Multi-Access Edge Offloading Based on Physical Layer Security in C-V2X System

Due to the gap between calculation-intensive and latency-sensitive features of self-driving tasks and the vehicle's limited computation and storage resources, the development of autonomous vehicles is situated in a bottleneck. Fortunately, multi-access edge computing (MEC) architecture offers a promising measure to bridge this gap. It brings resources proximity to mobile devices at the network edge to support task offloading. Nonetheless, it introduces the problem of insecure wireless communication. Beyond that, the autonomous vehicle also has strict requirements on latency and energy consumption of task offloading technique owing to its safety-related and electricity-driven characteristics. Many scholars have studied the related problems widely. Nevertheless, few papers combine these three significant factors, namely information security, task latency and energy consumption. Thus, we put forward a mobility-ware task offloading scheme in cellular vehicle-to-everything system, which carefully considers these three requirements together. In this scheme, a time approximation algorithm is proposed to tackle the channel condition variations caused by the vehicle movement. Small-cell base station proactively sends artificial noise to debase wiretapper decoding capability and further prevent data exchanged between vehicles and MEC from being eavesdropped at the physical layer. Moreover, the optimal offloading proportion is found to minimize the weighted sum of latency and energy consumption. Experimental performances validate the effectiveness and feasibility of the proposed task offloading scheme.