An enhanced whale optimization algorithm for vehicular communication networks

Abstract

SummaryIn the field of vehicle communication networks, vehicular ad hoc network (VANET) is established with the help of road side unit (RSU). Each vehicle in the traffic system is managed by RSU with certain mobility factor, but still, there are some issues in the mobility management. In order to avoid such expensive RSUs and to enhance the mobility management of VANET system, the paper proposes a novel algorithm for the process of organizing a cluster structure and cluster head (CH) election suitable for VANETs. The proposed adaptive weighted clustering protocol (AWCP) groups the random nodes, and then the optimal CH is attained by the optimization of network parameters. For the purpose of optimization, an innovative algorithm called the enhanced whale optimization algorithm (EWOA) is introduced. For each vehicle in a trusted clustering model, its movement is analyzed by vehicle network mobility routing protocol with identified speed and position. The distance between the trusted vehicle node and RSU is analyzed by the proposed AWCP‐EWOA model. The results demonstrate the proposed AWCP‐EWOA model outperforms compared with AWCP and AWCP‐Whale Algorithm (WA) protocols in terms of clustering efficiency and its mobility enhancement.