Long-range dependence and self-similarity of teletraffic with different protocols at the large time scale of day in the duration of 12 years: Autocorrelation modeling

Abstract

Teletraffic (traffic in short) modeling is crucial in the analysis and design of the infrastructure of cyber-physical network systems from a view of traffic engineering. However, reports regarding traffic modeling at the large time scale of day in the duration of years are rarely seen. This paper addresses our finding in autocorrelation function modeling in the closed form of traffic at the time scale of day (daily traffic for short) in the duration of 12 years with different protocols. We shall show that the autocorrelation function of daily traffic takes the autocorrelation function form of the generalized Cauchy process based on studying the autocorrelation function modeling of daily traffic with real traffic data. Thus, the long-range dependence and local self-similarity of daily traffic are in general uncorrelated according to the theory of the generalized Cauchy process. In addition, we will exhibit that the concrete values of long-range dependence measure and local self-similarity one of daily traffic may relate to protocol types.