混合对等网络中基于激励的可靠搜索算法

针对对等网络中因搭便车节点的消极行为所造成的搜索不可靠问题，提出了基于信度模型的可靠搜索算法(CMRRW)。应用信度模型来评价节点的服务能力和稳定性。提出查询可靠率的概念，用来反映经由该节点的历史查询成功率及其周边环境路由效率。在节点选择邻居进行消息转发时，优先选择信度高且历史命中率高的邻居节点。实验结果表明，CMRRW算法能显著提高搜索效率，提高搜索的可靠性。

Incentive-Based Search Algorithm in Hybrid Peer-to-Peer Networks

In peer-to-peer network, there exist lots of free riders, whose passive behaviors decrease the efficiency and reliability of search. A new search algorithm named credit model based restricted random walk (CMRRW), which is based on the credit model, is proposed to solve this problem. The credit model is applied to evaluate the reliability of the peers. The query reliability rate is gained to reflect the peer’s history query success rate and the routing efficiency of its neighbors. In our solutions, when the peer selects neighbors to forward the query message, the neighbors with higher credit and history hit rate will be selected in prior order. Simulation results indicate that CMRRW shows good performance.