DocumentCode
2221891
Title
SFARIMA: A New Network Traffic Prediction Algorithm
Author
Wang Pan ; Zhang Shun-Yi ; Chen Xue-Jiao
Author_Institution
Inf. Network Res. Inst., Nanjing Univ. of Posts & Telecommun., Nanjing, China
fYear
2009
fDate
26-28 Dec. 2009
Firstpage
1859
Lastpage
1863
Abstract
In this paper, we have studied on network traffic self-similarity as a starting point, analyze and predict data of the real network traffic by Fractal Autoregressive Integrated Moving Average (FARIMA), and propose sliding FARIMA (SFARIMA) network traffic prediction model. The model keeps sliding the time sequence to compensate the time lag of FARIMA and reduce the fitting error, therefore, it matches the original self-similar sequence better.
Keywords
autoregressive moving average processes; prediction theory; telecommunication traffic; SFARIMA network traffic prediction model; fractal autoregressive integrated moving average; network traffic prediction algorithm; network traffic self-similarity; sliding FARIMA; time lag; time sequence; Communication system traffic control; Data analysis; Educational institutions; Fractals; IP networks; Mathematical model; Prediction algorithms; Predictive models; Telecommunication traffic; Traffic control;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-4909-5
Type
conf
DOI
10.1109/ICISE.2009.1060
Filename
5455095
Link To Document