@inproceedings{3194108,
    title = "5Growth Data-driven AI-based Scaling",
    author = "de Vleeschauwer, Danny and Baranda, Jorge and Mangues-Bafalluy, Josep and and Fabiana Chiasserini, Carla and Malinverno, Marco and Puligheddu, and Corrado and Magoula, Lina and Martin-Perez, Jorge and Barmpounakis, and Sokratis and Kondepu, Koteswararao and Valcarenzhi, Luca and Li, Xi and and Papagianni, Chrysa and Garcia-Saavedra, Andres",
    year = "2021",
    pages = "383-388",
    publisher = "IEEE Comput. Soc",
    booktitle = "2021 JOINT EUROPEAN CONFERENCE ON NETWORKS AND COMMUNICATIONS & 6G
SUMMIT (EUCNC/6G SUMMIT)",
    doi = "10.1109/EUCNC/6GSUMMIT51104.2021.9482476",
    abstract = "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."
}