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
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;
Conference_Titel :
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4909-5
DOI :
10.1109/ICISE.2009.1060
