Archivio Istituzionale della RicercaWe 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].
A Data-Driven Approach to Autonomous Management of Photonic Switching System
Khan, Ihtesham;Masood, Muhammad Umar;Tunesi, Lorenzo;Bardella, Paolo;Carena, Andrea;Curri, Vittorio
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.
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https://hdl.handle.net/11583/2917842