Abstract:
In this paper, we study an unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) system with multiple energy harvesting (EH) devices. Considering the stochast...View moreMetadata
Abstract:
In this paper, we study an unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) system with multiple energy harvesting (EH) devices. Considering the stochastic energy and data arrivals in sequential time slots, we formulate the UAV propulsion energy minimization problem with long-term data queue stability and battery causality constraints as a multi-stage stochastic optimization programming. To facilitate online control without any prior knowledge of future information, we adopt the perturbed Lyapunov optimization method that decouples the control decisions made in sequential time slots and determines the real-time control decisions by solving a deterministic problem in each time slot. For the per-slot deterministic problem, we decouple it into three sub-problems: the optimal energy harvesting, the computation resource allocation and the UAV trajectory control, and propose a reduced-complexity method to solve them sepa-rately. Simulation results demonstrate that the proposed algorithm guarantees the data queue stability that is not achievable by the benchmark method when the two methods consume identical UAV propulsion energy.
Published in: 2021 IEEE Global Communications Conference (GLOBECOM)
Date of Conference: 07-11 December 2021
Date Added to IEEE Xplore: 02 February 2022
ISBN Information: