2014
DOI: 10.1016/j.tele.2013.10.006
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Measuring temporal redundancy in sequences of video requests in a News-on-Demand service

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Cited by 3 publications
(2 citation statements)
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“…To model such behavior, the experiments carried out in [15], which consider 30-minute intervals in which a certain amount of videos are played, are taken into account. The analyses show that pauses take place only in 4.3% of the playbacks.…”
Section: Characterization Of the Traffic Of Pause Fastforward Backward And Requestsmentioning
confidence: 99%
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“…To model such behavior, the experiments carried out in [15], which consider 30-minute intervals in which a certain amount of videos are played, are taken into account. The analyses show that pauses take place only in 4.3% of the playbacks.…”
Section: Characterization Of the Traffic Of Pause Fastforward Backward And Requestsmentioning
confidence: 99%
“…Starting from the experiments performed in [15], the PDF that describes the length of the forward, backward, and the time between playbacks is a Weibull with parameters for each characteristic α = 0.16827 and β = 0.45321, α = 0.09058 and β = 0.47459, and α = 0.16687 and β = 0.51107 respectively. By observing the number of videos, it was estimated that the number of reproductions in 30 minutes can be modeled with a Zipf distribution with a θ 1 = 1.77 parameter.…”
Section: Characterization Of the Traffic Of Pause Fastforward Backward And Requestsmentioning
confidence: 99%