End-to-End Intent-Based Networking

• Published in: IEEE communications magazine 2021-10, Vol.59 (10), p.106-112
• Main Authors: Velasco, Luis, Signorelli, Marco, De Dios, Oscar Gonzalez, Papagianni, Chrysa, Bifulco, Roberto, Olmos, Juan Jose Vegas, Pryor, Simon, Carrozzo, Gino, Schulz-Zander, Julius, Bennis, Mehdi, Martinez, Ricardo, Cugini, Filippo, Salvadori, Claudio, Lefebvre, Vincent, Valcarenghi, Luca, Ruiz, Marc
• Format: Magazinearticle
• Language: English
• Subjects: 5G mobile communication; Cloud computing; Elasticity; Infrastructure; Intelligence; Machine learning; Resilience; Virtualization
• ISSN: 0163-6804; 1558-1896
• DOI: 10.1109/MCOM.101.2100141

To reap its full benefits, 5G must evolve into a scalable decentralized architecture by exploiting intelligence ubiquitously and securely across different technologies, network layers, and segments. In this article, we propose end-to-end and ubiquitous secure machine learning (ML)-powered intent-based networking (IBN). The IBN framework is aware of its state and context to autonomously take proactive actions for service assurance. It is integrated in a zero-touch control and orchestration framework featuring an ML function orchestrator to manage ML pipelines. The objective is to create an elastic and dynamic infrastructure supporting per-domain and end-to-end network and services operation. The solution is supported by a radio access network and forwarding plane, and a cloud/edge virtualization infrastructure with ML acceleration. The resulting framework supports application-level resilience and intelligence through replication and elasticity. An illustrative intelligent application use case is presented.