Discrete event simulation (DES) is the process of codifying the behavior of a complex system as an ordered sequence of well-defined events. In this context, an event comprises a specific change in the system's state at a specific point in time.
Common applications of DES include stress testing, evaluating potential financial investments, and modeling procedures and processes in various industries, such as manufacturing and healthcare.
As an example of a situation that lends itself to DES, consider the amount of electrical power consumed by a corporation's office building as a function of time. Discrete events affecting this function include power-up or power-down of any electrical device in the building. Instantaneous changes of state in a device already powered-up are also discrete events; for example, a speed change in a cooling fan or a brightness change in a desk lamp.
An effective DES process must include, at a minimum, the following characteristics:
- Predetermined starting and ending points, which can be discrete events or instants in time.
- A method of keeping track of the time that has elapsed since the process began.
- A list of discrete events that have occurred since the process began.
- A list of discrete events pending or expected (if such events are known) until the process is expected to end.
- A graphical, statistical, or tabular record of the function for which DES is currently engaged.
DES is commonly used to monitor and predict the behavior of investments; the stock market is a classic example. DES can also help administrators predict how a network will behave under extraordinary conditions, such as the Internet during a major disaster.