Conservation Equations and Variance Reduction in Queueing Simulations

Variance Reduction in Simulation of Multiclass Queueing Networks

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 substan...

VARIANCE REDUCTION IN SIMULATIONS OF LOSS MODELS by

We propose a new estimator of steady-state blocking probabilities for simulations of stochastic loss models that can be much more efficient than the natural estimator (ratio of losses to arrivals). The proposed estimator is a convex combination of the natural estimator and an indirect estimator based on the average number of customers in service, obtained from Little’s law (L = λW ). It exploit...

Variance Reduction Techniques in . . .

Double Reduction of the Generalized Zakharov Equations via Conservation Laws

In this paper, we study the generalized Zakharov equations with perspective different from those done previously, namely, by determining its symmetry generators, constructing some conservation laws and then use the associations between these to attain a double reduction of the corresponding differential equations leading to two travelling wave solutions.

L2 Model reduction and variance reduction

In this contribution we examine certain variance properties of model reduction. The focus is on L2 model reduction, but some general results are also presented. These general results can be used to analyze various other model reduction schemes. The models we study are nite impulse respons (FIR) and output error (OE) models. We compare the variance of two estimated models. The rst one is estimat...