The authors address the problem of measuring asynchronous transfer mode (ATM) traffic on the cell, burst and activity level. With the aid of a traffic sampling mechanism it is shown that efficient data can be collected. These data are then used to estimate the spectral density on each level. It is shown that a forward-backward least square spectral estimator with prefiltering gives an accurate estimation even at low frequencies and that the power spectral density at frequency zero and the load are the most dominant parameters for the queue length and hence also for loss.>

A method of characterizing video codec sources in asynchronous transfer mode (ATM) networks as an autoregressive moving average (ARMA) process is described. Measurements of long-term mean and the autocorrelation function of cell interarrival times allow the parameter estimation of the ARMA model. The video source is then described by ARMA model. Furthermore, it is shown that the multiplexed stream of video cells is also an ARMA process. Such a cell stream is then applied to a model of a queuing system to obtain performance measures of the system. Perturbation analysis is then performed on the functional behavior of the queuing system by appropriate perturbation of the model parameters to determine cell waiting time sensitivity due to slight variations of the input process.>