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Power and performance analysis of network traffic prediction techniques

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2 Author(s)
Muhammad Faisal Iqbal ; University of Texas at Austin, USA ; Lizy K. John

We study power and performance characteristics of different traffic predictors for online one-step-ahead predictions. The goal is to identify a predictor with reasonable accuracy and low power consumption. Our experiments on a large number of real network traces indicate that Double Exponential Smoothing and Auto-Regressive Moving Average are low cost predictors with reasonable accuracy.

Published in:

Performance Analysis of Systems and Software (ISPASS), 2012 IEEE International Symposium on

Date of Conference:

1-3 April 2012