Title :
An analysis of the combined wavelet-GM (1,1) model for network traffic forecasting
Author :
Bai, Yan ; Ke Ma ; Ma, Guangsi
Author_Institution :
Sch. of Sci., Xi´´an Univ. of Archit. & Technol., Xi´´an, China
Abstract :
Based on grey theory, a combined wavelet-GM (1,1) forecasting model is proposed. The random properties of some non-stationary time series can be reduced by wavelet decomposition into many series according to different scales. Decomposed time series are predicted with GM (1,1) model to obtain forecasted results of the original time series. Experiments on network traffic show that the combined model is more effective than the common grey model. The application of the proposed combined model to network traffic forecasting may offer scientific rationale to Internet routing decision, LAN virus detection and illegal invasion prevention.
Keywords :
forecasting theory; telecommunication traffic; time series; wavelet transforms; Internet routing decision; LAN virus detection; combined wavelet-GM model; grey theory; illegal invasion prevention; network traffic forecasting; nonstationary time series; random properties; wavelet decomposition; Communication system traffic control; Differential equations; Economic forecasting; Predictive models; Routing; Stochastic processes; Technology forecasting; Telecommunication traffic; Traffic control; Wavelet analysis; Forecast Model; GM(1,1); Network Traffic; Wavelet Theory;
Conference_Titel :
Network Infrastructure and Digital Content, 2009. IC-NIDC 2009. IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4898-2
Electronic_ISBN :
978-1-4244-4900-6
DOI :
10.1109/ICNIDC.2009.5360794
