TY - CONF
TI - 5Growth Data-driven AI-based Scaling
AU - de Vleeschauwer, Danny
AU - Baranda, Jorge
AU - Mangues-Bafalluy, Josep
AU - and Fabiana Chiasserini, Carla
AU - Malinverno, Marco
AU - Puligheddu,
AU - Corrado
AU - Magoula, Lina
AU - Martin-Perez, Jorge
AU - Barmpounakis,
AU - Sokratis
AU - Kondepu, Koteswararao
AU - Valcarenzhi, Luca
AU - Li, Xi and
AU - Papagianni, Chrysa
AU - Garcia-Saavedra, Andres
PY - 2021
SP - 383-388
PB - IEEE Comput. Soc
T2 - 2021 JOINT EUROPEAN CONFERENCE ON NETWORKS AND COMMUNICATIONS & 6G
SUMMIT (EUCNC/6G SUMMIT)
TODO - 10.1109/EUCNC/6GSUMMIT51104.2021.9482476
TODO - null
TODO - This paper presents a data-driven approach leveraging AI/ML models to
automate the service scaling operation and, in this way, meet the
service requirements while minimizing the consumption of network,
computing, and storage resources. This approach is integrated into the
5Growth service management software platform. In particular, a prototype
was developed to demonstrate how the novel 5Growth AI/ML platform can be
used in a closed-loop automation system to support the automated service
scaling operation. Furthermore, a number of additional ML-based
approaches are developed in the context of eMBB and C-V2N scenarios,
which can be embedded into the system for handling more complex use
cases.
ER -