Abstract #301246

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JSM 2002 Abstract #301246
Activity Number: 67
Type: Topic Contributed
Date/Time: Monday, August 12, 2002 : 8:30 AM to 10:20 AM
Sponsor: Section on Physical & Engineering Sciences*
Abstract - #301246
Title: Prediction of Web Traffic
Author(s): Ta-Hsin Li*+
Affiliation(s): IBM T. J. Watson Research Center
Address: IBM T. J. Watson Research Center, Yorktown Heights, New York, 10598-0218, USA
Keywords: time series ; forecasting ; spectral analysis ; autoregressive ; least squares
Abstract:

A hierarchical method is proposed to forecast the Web traffic time series (e.g., the size of HTTP requests on a Web server aggregated over five-minute intervals). The method provides both long-term (in days) and short-term (in minutes) predictions with confidence bands. It takes into account many characteristics of the web traffic data, including diurnal cycle, multiple regime, non-stationarity, and heavy-tail distribution. The predictive model can also be used to simulate Web traffic.

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