101 research outputs found

    Computational inference and control of quality in multimedia services

    Get PDF
    Quality 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 delity, 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 aect the experienced quality, or Quality of Experience (QoE), tend to have complex non-linear relationships. The subjectively perceived QoE is hard to measure directly and continuously evolves with the user's expectations. Faced with the diculty of designing an expert system for QoE management that relies on painstaking measurements and intricate heuristics, we turn to an approach based on learning or inference. The set of solutions presented in this work rely on computational intelligence techniques that do inference over the large set of signals coming from the system to deliver QoE models based on user feedback. We furthermore present solutions for inference of optimized control in systems with no guarantees for resource availability. This approach oers the opportunity to be more accurate in assessing the perceived quality, to incorporate more factors and to adapt as technology and user expectations evolve. In a similar fashion, the inferred control strategies can uncover more intricate patterns coming from the sensors and therefore implement farther-reaching decisions. Similarly to natural systems, this continuous adaptation and learning makes these systems more robust to perturbations in the environment, longer lasting accuracy and higher eciency in dealing with increased complexity. Overcoming this increasing complexity and diversity is crucial for addressing the challenges of future multimedia system. Through experiments and simulations this work demonstrates that adopting an approach of learning can improve the sub jective and objective QoE estimation, enable the implementation of ecient and scalable QoE management as well as ecient control mechanisms

    Analyse intelligente de la qualité d'expérience (QoE) dans les réseaux de diffusion de contenu web et mutimédia

    Get PDF
    Today user experience is becoming a reliable indicator for service providers and telecommunication operators to convey overall end to end system functioning. Moreover, to compete for a prominent market share, different network operators and service providers should retain and increase the customers’ subscription. To fulfil these requirements they require an efficient Quality of Experience (QoE) monitoring and estimation. However, QoE is a subjective metric and its evaluation is expensive and time consuming since it requires human participation. Therefore, there is a need for an objective tool that can measure the QoE objectively with reasonable accuracy in real-Time. As a first contribution, we analyzed the impact of network conditions on Video on Demand (VoD) services. We also proposed an objective QoE estimation tool that uses fuzzy expert system to estimate QoE from network layer QoS parameters. As a second contribution, we analyzed the impact of MAC layer QoS parameters on VoD services over IEEE 802.11n wireless networks. We also proposed an objective QoE estimation tool that uses random neural network to estimate QoE from the MAC layer perspective. As our third contribution, we analyzed the effect of different adaption scenarios on QoE of adaptive bit rate streaming. We also developed a web based subjective test platform that can be easily integrated in a crowdsourcing platform for performing subjective tests. As our fourth contribution, we analyzed the impact of different web QoS parameters on web service QoE. We also proposed a novel machine learning algorithm i.e. fuzzy rough hybrid expert system for estimating web service QoE objectivelyDe nos jours, l’expĂ©rience de l'utilisateur appelĂ© en anglais « User Experience » est devenue l’un des indicateurs les plus pertinents pour les fournisseurs de services ainsi que pour les opĂ©rateurs de tĂ©lĂ©communication pour analyser le fonctionnement de bout en bout de leurs systĂšmes (du terminal client, en passant par le rĂ©seaux jusqu’à l’infrastructure des services etc.). De plus, afin d’entretenir leur part de marchĂ© et rester compĂ©titif, les diffĂ©rents opĂ©rateurs de tĂ©lĂ©communication et les fournisseurs de services doivent constamment conserver et accroĂźtre le nombre de souscription des clients. Pour rĂ©pondre Ă  ces exigences, ils doivent disposer de solutions efficaces de monitoring et d’estimation de la qualitĂ© d'expĂ©rience (QoE) afin d’évaluer la satisfaction de leur clients. Cependant, la QoE est une mesure qui reste subjective et son Ă©valuation est coĂ»teuse et fastidieuse car elle nĂ©cessite une forte participation humaine (appelĂ© panel de d’évaluation). Par consĂ©quent, la conception d’un outil qui peut mesurer objectivement cette qualitĂ© d'expĂ©rience avec une prĂ©cision raisonnable et en temps rĂ©el est devenue un besoin primordial qui constitue un challenge intĂ©ressant Ă  rĂ©soudre. Comme une premiĂšre contribution, nous avons analysĂ© l'impact du comportement d’un rĂ©seau sur la qualitĂ© des services de vidĂ©o Ă  la demande (VOD). Nous avons Ă©galement proposĂ© un outil d'estimation objective de la QoE qui utilise le systĂšme expert basĂ© sur la logique floue pour Ă©valuer la QoE Ă  partir des paramĂštres de qualitĂ© de service de la couche rĂ©seau. Dans une deuxiĂšme contribution, nous avons analysĂ© l'impact des paramĂštres QoS de couche MAC sur les services de VoD dans le cadre des rĂ©seaux sans fil IEEE 802.11n. Nous avons Ă©galement proposĂ© un outil d'estimation objective de la QoE qui utilise le rĂ©seau alĂ©atoire de neurones pour estimer la QoE dans la perspective de la couche MAC. Pour notre troisiĂšme contribution, nous avons analysĂ© l'effet de diffĂ©rents scĂ©narios d'adaptation sur la QoE dans le cadre du streaming adaptatif au dĂ©bit. Nous avons Ă©galement dĂ©veloppĂ© une plate-Forme Web de test subjectif qui peut ĂȘtre facilement intĂ©grĂ© dans une plate-Forme de crowd-Sourcing pour effectuer des tests subjectifs. Finalement, pour notre quatriĂšme contribution, nous avons analysĂ© l'impact des diffĂ©rents paramĂštres de qualitĂ© de service Web sur leur QoE. Nous avons Ă©galement proposĂ© un algorithme d'apprentissage automatique i.e. un systĂšme expert hybride rugueux basĂ© sur la logique floue pour estimer objectivement la QoE des Web service

    Communicating in virtual worlds through an accessible Web 2.0 solution

    Full text link

    Measuring And Improving Internet Video Quality Of Experience

    Get PDF
    Streaming multimedia content over the IP-network is poised to be the dominant Internet traffic for the coming decade, predicted to account for more than 91% of all consumer traffic in the coming years. Streaming multimedia content ranges from Internet television (IPTV), video on demand (VoD), peer-to-peer streaming, and 3D television over IP to name a few. Widespread acceptance, growth, and subscriber retention are contingent upon network providers assuring superior Quality of Experience (QoE) on top of todays Internet. This work presents the first empirical understanding of Internet’s video-QoE capabilities, and tools and protocols to efficiently infer and improve them. To infer video-QoE at arbitrary nodes in the Internet, we design and implement MintMOS: a lightweight, real-time, noreference framework for capturing perceptual quality. We demonstrate that MintMOS’s projections closely match with subjective surveys in accessing perceptual quality. We use MintMOS to characterize Internet video-QoE both at the link level and end-to-end path level. As an input to our study, we use extensive measurements from a large number of Internet paths obtained from various measurement overlays deployed using PlanetLab. Link level degradations of intra– and inter–ISP Internet links are studied to create an empirical understanding of their shortcomings and ways to overcome them. Our studies show that intra–ISP links are often poorly engineered compared to peering links, and that iii degradations are induced due to transient network load imbalance within an ISP. Initial results also indicate that overlay networks could be a promising way to avoid such ISPs in times of degradations. A large number of end-to-end Internet paths are probed and we measure delay, jitter, and loss rates. The measurement data is analyzed offline to identify ways to enable a source to select alternate paths in an overlay network to improve video-QoE, without the need for background monitoring or apriori knowledge of path characteristics. We establish that for any unstructured overlay of N nodes, it is sufficient to reroute key frames using a random subset of k nodes in the overlay, where k is bounded by O(lnN). We analyze various properties of such random subsets to derive simple, scalable, and an efficient path selection strategy that results in a k-fold increase in path options for any source-destination pair; options that consistently outperform Internet path selection. Finally, we design a prototype called source initiated frame restoration (SIFR) that employs random subsets to derive alternate paths and demonstrate its effectiveness in improving Internet video-QoE

    Context-awareness for ubiquitous media service delivery in next generation networks

    Get PDF
    Les rĂ©centes avancĂ©es technologiques permettent dĂ©sormais la fabrication de terminaux mobiles de plus en plus compacts et dotĂ©s de plusieurs interfaces rĂ©seaux. Le nouveau modĂšle de consommation de mĂ©dias se rĂ©sume par le concept "Anytime, Anywhere, Any Device" et impose donc de nouvelles exigences en termes de dĂ©ploiement de services ubiquitaires. Cependant la conception et le developpement de rĂ©seaux ubiquitaires et convergents de nouvelles gĂ©nĂ©rations soulĂšvent un certain nombre de dĂ©fis techniques. Les standards actuels ainsi que les solutions commerciales pourraient ĂȘtre affectĂ©s par le manque de considĂ©ration du contexte utilisateur. Le ressenti de l'utilisateur concernant certains services multimĂ©dia tels que la VoIP et l'IPTV dĂ©pend fortement des capacitĂ©s du terminal et des conditions du rĂ©seau d'accĂšs. Cela incite les rĂ©seaux de nouvelles gĂ©nĂ©rations Ă  fournir des services ubiquitaires adaptĂ©s Ă  l'environnement de l'utilisateur optimisant par la mĂȘme occasion ses resources. L'IP Multimedia Subsystem (IMS) est une architecture de nouvelle gĂ©nĂ©ration qui centralise l'accĂšs aux services et permet la convergence des rĂ©seaux fixe/mobile. NĂ©anmoins, l'Ă©volution de l'IMS est nĂ©cessaire sur les points suivants :- l'introduction de la sensibilitĂ© au contexte utilisateur et de la PQoS (Perceived QoS) : L'architecture IMS ne prend pas en compte l'environnement de l'utilisateur, ses prĂ©fĂ©rences et ne dispose pas d'un mĂ©chanisme de gestion de PQOS. Pour s'assurer de la qualitĂ© fournit Ă  l'utilisateur final, des informations sur l'environnement de l'utilisateur ainsi que ses prĂ©fĂ©rences doivent transiter en cƓur de rĂ©seau afin d'y ĂȘtre analysĂ©s. Ce traitement aboutit au lancement du service qui sera adaptĂ© et optimisĂ© aux conditions observĂ©es. De plus pour le service d'IPTV, les caractĂ©ristiques spatio-temporelles de la vidĂ©o influent de maniĂšre importante sur la PQoS observĂ©e cĂŽtĂ© utilisateur. L'adaptation des services multimĂ©dias en fonction de l'Ă©volution du contexte utilisateur et de la nature de la vidĂ©o diffusĂ©e assure une qualitĂ© d'expĂ©rience Ă  l'utilisateur et optimise par la mĂȘme occasion l'utilisation des ressources en cƓur de rĂ©seau.- une solution de mobilitĂ© efficace pour les services conversationnels tels que la VoIP : Les derniĂšres publications 3GPP fournissent deux solutions de mobilitĂ©: le LTE proposeMIP comme solution de mobilitĂ© alors que l'IMS dĂ©finit une mobilitĂ© basĂ©e sur le protocoleapplicatif SIP. Ces standards dĂ©finissent le systĂšme de signalisation mais ne s'avancent pas sur la gestion du flux mĂ©dia lors du changement d'interface rĂ©seau. La deuxiĂšme section introduit une Ă©tude comparative dĂ©taillĂ©e des solutions de mobilitĂ© dans les NGNs.Notre premiĂšre contribution est la spĂ©cification de l'architecture globale de notre plateforme IMS sensible au contexte utilisateur rĂ©alisĂ©e au sein du projet EuropĂ©en ADAMANTIUM. Nous dĂ©taillons tout d'abord le serveur MCMS intelligent placĂ© dans la couche application de l'IMS. Cet Ă©lĂ©ment rĂ©colte les informations de qualitĂ© de services Ă  diffĂ©rents Ă©quipements rĂ©seaux et prend la dĂ©cision d'une action sur l'un de ces Ă©quipements. Ensuite nous dĂ©finissons un profil utilisateur permettant de dĂ©crire son environnement et de le diffuser en coeur de rĂ©seau. Une Ă©tude sur la prĂ©diction de satisfaction utilisateur en fonction des paramĂštres spatio-temporels de la vidĂ©o a Ă©tĂ© rĂ©alisĂ©e afin de connaĂźtre le dĂ©bit idĂ©al pour une PQoS dĂ©sirĂ©e.Notre deuxiĂšme contribution est l'introduction d'une solution de mobilitĂ© adaptĂ©e aux services conversationnels (VoIP) tenant compte du contexte utilisateur. Notre solution s'intĂšgre Ă  l'architecture IMS existante de façon transparente et permet de rĂ©duire le temps de latence du handover. Notre solution duplique les paquets de VoIP sur les deux interfaces actives pendant le temps de la transition. ParallĂšlement, un nouvel algorithme de gestion de mĂ©moire tampon amĂ©liore la qualitĂ© d'expĂ©rience pour le service de VoIP.The latest advances in technology have already defied Moore s law. Thanks to research and industry, hand-held devices are composed of high processing embedded systems enabling the consumption of high quality services. Furthermore, recent trends in communication drive users to consume media Anytime, Anywhere on Any Device via multiple wired and wireless network interfaces. This creates new demands for ubiquitous and high quality service provision management. However, defining and developing the next generation of ubiquitous and converged networks raise a number of challenges. Currently, telecommunication standards do not consider context-awareness aspects for network management and service provisioning. The experience felt by the end-user consuming for instance Voice over IP (VoIP) or Internet Protocol TeleVision (IPTV) services varies depending mainly on user preferences, device context and network resources. It is commonly held that Next Generation Network (NGN) should deliver personalized and effective ubiquitous services to the end user s Mobile Node (MN) while optimizing the network resources at the network operator side. IP Multimedia Subsystem (IMS) is a standardized NGN framework that unifies service access and allows fixed/mobile network convergence. Nevertheless IMS technology still suffers from a number of confining factors that are addressed in this thesis; amongst them are two main issues :The lack of context-awareness and Perceived-QoS (PQoS):-The existing IMS infrastructure does not take into account the environment of the user ,his preferences , and does not provide any PQoS aware management mechanism within its service provisioning control system. In order to ensure that the service satisfies the consumer, this information need to be sent to the core network for analysis. In order to maximize the end-user satisfaction while optimizing network resources, the combination of a user-centric network management and adaptive services according to the user s environment and network conditions are considered. Moreover, video content dynamics are also considered as they significantly impact on the deduced perceptual quality of IPTV services. -The lack of efficient mobility mechanism for conversational services like VoIP :The latest releases of Third Generation Partnership Project (3GPP) provide two types of mobility solutions. Long-Term Evolution (LTE) uses Mobile IP (MIP) and IMS uses Session Initiation Protocol (SIP) mobility. These standards are focusing on signaling but none of them define how the media should be scheduled in multi-homed devices. The second section introduces a detailed study of existing mobility solutions in NGNs. Our first contribution is the specification of the global context-aware IMS architecture proposed within the European project ADAptative Management of mediA distributioN based on saTisfaction orIented User Modeling (ADAMANTIUM). We introduce the innovative Multimedia Content Management System (MCMS) located in the application layer of IMS. This server combines the collected monitoring information from different network equipments with the data of the user profile and takes adaptation actions if necessary. Then, we introduce the User Profile (UP) management within the User Equipment (UE) describing the end-user s context and facilitating the diffusion of the end-user environment towards the IMS core network. In order to optimize the network usage, a PQoS prediction mechanism gives the optimal video bit-rate according to the video content dynamics. Our second contribution in this thesis is an efficient mobility solution for VoIP service within IMS using and taking advantage of user context. Our solution uses packet duplication on both active interfaces during handover process. In order to leverage this mechanism, a new jitter buffer algorithm is proposed at MN side to improve the user s quality of experience. Furthermore, our mobility solution integrates easily to the existing IMS platform.BORDEAUX1-Bib.electronique (335229901) / SudocSudocFranceF

    Prediction of Quality of Experience for Video Streaming Using Raw QoS Parameters

    Get PDF
    Along with the rapid growth in consumer adoption of modern portable devices, video streaming is expected to dominate a large share of the global Internet traffic in the near future. Today user experience is becoming a reliable indicator for video service providers and telecommunication operators to convey overall end-to-end system functioning. Towards this, there is a profound need for an efficient Quality of Experience (QoE) monitoring and prediction. QoE is a subjective metric, which deals with user perception and can vary due to the user expectation and context. However, available QoE measurement techniques that adopt a full reference method are impractical in real-time transmission since they require the original video sequence to be available at the receiver’s end. QoE prediction, however, requires a firm understanding of those Quality of Service (QoS) factors that are the most influential on QoE. The main aim of this thesis work is the development of novel and efficient models for video quality prediction in a non-intrusive way and to demonstrate their application in QoE-enabled optimisation schemes for video delivery. In this thesis, the correlation between QoS and QoE is utilized to objectively estimate the QoE. For this, both objective and subjective methods were used to create datasets that represent the correlation between QoS parameters and measured QoE. Firstly, the impact of selected QoS parameters from both encoding and network levels on video QoE is investigated. The obtained QoS/QoE correlation is backed by thorough statistical analysis. Secondly, the development of two novel hybrid non-reference models for predicting video quality using fuzzy logic inference systems (FIS) as a learning-based technique. Finally, attention was move onto demonstrating two applications of the developed FIS prediction model to show how QoE is used to optimise video delivery

    Contribution to quality of user experience provision over wireless networks

    Get PDF
    The widespread expansion of wireless networks has brought new attractive possibilities to end users. In addition to the mobility capabilities provided by unwired devices, it is worth remarking the easy configuration process that a user has to follow to gain connectivity through a wireless network. Furthermore, the increasing bandwidth provided by the IEEE 802.11 family has made possible accessing to high-demanding services such as multimedia communications. Multimedia traffic has unique characteristics that make it greatly vulnerable against network impairments, such as packet losses, delay, or jitter. Voice over IP (VoIP) communications, video-conference, video-streaming, etc., are examples of these high-demanding services that need to meet very strict requirements in order to be served with acceptable levels of quality. Accomplishing these tough requirements will become extremely important during the next years, taking into account that consumer video traffic will be the predominant traffic in the Internet during the next years. In wired systems, these requirements are achieved by using Quality of Service (QoS) techniques, such as Differentiated Services (DiffServ), traffic engineering, etc. However, employing these methodologies in wireless networks is not that simple as many other factors impact on the quality of the provided service, e.g., fading, interferences, etc. Focusing on the IEEE 802.11g standard, which is the most extended technology for Wireless Local Area Networks (WLANs), it defines two different architecture schemes. On one hand, the infrastructure mode consists of a central point, which manages the network, assuming network controlling tasks such as IP assignment, routing, accessing security, etc. The rest of the nodes composing the network act as hosts, i.e., they send and receive traffic through the central point. On the other hand, the IEEE 802.11 ad-hoc configuration mode is less extended than the infrastructure one. Under this scheme, there is not a central point in the network, but all the nodes composing the network assume both host and router roles, which permits the quick deployment of a network without a pre-existent infrastructure. This type of networks, so called Mobile Ad-hoc NETworks (MANETs), presents interesting characteristics for situations when the fast deployment of a communication system is needed, e.g., tactics networks, disaster events, or temporary networks. The benefits provided by MANETs are varied, including high mobility possibilities provided to the nodes, network coverage extension, or network reliability avoiding single points of failure. The dynamic nature of these networks makes the nodes to react to topology changes as fast as possible. Moreover, as aforementioned, the transmission of multimedia traffic entails real-time constraints, necessary to provide these services with acceptable levels of quality. For those reasons, efficient routing protocols are needed, capable of providing enough reliability to the network and with the minimum impact to the quality of the service flowing through the nodes. Regarding quality measurements, the current trend is estimating what the end user actually perceives when consuming the service. This paradigm is called Quality of user Experience (QoE) and differs from the traditional Quality of Service (QoS) approach in the human perspective given to quality estimations. In order to measure the subjective opinion that a user has about a given service, different approaches can be taken. The most accurate methodology is performing subjective tests in which a panel of human testers rates the quality of the service under evaluation. This approach returns a quality score, so-called Mean Opinion Score (MOS), for the considered service in a scale 1 - 5. This methodology presents several drawbacks such as its high expenses and the impossibility of performing tests at real time. For those reasons, several mathematical models have been presented in order to provide an estimation of the QoE (MOS) reached by different multimedia services In this thesis, the focus is on evaluating and understanding the multimedia-content transmission-process in wireless networks from a QoE perspective. To this end, firstly, the QoE paradigm is explored aiming at understanding how to evaluate the quality of a given multimedia service. Then, the influence of the impairments introduced by the wireless transmission channel on the multimedia communications is analyzed. Besides, the functioning of different WLAN schemes in order to test their suitability to support highly demanding traffic such as the multimedia transmission is evaluated. Finally, as the main contribution of this thesis, new mechanisms or strategies to improve the quality of multimedia services distributed over IEEE 802.11 networks are presented. Concretely, the distribution of multimedia services over ad-hoc networks is deeply studied. Thus, a novel opportunistic routing protocol, so-called JOKER (auto-adJustable Opportunistic acK/timEr-based Routing) is presented. This proposal permits better support to multimedia services while reducing the energy consumption in comparison with the standard ad-hoc routing protocols.Universidad Politécnica de CartagenaPrograma Oficial de Doctorado en Tecnologías de la Información y Comunicacione

    Acta Universitatis Sapientiae - Electrical and Mechanical Engineering

    Get PDF
    Series Electrical and Mechanical Engineering publishes original papers and surveys in various fields of Electrical and Mechanical Engineering
    • 

    corecore