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- Title
UAV-Aided Multiuser Mobile Edge Computing Networks with Energy Harvesting.
- Authors
Wang, Changyu; Yu, Weili; Zhu, Fusheng; Ou, Jiangtao; Fan, Chengyuan; Ou, Jianghong; Fan, Dahua
- Abstract
This article studies a mobile edge computing (MEC) with one edge node (EN), where multiple unmanned aerial vehicles (UAVs) act as users which have some heavy tasks. As the users generally have limitations in both calculating and power supply, the EN can help calculate the tasks and meanwhile supply the power to the users through energy harvesting. We optimize the system by proposing a joint strategy to unpacking and energy harvesting. Specifically, a deep reinforcement learning (DRL) algorithm is implemented to provide a solution to the unpacking, while several analytical solutions are given to the power allocation of energy harvesting among multiple users. In particular, criterion I is the equivalent power allocation, criterion II is designed through equal data rate, while criterion III is based on the equivalent transmission delay. We finally give some results to verify the joint strategy for the UAV-aided multiuser MEC system with energy harvesting.
- Subjects
ENERGY harvesting; MOBILE computing; EDGE computing; REINFORCEMENT learning; POWER resources; DRONE aircraft
- Publication
Wireless Communications & Mobile Computing, 2022, p1
- ISSN
1530-8669
- Publication type
Article
- DOI
10.1155/2022/6723403