Optimizing Multi-UAV Deployment in 3D Space to Minimize Task Completion Time in UAV-Enabled Mobile Edge Computing Systems

TL;DR

This paper presents a convex optimization approach for 3D deployment of UAVs in MEC systems to minimize task completion time, demonstrating improved performance over traditional methods.

Contribution

It introduces a convex approximation method for optimizing UAV 3D placement in MEC, addressing a complex mixed-integer nonlinear problem.

Findings

Joint 3D UAV deployment reduces task completion time.

Convex approximation effectively solves the deployment optimization.

Simulation shows superior performance over traditional algorithms.

Abstract

In Unmanned Aerial Vehicle (UAV)-enabled mobile edge computing (MEC) systems, UAVs can carry edge servers to help ground user equipment (UEs) offloading their computing tasks to the UAVs for execution. This paper aims to minimize the total time required for the UAVs to complete the offloaded tasks, while optimizing the three-dimensional (3D) deployment of UAVs, including their flying height and horizontal positions. Although the formulated optimization is a mixed integer nonlinear programmming, we convert it to a convex problem and develop a successive convex approximation (SCA) based algorithm to effectively solve it. The simulation results show that the joint optimization of the horizontal and the vertical position of a group of UAVs can achieve better performance than the traditional algorithms.