Research Area:  Vehicular Ad Hoc Networks
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 vehicles 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.
Author(s) Name:  MengyingRenaLyes Khoukhi,Houda Labiod,Jun Zhang and Véronique Vèque
Journal name:  Vehicular Communications
Publisher name:  ELSEVIER
Volume Information:  Volume 9, July 2017, Pages 233-241
Paper Link:   https://www.sciencedirect.com/science/article/abs/pii/S2214209616300699