Continuous K-nearest neighbor queries for moving objects

  • Authors:

  • Hui Xiao;Qingquan Li;Qinghong Sheng

  • Affiliations:

  • Transportation Research Center, Wuhan University, Wuhan, China and Institute of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China;State Key Laboratory of Information Engineering in Surveying , Mapping and Remote Sensing, Wuhan University, Wuhan, China;Institute of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

  • Venue:
  • ISICA'07 Proceedings of the 2nd international conference on Advances in computation and intelligence
  • Year:
  • 2007

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Abstract

Continuous k-nearest neighbors (CKNN) search has been in the core of spatiotemporal database research during the last decade. It is interested in continuously finding the k closest objects to a predefined query object q during a time interval. Existing methods are either computationally intensive performing repetitive queries to the database or restrictive with respect to the application settings. In this paper we develop an efficient method in order to computes CKNN queries for a query point during a specified time interval. The basic advantage of the proposed approach is that only one query is issued per time interval. The R-tree structure is used to index the static objects. An extensive performance evaluation shows that all the techniques we presented boost the query performance greatly.