基于非结构化的P2P信息检索关键技术研究

如何在缺少集中控制、大规模、分布式的P2P（peer-to-peer）网络中找到并定位信息是所有的P2P共享系统面临的一个难题．现有的P2P信息检索机制存在着种种不足：基于结构化P2P网络的检索效率很高，然而由于构造过于严格，难以在Internet上普及，而且仅能支持粗粒度的文件共享；非结构化P2P网络实现简单，是P2P共享系统的主要实现方式，但是由于搜索的盲目性，其检索效率又普遍低下．建立了一个新的非结构化P2P共享原型系统．该系统利用改进的蚁群算法进行检索路由，使检索总是倾向于有利的方向．同时，有针对性的推荐服务能够减少盲目搜索，提高文件共享水平．仿真实验的结果表明，该系统所采用的信息检索与信息推荐相结合的策略能够有效地提高P2P信息检索的成功率，降低网络负载．

Research on key techniques about unstructured P2P information retrieval

How to find and locate information in a decentralized and dynamic network is a big problem for all P2P(peer-to-peer)file-sharing systems.Unfortunately,existing P2P searching mechanisms are usually dissatisfied.For example,structured P2P systems are efficient but lack of actual implementing on the Internet because of their complicated structures.Unstructured P2P systems are inefficient but more popular.In this paper,a new approach to P2P information retrieval based on unstructured P2P systems is presented by using ant colony algorithm and information recommendation services to improve the search efficiency.Ant colony algorithm is used to make routing decisions,which makes the searches tend to the most favorable direction.Besides,information recommendation services can reduce blind searches and raise the file-sharing level.In order to evaluate and validate this model,a simulated P2P application consisted of a network of peer nodes is built.The results show that the searching mechanism has good performances on the search success rate and load balancing.