Joint optimization for latency minimization in UAV-assisted MEC networks

Chen Wang, Ruonan Zhang, Haotong Cao, Junhao Song, W. Zhang
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引用次数: 1

Abstract

Combining unmanned aerial vehicles (UAVs) with multi-access edge computing (MEC) networks has been deemed as a potential approach for delay-sensitive applications. In this paper, we propose a UAV-assisted MEC network architecture and jointly optimize the UAVs' position, task offloading, bandwidth allocation, and computing resource allocation to minimize the time consumption of each terminal devices cluster. To solve this problem, we design a joint optimization algorithm based on the particle swarm optimization (PSO) and bisection searching (BSS) approach. The results of the simulation reveal that the devised algorithm can significantly reduce time consumption and guarantee the fairness of the whole network.
无人机辅助MEC网络时延最小化联合优化
将无人机(uav)与多接入边缘计算(MEC)网络相结合被认为是延迟敏感应用的一种潜在方法。本文提出了一种无人机辅助的MEC网络架构,并对无人机的位置、任务卸载、带宽分配和计算资源分配进行了共同优化,使每个终端设备集群的时间消耗最小。为了解决这一问题,我们设计了一种基于粒子群优化(PSO)和平分搜索(BSS)方法的联合优化算法。仿真结果表明,所设计的算法可以显著减少时间消耗,保证整个网络的公平性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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