Variance reduction for simulation in multiclass processing networks. Henderson, S. G. & Meyn, S. P. 2005.
Variance reduction for simulation in multiclass processing networks [link]Paper  abstract   bibtex   
We use simulation to estimate the steady-state performance of a stable multiclass queueing network. Standard estimators have been seen to perform poorly when the network is heavily loaded. We introduce two new simulation estimators. The first provides substantial variance reductions in moderately-loaded networks at very little additional computational cost. The second estimator provides substantial variance reductions in heavy traffic, again for a small additional computational cost. Both methods employ the variance reduction method of control variates, and differ in terms of how the control variates are constructed.
@unpublished{henmey05,
	abstract = {We use simulation to estimate the steady-state performance of a stable multiclass queueing network. Standard estimators have been seen to perform poorly when the network is heavily loaded. We introduce two new simulation estimators. The first provides substantial variance reductions in moderately-loaded networks at very little additional computational cost. The second estimator provides substantial variance reductions in heavy traffic, again for a small additional computational cost. Both methods employ the variance reduction method of control variates, and differ in terms of how the control variates are constructed.},
	author = {Shane G. Henderson and Sean P. Meyn},
	date-added = {2016-01-10 19:34:59 +0000},
	date-modified = {2020-06-01 13:23:38 -0400},
	title = {Variance reduction for simulation in multiclass processing networks},
	url_paper = {http://arxiv.org/abs/2005.14179},
	year = {2005}}
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