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Computer Science > Networking and Internet Architecture

arXiv:2109.09376 (cs)
[Submitted on 20 Sep 2021]

Title:Predictive Quality of Service (PQoS): The Next Frontier for Fully Autonomous Systems

Authors:Mate Boban, Marco Giordani, Michele Zorzi
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Abstract: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.
Comments: This paper has been accepted for publication in IEEE Network, 2021. 7 pages, 5 figures, 1 table
Subjects: Networking and Internet Architecture (cs.NI); Machine Learning (cs.LG)
Cite as: arXiv:2109.09376 [cs.NI]
  (or arXiv:2109.09376v1 [cs.NI] for this version)
  https://doi.org/10.48550/arXiv.2109.09376

Submission history

From: Marco Giordani [view email]
[v1] Mon, 20 Sep 2021 08:55:51 UTC (1,590 KB)
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