A reconstructing approach to end-to-end network traffic based on multifractal wavelet model

AbstractThis paper studies the reconstructing method of end-to-end network traffic. Due to the development of current communication networks, our networks become more complex and heterogeneous. Meanwhile, because of time-varying nature and spatio-temporal correlations of the end-to-end network traffic, to obtain it accurately is a great challenge. We propose to exploit discrete wavelet transforms and multifractal analysis to reconstruct the end-to-end network traffic from time-frequency domain. First, its time-frequency properties can be characterized in detail by discrete wavelet transforms. And then, we combine discrete wavelet transforms and multifractal analysis to reconstruct end-to-end network traffic from link loads. Furthermore, our method needs to measure end-to-end network traffic to build the statistical model named multifractal wavelet model. Finally, simulation results from the real backbone networks suggest that our method can reconstruct the end-to-end network traffic more accurately than previous methods. Copyright © 2013 John Wiley & Sons, Ltd.