MEC架构下基于DDPG的车联网任务卸载和资源分配OACSTPCD

To alleviate the severe task processing delay caused by insufficient computing resources of individual vehicle in the MEC-enabled internet of vehicles,a dynamic joint computation offloading and resource allocation scheme was proposed.With the goal of minimizing the holistic task processing delay in the internet of vehicles,the problem of joint computation offloading and resource allocation was modeled as a Markov decision process(MDP),and then the problem was further solved using a deep deterministic policy gradient(DDPG)algorithm.The simulation results show that compared with the actor-critic(AC)and deep Q-network(DQN)algorithms,the proposed DDPG algorithm attains the holistic task process-ing delay minimum with superior convergence.