基于紧缩状态表的高效数据定位方法

数据定位是松散式P2P系统面临的挑战性难题。本文提出了一种新的数据定位方法--紧缩状态表方法（CSTM）。在CSTM中，每个结点上维护一个状态表，保存了丁跳（Hop）内全部邻居上数据的关键字信息，各个结点按照状态表来转发数据定位消息。CSTM方法采用Bloom Filter技术来压缩表示状态表，采用查询Cache建立与最近访问的结点之间的快捷连接。模拟结果表明，与广播泛洪和二路随机转发方法相比，CSTM方法大大减低了P2P网络中数据定位的消息开销，并能够获得较短的查询路径长度。

A Compact Table-Based Search Mechanism for Peer-to-Peer Systems

Recently unstructured P2P systems have been deployed widely on the Internet. However, current search techniques used in the existing Gnutella-like peer-to-peer systems are often very inefficient. In this paper we propose the CSTM mechanism to improve the performance and scalability of such systems. In CSTM, each peer maintains a local state table containing the keyword information of data on all neighbors within T hops to guide query, and new peers joining in the system select their neighbors by the degree of similarity. CSTM adopts a query cache to utilize query locality and build shortcut connections to lately accessed peers. Simulations show that CSTM can reduce message cost one order of magnitude remarkably while maintaining short search path lengths compared with flooding or random forwarding algorithms.