Nonlinear Prediction of Network Traffic Measurements Data

Author

Meng, Qing-Fang ; Chen, Yuehui ; Peng, Yuhua ; Li, Wei

Author_Institution

Sch. of Inf. Sci. & Eng., Univ. of Jinan, Jinan, China

Volume

1

fYear

2009

fDate

24-26 April 2009

Firstpage

336

Lastpage

339

Abstract

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.

Keywords

computer networks; regression analysis; support vector machines; telecommunication traffic; time series; nearest neighbor point selection method; network traffic measurement data; nonlinear time series prediction method; phase space reconstruction; support vector machine prediction method; support vector machine regression model; Communication system traffic control; Delay; Information science; Prediction methods; Predictive models; Support vector machines; Telecommunication traffic; Time measurement; Time series analysis; Traffic control; network traffic; nonlinear prediction; support vector machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on

Conference_Location

Sanya, Hainan

Print_ISBN

978-0-7695-3605-7

Type

conf

DOI

10.1109/CSO.2009.293

Filename

5193708