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dc.contributor.authorPalacios, David
dc.contributor.authorFortes-Rodríguez, Sergio 
dc.contributor.authorDe la Bandera Cascales, Isabel
dc.contributor.authorBarco-Moreno, Raquel 
dc.date.accessioned2024-02-08T14:13:02Z
dc.date.available2024-02-08T14:13:02Z
dc.date.created2024
dc.date.issued2018-07-25
dc.identifier.citationD. Palacios, S. Fortes, I. de-la-Bandera and R. Barco, "Self-Healing Framework for Next-Generation Networks through Dimensionality Reduction," in IEEE Communications Magazine, vol. 56, no. 7, pp. 170-176, July 2018.es_ES
dc.identifier.urihttps://hdl.handle.net/10630/30162
dc.description.abstractNext generation self-organizing networks (NGSONs) are the key that will lead to the full automation of the network management in the forthcoming generations of cellular communications. New challenges, like the deployment of novel wireless services or the aim of operators at providing an end-to-end monitoring and optimization, make it necessary to develop an innovative scheme for network management. In this paper, a self-healing (SH) framework for next-generation networks using dimensionality reduction is proposed as the tool enabling the management of an increasingly complex network, taking advantage of both feature selection and feature extraction techniques. A proof of concept has been carried out in the context of automatic diagnosis in a live network. Results show that the proposed framework can effectively manage a high-dimensional environment, eventually automating the tasks usually performed by troubleshooting experts while optimizing the performance of the diagnosis tool.es_ES
dc.language.isoenges_ES
dc.publisherIEEEes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectTelecomunicacioneses_ES
dc.subject.otherSelf-organizing networks (SONs)es_ES
dc.subject.otherSelf-healinges_ES
dc.subject.otherPerformance indicatores_ES
dc.subject.otherRoot cause analysis (RCA)es_ES
dc.subject.otherDimensionality reductiones_ES
dc.titleSelf-Healing Framework for Next-Generation Networks through Dimensionality Reduction.es_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.identifier.doi10.1109/MCOM.2018.1700556
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersiones_ES


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