Clustering Algorithms and Comparisons in Vehicular Ad Hoc Networks

Abstract

Vehicular Ad hoc Network (VANET) is a new era in the transmission of dynamic information across communities. Intelligent Transportation Systems is only one of the many applications for VANET (ITS). The topology of VANET is extremely dynamic, and connections are irregular. These features cause information transmission in the VANET to be unreliable. Vehicle clustering is a successful strategy to increase the network's scalability and connection dependability. Characteristics of the VANET have an impact on clustering performance as well. An extensive explanation of VANET clustering algorithms is given in this article. A complete evaluation of clustering in VANETs is provided based on the clustering procedure. Most methods examine the clustering process in terms of Cluster Head selection metrics, formation, and its maintenance. The clustering methods are contrasted based on factors such as stability, convergence, overhead, and latency. There is also discussion of some of the most typical issues and the solutions used. Also, a summary of the performance metrics used to assess clustering algorithms is provided.