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Peer Offloading with Delayed Feedback in Fog Networks | |
2021-09-01 | |
发表期刊 | IEEE INTERNET OF THINGS JOURNAL (IF:8.2[JCR-2023],9.0[5-Year]) |
ISSN | 2327-4662 |
EISSN | 2327-4662 |
卷号 | 8期号:17页码:13690-13702 |
发表状态 | 已发表 |
DOI | 10.1109/JIOT.2021.3067919 |
摘要 | Comparing to cloud computing, fog computing performs computation and services at the edge of networks, thus relieving the computation burden of the data center and reducing the task latency of end devices. Computation latency is a crucial performance metric in fog computing, especially for real-time applications. In this article, we study a peer computation offloading problem for a fog network with unknown dynamics. In this scenario, each fog node (FN) can offload its computation tasks to neighboring FNs in a time slot manner. The offloading latency, however, could not be fed back to the task dispatcher instantaneously due to the uncertainty of the processing time in peer FNs. Besides, peer competition occurs when different FNs offload tasks to one FN at the same time. To tackle the above difficulties, we model the computation offloading problem as a sequential FN selection problem with delayed information feedback. Using the adversarial multiarm bandit framework, we construct an online learning policy to deal with delayed information feedback. Different contention resolution approaches are considered to resolve peer competition. Performance analysis shows that the regret of the proposed algorithm, or the performance loss with suboptimal FN selections, achieves a sublinear order, suggesting an optimal FN selection policy. Besides, we prove that the proposed strategy can result in a Nash equilibrium (NE) with all FNs playing the same policy. Simulation results validate the effectiveness of the proposed policy. © 2014 IEEE. |
关键词 | Fog Computation burden Computation offloading Contention resolution Delayed information Performance analysis Performance metrices Real time application Selection problems Task analysis Computational modeling Peer-to-peer computing Internet of Things Real-time systems Heuristic algorithms Edge computing Adversarial multiarm bandit delayed feedback fog computing reinforcement learning task offloading |
URL | 查看原文 |
收录类别 | SCI ; SCIE ; EI |
语种 | 英语 |
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:000688231600046 |
出版者 | Institute of Electrical and Electronics Engineers Inc. |
EI入藏号 | 20211310151501 |
EI主题词 | Fog computing |
EI分类号 | 443.1 Atmospheric Properties |
原始文献类型 | Journal article (JA) |
来源库 | IEEE |
引用统计 | 正在获取...
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文献类型 | 期刊论文 |
条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/133225 |
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 |
作者单位 | 1.Chinese Academy of Sciences, Shanghai Advanced Research Institute, Shanghai, China 2.School of Information Science and Technology, ShanghaiTech University, Shanghai, China 3.Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland 4.Department of Applied Probability and Informatics, Peoples’ Friendship University of Russia (RUDN University), Moscow, Russia 5.Key Laboratory of Wireless Sensor Network & Communication, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China |
推荐引用方式 GB/T 7714 | Miao Yang,Hongbin Zhu,Hua Qian,et al. Peer Offloading with Delayed Feedback in Fog Networks[J]. IEEE INTERNET OF THINGS JOURNAL,2021,8(17):13690-13702. |
APA | Miao Yang,Hongbin Zhu,Hua Qian,Yevgeni Koucheryavy,Konstantin Samouylov,&Haifeng Wang.(2021).Peer Offloading with Delayed Feedback in Fog Networks.IEEE INTERNET OF THINGS JOURNAL,8(17),13690-13702. |
MLA | Miao Yang,et al."Peer Offloading with Delayed Feedback in Fog Networks".IEEE INTERNET OF THINGS JOURNAL 8.17(2021):13690-13702. |
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