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Energy-Optimal and Delay-Bounded Computation Offloading in Mobile Edge Computing with heterogeneous clouds

China Communications 2020年第5期17卷 191-210页

作者： Tianchu Zhao Sheng Zhou Linqi Song Zhiyuan Jiang Xueying Guo Zhisheng Niu Beijing National Research Center for Information Science and Technology Department of Electronic EngineeringTsinghua UniversityBeijing 100080China Computer Science Department City University of Hong KongHongkong 999077China School of Communication and Information Engineering Shanghai UniversityShanghai 200444China Department of Computer Science University of CaliforniaDavisDavis 001313USA

By Mobile Edge Computing(MEC), computation-intensive tasks are offloaded from mobile devices to cloud servers, and thus the energy consumption of mobile devices can be notably reduced. In this paper, we study task offloading in multi-user MEC systems with heterogeneous clouds, including edge clouds and remote clouds. Tasks are forwarded from mobile devices to edge clouds via wireless channels, and they can be further forwarded to remote clouds via the Internet. Our objective is to minimize the total energy consumption of multiple mobile devices, subject to bounded-delay requirements of tasks. Based on dynamic programming, we propose an algorithm that minimizes the energy consumption, by jointly allocating bandwidth and computational resources to mobile devices. The algorithm is of pseudo-polynomial complexity. To further reduce the complexity, we propose an approximation algorithm with energy discretization, and its total energy consumption is proved to be within a bounded gap from the optimum. Simulation results show that, nearly 82.7% energy of mobile devices can be saved by task offloading compared with mobile device execution.

关键词： mobile edge computing heterogeneous clouds energy saving delay bounds dynamic programming

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