We propose a data-driven approach based on Machine Learning (ML) to predict control signals of a photonic switching system. The proposed ML agent is trained and tested in a completely topological and technological agnostic way and we envision its application in real-time control-planes.
A Data-Driven Approach to Autonomous Management of Photonic Switching System / Khan, Ihtesham; Masood, Muhammad Umar; Tunesi, Lorenzo; Ghillino, Enrico; Bardella, Paolo; Carena, Andrea; Curri, Vittorio. - ELETTRONICO. - (2021), pp. 1-2. ((Intervento presentato al convegno IEEE Photonics Society Summer Topicals Meeting Series (SUM) tenutosi a Cabo San Lucas, Mexico nel 19-21 July 2021 [10.1109/SUM48717.2021.9505780].
Titolo: | A Data-Driven Approach to Autonomous Management of Photonic Switching System | |
Autori: | ||
Data di pubblicazione: | 2021 | |
Abstract: | We propose a data-driven approach based on Machine Learning (ML) to predict control signals of a ...photonic switching system. The proposed ML agent is trained and tested in a completely topological and technological agnostic way and we envision its application in real-time control-planes. | |
ISBN: | 978-1-6654-1600-9 | |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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http://hdl.handle.net/11583/2917842