Efficient Routing Using Improved Ant Colony Optimization for Vehicular Communication in Urban Scenarios

VANET is crucial for the progress of smart city transportation, allowing immediate communication between vehicles. However, the dynamic and fast-changing nature of VANETs presents significant challenges in routing efficiency. This paper introduces an Enhanced Routing with Improved Ant Colony Optimization (ERIACO) Approach to address these challenges. ERIACO leverages ACO for optimal route discovery, adapting to the dynamic network topology. Additionally, the approach incorporates Effective Link Prediction to preemptively manage potential link failures, enhancing network reliability. Through comprehensive ns3 network simulations, the performance of the ERIACO is assessed according to essential metrics including data delivery ratio, network throughput, routing overhead, energy efficiency, and energy consumption. Comparative analysis with existing methods, including IORDM, ITDMP, and OPRPW, demonstrates the superior efficiency and effectiveness of ERIACO in VANET environments. The results showcase that ERIACO achieves significantly higher data delivery rates, network throughput, and energy efficiency, making it a promising solution for the optimization of VANET routing and communication.