Machine-learning-assisted Quality of Transmission Estimation in Optical Networks


Machine Learning (ML) tools have recently been adopted for a wide range of automated operations in optical networking, moving fundamental steps towards the paradigm of zero-touch infrastructures. One example of such tasks is estimating the Quality of transmission of a lightpath prior to its establishment, which is particularly challenging due to the non-linear characteristics of signal propagation in optical fibers and to the often-incomplete knowledge of equipment parameters.

This talk provides an overview of the contribution of my research team in the field of ML-based lightpath QoT estimation, including transfer learning approaches for inter-domain model adaptation, active learning for model building with small-sized training dataset, quantification of prediction uncertainty, and adoption of Explainable AI framework to expose the internal decisional mechanisms of trained models.

Brief Biography

Andrea Bianco is Full Professor and Head of the Electronics and Telecommunications Department at Politecnico di Torino. He is an IEEE Senior Member, member in the Academic Senate of Politecnico di Torino since 2016 and member of the Government Board of COPI (Italian Engineering Conference) since 2018. His research interests are in the fields of network control, high speed switching and data center architectures, SDN/NFV, optical networks and Network Music Performance. He holds three patents and has co-authored over 220 papers published in international journals and presented in leading international conferences in the area of telecommunication networks. Andrea Bianco is Associate Editor of the Elsevier Computer Communications journal and was Area Editor for the IEEE JLT (Journal of Lightwave Technology) 2013-2019.

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