Apport de la Qualité de l’Expérience dans l’optimisation de services multimédia : application à la diffusion de la vidéo et à la VoIP

The emerging and fast growth of multimedia services have created new challenges for network service providers in order to guarantee the best user's Quality of Experience (QoE) in diverse networks with distinctive access technologies. Usually, various methods and techniques are used to predict the user satisfaction level by studying the combined impact of numerous factors. In this thesis, we consider two important multimedia services to evaluate the user perception, which are: video streaming service, and VoIP. This study investigates user's QoE that follows three directions: (1) methodologies for subjective QoE assessment of video services, (2) regulating user's QoE using video a rate adaptive algorithm, and (3) QoE-based power efficient resource allocation methods for Long Term Evaluation-Advanced (LTE-A) for VoIP. Initially, we describe two subjective methods to collect the dataset for assessing the user's QoE. The subjectively collected dataset is used to investigate the influence of different parameters (e.g. QoS, video types, user profile, etc.) on user satisfaction while using the video services. Later, we propose a client-based HTTP rate adaptive video streaming algorithm over TCP protocol to regulate the user's QoE. The proposed method considers three Quality of Service (QoS) parameters that govern the user perception, which are: Bandwidth, Buffer, and dropped Frame rate (BBF). The BBF method dynamically selects the suitable video quality according to network conditions and user's device properties. Lastly, we propose a QoE driven downlink scheduling method, i.e. QoE Power Escient Method (QEPEM) for LTE-A. It esciently allocates the radio resources, and optimizes the use of User Equipment (UE) power utilizing the Discontinuous Reception (DRX) method in LTE-AL'émergence et la croissance rapide des services multimédia dans les réseaux IP ont créé de nouveaux défis pour les fournisseurs de services réseau, qui, au-delà de la Qualité de Service (QoS) issue des paramètres techniques de leur réseau, doivent aussi garantir la meilleure qualité de perception utilisateur (Quality of Experience, QoE) dans des réseaux variés avec différentes technologies d'accès. Habituellement, différentes méthodes et techniques sont utilisées pour prédire le niveau de satisfaction de l'utilisateur, en analysant l'effet combiné de multiples facteurs. Dans cette thèse, nous nous intéressons à la commande du réseau en intégrant à la fois des aspects qualitatifs (perception du niveau de satisfaction de l'usager) et quantitatifs (mesure de paramètres réseau) dans l'objectif de développer des mécanismes capables, à la fois, de s'adapter à la variabilité des mesures collectées et d'améliorer la qualité de perception. Pour ce faire, nous avons étudié le cas de deux services multimédia populaires, qui sont : le streaming vidéo, et la voix sur IP (VoIP). Nous investiguons la QoE utilisateur de ces services selon trois aspects : (1) les méthodologies d'évaluation subjective de la QoE, dans le cadre d'un service vidéo, (2) les techniques d'adaptation de flux vidéo pour garantir un certain niveau de QoE, et (3) les méthodes d'allocation de ressource, tenant compte de la QoE tout en économisant l'énergie, dans le cadre d'un service de VoIP (LTE-A). Nous présentons d'abord deux méthodes pour récolter des jeux de données relatifs à la QoE. Nous utilisons ensuite ces jeux de données (issus des campagnes d'évaluation subjective que nous avons menées) pour comprendre l'influence de différents paramètres (réseau, terminal, profil utilisateur) sur la perception d'un utilisateur d'un service vidéo. Nous proposons ensuite un algorithme de streaming vidéo adaptatif, implémenté dans un client HTTP, et dont le but est d'assurer un certain niveau de QoE et le comparons à l'état de l'art. Notre algorithme tient compte de trois paramètres de QoS (bande passante, taille de mémoires tampons de réception et taux de pertes de paquets) et sélectionne dynamiquement la qualité vidéo appropriée en fonction des conditions du réseau et des propriétés du terminal de l'utilisateur. Enfin, nous proposons QEPEM (QoE Power Efficient Method), un algorithme d'ordonnancement basé sur la QoE, dans le cadre d'un réseau sans fil LTE, en nous intéressant à une allocation dynamique des ressources radio en tenant compte de la consommation énergétiqu

A quality of experience approach in smartphone video selection framework for energy efficiency

Online video streaming is getting more common in the smartphone device nowadays. Since the Corona Virus (COVID-19) pandemic hit all human across the globe in 2020, the usage of online streaming among smartphone user are getting more vital. Nevertheless, video streaming can cause the smartphone energy to drain quickly without user to realize it. Also, saving energy alone is not the most significant issues especially if with the lack of attention on the user Quality of Experience (QoE). A smartphones energy management is crucial to overcome both of these issues. Thus, a QoE Mobile Video Selection (QMVS) framework is proposed. The QMVS framework will govern the tradeoff between energy efficiency and user QoE in the smartphone device. In QMVS, video streaming will be using Dynamic Video Attribute Pre-Scheduling (DVAP) algorithm to determine the energy efficiency in smartphone devices. This process manages the video attribute such as brightness, resolution, and frame rate by turning to Video Content Selection (VCS). DVAP is handling a set of rule in the Rule Post-Pruning (RPP) method to remove an unused node in list tree of VCS. Next, QoE subjective method is used to obtain the Mean Opinion Score (MOS) of users from a survey experiment on QoE. After both experiment results (MOS and energy) are established, the linear regression technique is used to find the relationship between energy consumption and user QoE (MOS). The last process is to analyze the relationship of VCS results by comparing the DVAP to other recent video streaming applications available. Summary of experimental results demonstrate the significant reduction of 10% to 20% energy consumption along with considerable acceptance of user QoE. The VCS outcomes are essential to help users and developer deciding which suitable video streaming format that can satisfy energy consumption and user QoE

Next generation control of transport networks

It is widely understood by telecom operators and industry analysts that bandwidth demand is increasing dramatically, year on year, with typical growth figures of 50% for Internet-based traffic [5]. This trend means that the consumers will have both a wide variety of devices attaching to their networks and a range of high bandwidth service requirements. The corresponding impact is the effect on the traffic engineered network (often referred to as the “transport network”) to ensure that the current rate of growth of network traffic is supported and meets predicted future demands. As traffic demands increase and newer services continuously arise, novel network elements are needed to provide more flexibility, scalability, resilience, and adaptability to today’s transport network. The transport network provides transparent traffic engineered communication of user, application, and device traffic between attached clients (software and hardware) and establishing and maintaining point-to-point or point-to-multipoint connections. The research documented in this thesis was based on three initial research questions posed while performing research at British Telecom research labs and investigating control of transport networks of future transport networks: 1. How can we meet Internet bandwidth growth yet minimise network costs? 2. Which enabling network technologies might be leveraged to control network layers and functions cooperatively, instead of separated network layer and technology control? 3. Is it possible to utilise both centralised and distributed control mechanisms for automation and traffic optimisation? This thesis aims to provide the classification, motivation, invention, and evolution of a next generation control framework for transport networks, and special consideration of delivering broadcast video traffic to UK subscribers. The document outlines pertinent telecoms technology and current art, how requirements I gathered, and research I conducted, and by which the transport control framework functional components are identified and selected, and by which method the architecture was implemented and applied to key research projects requiring next generation control capabilities, both at British Telecom and the wider research community. Finally, in the closing chapters, the thesis outlines the next steps for ongoing research and development of the transport network framework and key areas for further study

Regulating QoE for Adaptive Video Streaming using BBF Method

International audienceHTTP video streaming becomes a main contributor in the ever increasing Internet traffic. It is not an easy task for the network service provider to guarantee the best user's Quality of Experience (QoE) in diverse networks with different access technologies. This requires an adaptive method that dynamically adapts the video quality service over HTTP according to time varying network conditions. In this paper, a client-based rate adaptive method is proposed that dynamically selects the appropriate video quality according to network conditions and user's device properties. The proposed method considers three important Quality of Service (QoS) factors that regulate the user's QoE for video streaming over HTTP, which are: Bandwidth, Buffer, and dropped Frame rate (BBF). The network bandwidth significantly affects the video service, as it directly reduces the client buffering that may result in pausing or stalling during video streaming. The proposed BBF method efficiently deals with sudden drop of network bandwidth by using the new bandwidth metric, and reduces its impact on the buffer level of the end user. The buffer length plays a vital role to handle the dynamic change in bandwidth. The dropped frame rate (fps) is another influential factor that minimizes the user's QoE. The proposed BBF algorithm is evaluated with different buffer length, and it is compared to Adobe's OSMF adaptive method

Regulating QoE for Adaptive Video Streaming using BBF Method

International audienceHTTP video streaming becomes a main contributor in the ever increasing Internet traffic. It is not an easy task for the network service provider to guarantee the best user's Quality of Experience (QoE) in diverse networks with different access technologies. This requires an adaptive method that dynamically adapts the video quality service over HTTP according to time varying network conditions. In this paper, a client-based rate adaptive method is proposed that dynamically selects the appropriate video quality according to network conditions and user's device properties. The proposed method considers three important Quality of Service (QoS) factors that regulate the user's QoE for video streaming over HTTP, which are: Bandwidth, Buffer, and dropped Frame rate (BBF). The network bandwidth significantly affects the video service, as it directly reduces the client buffering that may result in pausing or stalling during video streaming. The proposed BBF method efficiently deals with sudden drop of network bandwidth by using the new bandwidth metric, and reduces its impact on the buffer level of the end user. The buffer length plays a vital role to handle the dynamic change in bandwidth. The dropped frame rate (fps) is another influential factor that minimizes the user's QoE. The proposed BBF algorithm is evaluated with different buffer length, and it is compared to Adobe's OSMF adaptive method

Contribution of Quality of Experience to optimize multimedia services : the case study of video streaming and VoIP

L'émergence et la croissance rapide des services multimédia dans les réseaux IP ont créé de nouveaux défis pour les fournisseurs de services réseau, qui, au-delà de la Qualité de Service (QoS) issue des paramètres techniques de leur réseau, doivent aussi garantir la meilleure qualité de perception utilisateur (Quality of Experience, QoE) dans des réseaux variés avec différentes technologies d'accès. Habituellement, différentes méthodes et techniques sont utilisées pour prédire le niveau de satisfaction de l'utilisateur, en analysant l'effet combiné de multiples facteurs. Dans cette thèse, nous nous intéressons à la commande du réseau en intégrant à la fois des aspects qualitatifs (perception du niveau de satisfaction de l'usager) et quantitatifs (mesure de paramètres réseau) dans l'objectif de développer des mécanismes capables, à la fois, de s'adapter à la variabilité des mesures collectées et d'améliorer la qualité de perception. Pour ce faire, nous avons étudié le cas de deux services multimédia populaires, qui sont : le streaming vidéo, et la voix sur IP (VoIP). Nous investiguons la QoE utilisateur de ces services selon trois aspects : (1) les méthodologies d'évaluation subjective de la QoE, dans le cadre d'un service vidéo, (2) les techniques d'adaptation de flux vidéo pour garantir un certain niveau de QoE, et (3) les méthodes d'allocation de ressource, tenant compte de la QoE tout en économisant l'énergie, dans le cadre d'un service de VoIP (LTE-A). Nous présentons d'abord deux méthodes pour récolter des jeux de données relatifs à la QoE. Nous utilisons ensuite ces jeux de données (issus des campagnes d'évaluation subjective que nous avons menées) pour comprendre l'influence de différents paramètres (réseau, terminal, profil utilisateur) sur la perception d'un utilisateur d'un service vidéo. Nous proposons ensuite un algorithme de streaming vidéo adaptatif, implémenté dans un client HTTP, et dont le but est d'assurer un certain niveau de QoE et le comparons à l'état de l'art. Notre algorithme tient compte de trois paramètres de QoS (bande passante, taille de mémoires tampons de réception et taux de pertes de paquets) et sélectionne dynamiquement la qualité vidéo appropriée en fonction des conditions du réseau et des propriétés du terminal de l'utilisateur. Enfin, nous proposons QEPEM (QoE Power Efficient Method), un algorithme d'ordonnancement basé sur la QoE, dans le cadre d'un réseau sans fil LTE, en nous intéressant à une allocation dynamique des ressources radio en tenant compte de la consommation énergétiqueThe emerging and fast growth of multimedia services have created new challenges for network service providers in order to guarantee the best user's Quality of Experience (QoE) in diverse networks with distinctive access technologies. Usually, various methods and techniques are used to predict the user satisfaction level by studying the combined impact of numerous factors. In this thesis, we consider two important multimedia services to evaluate the user perception, which are: video streaming service, and VoIP. This study investigates user's QoE that follows three directions: (1) methodologies for subjective QoE assessment of video services, (2) regulating user's QoE using video a rate adaptive algorithm, and (3) QoE-based power efficient resource allocation methods for Long Term Evaluation-Advanced (LTE-A) for VoIP. Initially, we describe two subjective methods to collect the dataset for assessing the user's QoE. The subjectively collected dataset is used to investigate the influence of different parameters (e.g. QoS, video types, user profile, etc.) on user satisfaction while using the video services. Later, we propose a client-based HTTP rate adaptive video streaming algorithm over TCP protocol to regulate the user's QoE. The proposed method considers three Quality of Service (QoS) parameters that govern the user perception, which are: Bandwidth, Buffer, and dropped Frame rate (BBF). The BBF method dynamically selects the suitable video quality according to network conditions and user's device properties. Lastly, we propose a QoE driven downlink scheduling method, i.e. QoE Power Escient Method (QEPEM) for LTE-A. It esciently allocates the radio resources, and optimizes the use of User Equipment (UE) power utilizing the Discontinuous Reception (DRX) method in LTE-