End-to-End Intent-Based Networking

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-bas...

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Detalles Bibliográficos
Autores: velasci, Luis, Signorelli, M, González Dios, Oscar, Papagianni, C, Bifulco, R, Vegas Olmos, Juan Jose, Pryor, S, Carrozzo, G, Schulz-Zander, J, Bennis, M, Martinez, R, Cugini, F, Salvadori, C, Lefebvre, V, Valcarenghi, L, Ruiz, M
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
Repositorio:r-CTTC. Repositorio Institucional Producción Científica del Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
OAI Identifier:oai:cttc.fundanetsuite.com:p4143
Acceso en línea:https://cttc.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=4143
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120528686&doi=10.1109%2fMCOM.101.2100141&partnerID=40&md5=6bf9a136765bf624f39588a7e280fc45
Access Level:acceso abierto
Palabra clave:5G mobile communication systems
Learning systems
Decentralized architecture
Dynamic infrastructure
End to end
End-to-end network
End-to-end service
Network operations
Network segment
Service assurance
Service operations
Technology network
Network layers
Descripción
Sumario: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. © 1979-2012 IEEE.

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