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Efficient clique detection among mobile targets

Published: 10 September 2008 Publication History

Abstract

Clique detection is a base mechanism of proactive multitarget Location-based Services (LBSs), ranging from mobile social network services to logistics. A clique is a set of n mobile targets which are pairwise located within spatial proximity range. Clique detection refers to automatically detecting such cliques within a set S of size sn of tracked targets. Assuming terminal-based positioning like GPS, the paper presents an efficient clique detection strategy for reducing the message exchange between the targets' devices and a central location server for correlating the targets' positions. The basic idea is to prove the non-existence of a clique as long as it does not exist. Based on conclusions from graph theory, this is achieved by distributing the members of S into n -- 1 so-called independent sets, which are sets of targets known to be pairwise not within proximity range. For maintaining the independent sets, proximity detection between two targets, for which efficient strategies already exist, is dynamically applied to selected pairs of targets. Based on simulations it turns out that, compared to a rudimentary strategy, the achieved message savings are substantial.

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cover image ACM Other conferences
Mobility '08: Proceedings of the International Conference on Mobile Technology, Applications, and Systems
September 2008
689 pages
ISBN:9781605580890
DOI:10.1145/1506270
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 September 2008

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Author Tags

  1. clique detection
  2. location-based services
  3. mobile computing
  4. proactive LBSs
  5. proximity detection

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