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dc.contributor.authorBaena, Carlos
dc.contributor.authorPeñaherrera-Pulla, Oswaldo Sebastián
dc.contributor.authorBarco-Moreno, Raquel 
dc.contributor.authorFortes-Rodríguez, Sergio 
dc.date.accessioned2023-06-07T10:43:11Z
dc.date.available2023-06-07T10:43:11Z
dc.date.issued2023
dc.identifier.citationBaena, C., Peñaherrera-Pulla, O. S., Barco, R., & Fortes, S. (2022). Measuring and estimating Key Quality Indicators in Cloud Gaming services. Computer Networks (Amsterdam, Netherlands : 1999), 231, 109808–. https://doi.org/10.1016/j.comnet.2023.109808es_ES
dc.identifier.urihttps://hdl.handle.net/10630/26850
dc.description.abstractThe gaming industry has proposed the concept of Cloud Gaming (CG), a paradigm that enhances the gaming experience on reduced hardware devices. However, this paradigm puts a lot of pressure on the communication links that connect the user to the cloud. As a result, the service experience becomes highly dependent on network connectivity. In this context, the present work proposes a framework for measuring and estimating the most important E2E (end-to-end) metrics of the CG service, namely Key Quality Indicators (KQIs). Therefore, different machine learning (ML) techniques are evaluated to predict KQIs related to the CG user experience. For this purpose, the most important KQIs of the service, such as input lag, freezes or perceived video frame rate, are collected in a real network deployment. The results show that ML techniques can be used to estimate these indicators solely from network-related metrics. This is seen as a valuable asset for the delivery of CG services over cellular networks, even without access to the user’s device, as it is expected for telecom operators.es_ES
dc.description.sponsorshipinisterio de Asuntos Económicos y Transformación Digital and European Union - NextGenerationEU, Spain within the framework ‘‘Recuperación, Transformación y Resiliencia y el Mecanismo de Recuperación y Resiliencia’’ under the project MAORI. This work has been also supported by Junta de Andalucía, Spain through Secretaría General de Universidades, Investigación y Tecnología, Spain with the predoctoral grant (Ref. PREDOC_01712) as well as by Ministerio de Ciencia y Tecnología, Spain through grant FPU19/04468. Funding for open access charge: University of Málaga / CBUAes_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectVideojuegoses_ES
dc.subjectServidores webes_ES
dc.subject.otherCloud gaminges_ES
dc.subject.otherMobile networkses_ES
dc.subject.otherQuality of experiencees_ES
dc.subject.otherKey Quality Indicatorses_ES
dc.subject.otherEnd-to-endes_ES
dc.subject.otherMachine learninges_ES
dc.titleMeasuring and estimating Key Quality Indicators in Cloud Gaming serviceses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.centroE.T.S.I. Telecomunicaciónes_ES
dc.identifier.doihttps://doi.org/10.1016/j.comnet.2023.109808
dc.rights.ccAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES


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