PISA: Federated Search in P2P Networks with Uncooperative Peers

Authors:
Zujie Ren;Lidan Shou;Gang Chen;Chun Chen;Yijun Bei
Affiliations:
Zhejiang University, China;Zhejiang University, China;Zhejiang University, China;Zhejiang University, China;Zhejiang University, China
Venue:
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
Year:
2009

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Abstract

Recently, federated search in P2P networks has received much attention. Most of the previous work assumed a cooperative environment where each peer can actively participate in information publishing and distributed document indexing. However, little work has addressed the problem of incorporating uncooperative peers, which do not publish their own corpus statistics, into a network. This paper presents a P2P-based federated search framework called PISA which incorporates uncooperative peers as well as the normal ones. In order to address the indexing needs for uncooperative peers, we propose a novel heuristic query-based sampling approach which can obtain high-quality resource descriptions from uncooperative peers at relatively low communication cost. We also propose an effective method called RISE to merge the results returned by uncooperative peers. Our experimental results indicate that PISA can provide quality search results, while utilizing the uncooperative peers at a low cost.