DocumentCode
3103573
Title
Testing the Gaussian assumption for self-similar teletraffic models
Author
Bates, Stephen ; Mclaughlin, Steve
Author_Institution
Dept. of Electr. Eng., Edinburgh Univ., UK
fYear
1997
fDate
21-23 Jul 1997
Firstpage
444
Lastpage
447
Abstract
Both the fractional Brownian motion (fBm) and the autoregressive integrated moving average (ARIMA) models have been applied to teletraffic scenarios in recent years. These models became popular after the discovery that Ethernet and VBR video data appear to possess the property of self-similarity. However the results presented in this paper suggest that Ethernet data is more impulsive than traffic generated by these models
Keywords
Brownian motion; Gaussian processes; autoregressive moving average processes; local area networks; modelling; random processes; telecommunication traffic; testing; Ethernet; Gaussian assumption; VBR video data; autoregressive integrated moving average model; fractional Brownian motion model; modelling; self-similar teletraffic models; testing; Autocorrelation; Automatic testing; Brownian motion; Ethernet networks; H infinity control; Markov processes; Resource management; Technological innovation; Time series analysis; Traffic control;
fLanguage
English
Publisher
ieee
Conference_Titel
Higher-Order Statistics, 1997., Proceedings of the IEEE Signal Processing Workshop on
Conference_Location
Banff, Alta.
Print_ISBN
0-8186-8005-9
Type
conf
DOI
10.1109/HOST.1997.613564
Filename
613564
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