Enabling Intelligent Mobility: A Survey of Vehicular Edge Computing and Task Offloading

Abstract

A new technology called vehicular edge computing (VEC) has the potential to revolutionize vehicular networks by harnessing the compute power of edge servers and nearby vehicles. Task offloading is a crucial mechanism within VEC for transferring computational tasks from the onboard resources of the vehicles to edge servers or peer vehicles. A number of task offloading strategies are discussed and categorized in this paper, from local, edge, and V2V offloading to collaborative, V2I, and V2V offloading. Following that, this study examines a variety of offloading techniques, including machine learning-based offloading and optimization algorithms. Besides mobility dynamics, resource management, security, privacy, and scalability considerations, the survey also focuses on the multifaceted challenges associated with VEC. The challenges are analyzed in relation to dynamic vehicular environments. The report also highlights emerging trends in VEC driven by technologies including 5G, IoT, and AI. Researchers, practitioners, and policymakers can gain insight and guidance from this survey on task offloading in virtual environments. Aside from capturing current research, it illuminates future directions, highlighting task offloading's profound impact on the evolution of vehicular edge computing.