A Novel Technique of Odịgbo Metaheuristic Algorithm Based Optimized Energy Efficient and Reliable Routing Protocol for VANETs to Augment QoS Conditions

Vehicular Ad Hoc Networks (VANETs) play a critical role in enabling real-time vehicle-to-vehicle (V2V) communication for intelligent transportation systems, supporting applications such as traffic management, navigation, and road safety. However, VANETs face significant challenges due to dynamic topology, high mobility, and varying traffic densities, which hinder reliable, energy-efficient, and QoS-aware routing. To address these issues, this paper proposes a novel hybrid routing framework based on the Ọdịgbo Metaheuristic Optimization Algorithm (OMOA). The proposed protocol integrates metaheuristic optimization, machine learning-based route scoring, and probabilistic filtering to enhance routing efficiency and reliability. Specifically, the model combines a Modified Extreme Learning Algorithm (M-ELA) with a Random Forest classifier to enable intelligent route prediction and prioritization. A Bloom Filter is employed to suppress redundant transmissions and improve communication efficiency. OMOA dynamically fine-tunes routing parameters by iteratively refining a population of candidate cluster head (CH) configurations using directional learning and adaptive exploration. The optimization process is guided by a multi-objective fitness function that considers residual energy, distance to sink, intra-cluster distance, and node connectivity, ensuring both optimal CH and route selection. The novelty of this work lies in its unified approach to both CH and route selection under a single optimization framework, significantly improving adaptability in highly dynamic VANET environments. Extensive simulations conducted under diverse mobility and traffic conditions demonstrate that the proposed protocol achieves higher packet delivery ratio, reduced end-to-end delay, balanced energy consumption, and prolonged network lifetime compared to traditional protocols. These results validate the proposed model as an effective and scalable solution for energy-efficient, QoS-compliant routing in next-generation VANET deployments.