Standardization activities in the ITU for a QoE assessment of IPTV

Takahashi, Akihiro; Hands, David S.; Barriac, Vincent

doi:10.1109/mcom.2008.4473087

Cited by 180 publications

(80 citation statements)

References 5 publications

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“…However, other definitions, such as the one from the ITU-T Focus Group on IPTV (FG IPTV) [9] avoid using the term quality. The FG IPTV defines QoE as the overall acceptability of an application or service, as perceived subjectively by the end-user.…”

Section: Qoe Definitionmentioning

confidence: 99%

Computational Inference and Control of Quality in Multimedia Services

Menkovski

2015

Springer Theses

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Please check the document version of this publication:• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:www.tue.nl/taverne Take down policyIf you believe that this document breaches copyright please contact us at:openaccess@tue.nl providing details and we will investigate your claim. Copyright c 2013 by Vlado Menkovski All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means without the prior written consent of the author. Typeset using L A T E X, printed in The NetherlandsTo my parents, Angel who dedicated his life to his sons and Snežana whose strength inspires me deeply. SummaryQuality is the degree of excellence we expect of a service or a product. It is also one of the key factors that determine its value. For multimedia services, understanding the experienced quality means understanding how the delivered fidelity, precision and reliability correspond to the users' expectations. Yet the quality of multimedia services is inextricably linked to the underlying technology. It is developments in video recording, compression and transport as well as display technologies that enables high quality multimedia services to become ubiquitous. The constant evolution of these technologies delivers a steady increase in performance, but also a growing level of complexity. As new technologies stack on top of each other the interactions between them and their components become more intricate and obscure. In this environment optimizing the delivered quality of multimedia services becomes increasingly challenging. The factors that affect the experienced quality, or Quality of Experience (QoE), tend to have complex non-linear relat...

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Section: Qoe Definitionmentioning

confidence: 99%

Computational Inference and Control of Quality in Multimedia Services

Menkovski

2015

Springer Theses

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“…The QoE measurement measures service delivery from the customer's perspective [14,15]: it is influenced by factors spanning the service plane; most of which are not subject to frequent change [11]. An accurate QoE measurement is of interest to service providers as it indicates how IPTV performs compared to the customer's expectation of how it should perform [10].…”

Section: Related Work: Iptv Monitoringmentioning

confidence: 99%

Integration of QoS Metrics, Rules and Semantic Uplift for Advanced IPTV Monitoring

et al. 2014

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Increasing and variable traffic demands due to triple play services pose significant Internet Protocol Television (IPTV) resource management challenges for service providers. Managing subscriber expectations via consolidated IPTV quality reporting will play a crucial role in guaranteeing return-on-investment for players in the increasingly competitive IPTV delivery ecosystem. We propose a fault diagnosis and problem isolation solution that addresses the IPTV monitoring challenge and recommends problem-specific remedial action. IPTV delivery-specific metrics are collected at various points in the delivery topology, the residential gateway and the Digital Subscriber Line Access Multiplexer (DSLAM) through to the video Head-End. They are then pre-processed using new metric rules. A semantic uplift engine takes these raw metric logs; it then transforms them into World Wide Web Consortium (W3C)'s standard Resource Description Framework (RDF) for knowledge representation and annotates them with expert knowledge from the IPTV domain. This system is then integrated with a monitoring visualization framework that displays monitoring events, alarms, and recommends solutions. A suite of IPTV fault scenarios is presented and used to evaluate the feasibility of the solution. We demonstrate that professional service providers can provide timely reports on the quality of IPTV service delivery using this system.Neither the entire paper nor any part of its content has been published or has been accepted for publication elsewhere. It has not been submitted to any other journal.

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“…Secondly, current QoE models including those promoted by standardisation bodies [11], do not focus on 5G networks where additional challenges such as virtualisation, mobility and multi-tenancy requirements exist.…”

Section: Introductionmentioning

confidence: 99%

5G-QoE: QoE Modelling for Ultra-HD Video Streaming in 5G Networks

Nightingale

Salvá-García

Calero

et al. 2018

IEEE Trans. on Broadcast.

148

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This version is available at https://strathprints.strath.ac.uk/65207/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. IEEE Transactions on BroadcastingPaper Identification Number BTS-yr-xxx (DOUBLE-CLICK HERE TO EDIT) 1  Abstract-Traffic on future Fifth-Generation (5G) mobile networks is predicted to be dominated by challenging video applications such as mobile broadcasting, remote surgery and augmented reality, demanding real-time and ultra-high quality delivery. Two of the main expectations of 5G networks are that they will be able to handle Ultra High Definition (UHD) video streaming and that they will deliver services that meet the requirements of the end user's perceived quality by adopting Quality of Experience (QoE) aware network management approaches. This paper proposes a 5G-QoE framework to address the QoE modelling for UHD video flows in 5G networks. Particularly, it focuses on providing a QoE prediction model that is both sufficiently accurate and of low enough complexity to be employed as a continuous real-time indicator of the 'health' of video applications flows at the scale required in future 5G networks. The model has been developed and implemented as part of the EU 5G PPP SELFNET autonomic management framework, where it provides a primary indicator of the likely perceptual quality of UHD video application flows traversing a realistic multi-tenanted 5G mobile edge network testbed. The proposed 5G-QoE framework has been implemented in the 5G testbed, and the high accuracy of QoE prediction has been validated through comparing the predicted QoE values with not only subjective testing results but also empirical measurements in the testbed. As such, 5G-QoE would enable a holistic video flow self-optimisation system employing the cutting-edge Scalable H.265 video encoding to transmit UHD video applications in a QoE-aware manner.Index Terms-QoE, 5G networks, video streaming, UHD.

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Standardization activities in the ITU for a QoE assessment of IPTV

Cited by 180 publications

References 5 publications

Computational Inference and Control of Quality in Multimedia Services

Computational Inference and Control of Quality in Multimedia Services

Integration of QoS Metrics, Rules and Semantic Uplift for Advanced IPTV Monitoring

5G-QoE: QoE Modelling for Ultra-HD Video Streaming in 5G Networks

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