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对无人机(Unmanned Aerial Vehicle, UAV)辅助边缘计算(Mobile Edge Computing, MEC)网络中的能耗与任务完成率联合优化问题进行研究，提出一种UAV-MEC网络高能效任务完成率最大化方案。该方案首先根据所建立的UAV-MEC网络系统模型建立UAV-MEC网络资源分配优化问题，然后采用分块迭代与连续凸近似(Successive Convex Approximation, SCA)算法将所建立的非凸问题转换成凸问题，并利用拉格朗日对偶算法进行问题求解。通过优化问题的最优解得到UAV-MEC网络中UAV算力、UAV轨迹、用户卸载任务量与UAV卸载任务量的优化参数。仿真结果表明，所提方案在不同网络参数下均有效可靠，不同参数对应的性能证明了所提方案的有效性。
Abstract：The joint optimization problem of energy consumption and task completion rate in unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC) networks is studied.An energy-efficient UAV task completion rate maximization scheme for UAV-assisted MEC networks is proposed.A resource allocation optimization problem of the UAV-MEC system is formulated based on the system model of the UAV-MEC network.The block iteration and successive convex approximation(SCA) algorithms are adopted to transform the non-convex problem into convex form, which is solved by the Lagrange dual algorithm.The obtained optimal solutions are used to get the UAV computing power, and the amount of the customer and UAV offloading tasks, respectively.The numerical results demonstrate that the proposed scheme is effective and reliable under different network parameters, the performance curves corresponding to different parameters prove the effectiveness of the proposed scheme.
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基本信息:
DOI：10.13682/j.issn.2095-6533.2022.04.001
中图分类号:TN929.5;V279
引用信息:
[1]刘伯阳,王怡心,杨宁乐,等.无人机边缘计算高能效任务完成率最大化方案[J].西安邮电大学学报,2022,27(04):1-9.DOI:10.13682/j.issn.2095-6533.2022.04.001.
基金信息:
陕西省自然科学基础研究计划项目(2020JQ-851); 陕西省教育厅专项科研计划项目(19JK0796); 陕西省普通高校青年杰出人才支持计划项目
2022-07-10
2022-07-10