A Mobility-Based Double-Head Clustering Algorithm for Dynamic VANET

Abstract

Vehicular Ad Hoc Network (VANET) is a promising technology that still faces many challenges such as scalability and the highly dynamic topology. An effective VANET clustering algorithm significantly relieves the effect of these challenges. In this paper, we propose a double-head clustering (DHC) algorithm for VANETs. Our proposed approach is a mobility-based clustering algorithm that exploits the most relevant mobility metrics such as vehicles' speed, position and direction, in addition to other metrics related to the communication link quality in order to achieve stable clusters. We compare the proposed algorithm against existing clustering algorithms using different evaluation metrics under dynamic and static mobility scenarios. The proposed algorithm proves its stability and efficiency under different mobility scenarios.