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Effective Bandwidths for Multiclass Markov Fluids and Other ATM Sources
, 1993
"... We show the existence of effective bandwidths for multiclass Markov fluids and other types of sources that are used to model ATM traffic. More precisely,we show that when such sources share a buffer with deterministic service rate, a constraint on the tail of the buffer occupancy distribution is a l ..."
Abstract
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Cited by 179 (14 self)
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We show the existence of effective bandwidths for multiclass Markov fluids and other types of sources that are used to model ATM traffic. More precisely,we show that when such sources share a buffer with deterministic service rate, a constraint on the tail of the buffer occupancy distribution is a linear constraint on the number of sources. That is, for a small loss probability one can assume that each source transmits at a fixed rate called its effective bandwidth. When traffic parameters are known, effective bandwidths can be calculated and may be used to obtain a circuit-switched style call acceptance and routing algorithm for ATM networks. The important feature of the effective bandwidth of a source is that it is a characteristic of that source and the acceptable loss probability only.Thus, the effective bandwidth of a source does not depend on the number of sources sharing the buffer nor on the model parameters of other types of sources sharing the buffer.
Quick simulation of ATM buffers with on-off multiclass Markov fluid sources
- ACM Transactions on Modeling and Computer Simulations
, 1993
"... The problem we address is how to quickly estimate by simulation the loss in a buffer with multiclass on-off Markov fluid sources. We generate the Markov fluids with the altered rate matrices given in [11], instead of the originals, to speed up the simulation. Likelihood ratios are used to recover an ..."
Abstract
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Cited by 8 (0 self)
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The problem we address is how to quickly estimate by simulation the loss in a buffer with multiclass on-off Markov fluid sources. We generate the Markov fluids with the altered rate matrices given in [11], instead of the originals, to speed up the simulation. Likelihood ratios are used to recover an estimate of the loss for the original traffic parameters.

