# Influence of Model and Traffic Pattern on Determining the Self-Similarity in IP Networks
## 5 Analysis of Network Processes for High-Intensity Traffic
For the standard method, the Hurst factor is subject to a smaller scale of changes. It was between 0.96 and 1.04. For the smoothed method, the Hurst factor had a more significant variation, between 0.97 and 1.2. The R language also offers other commands for determining the Hurst ratio. The RoverS command determines the Hurst factor by the scaled R/S range method. The data series are divided into several groups. The R/S statistics are determined, the number of groups is increased, and the calculations are repeated. The logarithmic graph R/S in relation to the number of groups is ideally linear, with a slope of H. The H-factor can be determined by  
Figure 8: Spectral regression graph by multitaper method: (**a**) the standard method, (**b**) the smoothed method. Figure 7: Spectral regression graph by Welch method: (**a**) the standard method, (**b**) the smoothed method. using linear regression [2; 21]. Table 3 below shows the Hurst exponent determined by the RoverS command. The classic methods of determining the H-factor can generally be divided into two main domains. The first is the time domain, which contains the aggregated variance method, [PERSON]'s [35] method, the rescaled range statistics method, and the detrended fluctuation analysis method. The second domain is the frequency domain by means of connections to Fourier or wavelet spectrum decay, for example, [PERSON] and [PERSON] [34], and includes the periodogram method, the modified periodogram method, and [PERSON]'s estimator [33]. The Hurst values determined by the RoverS command are close to the R/S estimation values calculated by the hurstexp command. It is not possible to calculate a factor value for a range higher than 128 because the values become collinear. The hurstBlock command estimates the Hurst factor in the time domain. It uses the following methods:  
Aggvar--The series is divided into \(m\) groups. In each group, the variance is evaluated (against the average of the whole series). A measure of the variability of these statistics between groups is calculated. The number of \(m\) groups is increased and the process is repeated. Hurst exponent is determined by the linear regression of the slope of the ideal line graph. Higuchi--In this case, it is assumed that the series has the character of noise, not motion. The series is divided into \(m\) groups. The total sum of the series is calculated to convert the series from noise to motion. Absolute differences in total sums between groups are analysed to estimate the fractal dimension of the pathway. The number of \(m\) groups is increased, and the process is repeated. The H-value is determined by the linear regression of a logarithmic chart [24; 30]. The Hurst coefficient estimation showed that for the Aggvar method, the H value was 0.813, and for the Higuchi method it was 1.028. The discrepancy was therefore about 25%. The Hurst exponent values are determined by the hurstBlock command shapes within limits set by the other commands. It can be stated that the H-value estimated by these methods is reliable.