423 research outputs found
Assessing quality of experience of IPTV and video on demand services in real-life environments
The ever growing bandwidth in access networks, in combination with IPTV and video on demand (VoD) offerings, opens up unlimited possibilities to the users. The operators can no longer compete solely on the number of channels or content and increasingly make high definition channels and quality of experience (QoE) a service differentiator. Currently, the most reliable way of assessing and measuring QoE is conducting subjective experiments, where human observers evaluate a series of short video sequences, using one of the international standardized subjective quality assessment methodologies. Unfortunately, since these subjective experiments need to be conducted in controlled environments and pose limitations on the sequences and overall experiment duration they cannot be used for real-life QoE assessment of IPTV and VoD services. In this article, we propose a novel subjective quality assessment methodology based on full-length movies. Our methodology enables audiovisual quality assessment in the same environments and under the same conditions users typically watch television. Using our new methodology we conducted subjective experiments and compared the outcome with the results from a subjective test conducted using a standardized method. Our findings indicate significant differences in terms of impairment visibility and tolerance and highlight the importance of real-life QoE assessment
Packet loss characteristics of IPTV-like traffic on residential links
Packet loss is one of the principal threats to quality of experience for IPTV systems. However, the packet loss characteristics of the residential access networks which carry IPTV are not widely understood. We present packet level measurements of streaming IPTV-like traffic over four residential access links, and describe the extent and nature of packet loss we encountered. We discuss the likely impact of these losses for IPTV traffic, and outline steps which can ameliorate this
Linking an integrated framework with appropriate methods for measuring QoE
Quality of Experience (QoE) has recently gained recognition for being an important determinant of the success of new technologies. Despite the growing interest in QoE, research into this area is still fragmented. Similar - but separate - efforts are being carried out in technical as well as user oriented research domains, which are rarely communicating with each other. In this paper, we take a multidisciplinary approach and review both user oriented and technical definitions on Quality of Experience (including the related concept of User Experience). We propose a detailed and comprehensive framework that integrates both perspectives. Finally, we take a first step at linking methods for measuring QoE with this framework
Quantifying subjective quality evaluations for mobile video watching in a semi-living lab context
This paper discusses results from an exploratory study in which Quality of Experience aspects related to mobile video watching were investigated in a semi-living lab setting. More specifically, we zoom in on usage patterns in a natural research context and on the subjective evaluation of high and low-resolution movie trailers that are transferred to a mobile device using two transmission protocols for video (i.e., real-time transport protocol and progressive download using HTTP). User feedback was collected by means of short questionnaires on the mobile device, combined with traditional pen and paper diaries. The subjective evaluations regarding the general technical quality, perceived distortion, fluentness of the video, and loading speed are studied and the influence of the transmission protocol and video resolution on these evaluations is analyzed. Multinomial logistic regression results in a model to estimate the subjective evaluations regarding the perceived distortion and loading speed based on objectively-measured parameters of the video session
A global customer experience management architecture
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. A. Cuadra-Sanchez, M. Cutanda-Rodriguez, I. Perez-Mateos, A. Aurelius, K. Brunnstrom, J. Laulajainen, M. Varela, and J. E. López de Vergara, "A global customer experience management architecture", in Future Network and Mobile Summit, 2012, 1-8The quality of experience (QoE) is one of the main research lines in ITC
industry, which seeks to manage quality as perceived by users. This document
analyzes and describes requirements of a QoE driven management system
architecture, which has been designed in the Celtic IPNQSIS project. The
architecture is grouped into different levels: Data acquisition level, Monitoring level
and Control Level. Each level comprises a specific set of capacities, such as Data
collector, or Traffic Monitor amongst others. The architecture described in this paper
constitutes the guidelines of the IPNQSIS project in terms of a QoE ecosystem that
will settle the basis of global customer experience management architecture.This work is carried out in the framework of the Celtic and EUREKA initiative IPNQSIS
(IP Network Monitoring for Quality of Service Intelligent Support) and has been partially
funded by CDTI under Spanish PRINCE (PRoducto INdustrial para la gestión de la
Calidad de Experiencia) project, meanwhile the Swedish part of the project is co funded by
VINNOVA and the work of Finnish partners has been partially funded by Tekes
QoE Modelling, Measurement and Prediction: A Review
In mobile computing systems, users can access network services anywhere and
anytime using mobile devices such as tablets and smart phones. These devices
connect to the Internet via network or telecommunications operators. Users
usually have some expectations about the services provided to them by different
operators. Users' expectations along with additional factors such as cognitive
and behavioural states, cost, and network quality of service (QoS) may
determine their quality of experience (QoE). If users are not satisfied with
their QoE, they may switch to different providers or may stop using a
particular application or service. Thus, QoE measurement and prediction
techniques may benefit users in availing personalized services from service
providers. On the other hand, it can help service providers to achieve lower
user-operator switchover. This paper presents a review of the state-the-art
research in the area of QoE modelling, measurement and prediction. In
particular, we investigate and discuss the strengths and shortcomings of
existing techniques. Finally, we present future research directions for
developing novel QoE measurement and prediction technique
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