IEEE International Conference on Communications, 2005. ICC 2005. 2005
DOI: 10.1109/icc.2005.1494326
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A novel method for modeling and analysis of distributed video on demand systems

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Cited by 9 publications
(2 citation statements)
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“…This reduces the error associated with assuming that all streams follow a Poisson process since 0-calls do not violate the Poisson assumption. Further, having the fictitious model discriminates between different streams of calls helps reduce the error caused by the independence assumption [5], [6]. The success of OPCA relies on the fact the fictitious model and true model have similar overall blocking probabilities, allowing the advantages described above to take effect.…”
Section: Opcamentioning
confidence: 99%
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“…This reduces the error associated with assuming that all streams follow a Poisson process since 0-calls do not violate the Poisson assumption. Further, having the fictitious model discriminates between different streams of calls helps reduce the error caused by the independence assumption [5], [6]. The success of OPCA relies on the fact the fictitious model and true model have similar overall blocking probabilities, allowing the advantages described above to take effect.…”
Section: Opcamentioning
confidence: 99%
“…In fact, the variance is much greater than the mean and these streams are highly correlated [5]. In an attempt to improve the estimate, a novel method known as overflow priority classification approximation (OPCA) was proposed [5], [6].…”
Section: Introductionmentioning
confidence: 99%