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<p>Vehicular Ad Hoc Networks (VANETs) require efficient routing protocols to ensure reliable communication in highly dynamic environments. This paper proposes a hybrid routing protocol that integrates Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) algorithms to determine optimal communication path between vehicles. The hybrid PSO-GWO approach combines the rapid convergence ability of PSO with the superior exploration and exploitation characteristics of GWO, leads to optimum route selection. The proposed model involves multiple performance metrics such as Round Trip Time (RTT), hop count, and path loss in the fitness function evaluation to enhance route selection decisions. Simulation results demonstrate that the hybrid PSO-GWO algorithm achieves a 12.3% higher Packet Delivery Ratio (PDR), a 12.3% increase in throughput, and a 12.9% reduction in End-to-End (E2E) Delay compared with the best-performing multimeric PSO algorithm. These outcomes validate the proposed algorithm’s effectiveness in improving optimal route selection and ensuring Quality of Service (QoS) in dynamic vehicular environments.</p>

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Multimetric Hybrid PSO-GWO Algorithm for Optimum Route Selection in VANETs

  • 期刊论文

  • 发表日期：

    2026年1月12日

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  • Mahabub Subhani Pathan,
  • K. Annapurna

摘要

Vehicular Ad Hoc Networks (VANETs) require efficient routing protocols to ensure reliable communication in highly dynamic environments. This paper proposes a hybrid routing protocol that integrates Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) algorithms to determine optimal communication path between vehicles. The hybrid PSO-GWO approach combines the rapid convergence ability of PSO with the superior exploration and exploitation characteristics of GWO, leads to optimum route selection. The proposed model involves multiple performance metrics such as Round Trip Time (RTT), hop count, and path loss in the fitness function evaluation to enhance route selection decisions. Simulation results demonstrate that the hybrid PSO-GWO algorithm achieves a 12.3% higher Packet Delivery Ratio (PDR), a 12.3% increase in throughput, and a 12.9% reduction in End-to-End (E2E) Delay compared with the best-performing multimeric PSO algorithm. These outcomes validate the proposed algorithm’s effectiveness in improving optimal route selection and ensuring Quality of Service (QoS) in dynamic vehicular environments.