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Network Traffic Model with Multi-fractal Discrete Wavelet Transform in Power Telecommunication Access Networks

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Simulation Tools and Techniques (SIMUtools 2019)


With the development of communication networks, a lot of new applications emerge in the power telecommunication access networks, which have many new features and properties of the network traffic. These features are important for modeling the network traffic in the network-level. This paper propose a new feature extraction and network traffic model method. Firstly, we analyze the features of network traffic in time-frequency domain. Then, we use discrete wavelet transform to exploit the features of network traffic in the time domain and frequency domain. We run multi-fractal discrete wavelet transform (MDWT) for network traffic to decompose them into different frequency component and train an artificial neural network to predict the low- and high-frequency components of network traffic, and use them to reconstruct the network traffic. Finally, in order to validate our network traffic model, we conduct the network traffic prediction on the actual data. Simulation results show that our approach is feasible.

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Correspondence to Xin Wei .

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Lu, Y. et al. (2019). Network Traffic Model with Multi-fractal Discrete Wavelet Transform in Power Telecommunication Access Networks. In: Song, H., Jiang, D. (eds) Simulation Tools and Techniques. SIMUtools 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 295. Springer, Cham.

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-32215-1

  • Online ISBN: 978-3-030-32216-8

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