Time Series Analysis of Computer Network Traffic in a Dedicated Link Aggregation

EasyChair Preprint 5644

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 traffic flows of current computer networks exhibit fractal behavior with a long-range dependency is reaffirmed.

Keyphrases: High-speed computer networks, Hurst exponent, fractal dimension, long-range dependence, time series, traffic flows

@booklet{EasyChair:5644,
  author    = {Ginno Millán and Gastón Lefranc and Román Osorio-Comparán and Víctor Lomas-Barrie},
  title     = {Time Series Analysis of Computer Network Traffic in a Dedicated Link Aggregation},
  howpublished = {EasyChair Preprint 5644},
  year      = {EasyChair, 2021}}