Advanced Search
    Wang Yang, Wang Ruchuan, Yan Yuanting, Han Zhijie, Zhao Baohua. TCLM-P2P: Task Collaboration Logic Model Oriented to P2P Community[J]. Journal of Computer Research and Development, 2012, 49(2): 270-277.
    Citation: Wang Yang, Wang Ruchuan, Yan Yuanting, Han Zhijie, Zhao Baohua. TCLM-P2P: Task Collaboration Logic Model Oriented to P2P Community[J]. Journal of Computer Research and Development, 2012, 49(2): 270-277.

    TCLM-P2P: Task Collaboration Logic Model Oriented to P2P Community

    • Traditional P2P networks mainly are applied to file sharing and instant message fields. However, how to perform the task collaboration based on P2P community is a challenging job. The former research work indicated that the task collaboration in P2P network had been greatly restricted by free riding behaviors. To realize effective task allocating and task collaborating in P2P network environment, this paper presents a task collaboration logic model oriented to P2P community. Based on agent and multi-agent theory, the paper firstly introduces some concepts including the peer body, half-peer body and P2P community; then the TCLM-P2P is presented including some collaboration axioms and rulers. In order to enhance the incentive mechanism, virtual score becomes the main goal which each peer endeavor pursues. In addition, based on the contract net protocol, a task collaboration algorithm is presented. The proposed algorithm is composed of two phases. One is the task collaboration and the other is the task second bid when some peers fail to complete the former task. Compared with the traditional task collaboration models, the presented model has the feasible incentive mechanism in the process of task allocation and collaboration. The developed prototype and simulation results indicate that TCLM-P2P model is feasible and effective. It could not only incentivize self-interested peer to participate in task allocation and collaboration, but also restrain peer’s free riding behaviors in some degree.
    • loading

    Catalog

      Turn off MathJax
      Article Contents

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return