SOMACA: A New Swarm Optimization-Based and Mobility-Aware Clustering Approach for the Internet of Vehicles

The Internet of Vehicles (IoV) has evolved from the classic Vehicular Ad-hoc NETworks (VANETs) as a result emergence Things (IoT). IoV is used for communication among vehicles in real-time with their drivers, other vehicles, pedestrians, fleet management systems, and roadside infrastructure. High vehicular speeds frequent network topology changes make vehicle extremely difficult on network. More constraints are imposed performance huge environment due to road conditions enormous quantity vehicles. A promising approach improve through clustering. Minimizing number clusters identifying reliable Cluster head (CH) some most challenging tasks. In this paper, we propose Swarm optimization-based mobility-aware clustering method termed SOMACA. SOMACA consists two phases phase routing phase. During phase, combine mobility measures cluster distance generate minimum having stable CHs employ Sparrow Search algorithm (SSA) CH selection. steps (1) Route Formation (2) Upkeep. main target route formation step build secure path between nodes base station (BS) by establishing an optimal list links that ordered high low, each round, it selects best one. Moreover, Upkeep aims update maintain existing connection. assessed using simulation experiments various metrics including average lifetime, transmission range, grid size. results show reduces $42\%, 48\%, 47\%, 9\%$ , 22%,31%, 16%, 43% less than CAVDO, GOA, GWOCNET, MFCA-IOV, MOGA-AWCP, HHOCNET, AMONE, p-WOA algorithms respectively when ranges vary 200 500. increases lifetime notation="LaTeX">$11\%, 12\%, 9\%, 6\%$ 7%, 9%, 3%, 13% longer mentioned above compared algorithms, respectively.