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Journal of Computer Science and Technology

, Volume 23, Issue 4, pp 538–556 | Cite as

Continually Answering Constraint k-NN Queries in Unstructured P2P Systems

  • Bin WangEmail author
  • Xiao-Chun Yang
  • Guo-Ren Wang
  • Ge Yu
  • Lei Chen
  • X. Sean Wang
  • Xue-Min Lin
Regular Paper
  • 39 Downloads

Abstract

We consider the problem of efficiently computing distributed geographical k-NN queries in an unstructured peer-to-peer (P2P) system, in which each peer is managed by an individual organization and can only communicate with its logical neighboring peers. Such queries are based on local filter query statistics, and require as less communication cost as possible, which makes it more difficult than the existing distributed k-NN queries. Especially, we hope to reduce candidate peers and degrade communication cost. In this paper, we propose an efficient pruning technique to minimize the number of candidate peers to be processed to answer the k-NN queries. Our approach is especially suitable for continuous k-NN queries when updating peers, including changing ranges of peers, dynamically leaving or joining peers, and updating data in a peer. In addition, simulation results show that the proposed approach outperforms the existing Minimum Bounding Rectangle (MBR)-based query approaches, especially for continuous queries.

Keywords

unstructured P2P k-NN queries answering queries constraints 

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Copyright information

© Springer 2008

Authors and Affiliations

  • Bin Wang
    • 1
    Email author
  • Xiao-Chun Yang
    • 1
  • Guo-Ren Wang
    • 1
  • Ge Yu
    • 1
  • Lei Chen
    • 2
  • X. Sean Wang
    • 3
  • Xue-Min Lin
    • 4
  1. 1.College of Information Science and EngineeringNortheastern UniversityShenyangChina
  2. 2.Department of Computer ScienceThe Hong Kong University of Science and TechnologyHong Kong S.A.R.China
  3. 3.Department of Computer ScienceUniversity of VermontVermontU.S.A.
  4. 4.Department of Computer ScienceThe University of New South WalesNew South WalesAustralia

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