Institute of Computing Technology, Chinese Academy IR
Data-Driven Optimization for Cooperative Edge Service Provisioning With Demand Uncertainty | |
Li, Liang1,2; Shi, Dian3; Hou, Ronghui1,2; Li, Xuanheng4; Wang, Jie4,5; Li, Hui1; Pan, Miao3 | |
2021-03-15 | |
发表期刊 | IEEE INTERNET OF THINGS JOURNAL |
ISSN | 2327-4662 |
卷号 | 8期号:6页码:4317-4328 |
摘要 | Multiaccess edge computing (MEC) empowers service providers (SPs) to run applications on the shared edge platforms in close proximity to mobile users, enabling ultralow latency access to a wide variety of cloud services. However, how to decide the amount of edge computing resources to rent for mobile service provisioning poses great challenges as the service demand is unknown to SPs a priori and may vary across the geographically distributed edge sites spatially and temporally. The resource rental decision also significantly affects SPs' deploying profits since it is critical for service deployment and workload assignment. This article investigates the service provisioning problem in a cooperative edge computing system under service demand uncertainty. We develop a holistic solution to make two-timescale decisions on edge resource rental and workload assignment to maximize SP's deploying profits. Briefly, we exploit historical service demand traces at the edge sites to characterize the uncertainty in a data-driven manner and formulate the edge service provisioning problem into a two-stage risk-averse optimization. To solve the formulated problem without compromising the data privacy, we propose an algorithm integrating Benders decomposition (BD) and alternating direction method of multipliers (ADMMs), which enables each edge site to keep the historical traces locally and participate in the optimization process. Based on real-world data sets, extensive simulations are conducted to validate the efficacy of our scheme. |
关键词 | Uncertainty Optimization Edge computing Servers Robustness Processor scheduling Internet of Things Data-driven optimization demand uncertainty edge computing resource provisioning |
DOI | 10.1109/JIOT.2020.3028242 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[61571351] ; National Natural Science Foundation of China[61801080] ; National Natural Science Foundation of China[62071081] ; State Key Laboratory of Computer Architecture (ICT, CAS)[CARCH201904] ; Shaanxi Science Foundation of China[2019ZDLGY12-08] ; 111 Project[B16037] ; 111 Project[ZD2004] ; U.S. National Science Foundation[US CNS-1646607] ; U.S. National Science Foundation[CNS-1801925] ; U.S. National Science Foundation[CNS-2029569] ; Fundamental Research Funds for the Central Universities[DUT20RC(4)007] ; Doctoral Research Initiation Fund of Liaoning Province[2019-BS-049] |
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:000626569700017 |
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/2XEOYT63/16751 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Hou, Ronghui |
作者单位 | 1.Xidian Univ, Sch Cyber Engn, Xian 710071, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100080, Peoples R China 3.Univ Houston, Dept Elect & Comp Engn, Houston, TX 77204 USA 4.Dalian Univ Technol, Fac Elect Informat & Elect Engn, Dalian 116024, Peoples R China 5.Dalian Maritime Univ, Sch Informat Sci & Technol, Dalian 116026, Peoples R China |
推荐引用方式 GB/T 7714 | Li, Liang,Shi, Dian,Hou, Ronghui,et al. Data-Driven Optimization for Cooperative Edge Service Provisioning With Demand Uncertainty[J]. IEEE INTERNET OF THINGS JOURNAL,2021,8(6):4317-4328. |
APA | Li, Liang.,Shi, Dian.,Hou, Ronghui.,Li, Xuanheng.,Wang, Jie.,...&Pan, Miao.(2021).Data-Driven Optimization for Cooperative Edge Service Provisioning With Demand Uncertainty.IEEE INTERNET OF THINGS JOURNAL,8(6),4317-4328. |
MLA | Li, Liang,et al."Data-Driven Optimization for Cooperative Edge Service Provisioning With Demand Uncertainty".IEEE INTERNET OF THINGS JOURNAL 8.6(2021):4317-4328. |
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