Time Series Analysis of Computer Network Traffic in a Dedicated Link Aggregation
G. Mill\'an, G. Lefranc, R. Osorio-Compar\'an, V. Lomas-Barrie

TL;DR
This study applies fractal analysis to high-speed network traffic, confirming that such traffic exhibits fractal behavior and long-range dependence, which is crucial for understanding and modeling network performance.
Contribution
It demonstrates the presence of fractal behavior and long-range dependence in high-speed network traffic using specific fractal analysis techniques.
Findings
Traffic exhibits fractal behavior with Hurst exponent between 0.5 and 1.
Fractal dimension ranges from 1 to 1.5.
Correlation coefficient between -0.5 and 0.
Abstract
Fractal behavior and long-range dependence are widely observed in measurements and characterization of traffic flow in high-speed computer networks of different technologies and coverage levels. This paper presents the results obtained when applying fractal analysis techniques on a time series obtained from traffic captures coming from an application server connected to the Internet through a high-speed link. The results obtained show that traffic flow in the dedicated high-speed network link have fractal behavior when the Hurst exponent is in the range of 0.5, 1, the fractal dimension between 1, 1.5, and the correlation coefficient between -0.5, 0. Based on these results, it is ideal to characterize both the singularities of the traffic and its impulsiveness during a fractal analysis of temporal scales. Finally, based on the results of the time series analyses, the fact that the…
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Theoretical and Computational Physics · Chaos control and synchronization
