In this paper the authors describe the mean number of busy servers as a function of time in an Mt/G/• queue (having a nonhomogeneous Poisson arrival process) with a sinusoidal arrival rate function. For an Mt/G/• model with appropriate initial conditions, it is known that the number of busy servers at time t has a Poisson distribution for each t, so that the full distribution is characterized by its mean. The present formulas show how the peak congestion lags behind the peak arrival rate and how much less is the range of congestion than the range of offered load. The simple formulas can also be regarded as consequences of linear system theory, because the mean function can be regarded as the image of a linear operator applied to the arrival rate function. The authors also investigate the quality of various approximations for the mean number of busy servers such as the pointwise stationary approximation and several polynomial approximations. Finally, they apply the results for sinusoidal arrival rate functions to treat general periodic arrival rate functions using Fourier series. These results are intended to provide a better understanding of the behavior of the Mt/G/• model and related Mt/G/s/r models where some customers are lost or delayed.
