Queue response to input correlation functions: continuous spectral analysis

Queueing performance in a richer, heterogeneous input environment is studied. A unique way to understand the effect of second- and higher-order input statistics on queues is offered, and new concepts of traffic measurement, network control, and resource allocation are developed for high-speed networks in the frequency domain. The technique applies to the analysis of queue response to the individual effects of input power spectrum, bispectrum, trispectrum, and input-rate steady-state distribution. The study provides clear evidence that of the four input statistics, the input power spectrum is most essential to queueing analysis. Furthermore, input power in the low-frequency band has a dominant impact on queueing performance, whereas high-frequency power to a large extent can be neglected