A mobility-based scheme for dynamic clustering in vehicular ad-hoc networks (VANETs)

Vehicle clustering is an efficient approach to improve the scalability of networking protocols in vehicular ad-hoc networks (VANETs). However, some characteristics, like highly dynamic topology and intermittent connections, may affect the performance of the clustering. Establishing and maintaining s...

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Bibliographic Details
Published in:Vehicular Communications Vol. 9; pp. 233 - 241
Main Authors: Ren, Mengying, Khoukhi, Lyes, Labiod, Houda, Zhang, Jun, Vèque, Véronique
Format: Journal Article
Language:English
Published: Elsevier Inc 01-07-2017
Elsevier
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Summary:Vehicle clustering is an efficient approach to improve the scalability of networking protocols in vehicular ad-hoc networks (VANETs). However, some characteristics, like highly dynamic topology and intermittent connections, may affect the performance of the clustering. Establishing and maintaining stable clusters is becoming one of big challenging issues in VANETs. Recent years' researches prove that mobility metric based clustering schemes show better performance in improving cluster stability. Mobility metrics, including moving direction, vehicle density, relative velocity and relative distance, etc., are more suitable for VANETs instead of the received radio strength (RSS) and identifier number metrics, which are applied for MANETs clustering. In this paper, a new dynamic mobility-based and stability-based clustering scheme is introduced for urban city scenario. The proposed scheme applies vehicle's moving direction, relative position and link lifetime estimation. We compared the performance of our scheme with Lowest-ID and the most recent and the most cited clustering algorithm VMaSC in terms of cluster head duration, cluster member duration, number of clusters, cluster head change rate and number of state changes. The extensive simulation results showed that our proposed scheme shows a better stability performance.
ISSN:2214-2096
2214-210X
DOI:10.1016/j.vehcom.2016.12.003