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.

中文翻译：

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优化 3D 空间中的多无人机部署，以最大限度地缩短支持无人机的移动边缘计算系统中的任务完成时间

在支持无人机 (UAV) 的移动边缘计算 (MEC) 系统中，无人机可以携带边缘服务器，帮助地面用户设备 (UE) 将计算任务卸载给无人机执行。本文旨在最小化无人机完成卸载任务所需的总时间，同时优化无人机的三维（3D）部署，包括其飞行高度和水平位置。尽管公式化优化是混合整数非线性规划，但我们将其转换为凸问题并开发基于逐次凸逼近 (SCA) 的算法来有效解决它。仿真结果表明，联合优化一组无人机的水平和垂直位置可以取得比传统算法更好的性能。