Continuous aggregate nearest neighbor queries

  • Authors:

  • Hicham G. Elmongui;Mohamed F. Mokbel;Walid G. Aref

  • Affiliations:

  • Department of Computer and Systems Engineering, Faculty of Engineering, Alexandria University, Alexandria, Egypt 21544;Department of Computer Science and Engineering, University of Minnesota - Twin Cities, Minneapolis, USA 55455;Department of Computer Science, Purdue University, West Lafayette, USA 47907

  • Venue:
  • Geoinformatica
  • Year:
  • 2013

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Abstract

This paper addresses the problem of continuous aggregate nearest-neighbor (CANN) queries for moving objects in spatio-temporal data stream management systems. A CANN query specifies a set of landmarks, an integer k, and an aggregate distance function f (e.g., min, max, or sum), where f computes the aggregate distance between a moving object and each of the landmarks. The answer to this continuous query is the set of k moving objects that have the smallest aggregate distance f. A CANN query may also be viewed as a combined set of nearest neighbor queries. We introduce several algorithms to continuously and incrementally answer CANN queries. Extensive experimentation shows that the proposed operators outperform the state-of-the-art algorithms by up to a factor of 3 and incur low memory overhead.