On the Integration of AI/ML-based scaling operations in the 5Growth platform

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dc.contributor.author Baranda, Jorge
dc.contributor.author Mangues-Bafalluy, Josep
dc.contributor.author Zeydan, Engin
dc.contributor.author Vettori, L.
dc.contributor.author Martínez, Ricardo
dc.contributor.author Li, Xi
dc.contributor.author Garcia Saavedra, Andres
dc.contributor.author Chiasserini, C. F.
dc.contributor.author Casetti, C.
dc.contributor.author Tomakh, K.
dc.contributor.author Kolodiazhnyi, O.
dc.contributor.author Bernardos Cano, Carlos Jesús
dc.date.accessioned 2021-01-21T12:53:15Z
dc.date.available 2021-01-21T12:53:15Z
dc.date.issued 2020-11-09
dc.identifier.bibliographicCitation Baranda, J., Mangues-Bafalluy, J., Zeydan, E., Vettori, L., Martínez, R., X. Li, X., Garcia-Saavedra, A., ... C. J. Bernardos, C. J. (2020). On the Integration of AI/ML-based scaling operations in the 5Growth platform. In 2020 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN).
dc.identifier.isbn 978-1-7281-8159-2
dc.identifier.uri http://hdl.handle.net/10016/31756
dc.description This paper has been presented at 2020 IEEE Conference on Network Function Virtualization and Software Defined Networks
dc.description.abstract The automated assurance of vertical service level agreements (SLA) is a challenge in 5G networks. The EU 5Growth project designs and develops a 5G End-to-End service platform that integrates Artificial Intelligence (AI) and Machine Learning (ML) techniques for any decision-making process in the management and orchestration (MANO) stack. This paper presents the detailed architecture and first prototype of the 5Growth platform taking AI/ML-based network service auto-scaling decisions. This also includes the modification of the ETSI network service descriptors for requesting AI/ML-based decisions for orchestration problems and the integration of a data engineering pipeline for real-time data gathering and model execution. Our evaluation shows that AI/ML-related service handling operations (1&-2 s.) are well below instantiation/termination procedures (80/60 s., respectively). Furthermore, online classification can be performed in the order of hundreds of milliseconds (600 ms).
dc.description.sponsorship This work has been partially funded by the EU H2020 5Growth Project (grant no. 856709), by MINECO grant TEC2017-88373-R (5G-REFINE) and Generalitat de Catalunya grant 2017 SGR 1195.
dc.format.extent 5
dc.language.iso eng
dc.publisher IEEE
dc.rights © 2020 IEEE.
dc.subject.other Scaling
dc.subject.other Management
dc.subject.other End-To-End service orchestration
dc.subject.other AI/ML
dc.subject.other NFV/SDN
dc.subject.other Automated network
dc.title On the Integration of AI/ML-based scaling operations in the 5Growth platform
dc.type bookPart
dc.type conferenceObject
dc.subject.eciencia Telecomunicaciones
dc.identifier.doi https://doi.org/10.1109/NFV-SDN50289.2020.9289863
dc.rights.accessRights openAccess
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/856709
dc.relation.projectID Gobierno de España. TEC2017-88373-R
dc.type.version acceptedVersion
dc.relation.eventdate 09 - 12 November 2020
dc.relation.eventplace En línea
dc.relation.eventtitle 2020 IEEE Conference on Network Function Virtualization and Software Defined Networks
dc.relation.eventtype proceeding
dc.identifier.publicationtitle Proceedings of 2020 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN)
dc.identifier.uxxi CC/0000031414
dc.contributor.funder European Commission
dc.contributor.funder Ministerio de Economía y Competitividad (España)
dc.affiliation.dpto UC3M. Departamento de Ingeniería Telemática
dc.affiliation.grupoinv UC3M. Grupo de Investigación: Network Technologies
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