Dynamic Task Offloading in Urban Saudi Arabia: Enhancing Vehicular Services through Edge Computing

Abstract

Effective task-offloading strategies become of paramount importance in the urban context, complementing the rapid developments and improvements being made in vehicular technologies to service delivery and customer experience. This paper reviews some challenges and solutions regarding the offloading of vehicular services in realistic urban scenarios while focusing on the peculiar characteristics of the cities in Saudi Arabia. In this paper, we investigate the ability of VEC to save computation resources by offloading computation-intensive tasks from vehicles to proximate edge servers. A general framework considers multiple factors, including vehicles' mobility, network latency, and resource availability, that lead to a dynamic task-offloading model with the goal of low delay and energy consumption while guaranteeing good service quality. We show the performance of our model using simulations emulating urban traffic in Saudi Arabia. We develop continuous connectivity and efficient task processing even at high vehicle mobility. In this way, the research work can contribute to enhancing smart transportation systems in Saudi Arabia by improving vehicular services and solutions to handle urban mobility