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5Growth Data-Driven AI-Based Scaling

Authors: Danny De Vleeschauwer; Jorge Baranda; Josep Mangues-Bafalluy; Carla Fabiana Chiasserini; Marco Malinverno; Corrado Puligheddu; Lina Magoula; +7 Authors

5Growth Data-Driven AI-Based Scaling

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 V2N scenarios, which can be embedded into the system for handling more complex use cases.

Keywords

Telecomunicaciones, NO KEYWORDS, 6G mobile communication, Computational Modeling, Prototypes, 5G, 6G, service scaling, AI/ML platform, AIMLaaS, resource scaling, Software, 620, 004

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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