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Efficient Computation Resource Management in Mobile Edge-Cloud Computing

delete2019-04-01
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张
张永敏 (Yongmin Zhang)
兰小龙 cover
兰小龙 (Xiaolong Lan)
Y
Yue Li
Lin Cai cover
Lin Cai (Lin Cai) *
J
Jianping Pan
DOI:10.1109/JIOT.2018.2885453delete
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Abstract

Abstract

En 中文
We study the computation resource management problem in mobile edge-cloud computing networks. Mobile edge servers shall first satisfy the computation requirements of mobile users and Internet of Things (IoT) devices, and then wholesale redundant computation resources to the cloud networks to maximize their profit. Due to the coarse time granularity of wholesales, computation resource buyback may happen occasionally to deal with traffic bursts. Thus, the mobile edge servers need to make a tradeoff between the wholesale profit and the buyback cost. In this paper, the computation resource management problem is modeled as profit maximization. To solve this problem, we first analyze the relationship among the reserved computation resources, the computation tasks of mobile users and IoT devices, and the buyback cost. Then, we design an efficient wholesale scheme to determine the amount of the wholesaled computation resources, by which the total expected profit of the mobile edge server can be maximized. Given the reserved computation resources, we also propose a fast-convergent realtime buyback scheme for mobile edge servers to minimize the buyback cost. Finally, the simulation results show that our proposed efficient wholesale and buyback scheme can increase the total profit while guaranteeing the computation delay of all the computation tasks, especially when the computation workloads are time-varying.
Keywords:
Cloud networks
computation resources
Internet of Things (IoT)
mobile edge server
profit maximization
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Journal

IEEE Internet of Things Journal cover
IEEE Internet of Things Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W

Organization

U
University of Victoria
Scholars:
1.0W
Papers: 1.0W
Citations: 1.5W
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