基于节点兴趣和Q-learning的P2P网络搜索机制

将智能手机设备加入基于非结构化P2P网络的资源共享系统中能够满足人们对资源共享的多样化、便利性、高频性、实时性、高效性等要求,但是该系统网络规模的扩张和网络节点互异性的加大,必将导致系统资源搜索效率的降低、冗余信息的剧增以及网络更加不稳定。为了解决这些问题,文中设计了一种改进的基于节点兴趣和Q-learning的资源搜索机制。首先将节点根据兴趣相似度进行兴趣聚类,划分兴趣集,然后根据兴趣集中节点的能力值构建兴趣树,该结构避免了消息环路的产生,极大地降低了冗余信息;在资源搜索中,兴趣树内采用洪泛算法转发消息,兴趣树之间采用基于Q-learning的消息转发机制,不断强化最可能获取目标资源的路径,查询消息优先在这些路径上传播。另外,针对“热点”资源问题,设计了自适应热点资源索引机制,减少了重复路径搜索,进一步减少了冗余消息量;针对节点失效的问题,给出了根节点冗余机制和捎带检测的策略方法,分别解决了根节点失效和普通节点失效导致的兴趣树的不完整性问题,分析表明该方法能够减少消息冗余量。仿真实验结果表明,与GBI-BI算法和Interest CN算法相比,所提搜索算法能够提高命中率,缩短响应时间,减少冗余信息,具有较好的综合性能,最终解决了由于智能手机设备加入P2P网络导致的资源搜索效率下降、网络流量开销大的问题。

P2P Network Search Mechanism Based on Node Interest and Q-learning

Adding smartphone devices to the resource sharing system based on unstructured P2P network can satisfy people’s requirements for diversity,convenience,high frequency,real-time and high efficiency of resource sharing.However,the expansion of network scale and the increase of network node heterogeneity will inevitably lead to the decrease of system resource search efficiency,the sharp increase of redundant information and the more non-network.To solve these problems,an improved resource search mechanism based on node interest and Q-learning was designed.Firstly,nodes are clustered according to interest similarity,and interest sets are divided.Then,interest trees are constructed according to the capability values of interest sets.This structure avoids the generation of message loops,which greatly reduces redundant information.In resource search,flooding algorithm is used to forward messages in interest trees,and Q-learning-based message forwarding mechanism is used among interest trees,which is constantly strengthened.The most likely paths to obtain the target resources are transformed,and query messages are propagated preferentially on these paths.In addition,for the“hot spot”resource problem,an adaptive hot spot resource index mechanism was designed to reduce the repeated path searching and redundant message volume.To solve the problem of node failure,the root node redundancy mechanism and the strategy method of piggyback detection were given.The analysis results show that the method can reduce message redundancy caused by root node failure and common node failure respectively.The simulation results show that compared with GBI-BI algorithm and Interest CN algorithm,the proposed search algorithm can improve hit rate,shorten response time,reduce redundant information,and has better comprehensive performance.Finally,it solves the problems of low efficiency of resource search and high overhead of network traffic caused by the addition of smartphone devices to P2P network.