2021/05/11 by G. Millán, G. Lefranc, Millán, G. +5
Economics, Econometrics and Finance · Physics and Astronomy · #68Q11 (Primary) #94A12 (Secondary) #Chaos control and synchronization #Complex Systems and Time Series Analysis #F.2.1 #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Physical sciences #G.2.0 #Networking and Internet Architecture (cs.NI) #Physics and Society (physics.soc-ph) #Signal Processing (eess.SP) #Theoretical and Computational Physics #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2107.05484
openalex publication_date 2021/05/11 · openalex created_date 2022/08/26 · openalex updated_date 2026/07/28
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.