Efficient Congestion Mitigation Using Adaptive Load Balancing for Vehicular Ad Hoc Networks
TL;DR
Simulations indicate the proposed approach improves overall performance over existing load‐balancing approaches by reducing processing delays, minimizing network congestion, and minimizing resource utilization.
Abstract
It is vitally important for intelligent transportation systems (ITS) to make use of vehicular ad hoc networks (VANETs) to improve road safety, traffic management, and communication. The mobility of vehicles and dynamic traffic conditions continue to pose challenges to network congestion. In this paper, we suggest a load‐balancing strategy for reducing network congestion through the optimization of control packet overhead and the enhancement of data dissemination between roadside units (RSUs) and vehicles. As part of the proposed methodology, real‐time traffic conditions, predictive modeling, and intelligent routing algorithms are incorporated to achieve an efficient load distribution among vehicular nodes. Urban VANETs can use the framework to measure performance metrics like packet delivery ratios (PDRs) and energy consumption (EC). Simulations indicate the proposed approach improves overall performance over existing load‐balancing approaches by reducing processing delays, minimizing network congestion, and minimizing resource utilization. Network operations need to optimize control packet overhead to achieve a balance between communication efficiency and network stability.