SAC-based Computation Offloading and Resource Allocation in Vehicular Edge Computing
Yanlang Zheng, Huan Zhou, Rui Chen, Kai Jiang, Yue Cao
Abstract
The Vehicular Edge Computing (VEC) provides powerful computing resources for intelligent terminals. However, the diversity of computing resources at edge nodes (i.e., edge servers and idle vehicles) and the mobility of vehicles impose great challenges on computation offloading. In this paper, we investigate the joint optimization problem of computation offloading and resource allocation in a cooperative vehicular network by exploiting idle vehicles and Road Side Units (RSUs) equipped with edge servers. In order to minimize the task completion time under latency constraint, a Soft Actor-Critic (SAC)-based algorithm is proposed to solve the problem. The simulation results show that the proposed SAC-based algorithm can effectively reduce the total latency of the system, and its performance is significantly better than other benchmark methods.