The model includes appropriate information about the system workload or input.
Analytic models describe the system with a set of equations, and are often stochastic.
This course teaches the basic concepts in stochastic modeling of systems for analysis and for simulation. Performance metrics taken from stochastic simulations are random variables, and are subject to the same types of statistical analysis as data obtained from real systems. Analytic modeling of many systems is computationally demanding. The use of some basic tools in matlab greatly simplifies the evaluation of Markov chains and will be required in several homework assignments. Constructing a simulation model by writing a program can also be simplified, through the use of a library that provides facilities for simulation model specification, data collection, and run-time simulation management.