A Wavelet Analysis-Based Dynamic Prediction Algorithm to Network Traffic

• Main Authors: Meng Fan-Bo, Zhao Hong-Hao, Zhao Si-Hang, Zhao Si-Wen, Lin Zhong-Qiu
• Format: Article
• Language: English
• Published: EDP Sciences 2016-01-01
• Series: ITM Web of Conferences
• Online Access: http://dx.doi.org/10.1051/itmconf/20160709025

Network traffic is a significantly important parameter for network traffic engineering, while it holds highly dynamic nature in the network. Accordingly, it is difficult and impossible to directly predict traffic amount of end-to-end flows. This paper proposes a new prediction algorithm to network traffic using the wavelet analysis. Firstly, network traffic is converted into the time-frequency domain to capture time-frequency feature of network traffic. Secondly, in different frequency components, we model network traffic in the time-frequency domain. Finally, we build the prediction model about network traffic. At the same time, the corresponding prediction algorithm is presented to attain network traffic prediction. Simulation results indicates that our approach is promising.