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

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.