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.
| File | Dimensione | Formato | |
|---|---|---|---|
|
A_Data-Driven_Approach_to_Autonomous_Management_of_Photonic_Switching_System.pdf
non disponibili
Tipologia:
2a Post-print versione editoriale / Version of Record
Licenza:
Non Pubblico - Accesso privato/ristretto
Dimensione
878.28 kB
Formato
Adobe PDF
|
878.28 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
|
C_IEEE_summer_topicals_A_Data_Driven_Approach_to____V1_02032021.pdf
accesso aperto
Tipologia:
2. Post-print / Author's Accepted Manuscript
Licenza:
PUBBLICO - Tutti i diritti riservati
Dimensione
599.26 kB
Formato
Adobe PDF
|
599.26 kB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11583/2917842