Dependency-Aware Vehicular Task Scheduling Policy for Tracking Service VEC Networks

doi:10.1109/TIV.2022.3224057

	Dependency-Aware Vehicular Task Scheduling Policy for Tracking Service VEC Networks
	Li, Chao 2; Liu, Fagui 1,2; Wang, Bin 1; Chen, C. L. Philip 2,3; Tang, Xuhao 2; Jiang, Jun 2; Liu, Jie 2
刊名	IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
	2023-03-01
卷号	8 期号:3 页码:2400-2414
关键词	Task analysis Intelligent vehicles Optimization Processor scheduling Vehicle dynamics Heuristic algorithms Costs Deep reinforcement learning (DRL) scheduling policy tracking service vehicular edge computing (VEC)
ISSN号	2379-8858
DOI	10.1109/TIV.2022.3224057
通讯作者	Liu, Fagui(fgliu@scut.edu.cn) ; Wang, Bin(wangb02@pcl.ac.cn)
英文摘要	In this paper, we study a tracking service vehicular edge computing (VEC) network that provides computation offloading service for Intelligent vehicles, where computational tasks with different urgency and dependency are required to be completed efficiently within strict time constraints. We consider the actual scenario where the environmental parameters fluctuate randomly and their distributions are unknown, thus, a long-term scheduling policy optimization problem needs to be solved. For this motivation, we first define a queueing criterion to sort the subtasks into a scheduling queue, and then model a specific Markov decision process (MDP) according to the scheduling queue. Furthermore, we propose our vehicular task scheduling policy optimizing (VTSPO) algorithm based on the most advanced policy-based deep reinforcement learning (DRL). The experimental results compared with known value-based DRL algorithms verify the advantages of the proposed VTSPO algorithm.
资助项目	Guangdong Major Project of Basic and Applied Basic Research[2019B030302002] ; Science and Technology Major Project of Guangzhou[202007030006] ; Major Key Project of PCL[PCL2021A09] ; Science and Technology Project of Guangdong Province[2021B1111600001] ; Engineering and Technology Research Center of Guangdong Province for Logistics Supply Chain and Internet of Things[GDDST[2016]176]
WOS关键词	EDGE ; VEHICLES
WOS研究方向	Computer Science ; Engineering ; Transportation
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000981348100034
资助机构	Guangdong Major Project of Basic and Applied Basic Research ; Science and Technology Major Project of Guangzhou ; Major Key Project of PCL ; Science and Technology Project of Guangdong Province ; Engineering and Technology Research Center of Guangdong Province for Logistics Supply Chain and Internet of Things
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/53335]
专题	离退休人员
通讯作者	Liu, Fagui; Wang, Bin
作者单位	1.Peng Cheng Lab, Cyberspace Secur Res Ctr, Shenzhen 518066, Peoples R China 2.South China Univ Technol, Sch Comp Sci & Engn, Guangzhou 510006, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Li, Chao,Liu, Fagui,Wang, Bin,et al. Dependency-Aware Vehicular Task Scheduling Policy for Tracking Service VEC Networks[J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,2023,8(3):2400-2414.
APA	Li, Chao.,Liu, Fagui.,Wang, Bin.,Chen, C. L. Philip.,Tang, Xuhao.,...&Liu, Jie.(2023).Dependency-Aware Vehicular Task Scheduling Policy for Tracking Service VEC Networks.IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,8(3),2400-2414.
MLA	Li, Chao,et al."Dependency-Aware Vehicular Task Scheduling Policy for Tracking Service VEC Networks".IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 8.3(2023):2400-2414.