Energy Consumption Aware Route Discovery using Improved Ant Colony Optimization in UAVs Guided VANETs

This article investigates about the effective energy and routing based optimization for Unmanned Aerial Vehicles (UAVs) assisted VANETs. Specifically, we solve the optimization based issues in the network and as well to achieve the cost-efficient communication model in UAVs assisted VANETs communication. The main negatives include increased UAV energy consumption, heavy road vehicle traffic, and significant information delay. To overcome this drawback in this article Energy Consumption Aware Route Discovery using Improved Ant Colony Optimization (ECRIA-UAVs) is proposed. The main categories of this method are effective system model, energy model and improved ant optimization. In the system and energy model section the localization of both the vehicles, road side units (RSUs) and UAVs are effectively performed and as well the energy is properly allocated among the vehicles. The upgraded ant optimization technique transmits data with optimum solutions, resulting in high-quality communication. The experimental simulation is done in NS3 with SUMO, and the parameters to analyze are packet delivery ratio, computational delay, computational overhead, and throughput. TOCA-UAVs and JDTO-UAVs are used for comparison. The installation findings show that ECRIA-UAVs had a 20% higher packet delivery ratio and 100 kbps greater throughput than previous techniques.