RT Conference Proceedings
T1 On the Integration of AI/ML-based scaling operations in the 5Growth platform
A1 Baranda, Jorge
A1 Mangues-Bafalluy, Josep
A1 Zeydan, Engin
A1 Vettori, L.
A1 Martínez, Ricardo
A1 Li, Xi
A1 Garcia Saavedra, Andres
A1 Chiasserini, C. F.
A1 Casetti, C.
A1 Tomakh, K.
A1 Kolodiazhnyi, O.
A1 Bernardos Cano, Carlos Jesús
AB The automated assurance of vertical service level agreements (SLA) is a challenge in 5G networks. The EU 5Growth project designs and develops a 5G End-to-End service platform that integrates Artificial Intelligence (AI) and Machine Learning (ML) techniques for any decision-making process in the management and orchestration (MANO) stack. This paper presents the detailed architecture and first prototype of the 5Growth platform taking AI/ML-based network service auto-scaling decisions. This also includes the modification of the ETSI network service descriptors for requesting AI/ML-based decisions for orchestration problems and the integration of a data engineering pipeline for real-time data gathering and model execution. Our evaluation shows that AI/ML-related service handling operations (1&-2 s.) are well below instantiation/termination procedures (80/60 s., respectively). Furthermore, online classification can be performed in the order of hundreds of milliseconds (600 ms).
PB IEEE
SN 978-1-7281-8159-2
YR 2020
FD 2020-11-09
LK https://hdl.handle.net/10016/31756
UL https://hdl.handle.net/10016/31756
LA eng
NO This paper has been presented at 2020 IEEE Conference on Network Function Virtualization and Software Defined Networks
NO This work has been partially funded by the EU H2020 5Growth Project(grant no. 856709), by MINECO grant TEC2017-88373-R (5G-REFINE) andGeneralitat de Catalunya grant 2017 SGR 1195.
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RD 27 jul. 2024