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我们提出了一种基于演化博弈论的方法来研究当P2P多媒体共享网络中存在自组织激励策略时,节点间合作行为的演化过程.由于媒体服务的时间敏感性,节点间的一次数据共享交易会涉及到多个节点.因此我们将节点间的交易建模为多人非对称博弈,而不是以前研究中使用的两人结对博弈模型.另外,节点基于其所获局部信息和有限的认知能力很难立刻发现自己在网络均衡时的最优策略.因此,我们假定模型中节点可以通过模仿当前收益最高的策略来最大化自己的收益.研究结果发现当激励策略的信息获取花费较小时,网络中节点间的合作行为可以得到很好的保证.
We propose a evolutionary game theory-based approach to study the evolution of cooperative behavior among nodes when there is a self-organizing incentive strategy in P2P multimedia sharing networks.Due to the time sensitivity of media services, a data sharing fair Therefore, we model the transaction between nodes as a multi-person asymmetric game instead of the two-person matching game model used in the previous study.In addition, based on the local information and limited cognitive ability Therefore, we assume that nodes in the model can maximize their profit by imitating the current highest-yielding strategy.The research results show that when the cost of incentive strategy is relatively low, the network The cooperation among the nodes can be well guaranteed.