无结构对等模型应用于很多领域,但其常用的Flooding等盲目搜索方式产生大量冗余消息,限制了带宽,易造成网络拥塞.针对传统发现方法中存在的问题,提出了一种基于节点兴趣相似度的资源发现方法,在分组的基础上,根据节点的兴趣相似度将相似节点划分为域,请求消息首先在域内同组节点中转发,搜索过程中动态调整网络拓扑,有效减少路由跳数,降低冗余消息量.通过仿真试验对该方法的搜索效率进行了分析验证.%Unstructured P2P model is widely used in many fields, but the common blind search method ofrnFlooding generates lots of redundant messages. The limited bandwidth can easily cause network congestion. Forrnthe existing problems in traditional discovery method, a resource discovery method based on peer interestrnsimilarity was put forward. Based on grouping, similar peers were divided into domain on the basis of peerrninterest similarity. Query message was forwarded in the same group of the present domain at first,and networkrntopology was adjusted dynamically during searching. Then route hops were reduced and the amount ofrnredundant messages was decreased effectively. Simulation shows the searching efficiency of the method.
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