A Betweenness Centrality Based Clustering in VANETs

A vehicular communication system in smart cities is critical. For vehicular ad hoc networks (VANETs), scalability and routing reliability are important challenges. Clustering can help to overcome these challenges. The network may seem smaller and more stable with a clustered architecture; however, because of the rapid mobility of the vehicles, the clustering can be unstable. The network's stability depends upon the suitable cluster head (CH) selection and maintaining a CH over a prolonged period is not easy. A new Betweenness Centrality Based Clustering approach (BCBC) is introduced which aims to increase the clustering stability by using the betweenness centrality method. Using this technique, the most significant vehicle in a cluster is chosen to serve as the CH. The results show the good performance of our proposed in terms of CH lifetime and cluster member lifetime at different transmission ranges, as well as its superiority over the most used techniques in the literature.