Federico Mason received the bachelor’s and master’s degree in telecommunication engineering from the University of Padua, Italy, in 2016 and 2018, respectively, where he is currently pursuing the Ph.D. degree. In 2020 he won a national grant from the GARR association to investigate new artificial intelligence solutions to enable the network slicing paradigm in future 5G and 6G networks. His current research interests include the analysis and development of deep reinforcement learning algorithms to optimize complex telecommunication systems, with a special focus on public safety services. Federico’s participation in Future Talent Programme (FTP21) was supported by GARR Italy.
Lightning Talk Topic
A Hierarchical Learning Approach to Enable Network Slicing in Future Telecommunication Systems.
In this work, we designed a hierarchical learning architecture, where multiple agents cooperate to orchestrate network slices under different working conditions. Our hierarchical architecture will support PSC in a much more efficient way than conventional approaches, allowing the current telecommunication networks to assist emergency operators (e.g., firefighters, policemen, healthcare professionals) without the need for a dedicated infrastructure.