期刊
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
卷 68, 期 11, 页码 11018-11030出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2019.2942334
关键词
Hybrid mobile cloud/edge computing; multi-user computation offloading; data caching; McCormick envelopes; ADMM
资金
- National Natural Science Foundation of China [61421001, 61871032, 61801505]
- China National SAMP
- T Major Projects [2017ZX03001017, MCM20170101]
- 111 Project of China [B14010]
- Beijing Natural Science Foundation [4152047, L182038]
- Jiangsu Provincial Nature Science Foundation of China [BK20170755]
- National Postdoctoral Program for Innovative Talents of China [BX201700109]
In this paper, we investigate a hybrid mobile cloud/edge computing system with coexistence of centralized cloud and mobile edge computing, which enables computation offloading and data caching to improve the performance of users. Computation offloading and data caching decisions are jointly optimized to minimize the total execution delay at the mobile user side, while satisfying the constrains in terms of the maximum tolerable energy consumption of each user, the computation capability of each MEC server, and the cache capacity of each access point (AP). The formulated problem is non-convex and challenging because of the highly coupled decision variables. To address such an untractable problem, we first transform the original problem into an equivalent convex one by McCormick envelopes and introducing auxiliary variables. To the end, we propose a distributed algorithm based on the alternating direction method of multipliers (ADMM), which can achieve near optimal computation offloading and data caching decisions. The proposed algorithm has lower computational complexity compared to the centralized algorithm. Simulation results are presented to verify that the proposed algorithm can effectively reduce computing delay for end users while ensuring the performance of each user.
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