基于感知位置与择优连接的P2P网络搜索方法

P2P技术使互联网计算机间数据交换和信息价值共享至最大化.无结构化P2P系统已得到广泛应用,但在无结构化P2P网络中,绝大部分资源搜索方法采用泛洪或随机游走等简单机制,易加重网络通信负担和导致搜索不确定性.基于P2P网、络幂律分布和小世界特性,提出一种结合流言传播中兴趣衰减机制、感知节点位置和择优连接原则的资源搜索算法.该方法分析网络层路径性能信息以感知节点位置,利用节点度信息扩大广播范围,应用流言传播机制建立概率广播模型.采用概率方法,将搜索导向与目标相关的节点,提高搜索性能.仿真实验结果表明该模型能有效降低查询通信的开销,并快速命中目标.

Peer to Peer Network Search Algorithm Based on Apperceiving Location and Preferential Attachment

Peer to peer(P2P) technology makes the value of information sharing and exchange data networking maximized.Unstructured P2P system has been widely used.Many ways of resources searching is applied in searching the resources,such as simple mechanism of the flooding-based broadcasting or random walk.But it′s easy to cause a serious burden on network traffic and search uncertainty.Based on the power-law distribution and small-world character of P2P network,the searching algorithm which combines the method of apperceiving location of nodes with the strategy of preferential attachment and a broadcasting strategy of interest attenuation mechanism in rumor spreading is proposed.The location of node is apperceived by analyzing the performance information of the network layer′s path,and the broadcasting range is expanded by using the degree information of node,also the probability model is established through rumor spreading mechanism.The performance of searching is improved by the probability method which can fast guide the search to targeted node.Simulation results indicate that the model can effectively reduce communication overhead and quickly hit the target.