Algorithm for modeling self-similar ethernet traffic

Authors:
Evgeniya Gospodinova
Affiliations:
-
Venue:
CompSysTech '09 Proceedings of the International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing
Year:
2009

Citing 4
Cited 1

Self-similarity through high-variability: statistical analysis of Ethernet LAN traffic at the source level

IEEE/ACM Transactions on Networking (TON)
Fast, approximate synthesis of fractional Gaussian noise for generating self-similar network traffic

ACM SIGCOMM Computer Communication Review
Synthesis of fractional gaussian noise using linear approximation for generating self-similar network traffic

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A wavelet-based joint estimator of the parameters of long-range dependence

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Abstract

This paper is presented and analysed an algorithm for modeling self-similar Ethernet traffic, based on the fractional Gaussian noise (FGN) and wavelet transformation. The algorithm uses a second-order approximation for calculation of the power spectrum of FGN and Daubeshies wavelets. It is investigated in terms of the accuracy of Hurst parameter by using the wavelet-based statistical estimator. The simulated self-similar Ethernet traffic is compared with actual Ethernet traffic. The obtained results show that the algorithm for modeling of self-similar Ethernet traffic is with high degree of accuracy and it can be used in practical computer simulation studies.