2026-06-01T03:35:04Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/310852026-02-03T10:55:44Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Luque Schempp, Francisco
author
Panizo-Jaime, Laura
author
Gallardo-Melgarejo, María del Mar
author
Merino-Gómez, Pedro
2024-04-18T11:55:23Z
2024-04-18T11:55:23Z
2023
F. Luque-Schempp, L. Panizo, M. -D. -M. Gallardo and P. Merino, "AutomAdapt: Zero Touch Configuration of 5G QoS Flows Extended for Time-Sensitive Networking," in IEEE Access, vol. 11, pp. 82960-82977, 2023, doi: 10.1109/ACCESS.2023.3302264
https://hdl.handle.net/10630/31085
10.1109/ACCESS.2023.3302264
The aim of IEEE Time-Sensitive Networking (TSN) standards is to grant deterministic communication in traditional Ethernet networks for Industry 4.0. Insofar as the use cases in the Factory need some mobility, the extension of the TSN capabilities over the fifth-generation (5G) cellular network is the next step. Some challenges in TSN over 5G, such as TSN translators time synchronization functionality, are well defined in the standards, even if they have not yet been addressed in the market. However other challenges, such as the dynamic configuration of the entire network (or part of the it) based on quality requirements of the current TSN traffic pattern, are defined at a very high level and delegated to vendors for implementation. This paper addresses this challenge, using an Automata Learning approach to monitor and reconfigure the end-to-end 5G QoS flow to keep the quality of a TSN session within the required values. Additionally, algorithms are provided to build the automata from network data and predict potential deviations of the requirements to meet the expected quality. Moreover, this work presents a functional TSN over a 5G testbed where the algorithms have been tested, demonstrating that the proposed solution achieves an improvement of around 40% compared to the usual operation of the network.
eng
Attribution 4.0 Internacional
Sistemas de comunicaciones inalámbricos
Aprendizaje automático (Inteligencia artificial)
Sistemas autoorganizativos
AutomAdapt: Zero Touch Configuration of 5G QoS Flows Extended for Time-Sensitive Networking.
journal article
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AutomAdapt_Zero_Touch_Configuration_of_5G_QoS_Flows_Extended_for_Time-Sensitive_Networking.pdf