Task offloading for edge-IoV networks in the industry 4.0 era and beyond: A high-level view

Abstract

As a promising platform on the Internet of Things (IoT), the smart Internet of Vehicle (IoV) has emerged with the advent of the key connectivity to Industry 4.0, i.e. Fifth-Generation Mobile Communication (5G). However, problems with adequate battery life, powerful computing, and energy economy have hampered the development of this technology in light of the enormous increase in data traffic in 5G and 6G mobile communication networks. To address these limitations, this study proposes an Internet of Vehicles (IoV) system empowered by Edge Computing (EC), wherein intelligent vehicle nodes interact with an anchor node integrated with an EC server for data upload and download. Rather than solely focusing on enhancing the central cloud infrastructure, the integration of EC and IoT enables real-time and efficient services, thereby bolstering the storage and processing capabilities of underlying networks. By employing an offloading strategy within the Edge Computing-based Internet of Vehicles (EC-IoV) framework, users can allocate their workloads to suitable EC servers, leading to improved resource management and computational capabilities. However, challenges persist in evaluating the impact of uncertain user-EC server connectivity on offloading decision-making and mitigating potential declines in offloading efficiency.