End-to-End Intent-Based Networking
Luis Velasco, Marco Signorelli, Óscar González de Dios, Chrysa Papagianni, Roberto Bifulco, Juan José Vegas Olmos, Simon Pryor, Gino Carrozzo, Julius Schulz-Zander, Mehdi Bennis, Ricardo Martínez, Filippo Cugini, Claudio Salvadori, Vincent Lefèbvre, Luca Valcarenghi, Marc Ruiz
Abstract
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.