A distributed clustering algorithm for target tracking in vehicular ad-hoc networks

Authors:
Sanaz Khakpour;Richard Werner Pazzi;Khalil El-Khatib
Affiliations:
University of Ontario Institute of Technology - UOIT, OSHAWA, ON, Canada;University of Ontario Institute of Technology - UOIT, OSHAWA, ON, Canada;University of Ontario Institute of Technology - UOIT, OSHAWA, ON, Canada
Venue:
Proceedings of the third ACM international symposium on Design and analysis of intelligent vehicular networks and applications
Year:
2013

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Abstract

Recently Vehicular Ad-hoc Networks (VANETs) have drawn the attention of academic and industry researchers due to their potential applications including driving safety, entertainment, emergency applications, and content sharing. In some applications such as multimedia sharing, large volume of information is required to be transferred between vehicles. Among the several proposed data routing and management methods implemented in VANETs, clustering has been used to reduce data propagation traffic and to facilitate network management. However, clustering for target tracking is still a challenge in VANET. This paper introduces a clustering mechanism based on a novel VANET compatible algorithm, which will be evaluated and tested in the context of vehicular target tracking. The key features of this algorithm comprise higher cluster head and cluster lifetime and distributed cluster head selection mechanism.