Diseño centrado en calidad para la difusión Peer-to-Peer de video en vivo

El uso de redes Peer-to-Peer (P2P) es una forma escalable para ofrecer servicios de video sobre Internet. Este documento hace foco en la definición, desarrollo y evaluación de una arquitectura P2P para distribuir video en vivo. El diseño global de la red es guiado por la calidad de experiencia (Quality of Experience - QoE), cuyo principal componente en este caso es la calidad del video percibida por los usuarios finales, en lugar del tradicional diseño basado en la calidad de servicio (Quality of Service - QoE) de la mayoría de los sistemas. Para medir la calidad percibida del video, en tiempo real y automáticamente, extendimos la recientemente propuesta metodología Pseudo-Subjective Quality Assessment (PSQA). Dos grandes líneas de investigación son desarrolladas. Primero, proponemos una técnica de distribución de video desde múltiples fuentes con las características de poder ser optimizada para maximizar la calidad percibida en contextos de muchas fallas y de poseer muy baja señalización (a diferencia de los sistemas existentes). Desarrollamos una metodología, basada en PSQA, que nos permite un control fino sobre la forma en que la señal de video es dividida en partes y la cantidad de redundancia agregada, como una función de la dinámica de los usuarios de la red. De esta forma es posible mejorar la robustez del sistema tanto como sea deseado, contemplando el límite de capacidad en la comunicación. En segundo lugar, presentamos un mecanismo estructurado para controlar la topología de la red. La selección de que usuarios servirán a que otros es importante para la robustez de la red, especialmente cuando los usuarios son heterogéneos en sus capacidades y en sus tiempos de conexión.Nuestro diseño maximiza la calidad global esperada (evaluada usando PSQA), seleccionado una topología que mejora la robustez del sistema. Además estudiamos como extender la red con dos servicios complementarios: el video bajo demanda (Video on Demand - VoD) y el servicio MyTV. El desafío en estos servicios es como realizar búsquedas eficientes sobre la librería de videos, dado al alto dinamismo del contenido. Presentamos una estrategia de "caching" para las búsquedas en estos servicios, que maximiza el número total de respuestas correctas a las consultas, considerando una dinámica particular en los contenidos y restricciones de ancho de banda. Nuestro diseño global considera escenarios reales, donde los casos de prueba y los parámetros de configuración surgen de datos reales de un servicio de referencia en producción. Nuestro prototipo es completamente funcional, de uso gratuito, y basado en tecnologías bien probadas de código abierto

Using Machine Learning in communication network research

International audienceNowadays, Machine Learning (ML) tools are commonly used in every area of science or technology. Networking is not an exception, and we find ML all over the research activities in most fields composing the domain. In this talk, we will briefly describe a set of research activities we have developed along several years around several pretty different families of problems, using ML methods. They concern (i) the automatic and accurate real time measure of the Quality of Experience of an application or service built on top of the Internet around the transport of video or audio content (e.g. video streaming, IP telephony, video-conferencing, etc.), (ii) network tomography (measuring on the edges to infer values inside the network), (iii) time series forecasting in several contexts, in particular concept drift detection or anomalies detection, and (iv) service placements in Software Defined Networks, a central problem in 5G and B5G technologies. The corresponding ML tools are mainly Supervised Learning and Reinforcement Learning, even if we are currently using Unsupervised Learning in recent activities of point (i). After this global presentation we will make one or two zooms on some specific results we obtained with these powerful tools, and some of the current projects we are currently developing

Random Neural Networks and applications

Context of the tutorial: the IEEE CIS Summer School on Computational Intelligence and Applications (IEEE CIS SSoCIA 2022), associated with the 8th IEEE Latin American Conference on Computational Intelligence (IEEE LA-CCI 2022).DoctoralRandom Neural Networks are a class of Neural Networks coming from Stochastic Processes and, in particular, from Queuing Models. They have some nice properties and they have reached good performances in several application areas. They are, in fact, queuing systems seen as Neural machines, and the two uses (probabilistic models for the performance evaluation of systems, or learning machines similar as the other more standard families of Neural Networks) refer to the same mathematical objects. They have the appealing that, as other special models that are unknown for most experts in Machine Learning, their testing in and/or adaptation to the many areas where standard Machine Learning techniques have obtained great successes is totally open.In the tutorial, we will introduce Random Neurons and the networks we can build with them, plus some details about the numerical techniques needed to learn with them. We will also underline the reasons that make them at least extremely interesting. We will also describe some of their successful applications, including our examples. We will focus on learning, but we will mention other uses of these models in performance evaluation, in the analysis of biological systems, and in optimization

Імітаційна модель для визначення сприйняття якості обслуговування абонентів IP-телефонії

Проведений аналіз сприйняття якості обслуговування (PQoS) як цільової функції задачі мережевого керування. Запропонована імітаційна модель для визначення значень PQoS. Проведене експериментальне дослідження гіпотези IQX для кодеку мови SPEEX.Проведен анализ восприятия качества обслуживания (PQoS) как целевой функции задачи сетевого управления. Предложена имитационная модель для определения значений PQoS. Проведено экспериментальное исследование гипотезы IQX для кодека речи SPEEX.The growing importance of perceived quality of service (PQoS) as the objective function of network management is analyzed. A simulation model for evaluation of the PQoS parameters is presented. The IQX hypothesis for SPEEX voice codec is experimentally investigated

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

Les récentes avancées technologiques permettent désormais la fabrication de terminaux mobiles de plus en plus compacts et dotés de plusieurs interfaces réseaux. Le nouveau modèle de consommation de médias se résume par le concept "Anytime, Anywhere, Any Device" et impose donc de nouvelles exigences en termes de déploiement de services ubiquitaires. Cependant la conception et le developpement de réseaux ubiquitaires et convergents de nouvelles générations soulèvent un certain nombre de défis techniques. Les standards actuels ainsi que les solutions commerciales pourraient être affectés par le manque de considération du contexte utilisateur. Le ressenti de l'utilisateur concernant certains services multimédia tels que la VoIP et l'IPTV dépend fortement des capacités du terminal et des conditions du réseau d'accès. Cela incite les réseaux de nouvelles générations à fournir des services ubiquitaires adaptés à l'environnement de l'utilisateur optimisant par la même occasion ses resources. L'IP Multimedia Subsystem (IMS) est une architecture de nouvelle génération qui centralise l'accès aux services et permet la convergence des réseaux fixe/mobile. Néanmoins, l'évolution de l'IMS est nécessaire sur les points suivants :- l'introduction de la sensibilité au contexte utilisateur et de la PQoS (Perceived QoS) : L'architecture IMS ne prend pas en compte l'environnement de l'utilisateur, ses préférences et ne dispose pas d'un méchanisme de gestion de PQOS. Pour s'assurer de la qualité fournit à l'utilisateur final, des informations sur l'environnement de l'utilisateur ainsi que ses préférences doivent transiter en cœur de réseau afin d'y être analysés. Ce traitement aboutit au lancement du service qui sera adapté et optimisé aux conditions observées. De plus pour le service d'IPTV, les caractéristiques spatio-temporelles de la vidéo influent de manière importante sur la PQoS observée côté utilisateur. L'adaptation des services multimédias en fonction de l'évolution du contexte utilisateur et de la nature de la vidéo diffusée assure une qualité d'expérience à l'utilisateur et optimise par la même occasion l'utilisation des ressources en cœur de réseau.- une solution de mobilité efficace pour les services conversationnels tels que la VoIP : Les dernières publications 3GPP fournissent deux solutions de mobilité: le LTE proposeMIP comme solution de mobilité alors que l'IMS définit une mobilité basée sur le protocoleapplicatif SIP. Ces standards définissent le système de signalisation mais ne s'avancent pas sur la gestion du flux média lors du changement d'interface réseau. La deuxième section introduit une étude comparative détaillée des solutions de mobilité dans les NGNs.Notre première contribution est la spécification de l'architecture globale de notre plateforme IMS sensible au contexte utilisateur réalisée au sein du projet Européen ADAMANTIUM. Nous détaillons tout d'abord le serveur MCMS intelligent placé dans la couche application de l'IMS. Cet élément récolte les informations de qualité de services à différents équipements réseaux et prend la décision d'une action sur l'un de ces équipements. Ensuite nous définissons un profil utilisateur permettant de décrire son environnement et de le diffuser en coeur de réseau. Une étude sur la prédiction de satisfaction utilisateur en fonction des paramètres spatio-temporels de la vidéo a été réalisée afin de connaître le débit idéal pour une PQoS désirée.Notre deuxième contribution est l'introduction d'une solution de mobilité adaptée aux services conversationnels (VoIP) tenant compte du contexte utilisateur. Notre solution s'intègre à l'architecture IMS existante de façon transparente et permet de réduire le temps de latence du handover. Notre solution duplique les paquets de VoIP sur les deux interfaces actives pendant le temps de la transition. Parallèlement, un nouvel algorithme de gestion de mémoire tampon améliore la qualité d'expérience 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

Evaluación de calidad de video en una aplicación P2P :Goalbit

El presente trabajo consiste en la aplicación de la metodología PSQA a una aplicación de streaming de video concreta como GoalBit y en redes de acceso frecuentes como ADSL y UMTS, para determinar la calidad de video percibida por el usuario. El trabajo consiste en tres instancias: 1) Interiorización en video streaming, la plataforma GoalBit, la metodología PSQA y determinación de potenciales parámetros de calidad que afecten al flujo de video. 2) Generar una maqueta de pruebas para emular la red P2P; para ello se contará con un cliente , un servidor y una emulación de red ADSL o 3G. Para la emulación de red se utiliza Netem(Network Emulator)y Netem2. Sobre éstas se analizará el impacto de la red de transporte en los parámetros de calidad definidos, a la vez que se validarán los mismos. 3) Aplicar la metodología PSQA: generando secuencias de prueba, presentándolas a un conjunto de observadores para obtener una medida tipo Mean Opinion Score(MOS), filtrando las mismas y entrenando una Red Neuronal(RN) con ellas para obtener una fórmula de calidad. Como producto se tendrá una fórmula de evaluación dinámica de la calidad basada en un conjunto reducido de parámetros, la cual podrá ser integrada a GoalBit. Esta herramienta es la base de mecanismos de estadística y monitoreo de calidad de la red P2P. Adicionalmente, en base a ella el servidor podría tomar acciones correctivas sobre la codificación, el fraccionamiento y/o la redundancia en esquemas multi-camino o multi-fuente, como se comentará en el Cap.II, sección II.

Cross-layer optimisation of quality of experience for video traffic

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