Secrecy-Driven Resource Management for Vehicular Computation Offloading Networks

Abstract

The growing developments in vehicular networks and vehicular Internet services have yielded a variety of computation-intensive applications, resulting in great pressure on vehicles equipped with limited computation resources. The cloud/ edge-based service, which enables in-motion vehicles to actively offload computation tasks to cloud/ edge servers, has provided a promising approach to address the intensive computation burden. However, due to the possibility of disclosing private data, offloading computation tasks suffers from potential eavesdropping attacks. In this article, we focus on the eavesdropping attack when vehicular users (VUs) deliver computation tasks to cloud/edge servers over radio frequency channels. We take the tool of physical layer security and investigate resource management for secrecy provisioning when the VUs offload computation tasks. We then discuss three promising technologies, including non-orthogonal multiple access, multi-access assisted computation offloading, and mobility- and delay-aware offloading, which facilitate the enhancement of secrecy against the eavesdropping attack. Finally, as a detailed example of the multi-access assisted computation offloading, we present a case study on the optimal dual-connectivity- assisted computation task offloading with secrecy provisioning and show the performance of the proposed computation offloading.