A threshold-based algorithm for continuous monitoring of k nearest neighbors

Kyriakos Mouratidis, Dimitris Papadias, Spiridon Bakiras, Yufei Tao

Research output: Contribution to journalArticle

76 Citations (Scopus)

Abstract

Assume a set of moving objects and a central server that monitors their positions over time, while processing continuous nearest neighbor queries from geographically distributed clients. In order to always report up-to-date results, the server could constantly obtain the most recent position of all objects. However, this naïve solution requires the transmission of a large number of rapid data streams corresponding to location updates. Intuitively, current information is necessary only for objects that may influence some query result (i.e., they may be included in the nearest neighbor set of some client). Motivated by this observation, we present a threshold-based algorithm for the continuous monitoring of nearest neighbors that minimizes the communication overhead between the server and the data objects. The proposed method can be used with multiple, static, or moving queries, for any distance definition, and does not require additional knowledge (e.g., velocity vectors) besides object locations.

Original languageEnglish
Pages (from-to)1451-1464
Number of pages14
JournalIEEE Transactions on Knowledge and Data Engineering
Volume17
Issue number11
DOIs
Publication statusPublished - 1 Nov 2005

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Keywords

  • Location-dependent and sensitive
  • Query processing
  • Spatial databases

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

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