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 6NVIDIA, USA 7Accelleran, Belgium 8Nextworks, Italy 9HHI, Germany 10University of Oulu, Finland 11CTTC/CERCA, USA 12CNIT, Italy 13NGS, USA 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: | http://urn.fi/urn:nbn:fi-fe2023030730248 |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers,
2021
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Publish Date: | 2023-03-07 |
Description: |
AbstractTo 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. see all
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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 |
OADOI: | https://oadoi.org/10.1109/MCOM.101.2100141 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
113 Computer and information sciences |
Subjects: | |
Copyright information: |
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