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

NCUIR > College of Electrical Engineering & Computer Science > Graduate Institute of Computer Science and Information Engineering > journal & Dissertation > Item 987654321/29123

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/29123

Title:	Improving peer-to-peer search performance through intelligent social search
Authors:	Yang,SJH;Zhang,J;Lin,L;Tsai,JJP
Contributors:	資訊工程研究所
Keywords:	SERVICE;ARCHITECTURE;ALGORITHMS;NETWORK;SYSTEM;TRUST
Date:	2009
Issue Date:	2010-06-29 20:14:16 (UTC+8)
Publisher:	中央大學
Abstract:	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. (C) 2009 Elsevier Ltd. All rights reserved.
Relation:	EXPERT SYSTEMS WITH APPLICATIONS
Appears in Collections:	[Graduate Institute of Computer Science and Information Engineering] journal & Dissertation

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