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dc.contributor.authorRafique, Danish
dc.contributor.authorVelasco Esteban, Luis Domingo
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2018-11-29T08:29:18Z
dc.date.available2018-11-29T08:29:18Z
dc.date.issued2018
dc.identifier.citationRafique, D., Velasco, L. Machine learning for network automation: Overview, architecture, and applications [invited tutorial]. "Journal of optical communications and networking", 2018, vol. 10, núm. 10, p. D126-D143.
dc.identifier.issn1943-0620
dc.identifier.urihttp://hdl.handle.net/2117/125214
dc.description.abstractNetworks are complex interacting systems involving cloud operations, core and metro transport, and mobile connectivity all the way to video streaming and similar user applications. With localized and highly engineered operational tools, it is typical of these networks to take days to weeks for any changes, upgrades, or service deployments to take effect. Machine learning, a sub-domain of artificial intelligence, is highly suitable for complex system representation. In this tutorial paper, we review several machine learning concepts tailored to the optical networking industry and discuss algorithm choices, data and model management strategies, and integration into existing network control and management tools. We then describe four networking case studies in detail, covering predictive maintenance, virtual network topology management, capacity optimization, and optical spectral analysis.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telecomunicació òptica
dc.subject.lcshOptical communications
dc.subject.lcshMachine learning
dc.subject.otherAnalytics
dc.subject.otherArtificial intelligence
dc.subject.otherAutonomous networking
dc.subject.otherBig data
dc.subject.otherCommunication networks
dc.subject.otherOptical fiber communication
dc.subject.otherTelemetry
dc.titleMachine learning for network automation: Overview, architecture, and applications [invited tutorial]
dc.typeArticle
dc.subject.lemacComunicacions òptiques
dc.subject.lemacAprenentatge automàtic
dc.contributor.groupUniversitat Politècnica de Catalunya. GCO - Grup de Comunicacions Òptiques
dc.identifier.doi10.1364/JOCN.10.00D126
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.osapublishing.org/jocn/abstract.cfm?URI=jocn-10-10-D126
dc.rights.accessOpen Access
local.identifier.drac23518489
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/761727/EU/METRO High bandwidth, 5G Application-aware optical network, with edge storage, compUte and low Latency/METRO-HAUL
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/TEC2017-90097-R
local.citation.authorRafique, D.; Velasco, L.
local.citation.publicationNameJournal of optical communications and networking
local.citation.volume10
local.citation.number10
local.citation.startingPageD126
local.citation.endingPageD143


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