Reinforcement Learning-Based Mobile Offloading for Edge Computing Against Jamming and Interference

doi:10.1109/TCOMM.2020.3007742

	Reinforcement Learning-Based Mobile Offloading for Edge Computing Against Jamming and Interference
	Xiao, Liang 1; Lu, Xiaozhen 1; Xu, Tangwei 1; Wan, Xiaoyue 1; Ji, Wen 2,3; Zhang, Yanyong 4
	2020-10-01
发表期刊	IEEE TRANSACTIONS ON COMMUNICATIONS
ISSN	0090-6778
卷号	68 期号:10 页码:6114-6126
摘要	Mobile edge computing systems help improve the performance of computational-intensive applications on mobile devices and have to resist jamming attacks and heavy interference. In this paper, we present a reinforcement learning based mobile offloading scheme for edge computing against jamming attacks and interference, which uses safe reinforcement learning to avoid choosing the risky offloading policy that fails to meet the computational latency requirements of the tasks. This scheme enables the mobile device to choose the edge device, the transmit power and the offloading rate to improve its utility including the sharing gain, the computational latency, the energy consumption and the signal-to-interference-plus-noise ratio of the offloading signals without knowing the task generation model, the edge computing model, and the jamming/interference model. We also design a deep reinforcement learning based mobile offloading for edge computing that uses an actor network to choose the offloading policy and a critic network to update the actor network weights to improve the computational performance. We discuss the computational complexity and provide the performance bound that consists of the computational latency and the energy consumption based on the Nash equilibrium of the mobile offloading game. Simulation results show that this scheme can reduce the computational latency and save energy consumption.
关键词	Task analysis Mobile handsets Edge computing Computational modeling Interference Energy consumption Jamming Mobile offloading edge computing interference jamming reinforcement learning
DOI	10.1109/TCOMM.2020.3007742
收录类别	SCI
语种	英语
资助项目	Natural Science Foundation of China[61971366] ; National Key R&D Program of China[2017YFB1400100] ; Beijing Natural Science Foundation[4202072] ; Key Research Program of Frontier Sciences, CAS[ZDBS-LY-JSC001]
WOS研究方向	Engineering ; Telecommunications
WOS类目	Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000579344400013
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：119[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/15699
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Xiao, Liang
作者单位	1.Xiamen Univ, Dept Informat & Commun Engn, Xiamen 361005, Fujian, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 3.Peng Cheng Lab, Shenzhen 518055, Guangdong, Peoples R China 4.Univ Sci & Technol China, Sch Comp Sci & Technol, Hefei 230027, Anhui, Peoples R China
推荐引用方式 GB/T 7714	Xiao, Liang,Lu, Xiaozhen,Xu, Tangwei,et al. Reinforcement Learning-Based Mobile Offloading for Edge Computing Against Jamming and Interference[J]. IEEE TRANSACTIONS ON COMMUNICATIONS,2020,68(10):6114-6126.
APA	Xiao, Liang,Lu, Xiaozhen,Xu, Tangwei,Wan, Xiaoyue,Ji, Wen,&Zhang, Yanyong.(2020).Reinforcement Learning-Based Mobile Offloading for Edge Computing Against Jamming and Interference.IEEE TRANSACTIONS ON COMMUNICATIONS,68(10),6114-6126.
MLA	Xiao, Liang,et al."Reinforcement Learning-Based Mobile Offloading for Edge Computing Against Jamming and Interference".IEEE TRANSACTIONS ON COMMUNICATIONS 68.10(2020):6114-6126.