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A novel hybrid prediction algorithm to network traffic

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Abstract

Network traffic describes the characteristics and users’ behaviors of communication networks. It is a crucial input parameter of network management and network traffic engineering. This paper proposes a new prediction algorithm to network traffic in the large-scale communication network. First, we use signal analysis theory to transform network traffic from time domain to time-frequency domain. In the time-frequency domain, the network traffic signal is decomposed into the low-frequency and high-frequency components. Second, the gray model is exploited to model the low-frequency component of network traffic. The white Gaussian noise model is utilized to describe its high-frequency component. This is reasonable because the low-frequency and high-frequency components, respectively, represent the trend and fluctuation properties of network traffic, while the gray model and white Gaussian noise model can well capture the characteristics. Third, the prediction models of low-frequency and high-frequency components are built. The hybrid prediction algorithm is proposed to overcome the problem of network traffic prediction in the communication network. Finally, network traffic data from the real network is used to validate our approach. Simulation results indicate that our algorithm holds much lower prediction error than previous methods.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China (No. 61071124), the Program for New Century Excellent Talents in University (No. NCET-11-0075), the Fundamental Research Funds for the Central Universities (Nos. N120804004, N130504003), and the State Scholarship Fund (201208210013). The authors wish to thank the reviewers for their helpful comments.

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Authors and Affiliations

  1. College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China

    Dingde Jiang & Hongwei Xu

  2. School of Economics and Management, Anqing Normal University, Anqing, 246011, China

    Zhengzheng Xu

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  1. Dingde Jiang
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  2. Zhengzheng Xu
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  3. Hongwei Xu
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Correspondence to Dingde Jiang.

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Jiang, D., Xu, Z. & Xu, H. A novel hybrid prediction algorithm to network traffic. Ann. Telecommun. 70, 427–439 (2015). https://doi.org/10.1007/s12243-015-0465-8

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  • DOI: https://doi.org/10.1007/s12243-015-0465-8

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