The modelling of very long stationary Gaussian sequences with an arbitary correlation function
USSR Computational Mathematics and Mathematical Physics
Digital spectral analysis: with applications
Digital spectral analysis: with applications
On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
Self-Similar Network Traffic and Performance Evaluation
Self-Similar Network Traffic and Performance Evaluation
The Fractal Internet: Traffic Analysis, Simulation, Estimation and Control
The Fractal Internet: Traffic Analysis, Simulation, Estimation and Control
Modeling randomness in network traffic
Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
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A method was proposed for numerical modeling of the time series of network traffic on the basis of the nonlinear transformation of the random Gaussian processes. The fractal characteristics of both initial and modeled time series were analyzed. The method was shown to be capable of reproducing one-dimensional distributions, correlations, and fractal characteristics of the time series under consideration.