IEEE Global Telecommunications Conference and Exhibition. Communications for the Information Age
DOI: 10.1109/glocom.1988.26037
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Statistical multiplexing of identical bursty sources in an ATM network

Abstract: In a broadband communication network based on the ATM concept it is suggested to use statistical multiplexing to gain better utilization of the bandwith. This paper analyses a statistical multiplexer where a number of identical bursty sources are multiplexed by use of a common buffer. Key parameters are identified and results concerning how the cell loss probability depends on these are obtained and discussed.

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Cited by 36 publications
(3 citation statements)
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References 10 publications
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“…Using (4) where less than packets are present in the buffer. In case of no loss, we therefore get (8) The term to the right is explained as follows. Because describes the probability of having packets in the queue while packets arrive, packets need to be treated in the given time slot.…”
Section: Linear Equations To Find the Joint Probabilities For Packmentioning
confidence: 99%
See 1 more Smart Citation
“…Using (4) where less than packets are present in the buffer. In case of no loss, we therefore get (8) The term to the right is explained as follows. Because describes the probability of having packets in the queue while packets arrive, packets need to be treated in the given time slot.…”
Section: Linear Equations To Find the Joint Probabilities For Packmentioning
confidence: 99%
“…However, the complexity of the switch increases with the number of fiber delay-lines, so a reduction of the fiber buffers is preferable. This is especially true under bursty traffic conditions where the required buffer capacity increases significantly compared to uniformly distributed traffic [8]. Here, we present an analytical traffic model for bursty traffic that is a generalization of the model presented in [9].…”
Section: Introductionmentioning
confidence: 99%
“…Regarding quality estimation for bursty traffic, cell loss probability and delay characteristics are analyzed using an MMPP model [3][4] and a UAS model [5] [6]. Basically, these methods of analysis are based on "queueing" models.…”
Section: Introductionmentioning
confidence: 99%