Atualmente existem inúmeros serviços multimídia que são transportados através da rede IP, dos quais, o tráfego dos serviços de vídeo experimentou um maior crescimento nos últimos anos. O sucesso de aplicações de streaming de vídeo é um dos fatores pelo qual, este tráfego se incrementou. Alguns recentes estudos projetam que este tipo de serviços no ano 2016, alcançará aproximadamente o 55% do tráfego total da Internet. Considerando a importância que os serviços de vídeo alcançarão nos próximos anos, este trabalho foca-se na avaliação da qualidade de experiência (QoE) dos usuários ao utilizar estes serviços. Assim, nesta tese é proposta uma métrica de avaliação de vídeo denominada eVsQM, do inglês enhanced Video streaming Quality Metric, a qual é baseada principalmente no número, duração e localização temporal dos congelamentos de imagens (pausas) durante uma transmissão de vídeo, considerando também o tipo de conteúdo do vídeo transmitido. Esta métrica foi determinada a partir de um modelo matemático que utilizou os resultados de testes subjetivos de avaliação de vídeo, pois, este tipo de testes são os que melhor se aproximam da QoE real do usuário. Cabe destacar, que na realização dos testes subjetivos foi utilizada uma metodologia concordante com o tipo de degradação que o vídeo possui, ou seja, a pausa. No streaming de vídeo novas soluções são criadas com a finalidade de melhorar a QoE do usuário. O DASH, do inglês Dynamic Adaptive Streaming over HTTP, muda a resolução do vídeo transmitido de acordo com as características da rede. Porém, se a rede é muito flutuante existirão muitas variações de resolução e a QoE do usuário será degradada. Neste trabalho é proposto um parâmetro a ser utilizado no algoritmo DASH que funciona como um limiar para controlar a frequência destas comutações de resolução. Este parâmetro é denominado como SDF (do inglês Switching Degradation Factor) e permite que a QoE mantida em níveis aceitáveis, inclusive em situações onde a rede é muito flutuante. Adicionalmente, neste trabalho é proposto um novo modelo de faturamento nos serviços de telecomunicações, que inclua no processo de tarifação um parâmetro relacionado com a QoE, visando ter uma tarifação de serviços de comunicações mais justa do ponto de vista dos usuários. Desta forma, usuários que recebem uma menor qualidade no serviço devem pagar menos em relação aos usuários que recebem uma melhor qualidade do mesmo serviço. / Nowadays, there are several multimedia services, which are carried via IP networks. From these all services; the traffic regarding video applications had the greatest growth in the last years. The success of video streaming applications is one of the major contributors to video traffic growth. Some recent studies project that video services, will reach approximately 55% of the total Internet traffic in 2016. Considering the relevance that video services will achieve in the coming years, this work focuses on the users Quality of Experience (QoE) when using these services. Thus, this thesis proposes an evaluation metric named enhanced Video streaming Quality Metric (eVsQM), which is based primarily on the number, duration and temporal location of the image freezes (pauses) during a video transmission. Also, this metric considers the video content type and was determined from a mathematical model that used as inputs, the video quality assessment results from subjective tests due, these types of test are the most correlated with real users QoE. It is worth noting that to perform these subjective tests was used a methodology consistent with the kind of video degradation (pause). For another hand, new video streaming solutions are created for the purpose of improving the users QoE of the user. Dynamic Adaptive Streaming over HTTP (DASH) changes the video resolution according to the network characteristics. However, if the network is very fluctuant, many video resolution switching events will be performed and users QoE will be degraded. This thesis proposes a parameter to be used in DASH algorithms that works as a threshold to control the resolution switching frequency. This parameter is named Switching Degradation Factor (SDF) and is responsible to maintain the QoE in acceptable levels, inclusive in scenarios in which the network capacity is very fluctuating.

A dominant source of Internet traffic, today, is constituted of compressed images. In modern multimedia communications, image compression plays an important role. Some of the image compression standards set by the Joint Photographic Expert Group (JPEG) include JPEG and JPEG2000. The expert group came up with the JPEG image compression standard so that still pictures could be compressed to be sent over an e-mail, be displayed on a webpage, and make high-resolution digital photography possible. This standard was originally based on a mathematical method, used to convert a sequence of data to the frequency domain, called the Discrete Cosine Transform (DCT). In the year 2000, however, a new standard was proposed by the expert group which came to be known as JPEG2000. The difference between the two is that the latter is capable of providing better compression efficiency. There is also a downside to this new format introduced. The computation required for achieving the same sort of compression efficiency as one would get with the original JPEG format is higher. JPEG is a lossy compression standard which can throw away some less important information without causing any noticeable perception differences. Whereas, in lossless compression, the primary purpose is to reduce the number of bits required to represent the original image samples without any loss of information. The areas of application of the JPEG image compression standard include the Internet, digital cameras, printing, and scanning peripherals. In this thesis work, a simulator kind of functionality setup is needed for conducting the objective quality assessment. An image is given as an input to our wireless communication system and its data size is varied (e.g. 5%, 10%, 15%, etc) and a Signal-to-Noise Ratio (SNR) value is given as input, for JPEG2000 compression. Then, this compressed image is passed through a JPEG encoder and then transmitted over a Rayleigh fading channel. The corresponding image obtained after having applied these constraints on the original image is then decoded at the receiver and inverse discrete wavelet transform (IDWT) is applied to inverse the JPEG 2000 compression. Quantization is done for the coefficients which are scalar-quantized to reduce the number of bits to represent them, without the loss of quality of the image. Then the final image is displayed on the screen. The original input image is co-passed with the images of varying data size for an SNR value at the receiver after decoding. In particular, objective perceptual quality assessment through Structural Similarity (SSIM) index using MATLAB is provided.

Atualmente existem inúmeros serviços multimídia que são transportados através da rede IP, dos quais, o tráfego dos serviços de vídeo experimentou um maior crescimento nos últimos anos. O sucesso de aplicações de streaming de vídeo é um dos fatores pelo qual, este tráfego se incrementou. Alguns recentes estudos projetam que este tipo de serviços no ano 2016, alcançará aproximadamente o 55% do tráfego total da Internet. Considerando a importância que os serviços de vídeo alcançarão nos próximos anos, este trabalho foca-se na avaliação da qualidade de experiência (QoE) dos usuários ao utilizar estes serviços. Assim, nesta tese é proposta uma métrica de avaliação de vídeo denominada eVsQM, do inglês enhanced Video streaming Quality Metric, a qual é baseada principalmente no número, duração e localização temporal dos congelamentos de imagens (pausas) durante uma transmissão de vídeo, considerando também o tipo de conteúdo do vídeo transmitido. Esta métrica foi determinada a partir de um modelo matemático que utilizou os resultados de testes subjetivos de avaliação de vídeo, pois, este tipo de testes são os que melhor se aproximam da QoE real do usuário. Cabe destacar, que na realização dos testes subjetivos foi utilizada uma metodologia concordante com o tipo de degradação que o vídeo possui, ou seja, a pausa. No streaming de vídeo novas soluções são criadas com a finalidade de melhorar a QoE do usuário. O DASH, do inglês Dynamic Adaptive Streaming over HTTP, muda a resolução do vídeo transmitido de acordo com as características da rede. Porém, se a rede é muito flutuante existirão muitas variações de resolução e a QoE do usuário será degradada. Neste trabalho é proposto um parâmetro a ser utilizado no algoritmo DASH que funciona como um limiar para controlar a frequência destas comutações de resolução. Este parâmetro é denominado como SDF (do inglês Switching Degradation Factor) e permite que a QoE mantida em níveis aceitáveis, inclusive em situações onde a rede é muito flutuante. Adicionalmente, neste trabalho é proposto um novo modelo de faturamento nos serviços de telecomunicações, que inclua no processo de tarifação um parâmetro relacionado com a QoE, visando ter uma tarifação de serviços de comunicações mais justa do ponto de vista dos usuários. Desta forma, usuários que recebem uma menor qualidade no serviço devem pagar menos em relação aos usuários que recebem uma melhor qualidade do mesmo serviço. / Nowadays, there are several multimedia services, which are carried via IP networks. From these all services; the traffic regarding video applications had the greatest growth in the last years. The success of video streaming applications is one of the major contributors to video traffic growth. Some recent studies project that video services, will reach approximately 55% of the total Internet traffic in 2016. Considering the relevance that video services will achieve in the coming years, this work focuses on the users Quality of Experience (QoE) when using these services. Thus, this thesis proposes an evaluation metric named enhanced Video streaming Quality Metric (eVsQM), which is based primarily on the number, duration and temporal location of the image freezes (pauses) during a video transmission. Also, this metric considers the video content type and was determined from a mathematical model that used as inputs, the video quality assessment results from subjective tests due, these types of test are the most correlated with real users QoE. It is worth noting that to perform these subjective tests was used a methodology consistent with the kind of video degradation (pause). For another hand, new video streaming solutions are created for the purpose of improving the users QoE of the user. Dynamic Adaptive Streaming over HTTP (DASH) changes the video resolution according to the network characteristics. However, if the network is very fluctuant, many video resolution switching events will be performed and users QoE will be degraded. This thesis proposes a parameter to be used in DASH algorithms that works as a threshold to control the resolution switching frequency. This parameter is named Switching Degradation Factor (SDF) and is responsible to maintain the QoE in acceptable levels, inclusive in scenarios in which the network capacity is very fluctuating.

Subjective video quality and video decoding complexity are jointly optimized in order to determine the video encoding parameters that will result in the best Quality of Experience (QoE) for an end user watching a video clip on a mobile device. Subjective video quality is estimated by an objective criteria, video quality metric (VQM), and a method for predicting the video quality of a test sequence from the available training sequences with similar content characteristics is presented. Standardized spatial index and temporal index metrics are utilized in order to measure content similarity. A statistical approach for modeling decoding complexity on a hardware platform using content features extracted from video clips is presented. The overall decoding complexity is modeled as the sum of component complexities that are associated with the computation intensive code blocks present in state-of-the-art hybrid video decoders. The content features and decoding complexities are modeled as random parameters and their joint probability density function is predicted as Gaussian Mixture Models (GMM). These GMMs are obtained off-line using a large training set comprised of video clips. Subsequently, decoding complexity of a new video clip is estimated by using the available GMM and the content features extracted in real time. A novel method to determine the video decoding capacity of mobile terminals by using a set of subjective decodability experiments that are performed once for each device is also proposed. Finally, the estimated video quality of a content and the decoding capacity of a device are combined in a utility-complexity framework that optimizes complexity-quality trade-off to determine video coding parameters that result in highest video quality without exceeding the hardware capabilities of a client device. The simulation results indicate that this approach is capable of predicting the user viewing satisfaction on a mobile device.

Today, the fulfillment of customer demands and user experience requirements are becoming the main differentiators for gauging the effectiveness of telecom operators and service providers. In this competitive market, the poor Quality of Experience (QoE) leads to a chain reaction of negative word of mouth, pushing customers into the arms of waiting competitors. Therefore it is important for service providers to ensure superior quality of experience in order to avoid customer disloyalty and negative reputation. QoE is a fast emerging multi-disciplinary field focused on understanding overall human quality requirements from different angles such as technology, business and context of use. The first and foremost challenge is to understand how different influencing characteristics related to business, technology, and context influence human behavior. In this thesis, initial work addresses this challenge of understanding the influence of disparate domains over QoE. A consolidated QoE interaction model is proposed which links disparate domains (human, business, technology, and context) to understand overall human quality of experience requirements. Then taxonomy is presented for QoE interaction model. Second contribution in this thesis is based on the first and its main objective is to capture and analyze QoE data through user studies. Based on user data, the influence of technological, contextual and business parameters over QoE are evaluated. Different multimedia services were selected for user study such as video streaming service, telephony (VoIP and PSTN), and 3D audio teleconferencing service. Depending upon multimedia service, different aspects were considered during each user study such as types of multimedia service parameters (QoS, content, context), the types of QoE metrics (subjective, objective cognitive or both), human characteristics (age, gender etc), and human roles (user, or customer). These findings help in understanding the link between QoE and other influencing domains. The third contribution is based upon ongoing work of developing QoE based tools for video streaming services. Two QoE based tools for the assessment of multimedia services have been presented in this thesis, their main functions are to capture, analyze and report QoE metrics in real time. These QoE tools are useful for real time measurement of QoE metrics

Haptic-based Virtual Reality (VR) applications have many merits. What is still obscure, from the designer’s perspective of these applications, is the experience the users will undergo when they use the VR system. Quality of Experience (QoE) is an evaluation metric from the user’s perspective that unfortunately has received limited attention from the research community. Assessing the QoE of VR applications reflects the amount of overall satisfaction and benefits gained from the application in addition to laying the foundation for ideal user-centric design in the future. In this thesis, we address certain issues and concerns regarding QoE of virtual environments. In essence, we propose a taxonomy for the evaluation of the QoE for multimedia applications and in particular VR applications. The taxonomy classifies QoE related parameters into groups. The groups’ organization is generated from the definition we have adopted for the QoE which is the Quality of Service (QoS) plus the user experience (UX). We model this taxonomy using first mathematical modeling based on weighted averages and then a Fuzzy logic Inference System (FIS) to quantitatively measure the QoE of haptic virtual environments. We test both models conducting user study analysis to evaluate the QoE of a VR application. These models serve as engines that facilitate the calculation of QoE with minimal amount of users. We specifically attend to the issue of the new media, haptics, within the context of increasing the QoE of virtual environments (VE). This special attention is important for comparing the effect of tactile and kinesthetic feedback on the QoE. In accordance, we investigate a particular topic that seems to have a colossal effect on QoE throughout our analysis, which is fatigue. Our analysis involved users' studies since the main focus is on the user. The QoE for virtual environments is in its primary stages. This thesis tackles issues that are vital in dealing with and understanding the importance of QoE. The various results suggest a positive user's disposition toward haptics and virtual environments, yet there will always be obstacles and challenges such as fatigue that if minimized will enhance the QoE of haptic-based applications.

Dans un contexte fortement concurrentiel, l'un des principaux enjeux pour les opérateurs et les fournisseurs de services de visiophonie est de garantir aux utilisateurs une qualité d'expérience (QoE) optimale. Il existe un fort besoin d'une mesure qui reflète la satisfaction et la perception des utilisateurs de ces services. La qualité audiovisuelle d'un appel vidéo doit être contrôlée pour répondre à deux besoins principaux. Le premier concerne la planification de nouvelles technologies en cours de développement. Le second est axé sur le contrôle des communications existantes en évaluant la qualité des services offerts. Aujourd'hui, deux approches sont utilisées pour évaluer la qualité audiovisuelle : les tests subjectifs en collectant des notes données par des participants sur des échelles de qualité, après visualisation et écoute de séquences audiovisuelles et les métriques objectives basées sur des algorithmes automatiques d'évaluation de la qualité d'un signal audio, vidéo ou audiovisuel. Concernant les services de téléphonie, des décennies de recherche, de standardisation et d'exploitation des réseaux ont permis aux opérateurs de maîtriser les outils de diagnostic et de déterminer les métriques représentatives de la qualité vocale. Cependant, les méthodes de mesure de la qualité audiovisuelle des services conversationnels ne sont pas encore matures et peu exploitées par les opérateurs de télécommunication. Le présent travail est centré sur la recherche de métriques représentatives de la perception de la qualité des nux associés aux services de visiophonie et de visioconférence. Ces métriques objectives sont calculées à partir du signal audio et vidéo. Des tests subjectifs sont menés afin de collecter le jugement des utilisateurs du service sur la qualité perçue en fonction de différents niveaux de dégradations. Nous avons étudié l'impact des conditions réseau (perte de paquet, gigue et désynchronisation) sur la QoE d'un appel vidéo. Le principe général est ensuite d'établir une corrélation forte entre les métriques objectives sélectionnées et la qualité perçue telle qu'elle est exprimée par les utilisateurs. Les résultats ont montré que les nouvelles métriques de qualité globale audiovisuelle qui prennent en compte l'aspect temporel de la vidéo sont plus performantes que les métriques basées qualité d'images. D'autre part l'utilisation d'une approche machine learning représente une solution pour générer un modèle de prédiction de la qualité globale à partir des métriques de dégradation (flou, pixellisation, gel d'images, ... ) / In a highly competitive environment, one of the key challenges for operators and providers of video telephony services is to ensure the highest quality of experience (QoE). There is a strong need for a measure that reflects users satisfaction and perception of these services. The audio-visual quality of a video call must be controlled to meet two main needs. The first concerns the planning of new technologies under development. The second is focused on the control of existing communications by assessing the quality of the services offered and evaluating them. Two approaches are used to evaluate audio-visual quality: subjective tests by collecting scores given by participants on quality scales, after viewing and listening to audiovisual sequences and objective metrics based on automatic audio/ video or audiovisual quality evaluation algorithms. Concerning telephony services, decades of research, standardization work and network exploitation, have allowed operators to master the automatic monitoring tools and to determine the representative metrics of voice quality. However, the metrics for measuring the audiovisual quality of a conversational services are not yet mature and not exploited by telecommunication operators. The present work focuses on finding representative metrics of the perception of the video telephony anc videoconferencing services quality. These objective metrics are calculated from the audio and video signals. Subjective tests are conducted to collect the judgment of service users on the perceived quality according to different levels of degradation. We studied the impact of network conditions (packet loss, jitter and desynchronization) on the QoE of a video call. The general principle is then to establish a correlation between the selected objective metrics and the perceived quality as expressed by the users. The results showed that new metric of overall audiovisual quality that take into account the temporal aspect of video are more powerful than image quality based metrics. On the other hand, the use of a machine learning approach represents a solution to generat a global quality prediction model from the degradation metrics (blur, pixelization, image freezing, ... )

Pour avoir une idée sur la qualité du réseau, la majorité des acteurs concernés (opérateurs réseau, fournisseurs de service) se basent sur la Qualité de Service (Quality of Service). Cette mesure a montré des limites et beaucoup d’efforts ont été déployés pour mettre en place une nouvelle métrique qui reflète, de façon plus précise, la qualité du service offert. Cette mesure s’appelle la qualité d’expérience (Quality of Experience). La qualité d’expérience reflète la satisfaction de l’utilisateur par rapport au service qu’il utilise. L’évaluation de la qualité d’expérience est devenue primordiale pour les fournisseurs de services et les fournisseurs de contenus. Cette nécessité nous a poussés à innover et mettre en place des nouvelles méthodes pour estimer la QoE. Dans cette thèse, nous travaillons sur l’estimation de la QoE dans le cas des communications Voix sur IP et dans le cas de la vidéo sur IP. Nous étudions les performances et la qualité des codecs iLBC, Speex et Silk pour la VoIP et les codecs MPEG-2 et H.264/SVC pour la vidéo sur IP. Nous étudions l’impact que peut avoir la majorité des paramètres réseaux, des paramètres sources (au niveau du codage) et destinations (au niveau du décodage) sur la qualité finale. Afin de mettre en place des outils précis d’estimation de la QoE en temps réel, nous nous basons sur la méthodologie Pseudo-Subjective Quality Assessment. La méthodologie PSQA est basée sur un modèle mathématique appelé les réseaux de neurones artificiels. En plus des réseaux de neurones, nous utilisons la régression polynomiale pour l’estimation de la QoE dans le cas de la VoIP. / Quality of Experience (QoE) is the key criteria for evaluating the Media Services. Unlike objective Quality of Service (QoS) metrics, QoE is more accurate to reflect the user experience. The Future of Internet is definitely going to be Media oriented. Towards this, there is a profound need for an efficient measure of the Quality of Experience (QoE). QoE will become the prominent metric to consider when deploying Networked Media services. In this thesis, we provide several methods to estimate the QoE of different media services: Voice and Video over IP. We study the performance and the quality of several VoIP codecs like iLBC, Speex and Silk. Based on this study, we proposed two methods to estimate the QoE in real-time context, without any need of information of the original voice sequence. The first method is based on polynomial regression, and the second one is based on an hybrid methodology (objective and subjective) called Pseudo-Subjective Quality Assessment. PSQA is based on the artificial neural network mathematical model. As for the VoIP, we propose also a tool to estimate video quality encoded with MPEG-2 and with H.264/SVC. We studied also the impact of several network parameters on the quality, and the impact of some encoding parameters on the SVC video quality. We tested also the performance of several SVC encoders and proposed some SVC encoding recommendations.

The ever increasing popularity and enormous growth in 3D movie industry is the stimulating phenomenon for the penetration of 3D services into home entertainment systems. Providing a third dimension gives intense visual experience to the viewers. Being a new eld, there are several researches going on to measure the end user's viewing experience. Research groups including 3D TV manufacturers, service providers and standards organizations are interested to improve user experience. Recent research in 3D video quality measurements have revealed uncertain issues as well as more well known results. Measuring the perceptual stereoscopic video quality by subjective testing can provide practical results. This thesis studies and investigate three di erent rating scales (Video Quality, Visual Discomfort and Sense of Presence) and compares them by subjective testing, combined with two viewing distances at 3H and 5H, where H is the hight of display screen. This thesis work shows that single rating scale produces the same result as three di erent scales and viewing distance has very less or no impact on Quality of Experience (QoE) of 3DTV for 3H and 5H distances for symmetric coding impairments. / indirajithv@gmail.com

Today, the increasing number of applications based on the Internet of Things, as well as advances in wireless communication, information and communication technology, and mobile cloud computing have allowed users to access a wide range of resources while mobile. Vehicular clouds are considered key elements for today’s intelligent transportation systems. They are outfitted with equipment to enable applications and services for vehicle drivers, surrounding vehicles, pedestrians and third parties. As vehicular cloud computing has become more popular, due to its ability to improve driver and vehicle safety and provide provisioning services and applications, researchers and industry have growing interest in the design and development of vehicular networks for emerging applications. Though vehicle drivers can now access a variety of on-demand resources en route via vehicular network service providers, the development of vehicular cloud provisioning services has many challenges. In this dissertation, we examine the most critical provisioning service challenges drivers face, including, cost, privacy and latency. To this point, very little research has addressed these issues from the driver perspective. Privacy and service latency are certainly emerging challenges for drivers, as are service costs since this is a relatively new financial concept. Motivated by the Quality of Experience paradigm and the concept of the Trusted Third Party, we identify and investigate these challenges and examine the limitations and requirements of a vehicular environment. We found no research that addressed these challenges simultaneously, or investigated their effect on one another. We have developed a Quality of Experience framework that provides scalability and reduces congestion overhead for users. Furthermore, we propose two theory-based frameworks to manage on-demand service provision in vehicular clouds: Auction-driven Multi-objective Provisioning and a Multiagent/Multiobjective Interaction Game System. We present different approaches to these, and show through analytical and simulation results that our potential schemes help drivers minimize costs and latency, and maximize privacy.