电子学报2024，Vol.52Issue(2)：385-395,11.DOI:10.12263/DZXB.20220922
基于Q学习的蜂窝车联网边缘计算系统PC-5/Uu接口联合卸载策略
Q-Learning Based Joint PC-5/Uu Offloading Strategy for C-V2X Based Vehicular Edge Computing System
摘要
Abstract
Intelligent transportation services,such as smart driving,put forward high requirements for latency.When the vehicle itself has insufficient computing power,the vehicle needs the surrounding vehicles and roadside edge computing units to help it complete the task computation.In this paper,based on the existing vehicular edge computing(VEC)offload-ing strategy,considering the differences between the 5G-NR interface and PC-5 interface link of cellular-V2X(C-V2X)sys-tem,we propose a Q-Learning based joint PC-5/Uu interface edge computing offloading strategy.The successful transmis-sion probability of PC-5 link in C-V2X system is modeled,and then the transmission rate characterization method of PC-5 link is deduced.We formulate a constrained Markov decision process(CMDP)to minimize the system latency,where the objective function is the task processing latency in C-V2X system,and constraints are transmission power at task vehicle and energy consumption of computation at vehicles with edge computing unit.By Lagrangian approach,the CMDP prob-lem is transformed into an equivalent min-max non-constrained MDP problem,and Q-Learning is introduced to design the offloading strategy,and then the offloading strategy of C-V2X based VEC system based on Q-Learning is proposed.Simu-lation results show that compared with other baseline schemes,the proposed algorithm can significantly improve the system latency performance by at least 27.3%.关键词
蜂窝车联网/边缘计算/有约束马尔科夫过程/计算迁移/Q学习Key words
cellular vehicular-to-everything/edge computing/constrained Markov decision process/computation offloading/Q learning分类
信息技术与安全科学引用本文复制引用
冯伟杨,林思雨,冯婧涛,李赟,孔繁鹏,艾渤..基于Q学习的蜂窝车联网边缘计算系统PC-5/Uu接口联合卸载策略[J].电子学报,2024,52(2):385-395,11.基金项目
国家重点研发计划(No.2022YFB3207400) （No.2022YFB3207400）
国家自然科学基金(No.62221001,No.61971030) （No.62221001,No.61971030）
中国国家铁路集团有限公司科技研究开发计划资助项目(No.P2021S005) National Key Research and Development Program of China(No.2022YFB3207400) （No.P2021S005）
National Natural Science Foundation of China(No.62221001,No.61971030) （No.62221001,No.61971030）
China National Railway Group Co.,Ltd.Science and Technology Research and Development Plan(No.P2021S005) （No.P2021S005）
