Energy-Efficient Resource Allocation in UAV Based MEC System for IoT Devices

Yao Du, Kezhi Wang, Kun Yang, Guopeng Zhang

Research output: Contribution to conferencePaperpeer-review

81 Citations (Scopus)
84 Downloads (Pure)


This paper considers an unmanned aerial vehicle based mobile edge computing (UAV based MEC) system, where we assume there is one UAV, acts as an edge cloud, providing data processing services to the Internet of things devices (IoTDs). We consider the UAV hovers at difference places for different time to receive and process data for IoTDs. We aim to minimize the energy consumption of the UAV, including its hovering energy and computation energy, by optimizing the hovering time, scheduling and resource allocation of the tasks received from IoTDs, subject to the quality of service (QoS) requirement of all the IoTDs and the computing resource available at UAV. This is formulated as a mixed-integer non-convex optimization problem, which is difficult to solve in general. We propose an efficient iterative algorithm to get a high-quality suboptimal solution. Simulation results show that our proposed method has a very good performance compared with the other benchmarks.
Original languageEnglish
Publication statusPublished - 11 Dec 2018
EventIEEE Global Communications Conference - Abu Dhabi National Exhibition Centre, Abu Dhabi, United Arab Emirates
Duration: 9 Dec 201813 Dec 2018


ConferenceIEEE Global Communications Conference
Abbreviated titleGLOBECOM 2018
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Internet address


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