Using Two-tier Bitwise Interest Oriented QRP Data Structure for High Clustering through Interest Similarity in SWB P2P Systems

T. Lim, Yong Liang Choong, A. Lee
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Abstract

The concept of "Small-World" paradigm has been used by many peer-to-peer (P2P) systems to achieve high clustering and low number of hops to arrive to its desired target. This approach intends to improve performance of P2P systems. The Small world concept requires that the architecture of a P2P system to achieve high cluster coefficient and low average hop between any two randomly chosen peers. In this research, we propose an enhanced hierarchical overlay network by incorporating the concept of Small world into the base hierarchical architecture. This research adopts the Query Routing Protocol (QRP) data structure of a hierarchical P2P network by storing the interest information of files in the leaf peers in the network. The QRP in the leaf peers will be aggregated and propagated to the Super Peer so that interest information could be used to form short-range, medium-range and long-range links with other Super Peers to achieve low average hop. As peers join and leave the network, a proposed rewiring protocol is used to ensure peers are clustered by interest to form high clustering coefficient so that search activities are yielding higher relevance results in a more predictable fashion. We simulated the porposed small world P2P using test scenarios to evaluate recall rate of the small world P2P system. Our simulated results evaluate and benchmark our proposed Small-World Bee (SWB) overlay network with iCluster [3], Firework Query Model [5] and Lime wire [1] to assess performance obtained and goals achieved in the research work so that future research directions could be planned.
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基于兴趣相似度的SWB P2P系统中基于两层位兴趣导向QRP数据结构的高聚类
“小世界”范式的概念已被许多点对点(P2P)系统用于实现高集群和低跳数到达预期目标。这种方法旨在提高P2P系统的性能。小世界概念要求P2P系统的架构在任意两个随机选择的对等点之间实现高簇系数和低平均跳数。在本研究中,我们提出了一种增强的分层覆盖网络,将小世界的概念融入到基本的分层体系结构中。本研究采用分层P2P网络的查询路由协议(Query Routing Protocol, QRP)数据结构,将网络中叶子节点上文件的兴趣信息存储起来。叶子对等体中的QRP将被聚合并传播到超级对等体中,以便利用兴趣信息与其他超级对等体建立短程、中程和远程链路,以达到低平均跳数的目的。当对等点加入和离开网络时,建议使用重新布线协议来确保对等点按兴趣聚类以形成高聚类系数,以便搜索活动以更可预测的方式产生更高相关性的结果。我们利用测试场景模拟了拟建的小世界P2P,以评估小世界P2P系统的召回率。我们的模拟结果对我们提出的小世界蜜蜂(Small-World Bee, SWB)覆盖网络进行了iCluster[3]、Firework Query Model[5]和Lime wire[1]的评估和基准测试,以评估研究工作中获得的性能和实现的目标,从而规划未来的研究方向。
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