Lazy updates: an efficient technique to continuously monitoring reverse kNN

  • Authors:

  • Muhammad Aamir Cheema;Xuemin Lin;Ying Zhang;Wei Wang;Wenjie Zhang

  • Affiliations:

  • The University of New South Wales, Australia;The University of New South Wales, Australia and NICTA, Australia;The University of New South Wales, Australia;The University of New South Wales, Australia and NICTA, Australia;The University of New South Wales, Australia and NICTA, Australia

  • Venue:
  • Proceedings of the VLDB Endowment
  • Year:
  • 2009

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Abstract

In this paper, we study the problem of continuous monitoring of reverse k nearest neighbor queries. Existing continuous reverse nearest neighbor monitoring techniques are sensitive towards objects and queries movement. For example, the results of a query are to be recomputed whenever the query changes its location. We present a framework for continuous reverse k nearest neighbor queries by assigning each object and query with a rectangular safe region such that the expensive recomputation is not required as long as the query and objects remain in their respective safe regions. This significantly improves the computation cost. As a by-product, our framework also reduces the communication cost in client-server architectures because an object does not report its location to the server unless it leaves its safe region or the server sends a location update request. We also conduct a rigid cost analysis to guide an effective selection of such rectangular safe regions. The extensive experiments demonstrate that our techniques outperform the existing techniques by an order of magnitude in terms of computation cost and communication cost.