Nonlinear Prediction of Network Traffic Measurements Data

In this paper we apply the nonlinear time series prediction method to the traffic measurements data. Based on the phase space reconstruction, the support vector machine prediction method is used to predict the traffic measurements data, and the neighbor point selection method is used to choose the n...

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Bibliographic Details
Published in2009 International Joint Conference on Computational Sciences and Optimization Vol. 1; pp. 336 - 339
Main Authors Qing-Fang Meng, Yuehui Chen, Yuhua Peng, Wei Li
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2009
Subjects
Communication system traffic control
Delay
Information science
network traffic
nonlinear prediction
Prediction methods
Predictive models
support vector machine
Support vector machines
Telecommunication traffic
Time measurement
Time series analysis
Traffic control
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Summary:In this paper we apply the nonlinear time series prediction method to the traffic measurements data. Based on the phase space reconstruction, the support vector machine prediction method is used to predict the traffic measurements data, and the neighbor point selection method is used to choose the number of nearest neighbor points for the support vector machine regression model. The experiment results show that the nonlinear time series prediction method can effectively predict the traffic measurements data and the prediction error mainly concentrates on the vicinity of zero.
ISBN:9780769536057
0769536050
DOI:10.1109/CSO.2009.293