Evaluation of CMAF in live streaming scenarios

HTTP Adaptive Streaming (HAS) technologies such as MPEG DASH are now used extensively to deliver television services to large numbers of viewers. In HAS, the client requests segments of content using HTTP, with an ABR algorithm selecting the quality at which to request each segment to trade-off video quality with the avoidance of stalling. This introduces significant end to end latency compared to traditional broadcast, due to the the client requiring a large enough buffer for the ABR algorithm to react to changes in network conditions in a timely manner. The recently standardised Common Media Application Format (CMAF) has helped address the issue of latency by defining segments as composed of independently transferable chunks. In this paper, we describe a simulation model we have developed to evaluate the performance of four popular ABR algorithms using DASH and CMAF in various low latency live streaming scenarios. Realistic network conditions are used for the evaluation, which are based on throughput data taken from the CDN logs of a commercial live TV service. We quantify the performance of the ABR algorithms using a selection of QoE metrics, and show that CMAF can significantly improve ABR performance in low delay scenarios

A DASH server-side delay-based representation switching solution to improve the quality of experience for low-latency live video streaming

[EN] This work addresses the integration of real-time transmission systems, including IP cameras and production systems (like OBS or vMix), that use protocols such as RTSP (Real Time Streaming Protocol) or SRT (Secure Reliable Transport), with content distribution technology based on LL-DASH (Low Latency DASH -Dynamic Adaptive Streaming over HTTP-), taking advantage of the fact that DASH offers significant well-known advan- tages for content distribution over the Internet and via CDNs (Content Delivery Networks). Considering the limitations of the LL-DASH standard regarding the adaptation to network conditions, this paper proposes a new solution called Server-Side Representation Switching (SSRS). SSRS uses an approach based on the server measuring the delay in the requests made by clients, whose variation may be due to a decrease in bandwidth, as occurs in Wi-Fi networks with a high number of clients. To evaluate the effectiveness of the proposed solution, a testbed has been developed that allows the performance evaluation of both the LL-DASH system and the solution based on server-side decision-making. In addition, the developed solution has been compared with known al- gorithms (L2A and LoL+) integrated into the Dash.js player. The results show that the Server-Side Representation Switching solution offers a good trade-off between the transmitted quality and the final delay measured at the client, compared to the other algorithms evaluated. Moreover, it holds the advantage of being straightforward to implement and does not require any modifications to the players used.This work is supported by the Centro para el Desarrollo Tecnologico Industrial (CDTI) from the Government of Spain under the project "Nueva plataforma a bordo basada en redes 5G y Wi-Fi 6 para medios de transporte terrestre" (CDTI IDI-20210624).Belda Ortega, R.; Arce Vila, P.; Guerri Cebollada, JC.; De Fez, I. (2023). A DASH server-side delay-based representation switching solution to improve the quality of experience for low-latency live video streaming. Computer Networks. 235:1-15. https://doi.org/10.1016/j.comnet.2023.10996111523

Network-aware video streaming for future media Internet

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An Experimental Study of Low-Latency Video Streaming over 5G

Low-latency video streaming over 5G has become rapidly popular over the last few years due to its increased usage in hosting virtual events, online education, webinars, and all-hands meetings. Our work aims to address the absence of studies that reveal the real-world behavior of low-latency video streaming. To that end, we provide an experimental methodology and measurements, collected in a US metropolitan area over a commercial 5G network, that correlates application-level QoE and lower-layer metrics on the devices, such as RSRP, RSRQ, handover records, etc., under both static and mobility scenarios. We find that RAN-side information, which is readily available on every cellular device, has the potential to enhance throughput estimation modules of video streaming clients, ultimately making low-latency streaming more resilient against network perturbations and handover events.Comment: 6 Page

Llama - Low Latency Adaptive Media Algorithm

In the recent years, HTTP Adaptive Bit Rate (ABR) streaming including Dynamic Adaptive Streaming over HTTP (DASH) has become the most popular technology for video streaming over the Internet. The client device requests segments of content using HTTP, with an ABR algorithm selecting the quality at which to request each segment to trade-off video quality with the avoidance of stalling. This introduces high latency compared to traditional broadcast methods, mostly in the client buffer which needs to hold enough data to absorb any changes in network conditions. Clients employ an ABR algorithm which monitors network conditions and adjusts the quality at which segments are requested to maximise the user's Quality of Experience. The size of the client buffer depends on the ABR algorithm's capability to respond to changes in network conditions in a timely manner, hence, low latency live streaming requires an ABR algorithm that can perform well with a small client buffer. In this paper, we present Llama - a new ABR algorithm specifically designed to operate in such scenarios. Our new ABR algorithm employs the novel idea of using two independent throughput measurements made over different timescales. We have evaluated Llama by comparing it against four popular ABR algorithms in terms of multiple QoE metrics, across multiple client settings, and in various network scenarios based on CDN logs of a commercial live TV service. Llama outperforms other ABR algorithms, improving the P.1203 Mean Opinion Score (MOS) as well as reducing rebuffering by 33% when using DASH, and 68% with CMAF in the lowest latency scenario

Improving quality of experience in adaptive low latency live streaming

HTTP Adaptive Streaming (HAS), the most prominent technology for streaming video over the Internet, suffers from high end-to-end latency when compared to conventional broadcast methods. This latency is caused by the content being delivered as segments rather than as a continuous stream, requiring the client to buffer significant amounts of data to provide resilience to variations in network throughput and enable continuous playout of content without stalling. The client uses an Adaptive Bitrate (ABR) algorithm to select the quality at which to request each segment to trade-off video quality with the avoidance of stalling to improve the Quality of Experience (QoE). The speed at which the ABR algorithm responds to changes in network conditions influences the amount of data that needs to be buffered, and hence to achieve low latency the ABR needs to respond quickly. Llama (Lyko et al. 28) is a new low latency ABR algorithm that we have previously proposed and assessed against four on-demand ABR algorithms. In this article, we report an evaluation of Llama that demonstrates its suitability for low latency streaming and compares its performance against three state-of-the-art low latency ABR algorithms across multiple QoE metrics and in various network scenarios. Additionally, we report an extensive subjective test to assess the impact of variations in video quality on QoE, where the variations are derived from ABR behaviour observed in the evaluation, using short segments and scenarios. We publish our subjective testing results in full and make our throughput traces available to the research community

Llama : Towards Low Latency Live Adaptive Streaming

Multimedia streaming, including on-demand and live delivery of content, has become the largest service, in terms of traffic volume, delivered over the Internet. The ever-increasing demand has led to remarkable advancements in multimedia delivery technology over the past three decades, facilitated by the concurrent pursuit of efficient and quality encoding of digital media. Today, the most prominent technology for online multimedia delivery is HTTP Adaptive Streaming (HAS), which utilises the stateless HTTP architecture - allowing for scalable streaming sessions that can be delivered to millions of viewers around the world using Content Delivery Networks. In HAS, the content is encoded at multiple encoding bitrates, and fragmented into segments of equal duration. The client simply fetches the consecutive segments from the server, at the desired encoding bitrate determined by an ABR algorithm which measures the network conditions and adjusts the bitrate accordingly. This method introduces new challenges to live streaming, where the content is generated in real-time, as it suffers from high end-to-end latency when compared to traditional broadcast methods due to the required buffering at client. This thesis aims to investigate low latency live adaptive streaming, focusing on the reduction of the end-to-end latency. We investigate the impact of latency on the performance of ABR algorithms in low latency scenarios by developing a simulation model and testing prominent on-demand adaptation solutions. Additionally, we conduct extensive subjective testing to further investigate the impact of bitrate changes on the perceived Quality of Experience (QoE) by users. Based on these investigations, we design an ABR algorithm suitable for low latency scenarios which can operate with a small client buffer. We evaluate the proposed low latency adaption solution against on-demand ABR algorithms and the state-of-the-art low latency ABR algorithms, under realistic network conditions using a variety of client and latency settings

DESARROLLO DE UN SISTEMA DE EVALUACIÓN DEL SERVICIO DE STREAMING DASH DE BAJA LATENCIA

[ES] El objetivo del TFG es el desarrollo de un sistema prototipo para la evaluación del servicio de streaming utilizando el protocolo DASH y configurando la generación de contenidos para reducir la latencia. Desde el punto de vista profesional se considera interesante la capacidad de instalar, configurar y evaluar un sistema de streaming. Se utilizarán las herramientas del navegador Chrome para modificar el ancho de banda disponible y evaluar la respuesta del sistema. Además se configurará el sistema para comprobar la mínima latencia posible usando el estándar DASH.[EN] The objective of the TFG is to develop a prototype system for evaluating the streaming service using the DASH protocol and configuring content generation to reduce latency. From the professional point of view, the ability to install, configure and evaluate a streaming system is considered interesting. Chrome browser tools will be used to modify the available bandwidth and evaluate the system response. In addition, the system will be configured to check the minimum possible latency using the DASH standard.Diyanov Nikolov, A. (2020). DESARROLLO DE UN SISTEMA DE EVALUACIÓN DEL SERVICIO DE STREAMING DASH DE BAJA LATENCIA. http://hdl.handle.net/10251/152366TFG