On the Integration of AI/ML-based scaling operations in the 5Growth platform
Jorge Baranda, Josep Mangues‐Bafalluy, Engin Zeydan, Luca Vettori, Ricardo Martínez, Xi Li, Andrés García‐Saavedra, Carla Fabiana Chiasserini, Claudio Casetti, Konstantin Tomakh, O. Kolodiazhnyi, Carlos J. Bernardos
Abstract
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).