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论文类型：会议论文

发表时间：2016-08-02

收录刊物：EI、CPCI-S

卷号：9773

页面范围：658-670

关键字：Adaptive function; Incentive mechanism; Evolutionary game

摘要：P2P systems provide peers a dynamic and distributed environment to share resource. Only if peers are voluntarily share with each other can system stably exist. However, peers in such systems are selfish and never want to share even with tiny cost. This can lead to serious free-riding problems. Incentive mechanisms based on evolutionary game aim at designing new strategies to distinguish defective peers from cooperative peers and induce them to cooperate more. Nevertheless, the behavior patterns of peers are versatile. Using only one certain strategy to depict peers' behaviors is incomplete. In this paper, we propose an adaptive strategy which integrates advantages of 3 classic strategies. These 3 strategies form a knowledge base. Each time a peer with this strategy can select one adjusting to system status according to the adaptive function. Through experiments, we find that in structured system, this strategy can not only promote cooperation but also the system performance.