Archivio Istituzionale della RicercaWe 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).
Softwarized and Autonomous Management of Photonic Switching Systems Using Machine Learning
KHAN,IHTESHAM;MASOOD, MUHAMMAD UMAR;Tunesi, Lorenzo;Bardella, Paolo;Carena, Andrea;Curri,Vittorio
2021
Abstract
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.
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https://hdl.handle.net/11583/2917844