IMFOCA-IOV: Intelligent Moth Flame Optimization based Clustering Algorithm for Internet of Vehicle

Intelligent transportation systems (ITS) are receiving much attention today because of their significant effect on transportation safety, efficiency, and convenience. The Vehicle ad hoc networks (VANETs) in the ITS network are enhanced through the Internet of Vehicles (IOV), a continuation of the Internet of Things (IoT). In the IOV paradigm, the network's topology is extremely dynamic, and data is transmitted using 5G cellular communication. This work proposes an intelligent moth flame optimization-based clustering algorithm (IMFOCA) for the IOVs (IMFOCA-IOV). The IMFOCA-IOV algorithm provides maximum coverage for the IOV node with minimum cluster heads (CHs) required for routing. Simulation results are delivered to confirm that the IMFOCA-IOV algorithm can decrease the power consumption of IOV. The proposed IMFOCA-IOV algorithm performed better than CACONET, GWOCNET CLPSO, and MOPSO algorithms regarding the number of clusters and transmission range.