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Improving peer-to-peer search performance through intelligent social search

机译:通过智能社交搜索提高对等搜索性能

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摘要

As a large amount of information is added onto the Internet on a daily basis, the efficiency of peer-to-peer (P2P) search has become increasingly important. However, how to quickly discover the right resource in a large-scale P2P network without generating too much network traffic remains highly challenging. In this paper, we propose a novel P2P search method, by applying the concept of social grouping and intelligent social search; we derive peers into social groups in a P2P network to improve search performance. Through a super-peer-based architecture, we establish and maintain virtual social groups on top of a P2P network. The interactions between the peers in the P2P network are used to incrementally build the social relationships between the peers in the associated social groups. In such a P2P network, a search query is propagated along the social groups in the overlay social network. Our preliminary experiments have demonstrated that our method can significantly shorten search routes and result in a higher peer search performance. In addition, our method also enhances the trustworthiness of search results because searches go through trusted peers.
机译:随着每天将大量信息添加到Internet上,对等(P2P)搜索的效率变得越来越重要。但是,如何在大型P2P网络中快速发现正确的资源而又不会产生太多的网络流量仍然是非常具有挑战性的。本文运用社交分组和智能社交搜索的概念,提出了一种新颖的P2P搜索方法。我们将对等点引入P2P网络中的社交群体,以提高搜索效果。通过基于超级对等的体系结构,我们在P2P网络之上建立和维护虚拟社交团体。 P2P网络中的对等方之间的交互用于逐步建立关联的社交组中的对等方之间的社交关系。在这种P2P网络中,搜索查询沿着覆盖的社交网络中的社交群体传播。我们的初步实验表明,我们的方法可以大大缩短搜索路径,并提高对等搜索性能。此外,我们的方法还增强了搜索结果的可信赖性,因为搜索是通过受信任的同级进行的。

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