Video streaming over the IP networks presents several challenges for remote drone piloting. To achieve a High Quality of Experience, minimal latency is mandatory. However, wireless links usually impose dynamic changes to the Quality of Service conditions. Moreover, bandwidth limitations can increase both the final perceived latency and packet loss during video streaming. These circumstances require an architecture capable of estimating network performance and applying corrective actions in a timely manner to optimize application-level quality. In this article, we present such an architecture, and discuss the results of its application in video streaming for remote drone piloting. Our proposal offers a framework with low coupling between its functional blocks and high adaptability to dynamic scenarios. Accordingly, we aim to pave the way for reactive applications that leverage edge-computing elements and adapt to network conditions.

中文翻译：

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用于无人机自适应视频流的网络质量感知架构

IP 网络上的视频流给远程无人机驾驶带来了几个挑战。为了获得高质量的体验，最小延迟是强制性的。然而，无线链路通常会动态改变服务质量条件。此外，带宽限制会增加视频流期间的最终感知延迟和数据包丢失。这些情况需要一种能够估计网络性能并及时采取纠正措施以优化应用程序级质量的架构。在本文中，我们将介绍这样一种架构，并讨论其在远程无人机驾驶视频流中的应用结果。我们的提议提供了一个框架，其功能块之间的耦合度低，对动态场景的适应性强。因此，