Difficulty-Aware Hybrid Search in Peer-to-Peer Networks

Authors:
Hanhua Chen;Hai Jin;Yunhao Liu;Lionel M. Ni
Affiliations:
Huazhong University of Science and Technology, Wuhan;Huazhong University of Science and Technology, Wuhan;Hong Kong Universtiy of Science and Technology, Hong Kong;Hong Kong Universtiy of Science and Technology, Hong Kong
Venue:
IEEE Transactions on Parallel and Distributed Systems
Year:
2009

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Resource searching in an unstructured P2P network based on Cloning Random Walker assisted by Dominating Set

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Abstract

By combining an unstructured protocol with a DHT-based index, hybrid Peer-to-Peer (P2P) improves search efficiency in terms of query recall and response time. The key challenge in hybrid search is to estimate the number of peers that can answer a given query. Existing approaches assume that such a number can be directly obtained by computing item popularity. In this work, we show that such an assumption is not always valid, and previous designs cannot distinguish whether items related to a query are distributed in many peers or are in a few peers. To address this issue, we propose QRank, a difficulty-aware hybrid search, which ranks queries by weighting keywords based on term frequency. Using rank values, QRank selects proper search strategies for queries. We conduct comprehensive trace-driven simulations to evaluate this design. Results show that QRank significantly improves the search quality as well as reducing system traffic cost compared with existing approaches.