In many fields of applied probability, one deals with an (observed) impact point process triggered by another (unobservable) point process with each triggering point causing an impact point after a random delay. We consider the common case of delays being i.i.d random variables and independent...

In many fields of applied probability, one deals with an (observed) impact point process triggered by another (unobservable) point process with each triggering point causing an impact point after a random delay. We consider the common case of delays being i.i.d random variables and independent...

We consider a multiserver service system with general nonstationary arrival and service-time processes in which s(t), the number of servers as a function of time, needs to be selected to meet projected loads. We try to choose s(t) so that the probability of a delay (before beginning service)...

The stationary Erlang loss model is a classic example of an insensitive queueing system: the steady-state distribution of the number of busy servers depends on the service-time distribution only through its mean. However, when the arrival process is a nonstationary Poisson process, the...