高技术通讯2026，Vol.36Issue(4)：364-373,10.DOI:10.3772/j.issn.1002-0470.2026.04.004
车联网边缘计算中的多跳任务卸载决策
Multi-hop task offloading decision in edge computing for Internet of Vehicles
摘要
Abstract
In Internet of Vehicle(IoV)edge computing offloading system,multi-hop offloading enables tasks to be off-loaded to vehicles outside the coverage area of road-side unit(RSU),effectively utilizing the computational re-sources of idle vehicles.However,the high-speed mobility of vehicles poses challenges to maintaining stability be-tween nodes.This paper proposes a centralized dynamic multi-hop offloading strategy based on the A*algorithm.The strategy aims to minimize task delay by modeling the problem as a Markov decision process(MDP).The A*algorithm is employed to determine the optimal task offloading queue for vehicles,and the proximal policy optimiza-tion(PPO)algorithm is utilized for problem-solving.Simulation results show that,compared with deep Q-learning and greedy strategies,the proposed method significantly improves task completion rates and reduces average delay by approximately 30％.关键词
车联网/移动边缘计算/集中式动态多跳卸载/近端策略优化算法Key words
Internet of Vehicle/mobile edge computing/centralized dynamic multi-hop offloading/proximal policy optimization algorithm引用本文复制引用
李亚,张原,王卫岗,郭一枫..车联网边缘计算中的多跳任务卸载决策[J].高技术通讯,2026,36(4):364-373,10.基金项目
河南省科技攻关(242102210201),河南省高校基本科研业务费专项资金(NSFRF240629)和河南理工大学博士基金(B2018-39)资助项目. （242102210201）
