Continuous aggregate nearest neighbor queries

Hicham G. Elmongui, Mohamed Mokbel, Walid G. Aref

Research output: Contribution to journalArticle

20 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)63-95
Number of pages33
JournalGeoInformatica
Volume17
Issue number1
DOIs
Publication statusPublished - 1 Jan 2013
Externally publishedYes

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state of the art

Keywords

  • Aggregate nearest neighbor
  • Continuous query
  • Spatio-temporal query

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Information Systems

Cite this

Continuous aggregate nearest neighbor queries. / Elmongui, Hicham G.; Mokbel, Mohamed; Aref, Walid G.

In: GeoInformatica, Vol. 17, No. 1, 01.01.2013, p. 63-95.

Research output: Contribution to journalArticle

Elmongui, Hicham G. ; Mokbel, Mohamed ; Aref, Walid G. / Continuous aggregate nearest neighbor queries. In: GeoInformatica. 2013 ; Vol. 17, No. 1. pp. 63-95.
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