Enhanced Ant Colony Optimization with Dynamic Evaporation Rate (EACO-DE): An Intelligent Congestion Control System in IoV Environment

Internet of Vehicle (IoV) is a combined form of Internet of Things (IoT) and Vehicular Ad-hoc Network (VANET). Its fundamental goal is to increase the service quality of Intelligent Transportation System (ITS). The dynamic nature of IoV such as high dynamic topology, high mobility of vehicles, etc. are some of the factors that causes more congestion thus reducing the efficiency of routing. Many algorithms were designed to obtain the shortest path from the source to the destination. Choosing of Ant Colony Optimization (ACO) algorithm is one of the best ways to obtain the shortest path. In this paper, an Enhanced Ant Colony Optimization with Dynamic Evaporation rate (EACODE) algorithm is proposed to obtain the congestion-free optimized path which reduces the travel time, travel cost and traffic problems. Instead of fixed evaporation rate, it dynamic predicts the pheromone evaporation rate with the help of run time metrics to avoid the congested paths thus improving the efficiency of the travel. The simulation results show that the proposed EACO-DE algorithm improves the efficiency of the routing compared with primitive Ant Colony Optimization (ACO) algorithm and Enhanced Hybrid Ant Colony Optimization Routing Protocol (EHACORP) under various performance metrics.