COA -Based on Stable Clustering Algorithm for VANET Using MATLAB

Vehicular Ad Hoc Networks (VANETs) play a pivotal role in advancing road safety and intelligent transportation systems. This study introduces a novel approach to the designation of cluster heads (CH) in VANETs, utilizing the Coati Optimization Algorithm (COA). Inspired by coati behavior, COA strategically balances exploration and exploitation through two distinct phases-mimicking prey attacks and predator escapes. The proposed algorithm incorporates energy efficiency and distance metrics, contributing to improved VANET performance by minimizing latency and enhancing energy efficiency. Key parameters such as vehicle speed, CH stability, service quality, reachability, and signal strength are considered during the CH selection process. Guided by COA, the optimization process aims to identify optimal CHs for specific road segments, facilitating efficient cluster formation and thereby improving data transmission. Simulation results underscore the superiority of COA over traditional clustering methods, highlighting its potential as a promising solution for creating safer and more efficient vehicular communication systems within VANET applications.