Enhancing Vehicular Service Allocation with MEC Dynamic Task Offloading in a Dammam District Using CloudSim-SUMO

The current paper therefore discusses the significance of effective task-offloading strategies especially in an urban environment due to the evolution of means to boost both service provision and customer satisfaction. More precisely, we look into issues and opportunities in offloading vehicular services in realistic urban conditions with more reference to cities of Saudi Arabia. The research explores the application of VEC through using MEC strategies in that helps to offload computationally intensive tasks from the vehicles to the edge servers minimising resource consumption. By considering some of the important factors such as movement of vehicles, network delay and load, we present a dynamic task-offloading model that seeks to reduce delay times and energy usage while at the same time offering high service quality. The efficiency of the model is established through CloudSim-SUMO simulations comparing actual and simulated traffic in the Dammam District. We have established constant connectedness and effective task execution even with a highly mobile vehicle environment. This work is useful in developing the smart transport systems of Saudi Arabia by adding solutions that improve vehicular services and solve issues associated with ITS.