University of Oulu

L. Velasco et al., "End-to-End Intent-Based Networking," in IEEE Communications Magazine, vol. 59, no. 10, pp. 106-112, October 2021, doi: 10.1109/MCOM.101.2100141.

End-to-end intent-based networking

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Author: Velasco, Luis1; Signorelli, Marco2; González De Dios, Oscar3;
Organizations: 1Universitat Politècnica de Catalunya, Spain
2Telecom Italia, Italy
3Tèlefonica, Spain
4University of Amsterdam, Netherlands
5NEC, Japan
7Accelleran, Belgium
8Nextworks, Italy
9HHI, Germany
10University of Oulu, Finland
12CNIT, Italy
14Tages Solidshield, USA
15Scuola Superiore Sant'Anna, Italy
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.7 MB)
Persistent link:
Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2023-03-07


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.

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Series: IEEE communications magazine
ISSN: 0163-6804
ISSN-E: 1558-1896
ISSN-L: 0163-6804
Volume: 59
Issue: 10
Pages: 106 - 112
DOI: 10.1109/MCOM.101.2100141
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
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