Fajardo Portillo Jose Oscar

Fajardo Portillo, Jose Oscar

Datu pertsonalak

Fajardo Portillo, Jose Oscar

Helbidea: Alda. de Urquijo s/n. C.P.: 48013. Bilbao
Email: joseoscar.fajardo@ehu.es
Teléfono: +34 94 601 7361

 

Titulazio akademikoa

Unibertsitateko Titulazioa

Titulua: Telekomunikazio Ingeniaritza
Areagotzea: Telematika
Zentroa: Euskal Herriko Unibertsitatea
Lorpen data: 2003

Doktoregoa

Egitarauaren titulua: Tecnologías de la información y comunicaciones en Redes Móviles
DEA lorpen data: 2005
Título de la tesis:  Adaptación de los mecanismos de provisión de calidad de servicio a las preferencias de los usuarios (Adaptation of QoS provisioning mechanisms to user requirements)
Lorpen data: (Amaiturik gabe)

Argitalpenak

A Social Relational Network-based Architecture for Maintaining the Media Integrity and Optimizing the Quality of Experience: A Technical and Business Perspective

Egileak:
Harilaos Koumaras, Jose Oscar Fajardo, Fidel Liberal, Lingfen Sun, Vaios Koumaras, Costas Troulos, Anastasios Kourtis
Urtea:
2011
Aldizkaria:
Handbook of Research on Social Computing Theory and Practice: Interdisciplinary Approaches Ed.: IGI Global
Liburukia:
Chapter 12
Hasierako orria - Amaierako orria:
242 - 263
Deskribapena:

<span lang="en>This chapter proposes a Content-aware and Network-aware Management System (CNMS) over a converged user-environment of social networking and mobile multimedia. The proposed CNMS will focus on applying dynamic personalized multi-layer adaptation for the optimization of the Quality of Experience (QoE) level in a requested media service according to the users' preferences, favourites provided in their social network profile, and prior experiences rated by users themselves. By user's preference extraction, a service/content classification will be performed according to an estimation of the user's favourites, which will be used to provide optimized media delivery across the delivery chain. Therefore, the end-user will always receive her/his favourite service, like Internet Protocol Television (IPTV), Voice over Internet Protocol (VoIP), interactive application/on-line gaming, web browsing, at requested QoE. The system will ensure optimal allocation of network resources and optimal selection of streaming scheme according to different services/content types and user preferences, and therefore enhance the ratio of price-for-value for the specific subscription and achieve an end-to-end, holistic QoE optimisation. Although QoE is perceived as subjective, it is the only measure that counts for customers of a service. Being able to estimate the user preferences in a controlled manner through the end-user's social networks profiles, helps operators understand what may be wrong with their services and their respective QoE. The proposed multimodal management system is user-centric and applies advanced machine learning techniques in order to extract user preferences from the social network profile of the user and build up a ranking scale of the services/contents. This ranking scale will be translated to adaptation actions per service type at several instances such as before the provision of the service takes place (i.e. Time Zero), during the delivering of the service (i.e. Time T), across all the network layers and delivery-chain nodes, while ensuring throughout the process that the main focus on the QoS-adaptation of the mobile access network is maintained.</span>

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