Adaptation algorithm for adaptive streaming over HTTP

Miller, Konstantin; Quacchio, E.; Gennari, G.; Wolisz, Adam

doi:10.1109/pv.2012.6229732

Cited by 203 publications

(138 citation statements)

References 3 publications

Supporting

Mentioning

135

Contrasting

Unclassified

Order By: Relevance

“…We compare our quality-adaptation algorithm based on the optimal SDP policies with another DASH algorithm [3] and with the HLS implementation in a commercial player.…”

Section: Simulation and Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Quality-optimization algorithm based on stochastic dynamic programming for MPEG DASH video streaming

Sánchez-García

Cabrera

García

2014

2014 IEEE International Conference on Consumer Electronics (ICCE)

View full text Add to dashboard Cite

Abstract-In contrast to traditional push-based protocols, adaptive streaming techniques like Dynamic Adaptive Streaming over HTTP (DASH) fix attention on the client, who dynamically requests different-quality portions of the content to cope with a limited and variable bandwidth but aiming at maximizing the quality perceived by the user. Since DASH adaptation logic at the client is not covered by the standard, we propose a solution based on Stochastic Dynamic Programming (SDP) techniques to find the optimal request policies that guarantee the users' Quality of Experience (QoE). Our algorithm is evaluated in a simulated streaming session and is compared with other adaptation approaches. The results show that our proposal outperforms them in terms of QoE, requesting higher qualities on average.

show abstract

“…We compare our quality-adaptation algorithm based on the optimal SDP policies with another DASH algorithm [3] and with the HLS implementation in a commercial player.…”

Section: Simulation and Resultsmentioning

confidence: 99%

“…Recent researches have been carried out to design algorithms based on either a heuristic [3] or a theoretical [4] approach. In this paper, we design an adaptation logic that maximizes the users' QoE by characterizing the stochastic nature of the system mathematically as a SDP problem.…”

Section: Introductionmentioning

confidence: 99%

Quality-optimization algorithm based on stochastic dynamic programming for MPEG DASH video streaming

Sánchez-García

Cabrera

García

2014

2014 IEEE International Conference on Consumer Electronics (ICCE)

View full text Add to dashboard Cite

show abstract

“…The purpose of buffer-based methods is to maintain the stability of the buffer within a certain range to ensure continuous video playback. However, when the bandwidth is drastically reduced, the buffer-based methods may cause sudden change of bitrate [5][6][7][8]. Meanwhile, throughput-based methods adaptively decide version based on the estimated throughput.…”

Section: Introductionmentioning

confidence: 99%

SDP-Based Quality Adaptation and Performance Prediction in Adaptive Streaming of VBR Videos

Nguyen

Ngoc

et al. 2017

Advances in Multimedia

View full text Add to dashboard Cite

Recently, various adaptation methods have been proposed to cope with throughput fluctuations in HTTP adaptive streaming (HAS). However, these methods have mostly focused on constant bitrate (CBR) videos. Moreover, most of them are qualitative in the sense that performance metrics could only be obtained after a streaming session. In this paper, we propose a new adaptation method for streaming variable bitrate (VBR) videos using stochastic dynamic programming (SDP). With this approach, the system should have a probabilistic characterization along with the definition of a cost function that is minimized by a control strategy. Our solution is based on a new statistical model where the future streaming performance is directly related to the past bandwidth statistics. We develop mathematical models to predict and develop simulation models to measure the average performance of the adaptation policy. The experimental results show that the prediction models can provide accurate performance prediction which is useful in planning adaptation policy and that our proposed adaptation method outperforms the existing ones in terms of average quality and average quality switch.

show abstract

“…However, partially due to the bursty nature of HAS traffic, it is difficult for the players to make accurate bandwidth estimations [3,7] . More sophisticated adaptation algorithms with better heuristics and conservative switching between video profiles can lower the number unnecessary quality switches and improve fairness [8][9][10][11][12] . However, fixing the problems only in the player remains difficult because players have a limited view on what occurs in the network.…”

Section: Introductionmentioning

confidence: 99%

A model for evaluating sharing policies for network-assisted HTTP adaptive streaming

et al. 2016

View full text Add to dashboard Cite

a b s t r a c t HTTP adaptive streaming (HAS) has become the dominant technology for streaming video over the Internet. It gained popularity because of its ability to adapt the video quality to the current network conditions and other appealing properties such as usage of off-the-shelf HTTP servers and easy firewall traversal. However, when multiple HAS players share a bottleneck link for streaming, the individual adaptation techniques in the players have difficulties to maintain a stable bitrate and fairly share the network resources. HAS-assisting network elements can solve these performance problems and allow execution of advanced policies for sharing the available bandwidth. Nonetheless, testing and evaluating new sharing policies is costly and time consuming. This motivated us to formulate a model that allows to differentiate between groups of users depending on the type of user or device, and that can describe the mean bitrate of the video streams and how often this bitrate is expected to change during playout. To show how our model can be used, we demonstrate two applications of our model. Furthermore, we validate the model based results against results obtained using our streaming testbed and proxy server based HASassistant. The results show that our model is highly accurate for both the mean bitrate and the number of changes in video bitrate. As such, our model is a useful tool for network administrators and internet service providers for evaluating the performance of sharing policies and for managing and provisioning video delivery networks.

show abstract

Adaptation algorithm for adaptive streaming over HTTP

Cited by 203 publications

References 3 publications

Quality-optimization algorithm based on stochastic dynamic programming for MPEG DASH video streaming

Quality-optimization algorithm based on stochastic dynamic programming for MPEG DASH video streaming

SDP-Based Quality Adaptation and Performance Prediction in Adaptive Streaming of VBR Videos

A model for evaluating sharing policies for network-assisted HTTP adaptive streaming

Contact Info

Product

Resources

About