为解决目前RandomWalk改进算法中过于依赖历史搜索记录而导致动态网络环境下搜索命中率低、网络开销过高和稀有资源的搜索成功率提高不明显等问题,通过分析随机漫步的基本性质和易转向高度数节点的搜索特性,提出了一种双向随机漫步搜索机制一一BRws(bidirectionalrandomwalksearch),并证明了其能够提高包括稀有资源在内的搜索成功率,抗扰动性强.分别在静态和动态网络环境中,将Randomwlalk,APS(adaptiveprobabilisticsearch),PQR(path—traceablequeryrouting),P2PBSN(peer-to-peerbasedonsocialnetwork)和BRWS基于RandomGraph、scaleFree网络、SmallWorld网络3种拓扑进行了对比实验.蛙果表明,BRWS可以以较少的网络搜索代价,极大地提高搜索成功率;并在动态网络环境中,对稀有资源的搜索成功率也有显著提高.所提出的方法可适用于P2P文件分发网络应用中.
The improvements of random walk search mainly depend on allocating weight for neighbor peers, which is always incurred on a high overhead and are not very helpful for rare items. This paper proposes a bidirectional random walk search mechanism (short for BRWS) for unstructured P2P network, according to the analysis of basic properties about random walk as well as the special property that random walk tends toward high degree nodes. The mechanism is proved theoretically in this paper, and can improve search success rate, including searching for rare items. It also has a high tolerance for churn. In the static and dynamic environment, comparisons were made among Random Walk, APS (adaptive probabilistic search), PQR (path-traceable query routing), P2PBSN (peer-to- peer based on social network) and BRWS based on three topologies: Random graph, scare free, small world. The experimental results show that BRWS can actually improve the search success rate with lower overhead even when searching rare resources. The method proposed in this paper can apply in P2P file sharing networks.