A Comprehensive Review of Computing Paradigms, enabling Computation Offloading and Task Execution in Vehicular Networks

Abstract

Road safety, optimized traffic management, and passenger comfort have always been the primary goals of the vehicle networking research community. Advances in computer and communication technology have made the dream of modern intelligent vehicles a reality through the use of smart sensors, cameras, networking devices, and storage capabilities. Autonomous operation of modern intelligent vehicles requires massive computations where tasks are outsourced. The research community has proposed various computing paradigms: mobile cloud computing, vehicle cloud computing, multi-access edge computing, vehicle edge computing, vehicle fog computing, and voluntary computing-based VANET (VCBV) to move computational power close to the user and handle the delay-sensitive applications of modern intelligent vehicles. In this study, we have provided a comprehensive overview of all computing paradigms related to vehicular networks. We have presented the architectural details, similarities, differences, and key features of each computing paradigm. Finally, we concluded the study with open research challenges in vehicular networks.