A trust-based clustering approach to form stable clusters in vehicular ad hoc networks

Over the last two decades, vehicular ad hoc networks (VANETs) have evolved to disseminate real-time traffic information, emergency information, and multimedia data to vehicles on highways and urban roads. Due to vehicles’ high-speed mobility, the topology in VANETs changes dynamically and causes instability in networks. It further degrades the performance of vehicular applications and consumes network resources. Clustering is one of the approaches in VANETs that is utilized to achieve stability. This paper proposes a Trust-based Stable Clustering (TSC) approach to form stable clusters in VANETs. This approach encompasses a significant cluster head election, cluster joining, and cluster leaving algorithms. The cluster head election algorithm forms stable clusters based on several parameters such as vehicles’ trust value, degree, position, remaining travel time, and speed. The cluster joining and cluster leaving algorithms improve the stability of formed clusters by reducing the cluster reformation frequency and selecting alternate cluster heads. The performance of the TSC is compared with the well-known clustering methods on different parameters such as average cluster head duration, number of state changes, and number of cluster formation messages. The results show that the TSC outperforms than the compared approaches.