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This queuing model illustrates service demand from a finite population of users. The underlying assumption is, if a significant fraction of these users are already waiting for service, then the arrival rate of further service demands decreasis until more of the users are serviced and returned to the calling community. We call this class of models Machine Rapairman models because you can think of the calling population as a set of machines that occasionally break down and need repair. The servers are thought of as repairmen.

The @PFS(Poisson Finite Source) function computes the expected number of customers either in repair or waiting for repair, given the number of customers, number of repairmen, and the limiting load of the queue. This model illustrates the use of the @PFS function to model a computer timesharing system. Each of the incoming ports can be thought of as a customer. Usually, the number of incomin ports is limited. Thus, the finite source assumptions are appropriate.