Optimization of Vehicular Edge Computing Under Time-Varying Fading Channels With Path Prediction

doi:10.1109/JIOT.2024.3488193

	Optimization of Vehicular Edge Computing Under Time-Varying Fading Channels With Path Prediction
	Hu, Dieli 1,2,3; Yuan, Mingang 1; Huang, Gaofei 1; Zhao, Sai 1; Tang, Dong 1
	2025-03-01
发表期刊	IEEE INTERNET OF THINGS JOURNAL
ISSN	2327-4662
卷号	12 期号:5 页码:5500-5514
摘要	This article studies the design of vehicular edge computing networks (VECNs) with multiple moving vehicles and roadside units (RSUs). Uniquely, our study reflects a pragmatic situation where wireless channels are time-varying in the duration of task offloading and vehicles can travel with inconstant speeds in a real-world scenario. By jointly optimizing transmit power and time allocation for task offloading as well as computation task partition in the VECN, our goal is to minimize the cost at the vehicles for energy consumption on task offloading and computing, and rent on task computing service at RSUs. However, solving the formulated optimization problem directly is impossible due to the requirement of noncausal vehicular position information (VPI) and noncausal channel state information (CSI) between vehicles and RSUs. To address this issue, a path prediction model is adopted to predict the noncausal VPI, based on which the noncausal CSI can be estimated. Then, a novel receding horizon optimization method is proposed to transform the original problem into a sequence of tractable problems. Despite this, the problems remain complex due to the computationally prohibitive task of identifying the optimal task offloading duration at each vehicle in a centralized manner. To overcome this difficulty, the consensus alternating directions method of multipliers is proposed to solve the problem in a distributed manner with low computational complexity. Numerical results show that our proposed scheme can save at most 30% of monetary cost as compared with existing baseline schemes.
关键词	Wireless communication Costs Optimization Fading channels Resource management Servers Delays Wireless sensor networks Internet of Things Vehicle-to-infrastructure Mobile edge computing path prediction task offloading time-varying channels vehicular network
DOI	10.1109/JIOT.2024.3488193
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2023YFB4502805] ; National Natural Science Foundation of China[62072440] ; Beijing Natural Science Foundation[L221004]
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:001433294700042
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/40707
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Tang, Dong
作者单位	1.GuangZhou Univ, Sch Elect & Commun Engn, Guangzhou 511370, Peoples R China 2.Peng Cheng Lab, Dept Networked Intelligence, Shenzhen 518066, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, State Key Lab Processors, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Hu, Dieli,Yuan, Mingang,Huang, Gaofei,et al. Optimization of Vehicular Edge Computing Under Time-Varying Fading Channels With Path Prediction[J]. IEEE INTERNET OF THINGS JOURNAL,2025,12(5):5500-5514.
APA	Hu, Dieli,Yuan, Mingang,Huang, Gaofei,Zhao, Sai,&Tang, Dong.(2025).Optimization of Vehicular Edge Computing Under Time-Varying Fading Channels With Path Prediction.IEEE INTERNET OF THINGS JOURNAL,12(5),5500-5514.
MLA	Hu, Dieli,et al."Optimization of Vehicular Edge Computing Under Time-Varying Fading Channels With Path Prediction".IEEE INTERNET OF THINGS JOURNAL 12.5(2025):5500-5514.