计算机与现代化Issue(4)：56-62,7.DOI:10.3969/j.issn.1006-2475.2025.04.009
基于A3C的车联网任务卸载和资源分配算法
A3C Based Task Offloading and Resource Allocation Algorithm for Internet of Vehicles
摘要
Abstract
Mobile Edge Computing(MEC),as a new technology,provides a new solution for the application of the Internet of Vehicles.However,the limited resources in the connected vehicle environment cannot meet the needs of the connected vehicle equipment,which leads to an increase in the service response time and execution energy consumption of tasks,which greatly af-fects the Quality of Experience(QoE)of users.In order to reduce the delay and energy consumption of task execution and im-prove the flexibility of algorithm deployment,this paper constructs the networked vehicle system model and proposes an asyn-chronous advantage actor-critic based task offloading and resource allocation strategy.The algorithm framework uses asynchro-nous updating to train the model,and adds time attenuation coefficient to reduce the adverse effect of backward model on global model updating.Experimental results show that the proposed algorithm can effectively improve model training efficiency and re-duce task execution delay and energy consumption.关键词
车联网/边缘计算/任务卸载/资源分配/深度强化学习Key words
Internet of Vehicles/edge computing/task offloading/resource allocation/deep reinforcement learning分类
信息技术与安全科学引用本文复制引用
吴一川..基于A3C的车联网任务卸载和资源分配算法[J].计算机与现代化,2025,(4):56-62,7.基金项目
陕西省科学技术厅一般项目(2023QCY-LL-34,2023QYPY-14) （2023QCY-LL-34,2023QYPY-14）
西安市科技局一般项目(2023JHQCYCK-0030) （2023JHQCYCK-0030）
咸阳市科技局一般项目(L2022-ZDYF-GY-015) （L2022-ZDYF-GY-015）
