Contribución a los mecanismos de adaptación dinámica para servicios de distribución multimedia sobre redes móviles

La amplia adopción de dispositivos móviles con capacidad para servicios multimedia, la disponibilidad de mejores redes con mayores anchos de banda y la disponibilidad de plataformas que ofrecen contenido digital han llevado a una creciente popularidad de los servicios de distribución de contenido multimedia. Sin embargo, los servicios de distribución de contenido multimedia pueden estar sujetos a diferentes factores que afectan a la calidad percibida por los usuarios, como las interrupciones del servicio o las oscilaciones de calidad debidas a las cambiantes condiciones de la red, especialmente en las redes móviles. El estándar “Dynamic Adaptive Streaming over HTTP (DASH)” ha surgido como una solución para ofrecer el servicio de distribución del contenido multimedia. DASH aprovecha el uso de redes de distribución de contenido y las capacidades de los dispositivos multimedia para permitir a los reproductores multimedia adaptar dinámicamente la calidad de la transmisión multimedia al ancho de banda disponible y a las características del dispositivo. Como parte de la Tesis doctoral se realizó un estudio del estado del arte de la tecnología para ofrecer el servicio de distribución de contenido multimedia utilizando el estándar DASH con el fin de detectar limitaciones y/o problemas en el servicio. Si bien muchos elementos de DASH están estandarizados, los algoritmos que proporcionan la adaptación dinámica en el reproductor DASH no lo son. La adaptación a menudo se basa en la estimación del rendimiento o un mecanismo de control del buffer, es por esto por lo que también se realizó un análisis de los distintos algoritmos de tasa adaptativa propuestos por la comunidad científica con el fin de detectar áreas de oportunidad para mejorar la calidad en los servicios de distribución multimedia para el estándar DASH. El objetivo de la presente Tesis Doctoral es mejorar la calidad percibida por los usuarios mediante la propuesta de soluciones para los servicios de distribución multimedia en redes móviles. La contribución principal de la Tesis Doctoral se ha concretado en un nuevo algoritmo de tasa adaptativa para estimar el throughput del reproductor DASH basado en un método estadístico denominado “Adaptive Forgetting Factor (AFF)”. Usando este método la lógica de adaptación puede reaccionar apropiadamente a las diferentes condiciones de distintos tipos de redes de acceso, en especial en las redes móviles. Para validar la propuesta del algoritmo de tasa adaptativa de estimación del throughput basado en el método AFF, se han desarrollado escenarios y varias plataformas virtualizadas para evaluar el algoritmo de tasa adaptativa. Este trabajo se ha realizado en el marco del proyecto INNPACTO LTExtreme financiado por el Ministerio de Ciencia e Innovación de España. ----------ABSTRACT---------- The wide adoption of multimedia-capable mobile devices, the availability of better networks with higher bandwidths, and the availability of platforms offering digital content has led to an increasing popularity for multimedia streaming services. Nonetheless, multimedia streaming services can be subject to different factors that affect the quality perceived by the users, such as service disruptions or quality oscillations due to the changing network conditions, especially in mobile networks. The Dynamic Adaptive Streaming over HTTP (DASH) standard has emerged as a solution for multimedia streaming services. DASH leverages the use of content-distribution networks and the capabilities of multimedia devices to allow multimedia players to dynamically adapt the quality of the media streaming to the available bandwidth and the device characteristics. As part of this thesis, a state of the art review of DASH multimedia streaming services has been conducted in order to detect limitations or problems with the service. While multiple elements of DASH are standardized, the algorithms providing the dynamic adaptation for the streaming are not. The adaptation algorithm is often based on the estimation of the throughput or a buffer control mechanism. Therefore, a study of the different algorithms proposed by the scientific community has been performed to detect areas of opportunity to enhance the quality of DASH multimedia streaming services. The overall objective of this thesis is to improve user perceived quality through the proposal of solutions for multimedia streaming services in mobile networks. The central thesis contribution is a new adaptive bitrate algorithm that estimates the throughput of the DASH player based on a statistical method named Adaptive Forgetting Factor (AFF). Using this method, the adaptation logic is able to react appropriately to the different conditions of different types of networks, especially mobile networks. In order to validate the proposal of the adaptive bitrate algorithm based on the AFF estimation method, a set of experiments and several virtualized platforms have been developed to evaluate the adaptive rate algorithm. This work has been accomplished within the framework of the INNPACTO LTExtreme project supported by the Ministry of Science and Innovation of Spain

Supporting handover between LTE video broadcasting and unicast streaming

The heterogeneity of the network poses new challenges on the paradigm of multimedia content distribution. Nowadays, different access technologies coexist in user terminals, so it is possible to improve the performance or avoid coverage problems by switching from one to another. This process is known as handover. In this work we have focused on vertical handover, which is the process of switching between different access technologies without losing connectivity. If a handover happens during a video streaming session, the session will need to adapt to the different channel conditions. This paper discusses the proposal of a new mechanism at the application level to support a handover between a unicast video streaming session and a video session based on LTE broadcasting

DASH Adaptation Algorithm Based on Adaptive Forgetting Factor Estimation

The wide adoption of multimedia service-capable mobile devices, the availability of better networks with higher bandwidths, and the availability of platforms offering digital content has led to an increasing popularity of multimedia streaming services. However, multimedia streaming services can be subject to different factors that affect the quality perceived by the users, such as service interruptions or quality oscillations due to changing network conditions, particularly in mobile networks. Dynamic Adaptive Streaming over HTTP (DASH), leverages the use of content-distribution networks and the capabilities of the multimedia devices to allow multimedia players to dynamically adapt the quality of the media streaming to the available bandwidth and the device characteristics. While many elements of DASH are standardized, the algorithms providing the dynamic adaptation of the streaming are not. The adaptation is often based on the estimation of the throughput or a buffer control mechanism. In this paper, we present a new throughput estimation adaptation algorithm based on a statistical method named Adaptive Forgetting Factor (AFF). Using this method, the adaptation logic is able to react appropriately to the different conditions of different types of networks. A set of experiments with different traffic profiles show that the proposed algorithm improves video quality performance in both wired and wireless environments

A virtualized platform for analyzing LTE broadcast services

Nowadays, users are demanding access to video content anytime and anywhere. LTE broadcast services and video streaming services can reduce the resources used by telecommunication companies to give access to video content and open up new business opportunities. In this context, testbeds and simulation tools can help in the analysis of the different parameters that need to be considered in the deployment of video services based on LTE. In this paper, we describe the design and implementation of an open-source virtualized platform that supports both LTE broadcast services and video streaming services. The testbed is being used both over real LTE networks and LTE network emulations to analyze the performance of video streaming services and to validate new proposals