19th AIAI 2023, 14 - 17 June 2023, León, Spain

Use Cases Employing a Machine Learning Network Architecture

ALEXANDROS KOSTOPOULOS, Ioannis P. Chochliouros, John Vardakas, Christos Verikoukis, Md Arifur Rahman, Andrea P. Guevara, Robbert Beerten, Philippe Chanclou, Roberto Gonzalez, Charalambos Klitis, Pierangela Samarati, Polyzois Soumplis, Emmanuel Varvarigos, Dimitrios Kritharidis, Kostas Chartsias, Christina Lessi


  5G mobile networks will soon be available to handle all types of applications and to provide services to massive numbers of users. In this complex and dynamic network ecosystem, an end-to-end performance analysis and optimisation will be “key” features to effectively manage the diverse requirements imposed by multiple vertical industries over the same shared infrastructure. To enable such a challenging vision, the MARSAL EU-funded project [1] targets the development and evaluation of a complete framework for the management and orchestration of network resources in 5G and beyond by utilizing a converged optical-wireless network infrastructure in the access and fronthaul/midhaul segments. In this paper, we present the network architecture of the MARSAL, as well as how the experimentation scenarios are mapped to the considered architecture.  

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