Wavelet Spectrum for Investigating Statistical Characteristics of UDP-Based Internet Traffic

In this paper, we consider statistical characteristics of real User Datagram Protocol (UDP) traffic. Four main issues in the study include(i) the presence of long rangedependence (LRD) in the UDP traffic,(ii) the marginal distribution of the UDP traces,(iii) dependence structure of wavelet coefficients,(iv) and performance evaluation of the Hurst parameter estimation based on different numbers of vanishing moments of the mother wavelet. By analyzing a large set of real traffic data, it is evident that the UDP Internet traffic reveals the LRD properties with considerably high non-stationary processes.Furthermore, it exhibits non-Gaussian marginal distributions. However, by increasing the number of vanishing moments,it is impossible to achieve reduction fromLRD to become a short range dependence. Thus, it can be shown that there is no significant difference in performance estimation of the Hurst parameter for different numbers of vanishing moments of the mother wavelet