Machine learning based routing and wavelength assignment in optical networks

The objective of this thesis is the application of machine learning approaches to perform routing and wavelength assignment in wavelength division multiplexed optical networks, with a specific focus on scalability to large scale scenarios. In particular, a Graph Neural Network will be trained based on various types of input graphs, in order to efficiently perform resource allocation in real time by implementing different routing and walength assignment strategies.