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Optimal Scheduling for Unmanned Aerial Vehicle Networks With Flow-Level Dynamics

机译:流量级动力学无人空中车辆网络的最佳调度

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Unmanned Aerial Vehicle (UAV) Networks have recently attracted great attention as being able to provide convenient and fast wireless connections. One central question is how to allocate a limited number of UAVs to provide wireless services across a large number of regions, where each region has dynamic arriving flows and flows depart from the system once they receive the desired amount of service (referred to as the flow-level dynamic model). In this article, we propose a MaxWeight-type scheduling algorithm taking into account sharp flow-level dynamics that efficiently redirect UAVs across a large number of regions. However, in our considered model, each flow experiences an independent fading channel and will immediately leave the system once it completes its service, which makes its evolution quite different from the traditional queueing model for wireless networks. This poses significant challenges in our performance analysis. Nevertheless, we incorporate sharp flow-dynamic into the Lyapunov-drift analysis framework, and successfully establish both throughput and heavy-traffic optimality of the proposed algorithm. Extensive simulations are performed to validate the effectiveness of our proposed algorithm.
机译:无人驾驶飞行器(UV)网络最近吸引了极大的关注,因为能够提供方便和快速的无线连接。一个核心问题是如何分配有限数量的无人机,以便在大量地区提供无线服务,其中每个区域都有动态到达流程,并且一旦它们收到所需的服务量(称为流量-Level动态模型)。在本文中,我们提出了一个Maxweight型调度算法考虑了大量的流量级动态,可有效地将UAV跨越大量区域重定向。然而,在我们考虑的模型中,每个流程都经历了一个独立的衰落通道,并将立即离开系统一旦完成其服务,它就会与无线网络传统排队模型完全不同。这在我们的性能分析中提出了重大挑战。尽管如此,我们将夏普流入Lyapunov漂移分析框架的急剧性流入,并成功地建立了所提出的算法的吞吐量和重型交易。进行广泛的模拟以验证我们所提出的算法的有效性。

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