Motion adaptive indexing for moving continual queries over moving objects

  • Authors:

  • Bugra Gedik;Kun-Lung Wu;Philip Yu;Ling Liu

  • Affiliations:

  • Georgia Institute of Tech.;T.J. Watson Research Center, Hawthorne, NY;T.J. Watson Research Center, Hawthorne, NY;Georgia Institute of Tech.

  • Venue:
  • Proceedings of the thirteenth ACM international conference on Information and knowledge management
  • Year:
  • 2004

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Abstract

This paper describes a motion adaptive indexing scheme for efficient evaluation of moving continual queries (MCQs) over moving objects. It uses the concept of motion-sensitive bounding boxes (MSBs) to model moving objects and moving queries. These bounding boxes automatically adapt their sizes to the dynamic motion behaviors of individual objects. Instead of indexing frequently changing object positions, we index less frequently changing object and query MSBs, where updates to the bounding boxes are needed only when objects and queries move across the boundaries of their boxes. This helps decrease the number of updates to the indexes. More importantly, we use predictive query results to optimistically precalculate query results, decreasing the number of searches on the indexes. Motion-sensitive bounding boxes are used to incrementally update the predictive query results. Our experiments show that the proposed motion adaptive indexing scheme is efficient for the evaluation of moving continual range queries.