We propose a data-driven technique for autonomous management of N×N photonic switching systems in a software-defined networking setup. This work aims to demonstrate the C+L multi-band switching system and proposes a softwarized model for control.
Autonomous Control Model for C+L Multi-band Photonic Switch System using Machine Learning / Khan, Ihtesham; Tunesi, Lorenzo; Masood, Muhammad Umar; Ghillino, Enrico; Bardella, Paolo; Carena, Andrea; Curri, Vittorio.. - ELETTRONICO. - (2021). (Intervento presentato al convegno Asia Communications and Photonics tenutosi a Shanghai China nel 24–27 October 2021) [10.1364/ACPC.2021.T4A.163].
Autonomous Control Model for C+L Multi-band Photonic Switch System using Machine Learning
Khan, Ihtesham;Tunesi, Lorenzo;Masood, Muhammad Umar;Bardella, Paolo;Carena, Andrea;Curri, Vittorio.
2021
Abstract
We propose a data-driven technique for autonomous management of N×N photonic switching systems in a software-defined networking setup. This work aims to demonstrate the C+L multi-band switching system and proposes a softwarized model for control.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2949527