基于Bloom Filter和概率分发队列的P2P网络快速查找算法

无结构化P2P网络资源定位过程中的响应时间、查准率及覆盖率难以同时被优化。提出一种面向有向无环随机网络的基于Bloom Filter和概率分发队列的快速查找算法BFPDQ(Bloom Filter and Probabilistic Distribution Queue),它用Bloom Filter表达和传递节点命中资源信息及查找请求信息,计算新查询消息与历史查询消息Bloom Filter语义向量相似度,并应用底层网络路径性能信息指导上层转发决策。概率分发队列(Probabilistic Distribution Queue,PDQ)把传统walkers表示成为查找消息分发队列,查找请求者协调各分发队列的查找方向和深度,并融合各队列查找过程中得到的定位消息。仿真实验表明,BFPDQ算法在保持较少冗余信息的同时有效缩短了响应时间。

Quick P2P Search Algorithm Based on Bloom Filter and Probabilistic Distribution Queue

The strategy of searching resource is a research hotspot in unstructured peer to peer network.It is hard to optimize response time,query hit,and coverage rate for resource location of unstructured P2P network simultaneously.This paper presented a quickly search algorithm called BFPDQ(Bloom filter and probabilistic distribution queue),which is based on probabilistic distribute queue and Bloom filter technology.BFPDQ is mainly used for acyclic random network.Information of resources and requests can be expressed by Bloom filter technology.Meanwhile,performance information of the underlying network’s path can be used to guide transmitting strategy for upper layers.PDQ(probabilistic distribute queue) uses distributed queues to substitute traditional walkers to search resources.Requester coordinates direction and depth of those queues and aggregates their resource location messages.Simulation results show that BFPDQ can decrease redundant information,while maintaining a significant reduction in response time.