonopoulos, Nick

  • Author_Institution
    Univ. of Surrey, Guildford
  • fYear
    2009
  • fDate
    18-21 May 2009
  • Firstpage
    532
  • Lastpage
    537
  • Abstract
    Free riders in Peer-to-peer (P2P) networks are the nodes only consume services but provide little or nothing. They seriously degrade the fault-tolerance and scalability of the P2P networks. A Cluster-Based Incentive Mechanism (CBIM) is proposed in this paper to prevent free riding problem in P2P networks regardless of their topologies and service diversity. Nodes with asymmetric interests are organized in clusters that consist of service exchange rings. A node in a ring can receive a service from its predecessor by providing a requested service to its successor. Free riders can not complete their requested services since a ring will collapse once free riding is detected. We firstly identify five design requirements, namely, adaptability, service diversity, reward and penalty, altruism and performance. Second, we describe the cluster formation process and a graph theory based ring identification algorithm. Finally, we describe our coarse-grained probability-based free riding prevention algorithm. Through a set of simulations, we find that the CBIM is feasible and outperforms other incentive mechanisms.
  • Keywords
    peer-to-peer computing; P2P networks; cluster-based incentive mechanism; peer-to-peer networks; Clustering algorithms; Computer networks; Costs; Fault tolerance; Monitoring; Network servers; Network topology; Peer to peer computing; Scalability; Streaming media; Peer-to-Peer; cluster; free riding; incentive mechansim; service exchange ring;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster Computing and the Grid, 2009. CCGRID '09. 9th IEEE/ACM International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3935-5
  • Electronic_ISBN
    978-0-7695-3622-4
  • Type

    conf

  • DOI
    10.1109/CCGRID.2009.92
  • Filename
    5071917