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Variance reduction in simulations of loss models
Rayadurgam Srikant
, Ward Whitt
Electrical and Computer Engineering
Coordinated Science Lab
Office of the Vice Chancellor for Research and Innovation
Siebel School of Computing and Data Science
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peer-review
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Keyphrases
Arrival Rate
20%
Blocking Probability
60%
Convex Combination
40%
Heavy Load
20%
Heavy Loading
20%
Indirect Estimator
80%
Light Load
20%
Light Loading
20%
Little's Law
20%
Loss Model
100%
Loss Networks
20%
Multiple Traffic Classes
20%
Natural Estimator
100%
Normal Loading
20%
Number of Customers
20%
Offered Load
20%
Service Time
40%
Steady State
20%
Stochastic Losses
20%
Strong Correlation
20%
Two-component
20%
Variance Reduction
100%
Mathematics
arrival rate λ
33%
Blocking Probability
100%
Convex Combination
66%
Loss Model
100%
Loss Network
33%
Offered Load
33%
Ratio Estimator
33%
Service Time
66%
Stochastics
33%
Variance
66%
Variance Reduction
100%