Exact Simulation of the Equilibrium Distribution of Reflected Stochastic Networks with Levy Input

Event Details
  • Date/Time:
    • Monday November 15, 2010
      10:00 am - 11:00 am
  • Location: ISyE Executive classroom
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Summary Sentence: Exact Simulation of the Equilibrium Distribution of Reflected Stochastic Networks with Levy Input

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TITLE: Exact Simulation of the Equilibrium Distribution of Reflected Stochastic
Networks with Levy Input

SPEAKER:  Jose Blanchet

ABSTRACT:

Reflected stochastic networks arise in the analysis of a large class of queueing systems. The most popular model of this type is perhaps reflected Brownian motion, which arises in the heavy-traffic analysis of generalized Jackson networks. In this talk we discuss Monte Carlo
simulation strategies for the steady-state analysis of reflected stochastic networks. In particular, we show how to exactly (i.e. without bias) simulate the equilibrium distribution of a reflected stochastic network with compound Poisson input and how to provide samples that are
close (with explicit and controlled error bounds) to both the transient and the steady-state distribution of reflected Brownian motion in the positive orthant. (Joint work with Xinyun Chen.)

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H. Milton Stewart School of Industrial and Systems Engineering (ISYE)

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Status
  • Created By: Anita Race
  • Workflow Status: Published
  • Created On: Nov 10, 2010 - 9:12am
  • Last Updated: Oct 7, 2016 - 9:53pm