This document provides a comprehensive overview of final design of all the Network Intelligence (NI) solutions for enhancing mobile network security, efficiency, and reliability developed in ORIGAMI. The deliverable emphasizes the role of machine learning, artificial intelligence, and advanced analytics in building the technology that supports ORIGAMI’s novel architectural components (namely, the Global Service Based Architecture, the Zero-Trust Layer and the Compute Continuum Layer). The project structures this report around three key network domains: the Radio Access Network (RAN), the Transport Network (TN), and the Core Network (CN). The project details the definitive design of the NI solutions across RAN, TN, and CN domains, addressing the specific Barriers the project identified in WP2. RAN solutions include task offloading, xApp conflict mitigation, and Machine Learning (ML) for energy efficiency across 12 use-cases. TN focuses on embedding ML in hardware for scalable user-plane intelligence, with 2 use-cases. CN presents 8 solutions for operational optimisation, security, and flexible operator models.
Marco Fiore (Tue,) studied this question.