预测服务质量（PQoS）：完全自治系统的下一个前沿
Predictive Quality of Service (PQoS): The Next Frontier for Fully Autonomous Systems
摘要：
软件、硬件、计算和控制方面的最新进展推动了自主系统领域的重大进展。值得注意的是，自主机器应该不断地估计它们移动和操作的场景将如何在预定义的时间范围内演变，并预见网络是否能够满足约定的服务质量（QoS）。否则，应采取适当的对策以满足应用要求。沿着这些路线，在本文中，我们提出了可能的方法，使预测QoS（PQoS）在自治系统中，并讨论哪些用例将特别受益于网络预测。然后，我们阐明了该领域的挑战，这些挑战对未来的研究仍然是开放的。作为一个案例研究，我们证明了机器学习是否可以促进PQoS在一个遥控驾驶类用例，作为不同的测量信号的函数。
英文摘要：
Recent advances in software, hardware, computing and control have fueled significant progress in the field of autonomous systems. Notably, autonomous machines should continuously estimate how the scenario in which they move and operate will evolve within a predefined time frame, and foresee whether or not the network will be able to fulfill the agreed Quality of Service (QoS). If not, appropriate countermeasures should be taken to satisfy the application requirements. Along these lines, in this paper we present possible methods to enable predictive QoS (PQoS) in autonomous systems, and discuss which use cases will particularly benefit from network prediction. Then, we shed light on the challenges in the field that are still open for future research. As a case study, we demonstrate whether machine learning can facilitate PQoS in a teleoperated-driving-like use case, as a function of different measurement signals.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
