End-to-End Intent-Based Networking

Authors
  • R. Bifulco
  • J.J. Vegas Olmos
  • S. Pryor
  • G. Carrozzo
  • J. Schulz-Zander
  • M. Bennis
  • R. Martinez
  • F. Cugini
  • C. Salvadori
  • V. Lefebvre
  • L. Valcarenghi
  • M. Ruiz
Publication date 10-2021
Journal IEEE Communications Magazine
Volume | Issue number 59 | 10
Pages (from-to) 106-112
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
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
Document type Article
Language English
Published at https://doi.org/10.1109/MCOM.101.2100141
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