Intelligent Orchestration of End-to-End Network Slices for the Allocation of Mission Critical Services over NFV Architectures

The challenge of deploying mission critical services upon virtualised shared network models is the allocation of both radio and cloud resources to the critical actors who require prioritized and high-quality services. This paper describes the design and deployment of an intelligent orchestration cyc...

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Detalles Bibliográficos
Autores principales: Blanco, Bego, Solozabal, Rubén, Sanchoyerto, Aitor, López-Cuadrado, Javier, Jimeno, Elisa, Catalan-Cid, Miguel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7256420/
http://dx.doi.org/10.1007/978-3-030-49190-1_7
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author Blanco, Bego
Solozabal, Rubén
Sanchoyerto, Aitor
López-Cuadrado, Javier
Jimeno, Elisa
Catalan-Cid, Miguel
author_facet Blanco, Bego
Solozabal, Rubén
Sanchoyerto, Aitor
López-Cuadrado, Javier
Jimeno, Elisa
Catalan-Cid, Miguel
author_sort Blanco, Bego
collection PubMed
description The challenge of deploying mission critical services upon virtualised shared network models is the allocation of both radio and cloud resources to the critical actors who require prioritized and high-quality services. This paper describes the design and deployment of an intelligent orchestration cycle to manage end-to-end slices on a NFV architecture. This novel tool includes the monitoring of the network elements at different levels and the processing of the gathered data to produce the corresponding alert mitigation actions.
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spelling pubmed-72564202020-05-29 Intelligent Orchestration of End-to-End Network Slices for the Allocation of Mission Critical Services over NFV Architectures Blanco, Bego Solozabal, Rubén Sanchoyerto, Aitor López-Cuadrado, Javier Jimeno, Elisa Catalan-Cid, Miguel Artificial Intelligence Applications and Innovations. AIAI 2020 IFIP WG 12.5 International Workshops Article The challenge of deploying mission critical services upon virtualised shared network models is the allocation of both radio and cloud resources to the critical actors who require prioritized and high-quality services. This paper describes the design and deployment of an intelligent orchestration cycle to manage end-to-end slices on a NFV architecture. This novel tool includes the monitoring of the network elements at different levels and the processing of the gathered data to produce the corresponding alert mitigation actions. 2020-05-04 /pmc/articles/PMC7256420/ http://dx.doi.org/10.1007/978-3-030-49190-1_7 Text en © IFIP International Federation for Information Processing 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Blanco, Bego
Solozabal, Rubén
Sanchoyerto, Aitor
López-Cuadrado, Javier
Jimeno, Elisa
Catalan-Cid, Miguel
Intelligent Orchestration of End-to-End Network Slices for the Allocation of Mission Critical Services over NFV Architectures
title Intelligent Orchestration of End-to-End Network Slices for the Allocation of Mission Critical Services over NFV Architectures
title_full Intelligent Orchestration of End-to-End Network Slices for the Allocation of Mission Critical Services over NFV Architectures
title_fullStr Intelligent Orchestration of End-to-End Network Slices for the Allocation of Mission Critical Services over NFV Architectures
title_full_unstemmed Intelligent Orchestration of End-to-End Network Slices for the Allocation of Mission Critical Services over NFV Architectures
title_short Intelligent Orchestration of End-to-End Network Slices for the Allocation of Mission Critical Services over NFV Architectures
title_sort intelligent orchestration of end-to-end network slices for the allocation of mission critical services over nfv architectures
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7256420/
http://dx.doi.org/10.1007/978-3-030-49190-1_7
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