An efficient algorithm for predictive continuous nearest neighbor query processing and result maintenance

  • Authors:
  • Ken C. K. Lee;Hong Va Leong;Jing Zhou;Antonio Si

  • Affiliations:
  • The Hong Kong Polytechnic University, Hong Kong;The Hong Kong Polytechnic University, Hong Kong;The Hong Kong Polytechnic University, Hong Kong;Oracle Corporation, Redwood Shores, CA

  • Venue:
  • Proceedings of the 6th international conference on Mobile data management
  • Year:
  • 2005

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Abstract

Predictive continuous nearest neighbor queries are concerned with finding the nearest neighbor objects for some future time period according to the current object and query locations and their motion information. Existing continuous query processing algorithms are not efficient enough, requiring multiple dataset lookups to evaluate the query results throughout the duration of a continuous query. More importantly, the complete result for the whole query time interval is only available at the moment when all object motion updates have been examined, based on which adjustment of the query result is made. In this paper, we propose an algorithm which requires only one dataset lookup to deliver a complete predictive result. We then apply a differential update technique to maintain the query results incrementally in the presence of object location and motion updates.