We propose a machine learning-based approach for the management of photonic switching systems in a software-defined network context. This work aims to describe a soft-warized system that is both topological and technological agnostic and can be employed in real-time.
Softwarized and Autonomous Management of Photonic Switching Systems Using Machine Learning / Khan, Ihtesham; Masood, Muhammad Umar; Tunesi, Lorenzo; Ghillino, Enrico; Bardella, Paolo; Carena, Andrea; Curri, Vittorio. - ELETTRONICO. - (2021). ((Intervento presentato al convegno 2021 International Conference on Optical Network Design and Modeling (ONDM) tenutosi a Gothenburg, Sweden nel June 28 - July 1, 2021.
Titolo: | Softwarized and Autonomous Management of Photonic Switching Systems Using Machine Learning | |
Autori: | ||
Data di pubblicazione: | 2021 | |
Abstract: | We propose a machine learning-based approach for the management of photonic switching system...s in a software-defined network context. This work aims to describe a soft-warized system that is both topological and technological agnostic and can be employed in real-time. | |
ISBN: | 978-3-903176-33-1 | |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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C_ONDM_Softwarized_and_Autonomous_Management____V1_10032021 (1).pdf | 2. Post-print / Author's Accepted Manuscript | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri |
http://hdl.handle.net/11583/2917844