MEC中基于混合元启发的无人机轨迹优化和任务卸载策略

Unmanned Aerial Vehicle Trajectory Optimization and Task Offloading Strategy Based on Hybrid Meta Heuristic Algorithm in Mobile Edge Computing

摘要

在无人机辅助的移动边缘计算通信系统中,无人机作为空中基站接收多个地面移动设备卸载的数据,本文为满足无人机的机动性以及三维避障约束条件,以最大化系统能效(定义为卸载数据总量和无人机能耗的比值)为目标,联合优化无人机飞行轨迹和地面设备任务卸载率,提出一种混合交替元启发式的优化方案.由于该优化问题具有非凸性和分式结构,可先通过Dinkelbach方法将其转化为等价的参数优化问题,然后将其拆分为两个子优化问题分别利用元启发式算法交替进行优化.通过仿真实验验证了所提的联合优化方案的有效性,结果表明,所提方案的无人机通信能效明显高于传统算法,为解决无人机辅助移动边缘计算网络中的能效问题提供了新的思路.

Abstract

In a UAV-assisted mobile edge computing communication system,a UAV acts as an airborne base station to receive data offloaded by multiple ground mobile devices,and in order to satisfy UAV maneuverability as well as 3D obstacle avoidance constraints,and with the goal of maximizing the system energy efficiency (defined as the ratio between the total amount of offloaded data and the UAV′s energy consumption),this study jointly optimizes the flight trajectory of the UAV and the ground devices′ task offloading rate by proposing an optimization scheme of a hybrid alternating element heuristic.Due to the non-convexity and fractional structure of this optimization problem,it can be transformed into an equivalent parametric optimization problem by Dinkelbach′s method,and then split into two sub-optimization problems to be optimized by using the meta-heuristic algorithm alternately respectively.The effectiveness of the proposed joint optimization scheme is verified through simulation experiments,and the results show that the energy efficiency of UAV communication of the proposed scheme is significantly higher than that of the traditional algorithm,which provides a new idea for solving the energy efficiency problem in UAV-assisted mobile edge computing networks.

关键词

移动边缘计算 / 无人机通信 / 任务卸载 / 轨迹优化 / 三维避障

Key words

mobile edge computing / UAV communication / task offloading / trajectory optimization / 3D obstacle avoidance

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基金资助

国家自然科学基金项目(62062007)资助;广西自然科学基金项目(2025GXNSFAA069236)资助;广西重点研发计划项目(2024AB33144)资助.