Energy-Efficient UAV-Assisted Mobile Edge Computing: Resource Allocation and Trajectory Optimization
University of Waterloo · Xidian University · +2 more institutions
Abstract
In this paper, we study unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) with the objective to optimize computation offloading with minimum UAV energy consumption. In the considered scenario, a UAV plays the role of an aerial cloudlet to collect and process the computation tasks offloaded by ground users. Given the service requirements of users, we aim to maximize UAV energy efficiency by jointly optimizing the UAV trajectory, the user transmit power, and computation load allocation. The resulting optimization problem corresponds to nonconvex fractional programming, and the Dinkelbach algorithm and the successive convex approximation (SCA) technique are adopted to solve it. Furthermore, we…
Citation impact
- FWCI
- 474.05
- Percentile
- 100%
- References
- 38
Authors
6- MLMushu LiCorresponding
University of Waterloo
- NCNan Cheng
Xidian University
- JGJie Gao
University of Waterloo
- YWYinlu Wang
Southeast University
- LZLian Zhao
Toronto Metropolitan University
Topics & keywords
- Mobile edge computing
- Cloudlet
- Computation offloading
- Computation
- Resource allocation
- Optimization problem
- Edge computing
- Convex optimization