Part I: Simulation Methodologies
Pseudo-random numbers, generation of samples of a distribution, the
Estimating expected-valued functions of a random variable by averaging the
outputs of independent random experiments. Special consideration will be
given to exponential, Poisson, Gaussian and geometric random variables.
The memoryless property of the exponential distribution, and its use in
simulating Poisson processes.
Input analysis: generating a distribution from experimental data.
Output analysis: variance reduction techniques.
Discrete event simulation: the structure of discrete event systems,
queueing systems, and fork-join networks.
Sensitivity analysis and optimization.
Part II: Networks
The ISO Reference Model and the IEEE-802 LAN architecture.
Asynchronous Transfer Mode: The basic protocol.
Network control: virtual connections, delay control and congestion control.
The lectures will cover the material in Part I and Part II in parallel,
with emphasis on performance issues in ATM networks. The students will
prepare a simulation project for performance evaluation or optimization,
and written reports on some of the main issues concerning ATM networks