Power and performance analysis of network traffic prediction techniques

Authors:
Muhammad Faisal Iqbal;Lizy K. John
Affiliations:
University of Texas at Austin, USA;University of Texas at Austin, USA
Venue:
ISPASS '12 Proceedings of the 2012 IEEE International Symposium on Performance Analysis of Systems & Software
Year:
2012

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Abstract

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.