摘要： 资源搜索是P2P技术的研究热点之一。该文针对现有P2P资源搜索算法消息开销大、搜索效率低等问题，提出一种基于蚁群算法的非结构化P2P资源搜索机制。利用蚂蚁信息素的正反馈原理，有效指导资源搜索路径的生成，将查询消息发送到可能存在目标的区域。仿真实验结果表明，该机制提高资源搜索命中率，减少冗余消息包，其搜索效果较好。

关键词: 蚁群算法, 群智能, 信息素

Abstract: Resources search is one of research hotspots in the filed of P2P technique. Aiming at the problems of existing P2P resources search algorithm, such as huge message packets, low search efficiency, this paper proposes resources search mechanism based on Ant Colony Optimization(ACO) for unstructured P2P. This mechanism directs the query routing effectively according to the positive feedback principle of the ant pheromone. It sends the query messages to the area where may store the requested resources. Simulation experimental results show that this mechanism can achieve better search performance by increasing the resource hit ratio and reducing the query message packets of redundancy.

Key words: Ant Colony Optimization(ACO), swarm intelligence, pheromone

中图分类号: 

• TP301.6