Quality of experience-centric management of adaptive video streaming services : status and challenges

Video streaming applications currently dominate Internet traffic. Particularly, HTTP Adaptive Streaming ( HAS) has emerged as the dominant standard for streaming videos over the best-effort Internet, thanks to its capability of matching the video quality to the available network resources. In HAS, the video client is equipped with a heuristic that dynamically decides the most suitable quality to stream the content, based on information such as the perceived network bandwidth or the video player buffer status. The goal of this heuristic is to optimize the quality as perceived by the user, the so-called Quality of Experience (QoE). Despite the many advantages brought by the adaptive streaming principle, optimizing users' QoE is far from trivial. Current heuristics are still suboptimal when sudden bandwidth drops occur, especially in wireless environments, thus leading to freezes in the video playout, the main factor influencing users' QoE. This issue is aggravated in case of live events, where the player buffer has to be kept as small as possible in order to reduce the playout delay between the user and the live signal. In light of the above, in recent years, several works have been proposed with the aim of extending the classical purely client-based structure of adaptive video streaming, in order to fully optimize users' QoE. In this article, a survey is presented of research works on this topic together with a classification based on where the optimization takes place. This classification goes beyond client-based heuristics to investigate the usage of server-and network-assisted architectures and of new application and transport layer protocols. In addition, we outline the major challenges currently arising in the field of multimedia delivery, which are going to be of extreme relevance in future years

QOE-AWARE CONTENT DISTRIBUTION SYSTEMS FOR ADAPTIVE BITRATE VIDEO STREAMING

A prodigious increase in video streaming content along with a simultaneous rise in end system capabilities has led to the proliferation of adaptive bit rate video streaming users in the Internet. Today, video streaming services range from Video-on-Demand services like traditional IP TV to more recent technologies such as immersive 3D experiences for live sports events. In order to meet the demands of these services, the multimedia and networking research community continues to strive toward efficiently delivering high quality content across the Internet while also trying to minimize content storage and delivery costs. The introduction of flexible and adaptable technologies such as compute and storage clouds, Network Function Virtualization and Software Defined Networking continue to fuel content provider revenue. Today, content providers such as Google and Facebook build their own Software-Defined WANs to efficiently serve millions of users worldwide, while NetFlix partners with ISPs such as ATT (using OpenConnect) and cloud providers such as Amazon EC2 to serve their content and manage the delivery of several petabytes of high-quality video content for millions of subscribers at a global scale, respectively. In recent years, the unprecedented growth of video traffic in the Internet has seen several innovative systems such as Software Defined Networks and Information Centric Networks as well as inventive protocols such as QUIC, in an effort to keep up with the effects of this remarkable growth. While most existing systems continue to sub-optimally satisfy user requirements, future video streaming systems will require optimal management of storage and bandwidth resources that are several orders of magnitude larger than what is implemented today. Moreover, Quality-of-Experience metrics are becoming increasingly fine-grained in order to accurately quantify diverse content and consumer needs. In this dissertation, we design and investigate innovative adaptive bit rate video streaming systems and analyze the implications of recent technologies on traditional streaming approaches using real-world experimentation methods. We provide useful insights for current and future content distribution network administrators to tackle Quality-of-Experience dilemmas and serve high quality video content to several users at a global scale. In order to show how Quality-of-Experience can benefit from core network architectural modifications, we design and evaluate prototypes for video streaming in Information Centric Networks and Software-Defined Networks. We also present a real-world, in-depth analysis of adaptive bitrate video streaming over protocols such as QUIC and MPQUIC to show how end-to-end protocol innovation can contribute to substantial Quality-of-Experience benefits for adaptive bit rate video streaming systems. We investigate a cross-layer approach based on QUIC and observe that application layer-based information can be successfully used to determine transport layer parameters for ABR streaming applications

QoE management of multimedia streaming services in future networks : a tutorial and survey

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Architectures and Algorithms for Content Delivery in Future Networks

Traditional Content Delivery Networks (CDNs) built with traditional Internet technology are less and less able to cope with today’s tremendous content growth. Enhancing infrastructures with storage and computation capabilities may help to remedy the situation. Information-Centric Networks (ICNs), a proposed future Internet technology, unlike the current Internet, decouple information from its sources and provide in-network storage. However, content delivery over in-network storage-enabled networks still faces significant issues, such as the stability and accuracy of estimated bitrate when using Dynamic Adaptive Streaming (DASH). Still Implementing new infrastructures with in-network storage can lead to other challenges. For instance, the extensive deployment of such networks will require a significant upgrade of the installed IP infrastructure. Furthermore, network slicing enables services and applications with very different characteristics to co-exist on the same network infrastructure. Another challenge is that traditional architectures cannot meet future expectations for streaming in terms of latency and network load when it comes to content, such as 360° videos and immersive services. In-Network Computing (INC), also known as Computing in the Network (COIN), allows the computation tasks to be distributed across the network instead of being computed on servers to guarantee performance. INC is expected to provide lower latency, lower network traffic, and higher throughput. Implementing infrastructures with in-network computing will help fulfill specific requirements for streaming 360° video streaming in the future. Therefore, the delivery of 360° video and immersive services can benefit from INC. This thesis elaborates and addresses the key architectural and algorithmic research challenges related to content delivery in future networks. To tackle the first challenge, we propose algorithms for solving the inaccuracy of rate estimation for future CDNs implementation with in-network storage (a key feature of future networks). An algorithm for implementing in-network storage in IP settings for CDNs is proposed for the second challenge. Finally, for the third challenge, we propose an architecture for provisioning INC-enabled slices for 360° video streaming in next-generation networks. We considered a P4-enabled Software-Defined network (SDN) as the physical infrastructure and significantly reduced latency and traffic load for video streaming

Application-Aware Network Design Using Software Defined Networking for Application Performance Optimization for Big Data and Video Streaming

Title from PDF of title page viewed October 30, 2017Dissertation advisor: Deep MedhiVitaIncludes bibliographical references (pages 122-135)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2017This dissertation investigates improvement in application performance. For applications, we consider two classes: Hadoop MapReduce and video streaming. The Hadoop MapReduce (M/R) framework has become the de facto standard for Big Data analytics. However, the lack of network-awareness of the default MapReduce resource manager in a traditional IP network can cause unbalanced job scheduling and network bottlenecks; such factors can eventually lead to an increase in the Hadoop MapReduce job completion time. Dynamic Video streaming over the HTTP (MPEG-DASH) is becoming the defacto dominating transport for today’s video applications. It has been implemented in today’s major media carriers such as Youtube and Netflix. It enables new video applications to fully utilize the existing physical IP network infrastructure. For new 3D immersive medias such as Virtual Reality and 360-degree videos are drawing great attentions from both consumers and researchers in recent years. One of the biggest challenges in streaming such 3D media is the high band width demands and video quality. A new Tile-based video is introduced in both video codec and streaming layer to reduce the transferred media size. In this dissertation, we propose a Software-Defined Network (SDN) approach in an Application-Aware Network (AAN) platform. We first present an architecture for our approach and then show how this architecture can be applied to two aforementioned application areas. Our approach provides both underlying network functions and application level forwarding logics for Hadoop MapReduce and video streaming. By incorporating a comprehensive view of the network, the SDN controller can optimize MapReduce work loads and DASH flows for videos by application-aware traffic reroute. We quantify the improvement for both Hadoop and MPEG-DASH in terms of job completion time and user’s quality of experience (QoE), respectively. Based on our experiments, we observed that our AAN platform for Hadoop MapReduce job optimization offer a significant improvement compared to a static, traditional IP network environment by reducing job run time by 16% to 300% for various MapReduce benchmark jobs. As for MPEG-DASH based video streaming, we can increase user perceived video bitrate by 100%.Introduction -- Research survey -- Proposed architecture -- AAN-SDN for Hadoop -- Study of User QoE Improvement for Dynamic Adaptive Streaming over HTTP (MPEG-DASH) -- AAN-SDN For MPEG-DASH -- Conclusion -- Appendix A. Mininet Topology Source Code For DASH Setup -- Appendix B. Hadoop Installation Source Code -- Appendix C. Openvswitch Installation Source Code -- Appendix D. HiBench Installation Guid

QoE on media deliveriy in 5G environments

231 p.5G expandirá las redes móviles con un mayor ancho de banda, menor latencia y la capacidad de proveer conectividad de forma masiva y sin fallos. Los usuarios de servicios multimedia esperan una experiencia de reproducción multimedia fluida que se adapte de forma dinámica a los intereses del usuario y a su contexto de movilidad. Sin embargo, la red, adoptando una posición neutral, no ayuda a fortalecer los parámetros que inciden en la calidad de experiencia. En consecuencia, las soluciones diseñadas para realizar un envío de tráfico multimedia de forma dinámica y eficiente cobran un especial interés. Para mejorar la calidad de la experiencia de servicios multimedia en entornos 5G la investigación llevada a cabo en esta tesis ha diseñado un sistema múltiple, basado en cuatro contribuciones.El primer mecanismo, SaW, crea una granja elástica de recursos de computación que ejecutan tareas de análisis multimedia. Los resultados confirman la competitividad de este enfoque respecto a granjas de servidores. El segundo mecanismo, LAMB-DASH, elige la calidad en el reproductor multimedia con un diseño que requiere una baja complejidad de procesamiento. Las pruebas concluyen su habilidad para mejorar la estabilidad, consistencia y uniformidad de la calidad de experiencia entre los clientes que comparten una celda de red. El tercer mecanismo, MEC4FAIR, explota las capacidades 5G de analizar métricas del envío de los diferentes flujos. Los resultados muestran cómo habilita al servicio a coordinar a los diferentes clientes en la celda para mejorar la calidad del servicio. El cuarto mecanismo, CogNet, sirve para provisionar recursos de red y configurar una topología capaz de conmutar una demanda estimada y garantizar unas cotas de calidad del servicio. En este caso, los resultados arrojan una mayor precisión cuando la demanda de un servicio es mayor

OpenCache:a content delivery platform for the modern internet

Since its inception, the World Wide Web has revolutionised the way we share information, keep in touch with each other and consume content. In the latter case, it is now used by thousands of simultaneous users to consume video, surpassing physical media as the primary means of distribution. With the rise of on-demand services and more recently, high-definition media, this popularity has not waned. To support this consumption, the underlying infrastructure has been forced to evolve at a rapid pace. This includes the technology and mechanisms to facilitate the transmission of video, which are now offered at varying levels of quality and resolution. Content delivery networks are often deployed in order to scale the distribution provision. These vary in nature and design; from third-party providers running entirely as a service to others, to in-house solutions owned by the content service providers themselves. However, recent innovations in networking and virtualisation, namely Software Defined Networking and Network Function Virtualisation, have paved the way for new content delivery infrastructure designs. In this thesis, we discuss the motivation behind OpenCache, a next-generation content delivery platform. We examine how we can leverage these emerging technologies to provide a more flexible and scalable solution to content delivery. This includes analysing the feasibility of novel redirection techniques, and how these compare to existing means. We also investigate the creation of a unified interface from which a platform can be precisely controlled, allowing new applications to be created that operate in harmony with the infrastructure provision. Developments in distributed virtualisation platforms also enables functionality to be spread throughout a network, influencing the design of OpenCache. Through a prototype implementation, we evaluate each of these facets in a number of different scenarios, made possible through deployment on large-scale testbeds