ESA: an efficient and stable approach to querying reverse k-nearest-neighbor of moving objects

  • Authors:
  • Dunlu Peng;Wenming Long;Ting Huang;Huan Huo

  • Affiliations:
  • School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China;School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China;School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China;School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China

  • Venue:
  • WISM'10 Proceedings of the 2010 international conference on Web information systems and mining
  • Year:
  • 2010

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Abstract

In this work, we study how to improve the efficiency and stability of querying reverse k-nearest-neighbor (RkNN) for moving objects. An approach named as ESA is presented in this paper. Different from the existing approaches, ESA selects k objects as pruning reference objects for each time of pruning. In this way, its greatly improves the query efficiency. ESA also reduces the communication cost and enhances the stability of the server by adaptively adjusting the objects' safe regions. Experimental results verify the performance of our proposed approach.