Adaptive Video Streaming Testbed Design for Performance Study and Assessment of QoE

dc.contributor.affiliationDepartamento de Comunicaciones
dc.contributor.affiliationEscuela Politécnica Superior de Gandia
dc.contributor.authorAbdullah, Miran Taha Abdullahes_ES
dc.contributor.authorLloret, Jaime
dc.contributor.authorAli, Areees_ES
dc.contributor.authorGarcía-García, Lauraes_ES
dc.contributor.funderMinisterio de Economía, Industria y Competitividades_ES
dc.date.accessioned2018-05-10T04:17:51Z
dc.date.available2018-05-10T04:17:51Z
dc.date.embargoEndDate2019-01-19es_ES
dc.date.issued2018es_ES
dc.description.abstract[EN] Hypertext Transfer Protocol adaptive streaming switches between different video qualities, adapting to the network conditions, and avoids stalling streamed frames over high¿oscillation client's throughput improving the users' quality of experience (QoE). Quality of experience has become the most important parameter to lead the service providers to know about the end¿user feedback. Implementing Hypertext Transfer Protocol adaptive streaming applications to find out QoE in real¿life scenarios of vast networks becomes more challenging and complex task regarding to cost, agile, time, and decisions. In this paper, a virtualized network testbed to virtualize various machines to support implementing experiments of adaptive video streaming has been developed. Within the test study, the metrics which demonstrate performance of QoE are investigated, respectively, including initial delay (ie, startup delay at the beginning of playback a video), frequency switches (ie, number of times the quality is changed), accumulative video time (ie, number and length of stalls), CPU usage, and battery energy consumption. Furthermore, the relation between effective parameters of QoS on the aforementioned metrics for different segment length is investigated. Experimental results show that the proposed virtualized system is agile, easy to install and use, and costs less than real testbeds. Moreover, the subjective and objective performance studies of QoE evaluation in the system have proven that the segment lengths of 6 to 8 seconds were faired and more efficient than others according to the investigated parameters.es_ES
dc.description.accrualMethodSes_ES
dc.description.bibliographicCitationAbdullah, MTA.; Lloret, J.; Ali, A.; García-García, L. (2018). Adaptive Video Streaming Testbed Design for Performance Study and Assessment of QoE. International Journal of Communication Systems. 1-15. https://doi.org/10.1002/dac.3551es_ES
dc.description.sponsorshipMinisterio de Economia y Competitividad, Grant/Award Number: TIN2014-57991-C3-1-Pen_EN
dc.description.upvformatpfin15es_ES
dc.description.upvformatpinicio1es_ES
dc.identifier.doi10.1002/dac.3551es_ES
dc.identifier.issn1074-5351es_ES
dc.identifier.urihttps://riunet.upv.es/handle/10251/101674
dc.languageIngléses_ES
dc.publisherJohn Wiley & Sonses_ES
dc.relation.ispartofInternational Journal of Communication Systemses_ES
dc.relation.pasarelaS\352956es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//TIN2014-57991-C3-1-P/ES/DISTRIBUCION INTELIGENTE DE SERVICIOS MULTIMEDIA UTILIZANDO REDES COGNITIVAS ADAPTATIVAS DEFINIDAS POR SOFTWARE/es_ES
dc.relation.publisherversionhttps://doi.org/10.1002/dac.3551es_ES
dc.rightsReserva de todos los derechoses_ES
dc.rights.accessRightsAbiertoes_ES
dc.subjectHTTP adaptive streaminges_ES
dc.subjectNetwork virtualizationes_ES
dc.subjectQoSes_ES
dc.subjectTestbedes_ES
dc.subjectQoE assessmentes_ES
dc.subject.classificationINGENIERIA TELEMATICAes_ES
dc.titleAdaptive Video Streaming Testbed Design for Performance Study and Assessment of QoEes_ES
dc.typeArtículoes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
dspace.entity.typePublication
person.identifier260345
person.identifier.orcid0000-0002-0862-0533
relation.isAuthorOfPublicatione6f912f7-e605-4217-ac55-555ebb925e03
relation.isAuthorOfPublication.latestForDiscoverye6f912f7-e605-4217-ac55-555ebb925e03
relation.isOrgUnitOfPublication02a0f2c5-c452-4e1d-a7d9-b731347d078c
relation.isOrgUnitOfPublication1db03441-9881-4e7e-a0a9-daca18341155
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upv.uuid2f2ef641-df3b-42d1-82ce-5f575c4cbfe9es_ES

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