Multi-criteria based stable clustering technique for vehicular ad-hoc networks.

Vehicular Ad-hoc Network (VANET) plays an important role in the realization of the Intelligent Transportation System (ITS) which leads to a plethora of new applications such as traffic/drivers safety, traffic management, and infotainment. However, the high mobility and dense distribution of the vehicles on the road cause problems for routes management and network scalability. These issues can be effectively resolved by employing clustering techniques which not only supports scalability of network thereby eradicating broadcast storms caused by packets flooding but also simplifies medium access control. Despite its numerous advantages, cluster formation and sustainability of clusters in high mobility scenarios is one of the major challenges in VANETs. To improve stability of the cluster, efficient cluster head selection in accordance with the various traits of VANETs among candidate vehicles is desired. In this paper, a Multi Criteria based Stable Clustering technique (MCSC) for VANETs is proposed. The proposed MCSC technique includes a novel feature of average Past Cluster head Lifetime (PCL) along with relative speed, distance and degree of connectivity for efficient selection of Cluster Head (CH) and elects Substitute Cluster Head (SCH) to maintain the stability of cluster structures. Apart from CH selection, cluster formation, maintenance and clusters merging features are also incorporated. A simulation based performance evaluation is conducted to evaluate efficacy of the proposed technique through different parameters and benchmarking with state-of-the-art. Demonstrated by simulation results, the proposed MCSC technique outperforms existing clustering techniques in VANETs with respect to key stability indicators. Specifically, MCSC improves the cluster-head and cluster-member lifetimes by approximately 16% and 14.5%, respectively, compared to existing approaches. Furthermore, the proposed technique reduces the re-clustering rate by about 13%, indicating enhanced cluster stability under dynamic vehicular conditions.