Adaptive video streaming over HTTP with dynamic resource estimation

Thang, Truong Cong; Lê, Hung; Nguyen, Hoc X.; Pham, Anh T.; Kang, Jung Won; Ro, Yong Man

doi:10.1109/jcn.2013.000112

Cited by 62 publications

(48 citation statements)

References 26 publications

(44 reference statements)

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“…We also compare our proposed method with two existing ones, namely, the SDP method presented [10] which could obtain the best performance among the SDP methods and the bitrate estimation based method presented [14], which is the best among the qualitative methods.…”

Section: Resultsmentioning

confidence: 99%

“…Next, we compare our proposed method with the SDP method [10] and the bitrate estimation based method [14] using the same simulation settings as in the first part of our experiment. The experimental results obtained by simulating the SDP method [10] and bitrate estimation based method [14] are shown in Figures 17 and 18, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…The experimental results obtained by simulating the SDP method [10] and bitrate estimation based method [14] are shown in Figures 17 and 18, respectively. We can see that both methods provide very fluctuating version switches.…”

Section: Resultsmentioning

confidence: 99%

“…In recent years, many heuristic adaptation methods for adaptive streaming have been developed (e.g., [5][6][7][8][9]14]). An extensive evaluation of typical adaptation methods has been carried out in [15].…”

Section: Related Workmentioning

confidence: 99%

“…The drawback of this method is the sudden version switch when the actual buffer level drops dramatically. In [14], the authors propose an adaptive logic for VBR videos based on bitrate estimation. The method demonstrates an effective adaptation behavior as it keeps the buffer at a stable and high level; however, it is still qualitative and has no mechanism to balance the streaming performance.…”

Section: Related Workmentioning

confidence: 99%

See 4 more Smart Citations

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

Nguyen

Ngoc

et al. 2017

Advances in Multimedia

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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.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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

Nguyen

Ngoc

et al. 2017

Advances in Multimedia

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Adaptive video streaming testbed design for performance study and assessment of QoE

Taha

Lloret

Ali

et al. 2018

Int J Communication

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Hypertext Transfer Protocol adaptive streaming switches between different video qualities, adapting to the network conditions, and avoids stalling streamed frames over high-oscillation client's throughput improving the users' quality of experience (QoE). Quality of experience has become the most important parameter to lead the service providers to know about the end-user feedback. Implementing Hypertext Transfer Protocol adaptive streaming applications to find out QoE in real-life scenarios of vast networks becomes more challenging and complex task regarding to cost, agile, time, and decisions.In this paper, a virtualized network testbed to virtualize various machines to support implementing experiments of adaptive video streaming has been developed. Within the test study, the metrics which demonstrate performance of QoE are investigated, respectively, including initial delay (ie, startup delay at the beginning of playback a video), frequency switches (ie, number of times the quality is changed), accumulative video time (ie, number and length of stalls), CPU usage, and battery energy consumption. Furthermore, the relation between effective parameters of QoS on the aforementioned metrics for different segment length is investigated. Experimental results show that the proposed virtualized system is agile, easy to install and use, and costs less than real testbeds. Moreover, the subjective and objective performance studies of QoE evaluation in the system have proven that the segment lengths of 6 to 8 seconds were faired and more efficient than others according to the investigated parameters.

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Hybrid Deep Neural Network - Hidden Markov Model Based Network Traffic Classification

Tan

Xie

2019

Communications and Networking

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Adaptive video streaming over HTTP with dynamic resource estimation

Cited by 62 publications

References 26 publications

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

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

Adaptive video streaming testbed design for performance study and assessment of QoE

Hybrid Deep Neural Network - Hidden Markov Model Based Network Traffic Classification

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