期刊
IEEE TRANSACTIONS ON COMMUNICATIONS
卷 65, 期 8, 页码 3571-3584出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2017.2699660
关键词
Mobile edge computing; fog computing; semi-definite relaxation; computation offloading; dynamic voltage and frequency scaling
资金
- MOE ARF [MOE2015-T2-2-104]
- Chongqing University of Posts and Telecommunications [A2016-114]
- National Natural Science Foundation of China (NSFC) [61601071]
- Open Foundation of State Key Lab of Integrated Services Networks of Xidian University [ISN17-01]
In this paper, we propose an optimization framework of offloading from a single mobile device (MD) to multiple edge devices. We aim to minimize both total tasks' execution latency and the MD's energy consumption by jointly optimizing the task allocation decision and the MD's central process unit (CPU) frequency. This paper considers two cases for the MD, i.e., fixed CPU frequency and elastic CPU frequency. Since these problems are NP-hard, we propose a linear relaxation-based approach and a semidefinite relaxation (SDR)-based approach for the fixed CPU frequency case, and an exhaustive search-based approach and an SDR-based approach for the elastic CPU frequency case. Our simulation results show that the SDR-based algorithms achieve near optimal performance. Performance improvement can be obtained with the proposed scheme in terms of energy consumption and tasks' execution latency when multiple edge devices and elastic CPU frequency are considered. Finally, we show that the MD's flexible CPU range can have an impact on the task allocation.
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