Overcoming the effects of correlation in packet delay measurements using inter-packet gaps

The end-to-end delay of packets in data streams is characterized with emphasis on effects due to cross traffic, sending rate and packet size. Measurements indicate that modeling delay of a packet stream with high sending rates, as a fraction of bandwidth, is difficult due to the correlations among the delay values. The correlations among inter-packet gaps (IPG) at these rates, however, are negligible. At lower sending rates, the delay correlations are negligible and the distribution of delay can be used as a delay model. We exploit the relation between delay and IPG to show that end-to-end delay can be approximated by a Markov process. Thus, a complete solution is presented for modeling delay for all sending rates. Further, a correlation estimation model is provided for delay and IPG values.