ONLINE LEARNING FOR COMPUTATION PEER OFFLOADING WITH SEMI-BANDIT FEEDBACK

doi:10.1109/ICASSP.2019.8682398

	ONLINE LEARNING FOR COMPUTATION PEER OFFLOADING WITH SEMI-BANDIT FEEDBACK
	Zhn, Hongbin1,2 ; Kang, Kai 3; Luo, Xiliang1 ; Qian, Hua3
	2019
会议录名称	2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
ISSN	1520-6149
卷号	2019-May
页码	4524-4528
发表状态	已发表
DOI	10.1109/ICASSP.2019.8682398
摘要	Fog computing is emerging as a promising paradigm to perform distributed, low-latency computation. Efficient computation peer offloading is critical to fully utilize the computational resources in fog networks. In this paper, we consider computation peer of-floading problem in a fog network with time-varying stochastic time of arrival tasks and channel conditions. Such time-varying conditions are not available to all fog nodes. In order to minimize the latency of accomplishing arrival tasks, we propose an online algorithm based on combinatorial upper confidence bounds algorithm with two uncertain variables under the non-stationary bandit model. The proposed computation offloading policy is optimized based on historical feedback. The performance of the proposed scheme is validated through numerical simulations.
会议录编者/会议主办者	Inst Elect & Elect Engineers,Inst Elect & Elect Engineers Signal Proc Soc
关键词	Fog Computing Computation Peer Offloading Online Learning Combinatorial Multi-Armed Bandit (CMAB)
会议名称	44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
出版地	NEW YORK
会议地点	Brighton, United kingdom
会议日期	12-17 May 2019
URL	查看原文
收录类别	EI ; CPCI ; CPCI-S
语种	英语
资助项目	Science and Technology Commission Foundation of Shanghai[18511103502]
WOS研究方向	Acoustics ; Engineering
WOS类目	Acoustics ; Engineering, Electrical & Electronic
WOS记录号	WOS:000482554004152
出版者	IEEE
EI入藏号	20192907201036
WOS关键词	RESOURCE ; ALLOCATION
原始文献类型	Proceedings Paper
引用统计
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/34286
专题	信息科学与技术学院_博士生信息科学与技术学院_特聘教授组_钱骅组信息科学与技术学院_PI研究组_罗喜良组
作者单位	1.School of Information Science and Technology, ShanghaiTech University, Shanghai, China 2.Shanghai Institute of Microsystem and Information Technology, CAS, Shanghai, China 3.Shanghai Advanced Research Institute, CAS, Shanghai, China
第一作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Zhn, Hongbin,Kang, Kai,Luo, Xiliang,et al. ONLINE LEARNING FOR COMPUTATION PEER OFFLOADING WITH SEMI-BANDIT FEEDBACK[C]//Inst Elect & Elect Engineers,Inst Elect & Elect Engineers Signal Proc Soc. NEW YORK:IEEE,2019:4524-4528.