An Ensemble Rate Adaptation Framework for Dynamic Adaptive Streaming Over HTTP

Yuan, Hui; Hu, Xiaoqian; Hou, Junhui; Wei, Xuekai

doi:10.1109/tbc.2019.2954074

Cited by 24 publications

(10 citation statements)

References 46 publications

(83 reference statements)

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“…Numerous studies have focused on improving the performance of adaptive video streaming. For example, Yuan et al in [15] proposed an ensemble rate adaptation framework which aims to take advantage of the benefits of multiple rate adaptation methods. The proposed framework mainly consists of two modules, a method pool to store the rate adaptation policy and a method controller to decide the policy to use.…”

Section: B Related Workmentioning

confidence: 99%

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Decentralized Optimization for Multicast Adaptive Video Streaming in Edge Cache-Assisted Networks

Zhong

Wang

et al. 2023

IEEE Trans. on Broadcast.

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Adaptive streaming based on DASH offers personalized video experience and smooth playback by allowing dynamical adjustments of the video bitrate to the variations of network conditions. This is especially important for current and future Internet video streaming applications, including emerging ones such as virtual reality-based, as adaptive streaming plays a key role in providing high quality viewing experience, especially in limited bandwidth delivery environments. To enable this promising avenue in a 5G context, efforts are made to consider it alongside multicast and edge caching, as part of the next generation communication technology. In this paper, we model the adaptive streaming transmission problem in a mobile scenario as a multi-source multicast multi-rate problem (MMMP) whose linear relaxation is concave. We decompose the problem in terms of clients and propose the distributed delivery algorithm (DDA). The computation complexity, convergence and time-varying adaptation of DDA are theoretically analyzed. Additionally, to further reduce the computation complexity of the solution, a heuristic approximation method (H-DDA) based on the physical meaning of the problem is proposed and it is also shown how H-DDA converges to the optimal value by numerical means. Finally, we conduct a series of simulation tests to demonstrate the superiority of the proposed HDDA in comparison with other state-of-art solutions.

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Section: B Related Workmentioning

confidence: 99%

“…Therefore, based on eq. ( 13), ( 14), (15), DDA solves the λ * l and υ * l of dual problem U1:D by gradient projection method [27], and updates x i,j (t) iteratively, as follows:…”

Section: B Distributed Optimal Rate Adaptation Algorithmmentioning

confidence: 99%

Decentralized Optimization for Multicast Adaptive Video Streaming in Edge Cache-Assisted Networks

Zhong

Wang

et al. 2023

IEEE Trans. on Broadcast.

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“…In addition to the online ABR schemes, a series of offline schemes that utilize machine learning (ML) have been proposed recently [14], [16]. We compare the performance of VAMP with one representative scheme, namely Pensieve [14], employing the pre-trained model provided by the authors.…”

Section: B Vamp Vs Offline Abr Schemementioning

confidence: 99%

VAMP: A Predictive Approach to Audio/Video Bitrate Adaptation Over Wireless Networks

Huang

Lyu

et al. 2022

IEEE Wireless Commun. Lett.

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Adaptive bitrate (ABR) algorithms are employed for delivering media content across wireless networks. Current ABR schemes only focus on video bitrate adaptation, considering that audio content encoding has negligible impact on streaming quality, due to its smaller size. However, many commercial platforms use high-quality audio which is significant in size. Improper audio bitrate selection thus leads to imbalanced audio/video buffer levels and adversely affects video bitrate selection. To tackle this issue, we propose VAMP, an approach that drives Video and Audio adaptation using Multi-step Predictions. Experimental results demonstrate VAMP's vast superiority over SOTA solutions.

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“…Our aim is to avoid from the traditional streaming protocols and to use the concept of DASH that provides the high video quality and minimizes the buffering level in the current video. Therefore, the authors in [18] proposed an ensemble rate adaptation algorithm that leverages the benefits of multiple methods to improve the user's quality at various decision times to network fluctuations. An adaptive framework in [19] balances the average video rate to guarantee viewing stability by minimizing the switching time.…”

Section: Related Workmentioning

confidence: 99%

A model for a practical evaluation of a DASH-based rate adaptive algorithm over HTTP

2022

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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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An Ensemble Rate Adaptation Framework for Dynamic Adaptive Streaming Over HTTP

Cited by 24 publications

References 46 publications

Decentralized Optimization for Multicast Adaptive Video Streaming in Edge Cache-Assisted Networks

Decentralized Optimization for Multicast Adaptive Video Streaming in Edge Cache-Assisted Networks

VAMP: A Predictive Approach to Audio/Video Bitrate Adaptation Over Wireless Networks

A model for a practical evaluation of a DASH-based rate adaptive algorithm over HTTP

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