HTTP adaptive streaming with media fragment URIs

HTTP adaptive streaming was introduced with the general idea that user agents interpret a manifest file (describing different representations and segments of the media); where-after they retrieve the media content using sequential HTTP progressive download operations. MPEG started with the standardization of an HTTP streaming protocol, defining the structure and semantics of a manifest file and additional restrictions and extensions for container formats. At the same time, W3C is working on a specification for addressing media fragments on the Web using Uniform Resource Identifiers. The latter not only defines the URI syntax for media fragment identifiers but also the protocol for retrieving media fragments over HTTP. In this paper, we elaborate on the role of Media Fragment URIs within HTTP adaptive streaming scenarios. First, we elaborate on how different media representations can be addressed by means of Media Fragment URIs, by using track fragments. Additionally, we illustrate how HTTP adaptive streaming is realized relying on the Media Fragments URI retrieval protocol. To validate the presented ideas, we implemented Apple's HTTP Live streaming technique using Media Fragment URI

An autonomic delivery framework for HTTP adaptive streaming in multicast-enabled multimedia access networks

The consumption of multimedia services over HTTP-based delivery mechanisms has recently gained popularity due to their increased flexibility and reliability. Traditional broadcast TV channels are now offered over the Internet, in order to support Live TV for a broad range of consumer devices. Moreover, service providers can greatly benefit from offering external live content (e. g., YouTube, Hulu) in a managed way. Recently, HTTP Adaptive Streaming (HAS) techniques have been proposed in which video clients dynamically adapt their requested video quality level based on the current network and device state. Unlike linear TV, traditional HTTP- and HAS-based video streaming services depend on unicast sessions, leading to a network traffic load proportional to the number of multimedia consumers. In this paper we propose a novel HAS-based video delivery architecture, which features intelligent multicasting and caching in order to decrease the required bandwidth considerably in a Live TV scenario. Furthermore we discuss the autonomic selection of multicasted content to support Video on Demand (VoD) sessions. Experiments were conducted on a large scale and realistic emulation environment and compared with a traditional HAS-based media delivery setup using only unicast connections

Minimizing the impact of delay on live SVC-based HTTP adaptive streaming services

HTTP Adaptive Streaming (HAS) is becoming the de-facto standard for Over-The-Top video streaming services. Video content is temporally split into segments which are offered at multiple qualities to the clients. These clients autonomously select the quality layer matching the current state of the network through a quality selection heuristic. Recently, academia and industry have begun evaluating the feasibility of adopting layered video coding for HAS. Instead of downloading one file for a certain quality level, scalable video streaming requires downloading several interdependent layers to obtain the same quality. This implies that the base layer is always downloaded and is available for playout, even when throughput fluctuates and enhancement layers can not be downloaded in time. This layered video approach can help in providing better service quality assurance for video streaming. However, adopting scalable video coding for HAS also leads to other issues, since requesting multiple files over HTTP leads to an increased impact of the end-to-end delay and thus on the service provided to the client. This is even worse in a Live TV scenario where the drift on the live signal should be minimized, requiring smaller segment and buffer sizes. In this paper, we characterize the impact of delay on several measurement-based heuristics. Furthermore, we propose several ways to overcome the end-to-end delay issues, such as parallel and pipelined downloading of segment layers, to provide a higher quality for the video service

QoE estimation for different adaptive streaming techniques in mobile networks

Video services are becoming more and more popular for mobile network users and require greater and greater resources and provisions from telecommunications service providers. But operators suffer from problems of interoperability between the different adaptive transmissions techniques they employ in an attempt to satisfy the quality of experience (QoE) of the service provided to users and improve network performance. This article presents a comparison of four such streaming techniques - DASH (dynamic adaptive streaming over HTTP), HDS (HTTP dynamic streaming), HLS (HTTP2 live streaming) and HSS (HTTP smooth streaming) - used in a live video playback by a user in different test scenarios on an emulated long-term evolution (LTE) network. Comparison of performance was carried out using the mean opinion score (MOS) metric calculated based on ITU-T Recommendation P.1203. The streaming techniques that performed best in each of the different test scenarios are revealed.El servicio de video es cada vez más popular por parte de los usuarios de redes móviles, además exige mayores recursos y prestaciones por parte de los proveedores de servicios de telecomunicaciones. Para satisfacer la calidad de la experiencia del servicio suministrado a los usuarios - QoE y mejorar el rendimiento de las redes, los operadores utilizan diferentes técnicas de transmisión adaptativa, las cuales presentan inconvenientes de interoperabilidad entre ellas.  En este artículo se presenta una comparación de las técnicas de streaming DASH (dynamic adaptive streaming over HTTP), HDS (HTTP dynamic streaming), HLS (HTTP2 live streaming) and HSS (HTTP smooth streaming) empleadas en la reproducción de vídeo en vivo por parte de un usuario en diferentes escenarios de prueba, en una red LTE emulada. La comparación de desempeño se realiza mediante la métrica de la MOS calculada a partir de la Recomendación ITU-T P.1203. Se presenta para los diferentes escenarios bajo prueba, la técnica de streaming que mejor desempeño obtiene

QoE estimation for different adaptive streaming techniques in mobile networks

Video services are becoming more and more popular for mobile network users and require greater and greater resources and provisions from telecommunications service providers. But operators suffer from problems of interoperability between the different adaptive transmissions techniques they employ in an attempt to satisfy the quality of experience (QoE) of the service provided to users and improve network performance. This article presents a comparison of four such streaming techniques - DASH (dynamic adaptive streaming over HTTP), HDS (HTTP dynamic streaming), HLS (HTTP2 live streaming) and HSS (HTTP smooth streaming) - used in a live video playback by a user in different test scenarios on an emulated long-term evolution (LTE) network. Comparison of performance was carried out using the mean opinion score (MOS) metric calculated based on ITU-T Recommendation P.1203. The streaming techniques that performed best in each of the different test scenarios are revealed.El servicio de video es cada vez más popular por parte de los usuarios de redes móviles, además exige mayores recursos y prestaciones por parte de los proveedores de servicios de telecomunicaciones. Para satisfacer la calidad de la experiencia del servicio suministrado a los usuarios - QoE y mejorar el rendimiento de las redes, los operadores utilizan diferentes técnicas de transmisión adaptativa, las cuales presentan inconvenientes de interoperabilidad entre ellas.  En este artículo se presenta una comparación de las técnicas de streaming DASH (dynamic adaptive streaming over HTTP), HDS (HTTP dynamic streaming), HLS (HTTP2 live streaming) and HSS (HTTP smooth streaming) empleadas en la reproducción de vídeo en vivo por parte de un usuario en diferentes escenarios de prueba, en una red LTE emulada. La comparación de desempeño se realiza mediante la métrica de la MOS calculada a partir de la Recomendación ITU-T P.1203. Se presenta para los diferentes escenarios bajo prueba, la técnica de streaming que mejor desempeño obtiene

QoE estimation for different adaptive streaming techniques in mobile networks

Video services are becoming more and more popular for mobile network users and require greater and greater resources and provisions from telecommunications service providers. But operators suffer from problems of interoperability between the different adaptive transmissions techniques they employ in an attempt to satisfy the quality of experience (QoE) of the service provided to users and improve network performance. This article presents a comparison of four such streaming techniques - DASH (dynamic adaptive streaming over HTTP), HDS (HTTP dynamic streaming), HLS (HTTP2 live streaming) and HSS (HTTP smooth streaming) - used in a live video playback by a user in different test scenarios on an emulated long-term evolution (LTE) network. Comparison of performance was carried out using the mean opinion score (MOS) metric calculated based on ITU-T Recommendation P.1203. The streaming techniques that performed best in each of the different test scenarios are revealed.El servicio de video es cada vez más popular por parte de los usuarios de redes móviles, además exige mayores recursos y prestaciones por parte de los proveedores de servicios de telecomunicaciones. Para satisfacer la calidad de la experiencia del servicio suministrado a los usuarios - QoE y mejorar el rendimiento de las redes, los operadores utilizan diferentes técnicas de transmisión adaptativa, las cuales presentan inconvenientes de interoperabilidad entre ellas.  En este artículo se presenta una comparación de las técnicas de streaming DASH (dynamic adaptive streaming over HTTP), HDS (HTTP dynamic streaming), HLS (HTTP2 live streaming) and HSS (HTTP smooth streaming) empleadas en la reproducción de vídeo en vivo por parte de un usuario en diferentes escenarios de prueba, en una red LTE emulada. La comparación de desempeño se realiza mediante la métrica de la MOS calculada a partir de la Recomendación ITU-T P.1203. Se presenta para los diferentes escenarios bajo prueba, la técnica de streaming que mejor desempeño obtiene

Design and evaluation of a DASH-compliant second screen video player for live events in mobile scenarios

The huge diffusion of mobile devices is rapidly changing the way multimedia content is consumed. Mobile devices are often used as a second screen, providing complementary information on the content shown on the primary screen, as different camera angles in case of a sport event. The introduction of multiple camera angles poses many challenges with respect to guaranteeing a high Quality of Experience to the end user, especially when the live aspect, different devices and highly variable network conditions typical of mobile environments come into play. Due to the ability of HTTP Adaptive Streaming (HAS) protocols to dynamically adapt to bandwidth fluctuations, they are especially suited for the delivery of multimedia content in mobile environments. In HAS, each video is temporally segmented and stored in different quality levels. Rate adaptation heuristics, deployed at the video player, allow the most appropriate quality level to be dynamically requested, based on the current network conditions. Recently, a standardized solution has been proposed by the MPEG consortium, called Dynamic Adaptive Streaming over HTTP (DASH). We present in this paper a DASH-compliant iOS video player designed to support research on rate adaptation heuristics for live second screen scenarios in mobile environments. The video player allows to monitor the battery consumption and CPU usage of the mobile device and to provide this information to the heuristic. Live and Video-on-Demand streaming scenarios and real-time multi-video switching are supported as well. Quantitative results based on real 3G traces are reported on how the developed prototype has been used to benchmark two existing heuristics and to analyse the main aspects affecting battery lifetime in mobile video streaming

HTTP Live Streaming for zoomable video

Master'sMASTER OF SCIENC

QoE-Based Low-Delay Live Streaming Using Throughput Predictions

Recently, HTTP-based adaptive streaming has become the de facto standard for video streaming over the Internet. It allows clients to dynamically adapt media characteristics to network conditions in order to ensure a high quality of experience, that is, minimize playback interruptions, while maximizing video quality at a reasonable level of quality changes. In the case of live streaming, this task becomes particularly challenging due to the latency constraints. The challenge further increases if a client uses a wireless network, where the throughput is subject to considerable fluctuations. Consequently, live streams often exhibit latencies of up to 30 seconds. In the present work, we introduce an adaptation algorithm for HTTP-based live streaming called LOLYPOP (Low-Latency Prediction-Based Adaptation) that is designed to operate with a transport latency of few seconds. To reach this goal, LOLYPOP leverages TCP throughput predictions on multiple time scales, from 1 to 10 seconds, along with an estimate of the prediction error distribution. In addition to satisfying the latency constraint, the algorithm heuristically maximizes the quality of experience by maximizing the average video quality as a function of the number of skipped segments and quality transitions. In order to select an efficient prediction method, we studied the performance of several time series prediction methods in IEEE 802.11 wireless access networks. We evaluated LOLYPOP under a large set of experimental conditions limiting the transport latency to 3 seconds, against a state-of-the-art adaptation algorithm from the literature, called FESTIVE. We observed that the average video quality is by up to a factor of 3 higher than with FESTIVE. We also observed that LOLYPOP is able to reach a broader region in the quality of experience space, and thus it is better adjustable to the user profile or service provider requirements.Comment: Technical Report TKN-16-001, Telecommunication Networks Group, Technische Universitaet Berlin. This TR updated TR TKN-15-00