Request adaptation for adaptive streaming over HTTP/2

Nguyen, Duc V.; Lê, Hung; Nam, Pham Ngoc; Pham, Anh T.; Thang, Truong Cong

doi:10.1109/icce.2016.7430575

Cited by 9 publications

(8 citation statements)

References 3 publications

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“…Adaptive streaming over HTTP/2 [192], [260]- [262], client-based prefetching [263], Meta-heuristics for increased client QoE-awareness [264], [60] Improving the video quality and reduce the live latency using HTTP/2 protocol. HTTP/2 is a server push mechanism that also increase link utilization compared to HTTP/1.1 [260].…”

Section: Application-level Optimizationsmentioning

confidence: 99%

QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey

Barakabitze

Barman

Ahmad

et al. 2020

IEEE Commun. Surv. Tutorials

168

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The highly demanding Over-The-Top (OTT) multimedia applications pose increased challenges to Internet Service Providers (ISPs) for assuring a reasonable Quality of Experience (QoE) to their customers due to lack of flexibility, agility and scalability in traditional networks. The future networks are shifting towards the cloudification of the network resources via Software Defined Networks (SDN) and Network Function Virtualization (NFV). This will equip ISPs with cutting-edge technologies to provide service customization during service delivery and offer QoE which meets customers' needs via intelligent QoE control and management approaches. Towards this end, we provide in this paper a tutorial and a comprehensive survey of QoE management solutions in current and future networks. We start with a highlevel description of QoE management for multimedia services, which integrates QoE modelling, monitoring, and optimization. This followed by a discussion of HTTP Adaptive Streaming (HAS) solutions as the dominant technique for streaming videos over the best-effort Internet. We then summarize the key elements in SDN/NFV along with an overview of ongoing research projects, standardization activities and use cases related to SDN, NFV, and other emerging applications. We provide a survey of the state-of-the-art of QoE management techniques categorized into three different groups: a) QoE-aware/driven strategies using SDN and/or NFV; b) QoE-aware/driven approaches for adaptive streaming over emerging architectures such as multi-access edge computing, cloud/fog computing, and information-centric networking; and c) extended QoE management approaches in new domains such as immersive augmented and virtual reality, mulsemedia and video gaming applications. Based on the review, we present a list of identified future QoE management challenges regarding emerging multimedia applications, network management and orchestration, network slicing and collaborative service management in softwarized networks. Finally, we provide a discussion on future research directions with a focus on emerging research areas in QoE management, such as QoEoriented business models, QoE-based big data strategies, and scalability issues in QoE optimization.

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Section: Application-level Optimizationsmentioning

confidence: 99%

QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey

Barakabitze

Barman

Ahmad

et al. 2020

IEEE Commun. Surv. Tutorials

168

View full text Add to dashboard Cite

show abstract

“…This is in contrast with traditional pull-based HAS approaches, where the client has to make an explicit request for new segments. In light of these advantages, the server push performance has been extensively investigated in order to reduce the live latency and the initial delay in HAS [15,69,100,104,105,107]. Wei et al have been the first to investigate the performance of HTTP/2 server push in the context of adaptive streaming [104].…”

Section: Application Level Optimizationsmentioning

confidence: 99%

“…This approach allows to eliminate video freezes and obtain 15% higher quality compared to classical adaptive streaming over HTTP/1.1. The buffer filling level can be included directly into the computation of the K value [69]. In this work, the optimal K is set in order to keep the buffer filling level above a specific threshold.…”

Section: Application Level Optimizationsmentioning

confidence: 99%

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Quality of Experience-Centric Management of Adaptive Video Streaming Services

Petrangeli

Hooft

Wauters

et al. 2018

ACM Trans. Multimedia Comput. Commun. Appl.

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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 paper, 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.

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“…Specifically, the so-called k-push strategy has been adopted, where the client receives k video segments with one request [4]. Prior studies have confirmed the promising performance with short segment duration of such a strategy in reducing request-related overheads [5,12,13], startup and delivering delay [3,4], unnecessary RTTs [3,14], power consumption [13,15] and in improving the QoE [16,17]. However, those existing works only focused on optimizing the performance of one client without considering the impact on other clients sharing the same bandwidth.…”

Section: Introductionmentioning

confidence: 99%

FAURAS: A Proxy-Based Framework for Ensuring the Fairness of Adaptive Video Streaming over HTTP/2 Server Push

et al. 2020

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HTTP/2 video streaming has gotten a lot of attention in the development of multimedia technologies over the last few years. In HTTP/2, the server push mechanism allows the server to deliver more video segments to the client within a single request in order to deal with the requests explosion problem. As a result, recent research efforts have been focusing on utilizing such a feature to enhance the streaming experience while reducing the request-related overhead. However, current works only optimize the performance of a single client, without necessary concerns of possible influences on other clients in the same network. When multiple streaming clients compete for a shared bandwidth in HTTP/1.1, they are likely to suffer from unfairness, which is defined as the inequality in their bitrate selections. For HTTP/1.1, existing works have proven that the network-assisted solutions are effective in solving the unfairness problem. However, the feasibility of utilizing such an approach for the HTTP/2 server push has not been investigated. Therefore, in this paper, a novel proxy-based framework is proposed to overcome the unfairness problem in adaptive streaming over HTTP/2 with the server push. Experimental results confirm the outperformance of the proposed framework in ensuring the fairness, assisting the clients with avoiding rebuffering events and lowering bitrate degradation amplitude, while maintaining the mechanism of the server push feature.

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Request adaptation for adaptive streaming over HTTP/2

Cited by 9 publications

References 3 publications

QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey

QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey

Quality of Experience-Centric Management of Adaptive Video Streaming Services

FAURAS: A Proxy-Based Framework for Ensuring the Fairness of Adaptive Video Streaming over HTTP/2 Server Push

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