A Practical Evaluation of Rate Adaptation Algorithms in HTTP-based Adaptive Streaming

Ayad, Ibrahim; Im, Youngbin; Keller, Eric; Ha, Sangtae

doi:10.1016/j.comnet.2018.01.019

Cited by 31 publications

(19 citation statements)

References 9 publications

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“…We do not propose a new ABR adaptation algorithm, instead evaluating 3 very different types of existing algorithms: Rate-based adaptation (RB) tries to fetch the next segment at a bitrate matching the estimated network bandwidth. We adapt the simple, demo implementation of this strategy provided by Bitmovin [4]. This approach requires no modifica-tion to use SEGUE's modified encoding.…”

Section: Online Playback and Rate Adaptationmentioning

confidence: 99%

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Licciardello¹,

Humbel²,

Rohr³

et al. 2022

Preprint

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We identify new opportunities in video streaming, involving the joint consideration of offline video chunking and online rate adaptation. We observe that due to a video's complexity varying over time, certain parts are more likely to cause performance impairments during playback with a particular rate adaptation algorithm. To address this, we propose careful use of variable-length video segments, and augmentation of certain segments with additional bitrate tracks. The key novelty of SEGUE is in making these decisions based on the video's time-varying complexity and the expected rate adaptation behavior over time. We propose and implement several methods for such adaptation-aware chunking. Our results show that SEGUE substantially reduces rebuffering and quality fluctuations, while maintaining video quality delivered; SEGUE improves QoE by 9% on average, and by 22% in low-bandwidth conditions. Beyond our specific approach, we view our problem framing as a first step in a new thread on algorithmic and design innovation in video streaming, and leave the reader with several interesting open questions.

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Section: Online Playback and Rate Adaptationmentioning

confidence: 99%

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Licciardello¹,

Humbel²,

Rohr³

et al. 2022

Preprint

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“…As the stability in terms of quality levels is one of the significant issues to compete with HAS players. The authors in [12] discussed that a HAS player behaviour in adaptive video streaming may lead to the fairness issue when HAS clients are competing for a bottleneck link. In another study [13], the experimentation tools have been provided by introducing an evaluation framework for adaptive streaming.…”

Section: Related Workmentioning

confidence: 99%

A Model for a Practical Evaluation of a DASH-based Rate Adaptive Algorithm over HTTP.

Younus¹,

Shafi

2021

Preprint

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The proliferation of multimedia devices and user-generated content has driven massive growth in Internet traffic for video streaming. There is a dire need to propose solutions that can pose challenging multimedia streaming issues to achieve a user’s quality. Dynamic adaptive streaming over HTTP (DASH) improves the user’s quality through practical systems with limited bandwidth that enables the streaming media to run smoothly. This modern technology can easily improve user perception and defines the media presentation description (MPD) in terms of URL, content file, etc. The proposed adaptation algorithm attempts to determine the optimal solution to alleviate the conflict between maximizing the video quality and avoiding buffer stalls. We evaluate the proposed algorithm against alternative solutions such as ALDASH and FDASH for video content by taking into account the video bitrate, buffer level, and video bitrate switches for the single-user environment. A set of experiments have been conducted to investigate and analyze the benefits of our proposed algorithm. A network simulator NS-3 is used to conduct the performance evaluation by our proposed algorithm. Furthermore, simulation results show that our proposed algorithm enhances video quality performance compared to ALDASH and FDASH in terms of user satisfaction. Last but not least, the experimental results of our proposed algorithm can provide high viewer quality in adaptive streaming as compared to ALDASH and FDASH.

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“…In their study, Kakhki et al found that QUIC provided better streaming QoE, but only for high-quality video [20]. Ayad et al studied the performance of commercial and open-source players and found that the QUIC protocol was quite aggressive when competing with other TCP flows and not as responsive to congestion as other TCP flows [10].…”

Section: Related Workmentioning

confidence: 99%

Quickly Starting Media Streams Using QUIC

Arısu

Begen

2018

Proceedings of the 23rd Packet Video Workshop

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Originally proposed by Google, QUIC is a low-latency transport protocol currently being developed and specified in the IETF. QUIC's low-latency, improved congestion control, multiplexing features are promising and may help improve viewer experience in HTTP adaptive streaming applications. To investigate what issues due to running HTTP over TCP can be alleviated by using HTTP over QUIC, we measured QUIC's streaming performance on wireless and cellular networks. Specifically, we examined QUIC's performance during network interface changes due to viewer's mobility and under unstable network conditions. Results show that QUIC starts media streams more quickly, providing a better streaming and seeking experience, in particular, when there is more congestion in the network, and outperforms TCP when the viewer is mobile and switches between the networks.

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A Practical Evaluation of Rate Adaptation Algorithms in HTTP-based Adaptive Streaming

Cited by 31 publications

References 9 publications

Prepare your video for streaming with Segue

Prepare your video for streaming with Segue

A Model for a Practical Evaluation of a DASH-based Rate Adaptive Algorithm over HTTP.

Quickly Starting Media Streams Using QUIC

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