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基于加权信任向量的混合结构式P2P网络信任模型 被引量:1

Weighted Trust Vector Model for P2P Network Based on Hybrid Structure
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摘要 为了解决非结构化P2P网络信任模型的全局信任度的迭代计算和结构化P2P网络信任模型的网络规模不易扩展性的缺点,设计了基于加权信任向量的混合结构式P2P网络信任模型(简称W-TPP),它采用信任向量来存储历史经验数据,利用结构化网络中的节点来分布式存取全局信任向量表.并且为了解决历史经验数据的时间有效性问题,提出一种新的节点信任值算法—加权信任向量算法.通过对W-TPP信任模型的性能分析和模拟仿真试验,验证了该信任模型具有可扩展性,降低了查询全局信任度所占的网络资源. Unstructured P2P trust model needs iterative calculation for global trust tables and structured P2P trust model's network size is not scalable. In order to solve these problems, design weighted trust vector model for P2P network based hybrid structure (referred to as W-TPP). It adopts trust vector to save all history transaction records and use peers in the structured network to access the global trust tables. In order to resolve the timing of history transaction records, weighted trust algorithm is presented. By analyzing the performance of W-TPP trust model, trust model' s scalability is verified and the network resource for accessing global trust tables is reduced.
作者 李刚 李季
出处 《微电子学与计算机》 CSCD 北大核心 2009年第9期93-98,共6页 Microelectronics & Computer
关键词 P2P网络 信任值算法 混合结构式 加权信任向量 P2P reputation hybrid structure weighted trust vector
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参考文献9

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共引文献57

同被引文献7

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