Simulation Methods for Queues: An Overview

Abstract

This paper gives an overview of those aspects of simulation methodology that are (to some extent) peculiar to the simulation of queueing systems. A generalized semi-Markov process framework for describing queueing systems is used through much of the paper. The main topics covered are: output analysis for simulation of transient and steady-state quantities, variance reduction methods that exploit queueing structure, and gradient estimation methods for performance parameters associated with queueing networks.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1988
Accession Number
ADA197084

Entities

People

  • Donald Iglehart
  • Peter W. Glynn

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Computers
  • Data Science
  • Estimators
  • Information Science
  • Markov Chains
  • Markov Processes
  • Monte Carlo Method
  • New York
  • Operations Research
  • Probability
  • Queueing Theory
  • Random Walk
  • Simulations
  • Simulators
  • Steady State
  • Stochastic Processes

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Computer Networking
  • Systems Analysis and Design