TABLE OF CONTENTS In this chapter, we will build upon the basic probability theory covered in Chapter 5 and stochastic processes covered in Chapter 6. The discussions will lead to the definition and analysis of several useful queuing models for the behavior of many types of service systems. The methods discussed herein complement those provided by simulation analysis. Frequently, the development of a general queuing model for a particular system will aid in the development of a refined Petri net model or a detailed simulation of specific parts of the system. Also, the results and behavior observed from simulation help to tune the analytical models.
This chapter is organized into three general topics: queuing models, estimation, and computational methods for theoretical systems analysis. Stochastic processes form the basis for many of the analytical techniques that apply to the queuing systems that we will discuss. The section on estimation provides some methods for defining the values that parameterize the queuing models with real-world data.
In this section, we will cover the basic analysis techniques associated with queuing systems. The prime motivation for performing queuing analysis is to assess local system behavior under a variety of assumptions, initial conditions, and operational scenarios. The modeling aspect seeks to represent the behavior of system components as processes that have calculable statistics and that adequately reflect reality. Thus, the use of queuing analysis provides us with a set of techniques for calculating quantities, such as wait time for service, throughput of a server, the effect...
