Increasing Cluster Stability in VANET by Candidate Cluster Head Nomination Algorithm

Abstract

Abstract A vehicular ad hoc network (VANET) is an extended subtype of a mobile ad hoc network (MANET). VANET has applied the principles of MANET, such as intelligent transport systems (ITS) and road security. However, the vehicles in a VANET must transmit considerable information within a limited time while their mobility is rapid, which causes the instability of VANET. Using clustering methods proposed in many kinds of research can be used to improve routing efficiency and reliability in VANETs, as it enables the grouping of vehicles based on some predefined metrics such as density, velocity, and geographical locations of the vehicles, resulting in a distributed structure of hierarchical network structures. Most of the algorithms explore the selection index, cluster formation, and cluster maintenance of the Cluster Head (CH) in the process of clustering. Therefore, considering the parameter index between nodes and selecting the optimal cluster head to stabilize a VANET environment, improving the routing efficiency of this environment, and reducing message overhead are the key challenges for this research. To help vehicles receive and send road information more quickly and efficiently under the high-speed mobile environment, this study proposes a four-step candidate cluster head nomination algorithm (CCHNA) that enables the formation of fewer clusters and reduces the amount of data transmitted between clusters and among the members within a cluster. The basic idea is to group the vehicles according to some parameter, and then select a proper cluster head to help communicate with other groups. The algorithm also proposed The CH Pruning Stage to reduce the number of CH generated in The CH Nomination Stage by comparing the parameters. The results revealed that the proposed CCHNA can on average, it can reduce 1–3 cluster heads more than other algorithms. During the Cluster Maintenance stage, reducing the message overhead during cluster reorganization, and the number of message exchanges can be reduced by up to 6 times. Therefore, the CCHNA can obtain fewer clusters and considerably reduce communication costs among messages involved in cluster formation.