## Performance Evaluation by Simulation and Analysis with Applications to Computer NetworksThis book is devoted to the most used methodologies for performance evaluation: simulation using specialized software and mathematical modeling. An important part is dedicated to the simulation, particularly in its theoretical framework and the precautions to be taken in the implementation of the experimental procedure. These principles are illustrated by concrete examples achieved through operational simulation languages (OMNeT ++, OPNET). Presented under the complementary approach, the mathematical method is essential for the simulation. Both methodologies based largely on the theory of probability and statistics in general and particularly Markov processes, a reminder of the basic results is also available. |

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### Contents

INTRODUCTION TO THE QUEUEING THEORY | 131 |

POISSON PROCESS | 141 |

MARKOV QUEUEING SYSTEMS | 153 |

THE MG1 QUEUES | 169 |

QUEUEING NETWORKS | 189 |

AN INTRODUCTION TO THE THEORY | 203 |

AN INTRODUCTION TO STATISTICS | 229 |

MARKOV PROCESS | 247 |

LIST OF TABLES | ix |

PREFACE | xxiii |

INTRODUCTION TO SIMULATION | 13 |

MODELING OF STOCHASTIC BEHAVIORS | 21 |

SIMULATION LANGUAGES | 53 |

SIMULATION RUNNING AND DATA ANALYSIS | 63 |

OMNET++ | 81 |

BIBLIOGRAPHY | 273 |

### Other editions - View all

Performance Evaluation by Simulation and Analysis with Applications to ... Ken Chen Limited preview - 2015 |

Performance Evaluation by Simulation and Analysis with Applications to ... Ken Chen Limited preview - 2015 |

### Common terms and phrases

algorithm analysis analytical modeling application arrival rate behavior Bernoulli distribution buffer calculate computer networks condition confidence interval configuration consider convergence defined definition denoted discrete r.v. duration entity equation estimate event evolution example existence exponential distribution Figure formula function given implementation independent initial interface Internet Jackson network Little’s law log-normal distribution M/G/1 queue Markov chain Markov process mathematical matrix mean value method MLCG module noted number of customers observations obtain OMNeT++ outcomes parameters Pareto distribution particular phenomena Poisson distribution Poisson process possible present PRNG probability distribution process with rate programming provides queueing theory random variables recurrent respectively router sample mean scenario sequence server service distribution simulation language simulation run Software sojourn statistical stochastic process target THEOREM Token tool traffic transient period Transition diagram transmission vacation Var[X variance various waiting