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    乐光学, 李仁发, 陈 志, 周 旭. P2P网络中搭便车行为分析与抑制机制建模[J]. 计算机研究与发展, 2011, 48(3): 382-397.
    引用本文: 乐光学, 李仁发, 陈 志, 周 旭. P2P网络中搭便车行为分析与抑制机制建模[J]. 计算机研究与发展, 2011, 48(3): 382-397.
    Yue Guangxue, Li Renfa, Chen Zhi, Zhou Xu. Analysis of Free-riding Behaviors and Modeling Restrain Mechanisms for Peer-to-Peer Networks[J]. Journal of Computer Research and Development, 2011, 48(3): 382-397.
    Citation: Yue Guangxue, Li Renfa, Chen Zhi, Zhou Xu. Analysis of Free-riding Behaviors and Modeling Restrain Mechanisms for Peer-to-Peer Networks[J]. Journal of Computer Research and Development, 2011, 48(3): 382-397.

    P2P网络中搭便车行为分析与抑制机制建模

    Analysis of Free-riding Behaviors and Modeling Restrain Mechanisms for Peer-to-Peer Networks

    • 摘要: 在现实网络中,节点日益严重的搭便车行为对P2P可信流媒体网络的健壮性、可用性、服务响应速度和生命周期等产生了重要的影响.设计合理且有效的搭便车行为抑制和鼓励自私节点为系统作贡献的策略已成为P2P可信流媒体系统应用研究的一个重要方向.在全面分析节点的搭便车行为机理和搭便车行为对网络性能影响的基础上,对节点在P2P可信流媒体网络中的行为建模,在保证网络性能的前提下引入“适度安全、容错不容罪”的思想以保持网络系统共享资源的丰富,以P2P可信流媒体网络中节点的信誉度、贡献度和收益等为评价指标,运用博弈论构建了一个具有纳什均衡的搭便车行为抑制和激励节点为系统作贡献的策略模型,给出了相应的规则和约束条件,并进行了较为详细的分析.仿真实验表明,该策略模型能很好地解决搭便车行为抑制和激励节点为系统作贡献的问题,提高了P2P可信流媒体网络的性能和服务质量,使P2P可信流媒体网络系统实现相对平衡.

       

      Abstract: In a real peer-to-peer (P2P) network, large amounts of network measurement results show that free riding is prevalent in almost all P2P reliable streaming media networks, which reduces the robustness, availability, service response speed, and lifetime of P2P reliable streaming media networks. Research of the reasonable and effective mechanisms to prohibit free-riders and incite selfish nodes to contribute more to the system has become an important direction for application research of P2P reliable streaming media network. Analysis by the intrinsic characteristics of free-riding and the related impacts on system performance, the behaviors of P2P reliable streaming media nodes are modeled and an idea with the goal of keeping moderate safety by allowing some errors but no crimes is introduced without sacrificing overall performance. Furthermore, the game theory is used to restrain free-riders and encourage them to be more altruistic. Reputation, contribution, and revenue of each node are adopted as metrics to assess the model. And the existence of Nash equilibrium for the model is proved; the rules, constraints, and a detailed analysis of it are given as well. Simulations show that the proposed model is effective in countering free-riding behavior, improving the performance and quality of service (QoS) of the P2P reliable streaming media network. It is able to keep relative balance.

       

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