Adaptive Streaming Protocol Research Articles

The Protocol Play: DASHing Ahead or HLSing Back?

This paper presents a comprehensive comparative analysis of two widely adopted adaptive streaming protocols, Dynamic Adaptive Streaming over HTTP (DASH) and HTTP Live Streaming (HLS), within the contemporary landscape of video delivery. Delving into the background of both protocols, the study explores their architectures, media format support, and adaptability to diverse network conditions. A meticulous examination of strengths and weaknesses encompasses performance, scalability, user experience, device compatibility, and implementation ease. The implications for content delivery, including considerations of quality of experience, Content Delivery Network (CDN) compatibility, and cost factors, are thoroughly discussed. The paper also sheds light on current trends, emerging technologies, and the evolving nature of DASH and HLS. In conclusion, the study provides a synthesis of key insights, offering practical recommendations for protocol selection based on specific use cases and contributing valuable perspectives to the dynamic realm of adaptive video streaming.

Design and analysis of a fair, efficient and stable multi-server adaptive streaming protocol

Due to the surging bandwidth demand for applications like 360° video streaming, hypertext transfer protocol (HTTP) adaptive video streaming has been extended to fetch contents from a single server to multiple servers. However, when players share a bottleneck link, it fails to hold three critical properties: fairness, efficiency, and stability. Effective algorithms have been proposed to tackle the problem in the single-server case. We revisit the three properties and show that they degenerate in multi-server streaming. In this paper, we propose MultiFast, a protocol that offers the best user experience by achieving fair, efficient, and stable multi-server video streaming. MultiFast consists of (1) a bitrate selection algorithm that ensures fairness with concurrent connections; (2) a connection management algorithm that ensures efficiency and stability by managing connections based on network conditions. Our real-world experiments show that MultiFast achieves the best performance in fairness, efficiency, and stability metrics, outperforming its closest alternative.

Pengiriman Video secara Live Streaming Menggunakan Dynamic Adaptive Streaming over HTTP (DASH)

Keterbatasan bandwidth dan fluktuasi trafik pada jaringan menjadi kendala dalam proses pengiriman video. Pada saat ketersediaan bandwidth kecil dan traffic jaringan yang tinggi, proses pengiriman video akan memakan waktu yang lama dikarenakan proses transmisi video yang lambat atau lebih umum disebut dengan buffering. Penelitian ini melakukan evaluasi pengiriman video secara live streaming menggunakan metode Dynamic Adaptive Streaming over HTTP (DASH) pada jaringan LAN. DASH merupakan sebuah protokol streaming adaptive yang mampu menyajikan video dengan kualitas video sesuai kemampuan jaringan pada klien. Implementasi ini dilakukan menggunakan video kompresi H.265 dan proses streaming dilakukan pada jaringan LAN secara live streaming sebanyak 20 klien. Hasil penelitian ini diperoleh nilai throughput pengiriman video mencapai 1,4 Mbps dan nilai delay terbesar 12,5 ms. Persentase permintaan klien terhadap kualitas video tertinggi untuk 1 klien sebanyak 98%. Sedangkan penggunaan 20 klien, permintaan untuk video kualitas tinggi berkurang menjadi 46% yang membuktikan bahwa DASH berhasil diimplementasikan secara live streaming.
 Kata kunci: Video, Live, Streaming, H.265, DASH

Dynamic Cross-Layer Signaling Exchange for Real-Time and On-Demand Multimedia Streams

Multimedia streams consume a significant chunk of the consumer Internet traffic exchanged and will continue to do so due to the ever-increasing connection among people, businesses, and industries. To cope with the deviation of the Internet's intended use, unreliable underlying infrastructure, and best effort protocols while leveraging existing technologies, Hypertext Transfer Protocol Adaptive Streaming is utilized by numerous multimedia services. Performance of HAS-based streaming services is limited by the growing control overhead generated by the Transmission Control Protocol/Internet Protocol (TCP/IP) stack as the stream length, multimedia fidelity, and network conditions vary. In this paper, a novel cross-layer steganographic-enabled signaling scheme is proposed to reduce service provider costs while improving multimedia session performance and maintaining expected Quality-of-Service (QoS). The proposed scheme is designed to encode control stream messages from any TCP/IP layer within payload messages to reduce the total amount of overhead exchanged, thereby decreasing resource utilization within source and intermediate nodes. Furthermore, the encoding scheme probes network conditions and session statistics for adaptive decision-making to enable real-time pliability of the proposed process. A utility function is developed to find the optimal cost savings where simulations are conducted to verify the designs. The proposed solution is then implemented using VideoLan Media Player transceivers residing in linux containers virtual machines, where a multimedia file is exchanged in the popular Advanced Video Coding (H.264) format. The results show a decrease in bandwidth and average queue waiting time costs of 4.71% and 29.61%, respectively, with a throughput increase of 5.77%.

Model-based testing of apps in real network scenarios

Traditional testing methods for mobile apps focus on detecting execution errors. However, the evolution of mobile networks toward 5G will require additional support for app developers to also ensure good performance and user experience. Manual testing in a number of scenarios is not enough to satisfy the expectations of the apps’ end users. This paper presents the testing framework developed in the TRIANGLE project (https://www.triangle-project.eu/), which integrates a complete mobile network testbed to test, benchmark and certify mobile apps. In this paper, we focus on a recent extension of the TRIANGLE framework that uses model-based testing based on model checking to support the automatic generation of user interactions. We introduce the complete testing framework and the basis of the model-based extension. Finally, we use the testing framework to evaluate the performance of the ExoPlayer app in different network scenarios. ExoPlayer is a video streaming app for Android that implements different adaptive streaming protocols.

Real Time ML-Based QoE Adaptive Approach in SDN Context for HTTP Video Services

Due to the high dynamism of network conditions, operators and service providers are facing the challenge of providing satisfactory user experience during a real-time video streaming session where clients are often suffering from frequent interruptions and significant visual quality degradation. Video parameters such as playback quality, rate switching amplitude/frequency, occupancy, overflow/underflow buffer are the main key factors responsible for affecting the user experience’s quality. Recently, adaptive streaming protocols over HTTP have become widely adopted for providing continuous video streaming services to users with their different heterogeneous devices under dynamic network conditions. In this paper, we leverage the emerging paradigm of software defined networking SDN. Our contribution consists in developing some scenarios on SDN helping to adapt video streaming to the network state. The current work proposes to experience ML algorithms in order to predict user QoE over SDN networks. We present an approach that collects MOS score from users under varying network parameters as well as objective parameters such as SSIM, VQM and PSNR. The MOS scores are collected by playing videos to actual users in an SDN environment. We design an architecture which could use the measured MOS values under varying network conditions to predict the expected MOS based on machine learning algorithms. This work provides an outlook of experiments done for demonstration, by describing SDN environment deployment, detailing the realized scenarios and finally giving the results and values. We highlight, at the end of this paper, the perspectives of our proposition.

Toward QoE-Assured 4K Video-on-Demand Delivery Through Mobile Edge Virtualization With Adaptive Prefetching

Internet video streaming applications have been demanding more bandwidth and higher video quality, especially with the advent of virtual reality and augmented reality appli-cations. While adaptive strea ming protocols like MPEG-DASH (dynamic adaptive streaming over HTTP) allows video quality to be flexibly adapted, e.g., degraded when mobile network condition deteriorates, this is not an option if the application itself requires guaranteed 4K quality at all time. On the other hand, conventional end-to-end transmission control protocol (TCP) has been struggling in supporting 4K video delivery across long-distance Internet paths containing both fixed and mobile network segments with heterogeneous characteristics. In this paper, we present a novel and practically feasible system architecture named MVP (mobile edge virtualization with adaptive prefetching), which enables content providers to embed their content intelligence as a virtual network function into the mobile network operator's infrastructure edge. Based on this architecture, we present a context-aware adaptive video prefetching scheme in order to achieve quality of experience (QoE)-assured 4K video on demand (VoD) delivery across the global Internet. Through experiments based on a real LTE-A network infrastructure, we demonstrate that our proposed scheme is able to achieve QoE-assured 4K VoD streaming, especially when the video source is located remotely in the public Internet, in which case none of the state-of-the-art solutions is able to support such an objective at global Internet scale.

Efficient Media Streaming with Collaborative Terminals for the Smart City Environment

Among multiple services delivered over future mobile networks, the most demanding (from the required bandwidth point of view) are related to media streaming, which is a key component in smart applications (entertainment, tourism, surveillance, etc.). Such applications have to exploit a considerable amount of data, which is difficult to achieve especially in dense urban environments. In this context, the article presents a new solution for HTTP-compliant adaptive media streaming applicable to future 5G mobile networks, aimed at increasing bandwidth availability through the use of multiple radio access technologies and direct connections between devices if they are in proximity of each other. The proposed solution considers a scenario in which a high-quality media stream is received by multipath transmission through the radio access network. Collaboration of neighboring devices is exploited by using direct device-to-device links. Thus, proxy nodes can be inserted between a given media receiver and an access network. Toward ensuring optimized resource allocation at both levels, base station-to-device and device-to-device, this article introduces the architectural modules required for collaboration streaming inside the radio access network and end user's device, and proposes enhancements in HTTP-compliant adaptive streaming protocols in order to become suitable for a multipath collaborative scenario.

Advanced multimedia service provisioning based on efficient interoperability of adaptive streaming protocol and high efficient video coding

The popularity of the new standard H.265 (High Efficiency Video Coding) depends on two factors: the rapidity of deploying clients for the most outstanding platforms and the capacity of service providers to develop efficient encoders for serving demanding multimedia services such as Live TV. Both encoders and decoders should inter-operate efficiently with the streaming protocols to limit the risks of implementation incompatibilities.This paper presents a synergy framework between High Efficiency Video Coding (HEVC) and Dynamic Adaptive Streaming over HTTP (DASH) that increases the compression capabilities of the encoder and opens new parallel encoding points for accelerating the video content coding and formatting processes. The synergy takes advantage of inter-motion prediction in HEVC for delimiting the segments of DASH protocol, which increases the motion compensation in each segment. Moreover, the impact of encoding multiple DASH representations is limited due to the parallel encoding presented in this paper.