Optimal Scheduling for Unmanned Aerial Vehicle Networks With Flow-Level Dynamics
Optimal Scheduling for Unmanned Aerial Vehicle Networks With Flow-Level Dynamics
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DOI：
10.1109/tmc.2019.2952848
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发表时间：
2021-03
影响因子：
7.9
通讯作者：
Xiangqi Kong;N. Lu;Bin Li
中科院分区：
文献类型：
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作者：
Xiangqi Kong;N. Lu;Bin Li
无人机（UAV）网络最近由于能够提供方便和快速的无线连接而引起了极大的关注。一个中心问题是如何分配有限数量的无人机在大量的区域提供无线服务，其中每个区域具有动态到达流，并且一旦它们接收到期望的服务量，流就离开系统（称为流级动态模型）。在这篇文章中，我们提出了一个MaxWeight型调度算法，考虑到尖锐的流级动态，有效地重定向无人机在大量的区域。然而，在我们考虑的模型中，每个流经历一个独立的衰落信道，并将立即离开系统，一旦它完成其服务，这使得它的演变与传统的无线网络的路由模型有很大的不同。这对我们的性能分析提出了重大挑战。尽管如此，我们将尖锐的流量动态的Lyapunov漂移分析框架，并成功地建立吞吐量和大流量的最优算法。大量的仿真实验验证了该算法的有效性。
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.