RT Conference Proceedings
T1 5Growth: AI-driven 5G for Automation in Vertical Industries
A1 Papagianni, Chrysa
A1 Murillo, Pablo
A1 Mangues-Bafalluy, Josep
A1 Bermudez, Pedro
A1 Barmpounakis, Sokratis
A1 Vleeschauwer, Danny De
A1 Brenes, Juan
A1 Zeydan, Engin
A1 Casetti, Claudio
A1 Guimarães, Carlos
A1 Garcia Saavedra, Andres
A1 Corujo, Daniel
A1 Pepe, Teresa
AB Spurred by a growing demand for higher-quality mobile services in vertical industries, 5G is integrating a rich set of technologies, traditionally alien to the telco ecosystem, such as machine learning or cloud computing. Despite the initial steps taken in prior research projects in Europe and beyond, additional innovations are needed to support vertical use cases. This is the objective of the 5Growth project: automate vertical support through (i) a portal connecting verticals to 5G platforms (a.k.a. vertical slicer), a multi-domain service orchestrator and a resource management layer, (ii) closed-loop machine-learning-based Service Level Agreement (SLA) control, and (iii) end-to-end optimization. In this paper, we introduce a set of key 5Growth innovations supporting radio slicing, enhanced monitoring and analytics and integration of machine learning.
PB IEEE
SN 978-1-7281-4355-2
YR 2020
FD 2020-06-15
LK https://hdl.handle.net/10016/31361
UL https://hdl.handle.net/10016/31361
LA eng
NO This paper has been presented at 2020 European Conference on Networks and Communications (EuCNC).
NO This work has been partially supported by EC H2020 5GPPP 5Growth project (Grant 856709).
DS e-Archivo
RD 17 jul. 2024