An adaptive-predictive architecture for video streaming servers

Fernandes, Stênio; Kelner, Judith; Sadok, Djamel

doi:10.1016/j.jnca.2011.05.007

Cited by 7 publications

(3 citation statements)

References 43 publications

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“…On the client side, an adaption algorithm is implemented that request a segment of the required and most relevant quality based on the current network quality level. When the bandwidth fluctuates or becomes very low abruptly, present algorithms do not perform very well [11]. This leads to buffering on the client side, and this severely affects the user's quality of experience.…”

Section: Related Workmentioning

confidence: 99%

Adaptive video streaming over HTTP through 4G wireless networks based on buffer analysis

Raj

Kumar

Iswarya

et al. 2017

J Image Video Proc.

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One of the main challenges in video transmission is understanding and adapting to the varying network bandwidth. The traditional approach of bandwidth estimation is not accurate as there are many factors like congestion that can delay the arrival rate of the ping packet which may lead to a misconception that the bandwidth was low. Thus, the better approach to this problem will be to estimate the link conditions based on the buffer fullness. In this paper, a new system to support streaming of live and stored video through wireless network is proposed which is based on adaptive playback buffer management on the top of HTTP at the client. The buffer fullness is treated as a direct state variable that reflects the fluctuation of the network bandwidth. The buffer fullness estimation predicts the buffer status at a point in the future based on observations of the buffer over a stipulated period of time. The proposed algorithm uses non-linear exponential non-parametric regression for computing the decision parameter. A feedback message is then sent to the server in order to change the quality of the video stream for smoother video play at the client side. The synchronized update and feedback between the server and clients is achieved using HTTP protocol. During the experimentation with live video streaming, the proposed algorithm shows an improvement of 24.48% in average peak signal-to-noise ratio and 6.63% in average structural similarity index against the buffer underflow probability algorithm.

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Section: Related Workmentioning

confidence: 99%

Adaptive video streaming over HTTP through 4G wireless networks based on buffer analysis

Raj

Kumar

Iswarya

et al. 2017

J Image Video Proc.

View full text Add to dashboard Cite

show abstract

“…Where X @ denotes the download capacity of the link between the receiving peer i and its neighbor k. Our scheduling mechanism will therefore maximize a figure of merit that trades off chunk urgency with stream quality, subject to a constraint on total link capacity (7). Equation (8) ensures that a receiver peer does not request a chunk j from more than one neighbor.…”

Section: B the Scheduling Functionmentioning

confidence: 99%

“…Recently, Fernandes et al [7] proposed a mechanism for scalable streaming of stored video over the networks with explicit feedback notification. The mechanism considers the unpredictability of the available rate in order to determine the output sending rate target.…”

Section: Related Workmentioning

confidence: 99%