非结构化P2P网络中IACO资源搜索算法  

IACO resources search algorithm in unstructured P2P network

作　　者：房佩[1] 闫向龙 良梓[1] 吴晓军[1] 

机构地区：[1]陕西师范大学计算机科学学院,西安710062 [2]陕西师范大学物理学与信息技术学院,西安710062

出　　处：《计算机应用研究》2014年第2期522-525,共4页Application Research of Computers

基　　金：国家自然科学基金面上项目(11172342);国家教育部新世纪优秀人才支持计划资助项目(NCET-11-0674);陕西省自然科学基金资助项目(2012JM8043)

摘　　要：针对非结构化P2P网络中资源搜索效率低、冗余消息较多的情况,提出一种基于兴趣因子的蚁群优化算法(IACO)。该算法充分考虑了节点价值对资源搜索的影响,在传统蚁群算法中引入节点的兴趣因子,以动态调整节点价值和信息素在计算转发概率时的权重关系,有效地指导了资源查询路径的生成。仿真结果表明,该算法可以显著提高资源查询的成功率,同时在一定程度上减少了网络中的冗余消息量。To solve the problems of low efficiency and more redundant messages in unstructured P2P. network resources search, this paper proposed an ant colony optimization based on interest factor（IACO）. It gave full consideration to the effects of node value of resources search. It introduced node interest factor into traditional ant colony algorithm to adjust the weight relationship of node value and pheromones dynamically in the forward probability calculation, and effectively guided the generation of resources query path. The simulation results show that the proposed algorithm can improve the success significantly rate and to a certain extent can reduce the amount of redundant messages in the network at the same time.

关 键 词：对等网络 资源搜索 节点价值 蚁群优化算法 兴趣因子 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]