11 research outputs found

    Adaptive Streaming: A subjective catalog to assess the performance of objective QoE metrics

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    Scalable streaming has emerged as a feasible solution to resolve users' heterogeneity problems. SVC is the technology that has served as the definitive impulse for the growth of streaming adaptive systems. Systems seek to improve layer switching efficiency from the network point of view but, with increasing importance, without jeopardizing user perceived video quality, i.e., QoE. We have performed extensive subjective experiments to corroborate the preference towards adaptive systems when compared to traditional non-adaptive systems. The resulting subjective scores are correlated with most relevant Full Reference (FR) objective metrics. We obtain an exponential relationship between human decisions and the same decisions expressed as a difference of objective metrics. A strong correlation with subjective scores validates objective metrics to be used as aid in the adaptive decision taking algorithms to improve overall systems performance. Results show that, among the evaluated objective metrics, PSNR is the metric that provide worse results in terms of reproducing the human decision

    Analysis of User Experience in Mobile Video Watching Scenarios

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    Mobiilin videon katselu on mobiilin verkkoliikenteen suurimpia kasvattajia. Lisäksi niin mobiiliverkon kuin mobiilien päätelaitteiden teknologia on kehittynyt niin pitkälle, että omalla älypuhelimella on mahdollista seurata teräväpiirtoisia videolähetyksiä verkon yli. Nämä asettavat haasteita käyttäjäkokemukselle. Tämän diplomityön tarkoituksena on tutkia seikkoja, jotka vaikuttavat mobiilin videonkatselun käyttäjäkokemukseen sekä perehtyä yleisesti käyttäjäkokemukseen, palvelun ja kokemuksen laadun käsitteisiin. Tavoitteena oli myös luoda teoreettinen malli sille, miten käyttäjäkokemusta voidaan mallintaa ottamatta käyttäjä ja hänen näkökulmaa mukaan tutkimusprosessiin. Työssä kehitettiin kolmijakoinen malli kuvaamaan mobiilin videonkatselun käyttäjäkokemuksen laatua teknisestä, verkon ja käyttäjän näkökulmasta. Mallista otettiin teknisen ulottuvuuden osalta lähempään tarkasteluun bittinopeuden, viiveen ja näiden vaihtelun pohjalle luotu matemaattinen malli, jota testattiin skenaarioanalyysin voimin. Tämän mallin pääpaino on kirjallisuustutkimuksen perustella tärkeäksi havaittu bittinopeus. Skenaariot olivat paikallaololle, liikkeelle hyvissä verkko-olosuhteissa ja liikkeelle huonoissa verkko-olosuhteissa ja mittausdata saatiin nettitutka sovelluksesta, jonka avulla mitataan verkkoyhteyksien laatua käyttäjien keräämän datan avulla. Malli ennusti hyvää käyttäjäkokemusta niin paikalla- kuin liikkeelläololle suotuisissa verkko-olosuhteissa ja heikkoa käyttäjäkokemusta haastaviin verkko-olosuhteisiin.Mobile data traffic grows rapidly each passing year and the biggest contributor to this trend is mobile video watching. Additionally, mobile technologies both in network and end-user device sector have evolved quickly in the passing years allowing users to watch even high quality and high definition video streams from their mobile devices. However, since there are limits to bandwidth, this creates challenges for user experience. The purpose of this thesis is to find out which factors affect user experience in mobile video watching scenarios. Second purpose was creating a model based on what was found in the academic literature to describe user experience in mobile video watching and help analyse it. Model is three-fold and has dimensions in video and connection’s technical aspects, network and operator aspects as well as in user aspects. User experience model was further specified in a mathematical way to describe bitrate’s and delay’s effect on user experience. These were the aspects, according to the academic literature, that weigh most when watching streamed video online on a mobile device. This mathematical model was tested using scenario analysis where there were three scenarios: stationary, moving with good connection and moving with bad connection. The model forecast excellent or good user experience in the first two scenarios and weak or bad user experience in the last scenario

    Протокол обмена данными в самоорганизующихся вычислительных средах

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    Работа посвящена разработке протокола обмена данными для самоорганизующихся вычислительных сред с минимальным временем задержки. Этот протокол предполагается реализовывать для сетей мобильных устройств на базе метода окрестностей. Протокол предусматривает разметку конфигурации и построение маршрута при помощи двух широковещательных запросов. Один из запросов исходит от узла в начале маршрута, другой от конечной точки. Метод окрестностей позволил выбрать типы данных и размеры полей заголовка коммуникационных пакетов. Работа содержит обоснование метрики, применяемой для выбора маршрута.Работа выполнена в рамках государственного задания Министерства образования и науки РФ и при поддержке гранта РФФИ № 16-07-00218а

    Empirical studies of Quality of Experience (QoE) : A Systematic Literature Survey

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    Quality of Experience (QoE) is a relatively new phenomenon. The main focus of this thesis has been to conduct a systematic literature survey of research done in the field of QoE over a ten year period. The method, developed by A. Fink, has been used to survey empirical studies. A framework of QoE has been developed, which created the possibility of grouping together and analysing all the studies in a common framework. In total, 44 studies were analysed. 66 per cent of them were studies with human participants and 34 per cent of them were studies without human participants. The majority of the selected empirical studies have analysed the sub-aspect ‘satisfaction’. Among other vital sub-aspects, which were of interest to researches, were ‘usefulness’, ‘ease of use’, ‘communication’, ‘loss/packet loss’, ‘delay’, ‘bandwidth’, and ‘jitter’. The results of this survey show that different sub-aspects depend on different services. It is not enough that one sub-aspect functions very well, because most of sub-aspects are closely related to each other. Therefore, it is very important that sub-aspects, which are dependent on each other, are functioning as one group to achieve higher QoE on user experience. This thesis may contribute to deeper understanding of the phenomenon QoE. Knowledge of QoE can bring in new ideas and new possibilities for developing a new system or products for achieving satisfaction of user experience

    Interface diversity for enhanced quality of experience in home networks

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    Most of the modern home-networking devices have multiple interfaces, e.g., WiFi, PLC, Ethernet, for connection. These devices constitute an in home heterogeneous mesh network. Channel aggregation and routing between these mesh-nodes are critical challenges that have potential to improve application quality. In order to aggregate the channels and nd a best route, variety of parameters, such as interference, link quality and access technology must be considered. In this work, we propose to use multiple interfaces as an apparatus of diversity to enhance the Quality of Experience of video streaming users. The proposed method, Interface Diversity, provides full-redundancy, and thus, not only decreases the packet loss, and average delay but also increases the saturation throughput. We formulated a multi-radio mesh network considering Interface Diversity. Centralized solutions are obtained for di erent network scenarios. Then, the distributed end-to-end routing using the Interface Diversity method and AODV is implemented by modifying a wellknown multi-radio routing method available in the literature. The performance of our interface diversity method and the proposed routing method are validated by extensive simulations in OPNET

    Cross-layer optimisation of quality of experience for video traffic

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    Realtime video traffic is currently the dominant network traffic and is set to increase in volume for the foreseeable future. As this traffic is bursty, providing perceptually good video quality is a challenging task. Bursty traffic refers to inconsistency of the video traffic level. It is at high level sometimes while is at low level at some other times. Many video traffic measurement algorithms have been proposed for measurement-based admission control. Despite all of this effort, there is no entirely satisfactory admission algorithm for variable rate flows. Furthermore, video frames are subjected to loss and delay which cause quality degradation when sent without reacting to network congestion. The perceived Quality of Experience (QoE)-number of sessions trade-off can be optimised by exploiting the bursty nature of video traffic. This study introduces a cross-layer QoE-aware optimisation architecture for video traffic. QoE is a measure of the user's perception of the quality of a network service. The architecture addresses the problem of QoE degradation in a bottleneck network. It proposes that video sources at the application layer adapt their rate to the network environment by dynamically controlling their transmitted bit rate. Whereas the edge of the network protects the quality of active video sessions by controlling the acceptance of new sessions through a QoE-aware admission control. In particular, it seeks the most efficient way of accepting new video sessions and adapts sending rates to free up resources for more sessions whilst maintaining the QoE of the current sessions. As a pathway to the objective, the performance of the video flows that react to the network load by adapting the sending rate was investigated. Although dynamic rate adaptation enhances the video quality, accepting more sessions than a link can accommodate will degrade the QoE. The video's instantaneous aggregate rate was compared to the average aggregate rate which is a calculated rate over a measurement time window. It was found that there is no substantial difference between the two rates except for a small number of video flows, long measurement window, or fast moving contents (such as sport), in which the average is smaller than the instantaneous rate. These scenarios do not always represent the reality. The finding discussed above was the main motivation for proposing a novel video traffic measurement algorithm that is QoE-aware. The algorithm finds the upper limit of the video total rate that can exceed a specific link capacity without the QoE degradation of ongoing video sessions. When implemented in a QoE-aware admission control, the algorithm managed to maintain the QoE for a higher number of video session compared to the calculated rate-based admission controls such as the Internet Engineering Task Force (IETF) standard Pre-Congestion Notification (PCN)-based admission control. Subjective tests were conducted to involve human subjects in rating of the quality of videos delivered with the proposed measurement algorithm. Mechanisms proposed for optimising the QoE of video traffic were surveyed in detail in this dissertation and the challenges of achieving this objective were discussed. Finally, the current rate adaptation capability of video applications was combined with the proposed QoE-aware admission control in a QoE-aware cross-layer architecture. The performance of the proposed architecture was evaluated against the architecture in which video applications perform rate adaptation without being managed by the admission control component. The results showed that our architecture optimises the mean Mean Opinion Score (MOS) and number of successful decoded video sessions without compromising the delay. The algorithms proposed in this study were implemented and evaluated using Network Simulator-version 2 (NS-2), MATLAB, Evalvid and Evalvid-RA. These software tools were selected based on their use in similar studies and availability at the university. Data obtained from the simulations was analysed with analysis of variance (ANOVA) and the Cumulative Distribution Functions (CDF) for the performance metrics were calculated. The proposed architecture will contribute to the preparation for the massive growth of video traffic. The mathematical models of the proposed algorithms contribute to the research community

    Video Quality Prediction for Video over Wireless Access Networks (UMTS and WLAN)

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    Transmission of video content over wireless access networks (in particular, Wireless Local Area Networks (WLAN) and Third Generation Universal Mobile Telecommunication System (3G UMTS)) is growing exponentially and gaining popularity, and is predicted to expose new revenue streams for mobile network operators. However, the success of these video applications over wireless access networks very much depend on meeting the user’s Quality of Service (QoS) requirements. Thus, it is highly desirable to be able to predict and, if appropriate, to control video quality to meet user’s QoS requirements. Video quality is affected by distortions caused by the encoder and the wireless access network. The impact of these distortions is content dependent, but this feature has not been widely used in existing video quality prediction models. The main aim of the project is the development of novel and efficient models for video quality prediction in a non-intrusive way for low bitrate and resolution videos and to demonstrate their application in QoS-driven adaptation schemes for mobile video streaming applications. This led to five main contributions of the thesis as follows:(1) A thorough understanding of the relationships between video quality, wireless access network (UMTS and WLAN) parameters (e.g. packet/block loss, mean burst length and link bandwidth), encoder parameters (e.g. sender bitrate, frame rate) and content type is provided. An understanding of the relationships and interactions between them and their impact on video quality is important as it provides a basis for the development of non-intrusive video quality prediction models.(2) A new content classification method was proposed based on statistical tools as content type was found to be the most important parameter. (3) Efficient regression-based and artificial neural network-based learning models were developed for video quality prediction over WLAN and UMTS access networks. The models are light weight (can be implemented in real time monitoring), provide a measure for user perceived quality, without time consuming subjective tests. The models have potential applications in several other areas, including QoS control and optimization in network planning and content provisioning for network/service providers.(4) The applications of the proposed regression-based models were investigated in (i) optimization of content provisioning and network resource utilization and (ii) A new fuzzy sender bitrate adaptation scheme was presented at the sender side over WLAN and UMTS access networks. (5) Finally, Internet-based subjective tests that captured distortions caused by the encoder and the wireless access network for different types of contents were designed. The database of subjective results has been made available to research community as there is a lack of subjective video quality assessment databases.Partially sponsored by EU FP7 ADAMANTIUM Project (EU Contract 214751

    Video Content-Based QoE Prediction for HEVC Encoded Videos Delivered over IP Networks

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    The recently released High Efficiency Video Coding (HEVC) standard, which halves the transmission bandwidth requirement of encoded video for almost the same quality when compared to H.264/AVC, and the availability of increased network bandwidth (e.g. from 2 Mbps for 3G networks to almost 100 Mbps for 4G/LTE) have led to the proliferation of video streaming services. Based on these major innovations, the prevalence and diversity of video application are set to increase over the coming years. However, the popularity and success of current and future video applications will depend on the perceived quality of experience (QoE) of end users. How to measure or predict the QoE of delivered services becomes an important and inevitable task for both service and network providers. Video quality can be measured either subjectively or objectively. Subjective quality measurement is the most reliable method of determining the quality of multimedia applications because of its direct link to users’ experience. However, this approach is time consuming and expensive and hence the need for an objective method that can produce results that are comparable with those of subjective testing. In general, video quality is impacted by impairments caused by the encoder and the transmission network. However, videos encoded and transmitted over an error-prone network have different quality measurements even under the same encoder setting and network quality of service (NQoS). This indicates that, in addition to encoder settings and network impairment, there may be other key parameters that impact video quality. In this project, it is hypothesised that video content type is one of the key parameters that may impact the quality of streamed videos. Based on this assertion, parameters related to video content type are extracted and used to develop a single metric that quantifies the content type of different video sequences. The proposed content type metric is then used together with encoding parameter settings and NQoS to develop content-based video quality models that estimate the quality of different video sequences delivered over IP-based network. This project led to the following main contributions: (1) A new metric for quantifying video content type based on the spatiotemporal features extracted from the encoded bitstream. (2) The development of novel subjective test approach for video streaming services. (3) New content-based video quality prediction models for predicting the QoE of video sequences delivered over IP-based networks. The models have been evaluated using subjective and objective methods

    Análisis de la calidad experimentada en aplicaciones de voz sobre IP de libre distribución

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    En este proyecto el trabajo que se ha realizado ha consistido en determinar los parámetros de la red que determinan la calidad de servicio de las aplicaciones de VoIP y comparar los resultados obtenidos con las encuestas realizadas a un número de personas. Para ello, primeramente se ha realizado un estudio de las características y funcionamiento de los protocolos para VoIP. Seguidamente se eligieron 5 aplicaciones de VoIP y se realizaron capturas de su transferencia de paquetes. Con estos datos se ha podido calcular los parámetros de la red y se ha establecido de este modo la calidad de servicio ofrecida. El análisis de las aplicaciones se realizará mediante capturas con la herramienta wireshark, que serán analizadas posteriormente utilizando awk. Por otro lado para medir la QoE se han realizado encuestas de las mismas aplicaciones a un número elevado de personas. Con estos datos, hemos podido establecer una comparación de los resultados obtenidos en ambos estudios para realizar una posterior conclusión de los mismos.Escuela Técnica Superior de Ingeniería de Telecomunicació
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