期刊
IEEE INTERNET OF THINGS JOURNAL
卷 6, 期 2, 页码 3688-3699出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2018.2890133
关键词
Mobile edge computing (MEC); stochastic computation offloading; trajectory scheduling; unmanned aerial vehicle (UAV)-assisted
资金
- National Natural Science Foundation of China [61601482, 61471376]
- Key Research Plan of Hunan Province [2016JC2021]
Unmanned aerial vehicle (UAV) has been witnessed as a promising approach for offering extensive coverage and additional computation capability to smart mobile devices (SMDs), especially in the scenario without available infrastructures. In this paper, a UAV-assisted mobile edge computing system with stochastic computation tasks is investigated. The system aims to minimize the average weighted energy consumption of SMDs and the UAV, subject to the constraints on computation offloading, resource allocation, and flying trajectory scheduling of the UAV. Due to nonconvexity of the problem and the time coupling of variables, a Lyapunov-based approach is applied to analyze the task queue, and the energy consumption minimization problem is decomposed into three manageable subproblems. Furthermore, a joint optimization algorithm is proposed to iteratively solve the problem. Simulation results demonstrate that the system performance obtained by the proposed scheme can outperform the benchmark schemes, and the optimal parameter selections are concluded in the experimental discussion.
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