Title:
Time Series Models for Internet Traffic
Time Series Models for Internet Traffic
Author(s)
Basu, Sabyasachi
Mukherjee, Amarnath
Klivansky, Steven M.
Mukherjee, Amarnath
Klivansky, Steven M.
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Abstract
Data traffic sequences from two campus FDDI rings, an Ethernet, two entry/exit
points of the NSFNET, and sub-sequences belonging to popular TCP port numbers
on one of the FDDI rings indicate that appropriately differenced time-series
generated from these traces can be modeled as Auto-Regressive-Moving-Average
(ARMA) processes. The variates of the ARMA filter are, however, non-Gaussian.
A sequence of steps leading through
(i) parameter estimation,
(ii) generating the distribution of the variates,
(iii) forecasting tail percentiles, and
(iv) synthetic generation of non-negative integer sequences is presented.
The data indicates that parameter estimates drift slowly with time and may
need to be re-computed periodically for accurate forecasts. The forecasting
algorithm has potential application in dynamic resource allocation. The
synthetic traffic generation algorithm may be used in simulation studies of
resource management algorithms.
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Date Issued
1995
Extent
316296 bytes
Resource Type
Text
Resource Subtype
Technical Report