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A Time-Series Model of Long-Term Traffic on the NSFNET Backbone
N. Groschwitz and G. Polyzos, "A Time-Series Model of Long-Term Traffic on the NSFNET Backbone", in IEEE Conference on Communications (ICC), May 1994, pp. 1400--1404.
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A Time-Series Model of Long-Term Traffic on the NSFNET Backbone

Nancy Groschwitz
George Polyzos

University of California, San Diego

We used time series analysis to create detailed forecasts of future NSFNET backbone traffic. The resulting ARIMA model made quite accurate forecasts of traffic levels up to a year in advance. It appears that the model can make reasonable predictions for two or more years into the future, suggesting that ARIMA modeling has great promise as a tool for long-range NSFNET forecasting and planning.

Keywords: measurement methodology, passive data analysis
  Last Modified: Wed Oct-11-2017 17:03:43 PDT
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