• DocumentCode
    788947
  • Title

    Incentive and Service Differentiation in P2P Networks: A Game Theoretic Approach

  • Author

    Ma, Richard T B ; Lee, Sam C M ; Lui, John C S ; Yau, David K Y

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong
  • Volume
    14
  • Issue
    5
  • fYear
    2006
  • Firstpage
    978
  • Lastpage
    991
  • Abstract
    Conventional peer-to-peer (P2P) networks do not provide service differentiation and incentive for users. Therefore, users can easily obtain information without themselves contributing any information or service to a P2P community. This leads to the well known free-riding problem. Consequently, most of the information requests are directed towards a small number of P2P nodes which are willing to share information or provide service, causing the "tragedy of the commons." The aim of this paper is to provide service differentiation in a P2P network based on the amount of services each node has provided to the network community. Since the differentiation is based on nodes\´ prior contributions, the nodes are encouraged to share information/services with each other. We first introduce a resource distribution mechanism for all the information sharing nodes. The mechanism is distributed in nature, has linear time complexity, and guarantees Pareto-optimal resource allocation. Second, we model the whole resource request/distribution process as a competition game between the competing nodes. We show that this game has a Nash equilibrium. To realize the game, we propose a protocol in which the competing nodes can interact with the information providing node to reach Nash equilibrium efficiently and dynamically. We also present a generalized incentive mechanism for nodes having heterogeneous utility functions. Convergence analysis of the competition game is carried out. Examples are used to illustrate that the incentive protocol provides service differentiation and can induce productive resource sharing by rational network nodes. Lastly, the incentive protocol is adaptive to node arrival and departure events, and to different forms of network congestion
  • Keywords
    DiffServ networks; Pareto analysis; computational complexity; game theory; peer-to-peer computing; protocols; Nash equilibrium; P2P networks; Pareto-optimal resource allocation; free-riding problem; game theoretic; linear time complexity; network congestion; peer-to-peer networks; protocol; resource distribution mechanisms; service differentiation; Computer science; Convergence; Game theory; Intelligent networks; Nash equilibrium; Network servers; Peer to peer computing; Protocols; Resource management; Telecommunication traffic; Contribution-based service differentiation; game theory; incentive protocol; peer-to-peer network;
  • fLanguage
    English
  • Journal_Title
    Networking, IEEE/ACM Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6692
  • Type

    jour

  • DOI
    10.1109/TNET.2006.882904
  • Filename
    1709951