Enhancing Performance in Vehicular Ad Hoc Networks: The Optimization Algorithm Perspective

Vehicular Ad Hoc Networks (VANETs) have gained attention for their potential in self-driving cars and traffic services. However, challenges like precise vehicle tracking, network management, high node counts, rapid mobility changes, and disconnections hinder their effectiveness. Protocols play a vital role in VANETs, establishing communication guidelines for reliable data transmission. Adapted protocols enable services like traffic management and autonomous driving support. Nature-inspired algorithms have advanced VANET routing protocols. Optimization algorithms in VANETs provide significant advantages by improving network efficiency, adaptability, resource management, quality of service, and scalability. They have the potential to enhance multiple parameters such as throughput, connectivity, latency, packet delivery ratio, energy efficiency, fairness, and scalability. We present a comparative analysis table featuring optimization algorithms in VANETs, evaluated across various parameters, serving as a guide for making informed selections based on suitability and credibility. This research entails a meticulous comparative analysis of optimization algorithms in VANETs, focusing on diverse metrics and network characteristics. It introduces a novel approach that incorporates quality of service (QoS) considerations. The study examines convergence, complexity, and computational challenges, leading to enhanced VANET performance and reliability.