Statistical modeling and correlation analysis of end-to-end delay in wide area networks

End-to-end delay is a very important network performance parameter. Consequently, research on end-to-end delay has received a great deal of interest. In this paper, we model end-to-end delay using statistical methods. In particular, we use three statistical distribution models to study end-to-end delay, i.e., Pareto distribution, normal distribution and lognormal distribution. Our analysis results show that Pareto distribution is most appropriate to model end-to-end delay while normal or normal-related distribution is not. We also study delay correlation in different time ranges to find out if delay in the past can provide any indication on delay in the future. Our study shows that there is indeed a good correlation when the time range is about 1.25 seconds.