Traffic-Aware Task Offloading Based on Convergence of Communication and Sensing in Vehicular Edge Computing

doi:10.1109/JIOT.2021.3083065

	Traffic-Aware Task Offloading Based on Convergence of Communication and Sensing in Vehicular Edge Computing
	Qi, Yanli 2,3; Zhou, Yiqing 2,3; Liu, Ya-Feng 4; Liu, Ling 2,3; Pan, Zhengang 1
刊名	IEEE INTERNET OF THINGS JOURNAL
	2021-12-15
卷号	8 期号:24 页码:17762-17777
关键词	Task analysis Sensors Servers Wireless sensor networks Wireless communication Data communication Cameras Convergence of communication and sensing overall response time (ORT) traffic-aware task offloading vehicular network
ISSN号	2327-4662
DOI	10.1109/JIOT.2021.3083065
英文摘要	With the explosive growth of computation-intensive and latency-sensitive vehicular applications, limited on-board computing resources can hardly satisfy these heterogeneous requirements and task offloading becomes a potential solution. However, task offloading in vehicular networks may face the dilemma of unaffordable uploading time caused by the huge amount of uploading traffic. Therefore, considering the applications which use the environmental data as their input, the sensing abilities of serving nodes (SNs) are exploited and a traffic-aware task offloading (TATO) mechanism based on convergence of communication and sensing is proposed. In the TATO mechanism, a task vehicle can adaptively upload the input data to some SNs and transmit the computation instructions to others which use the environmental data sensed by themselves as input. The objective is to minimize the overall response time (ORT) by jointly optimizing the task and wireless bandwidth ratios. Next, a binary search and feasibility check (BSFC) algorithm is designed to solve the optimization problem. Simulation results demonstrate the effectiveness of the proposed BSFC algorithm and show that the TATO mechanism always outperforms the benchmark mechanisms (i.e., communication-based offloading and sensing-based offloading) in terms of the ORT. Specifically, when the task offloading traffic is huge and the wireless transmission capability becomes a bottleneck, TATO can reduce the ORT by 42.8% compared with that of the communication-based offloading.
资助项目	National Key Research and Development Program of China[2020YFB1807803] ; National Natural Science Youth Fund of China[61901452] ; National Natural Science Foundation of China[12022116] ; National Natural Science Foundation of China[12021001] ; National Natural Science Foundation of China[11991021] ; National Natural Science Foundation of China[11688101] ; Innovative Project of ICT/CAS[20196110]
WOS研究方向	Computer Science ; Engineering ; Telecommunications
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000728152700044
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/59688]
专题	中国科学院数学与系统科学研究院
通讯作者	Zhou, Yiqing
作者单位	1.Adv Technol Res Inst Unisoc, Beijing 100191, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing Key Lab Mobile Comp & Pervas Device, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Acad Math & Syst Sci, Inst Computat Math & Sci Engn Comp, State Key Lab Sci & Engn Comp, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Qi, Yanli,Zhou, Yiqing,Liu, Ya-Feng,et al. Traffic-Aware Task Offloading Based on Convergence of Communication and Sensing in Vehicular Edge Computing[J]. IEEE INTERNET OF THINGS JOURNAL,2021,8(24):17762-17777.
APA	Qi, Yanli,Zhou, Yiqing,Liu, Ya-Feng,Liu, Ling,&Pan, Zhengang.(2021).Traffic-Aware Task Offloading Based on Convergence of Communication and Sensing in Vehicular Edge Computing.IEEE INTERNET OF THINGS JOURNAL,8(24),17762-17777.
MLA	Qi, Yanli,et al."Traffic-Aware Task Offloading Based on Convergence of Communication and Sensing in Vehicular Edge Computing".IEEE INTERNET OF THINGS JOURNAL 8.24(2021):17762-17777.