Silvio Marcato
Network Slice Reuse in 5G Network: A Machine Learning Approach.
Rel. Carla Fabiana Chiasserini, Claudio Ettore Casetti. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2021
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Abstract
The rise of 5G networks has been fundamental in these last decades, giving the possibility of handling the user demand in a sustainable way. The concept of a flexible and standard architecture brought by the 5G-TRANSFORMER project and later by the 5Growth project has revolutionized the approach in 5G networks. The network slicing approach is the key factor of this thesis. As a matter of fact, it enables a logical and physical separation in terms of amount of resources, with the possibility of sharing and scaling them. Further improvements can be done in these terms of optimization of resources, essential in handling a wide range of services with different requirements.
Our work is focused on automatizing the resources optimization by the use of a machine learning model
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