A Proposed Multi -Head Clustering Algorithm for VANET Environments

Vehicular Ad Hoc Networks (VANETs) have the potential to become viable to Intelligent Transportation System (ITS) real-world applications. Vehicles' high mobility along with real-world application scalability are some of the main challenges in this network environment. The various mobility-based characteristics can be exploited by forming clusters of vehicles with similar attributes within the network. Clustering in VANET environments is an approach that converts the network structure from flat into hierarchical by dividing the network into groups of vehicles, called clusters. One of the main requirements for effective VANET clustering is stability given the dynamicity of the environment. This paper presents a multi-head clustering algorithm that utilizes mobility-based metrics to form clusters in a vehicular network. The proposed algorithm assumes that each vehicle can be a member of multiple clusters, thus creating stable clusters that are robust in this environment. Several simulations are carried out to test the algorithm's effectiveness under different scenarios. The proposed algorithm is also compared against a previously presented algorithm, called Double-Head Clustering Algorithm. The performance evaluation is based on metrics regarding the clusters' lifetime. The results outline that the presented algorithm outperforms the clustering algorithm of the bibliography both in cluster stability and cluster size.