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

  • Authors:

  • Hanhua Chen;Hai Jin;Yunhao Liu;Lionel M. Ni

  • Affiliations:

  • Huazhong Univ. of Science and Technology, China;Huazhong Univ. of Science and Technology, China;Hong Kong Univ. of Science and Technology, Hong Kong;Hong Kong Univ. of Science and Technology, Hong Kong

  • Venue:
  • ICPP '07 Proceedings of the 2007 International Conference on Parallel Processing
  • Year:
  • 2007

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Abstract

By combining an unstructured protocol with a DHT-based global 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.