赖英旭, 高春梅. 工业控制网络流量特性分析与建模[J]. 北京工业大学学报, 2015, 41(7): 991-999. DOI: 10.11936/bjutxb2014050037
    引用本文: 赖英旭, 高春梅. 工业控制网络流量特性分析与建模[J]. 北京工业大学学报, 2015, 41(7): 991-999. DOI: 10.11936/bjutxb2014050037
    LAI Ying-xu, GAO Chun-mei. Industrial Control Network Traffic Characteristic Analysis and Modeling[J]. Journal of Beijing University of Technology, 2015, 41(7): 991-999. DOI: 10.11936/bjutxb2014050037
    Citation: LAI Ying-xu, GAO Chun-mei. Industrial Control Network Traffic Characteristic Analysis and Modeling[J]. Journal of Beijing University of Technology, 2015, 41(7): 991-999. DOI: 10.11936/bjutxb2014050037

    工业控制网络流量特性分析与建模

    Industrial Control Network Traffic Characteristic Analysis and Modeling

    • 摘要: 采集了真实环境中的基于工业以太网的工业控制网络流量,通过对流量特性的分析发现其流量特性与普通IT网络流量特性的差异,并详细分析了其成因.通过分析发现,工业控制网络流量分布整体较规律,数据包时间间隔既不服从泊松分布又不服从重尾分布,小时间尺度上具有周期性,没有表现出自相似的特性,大时间尺度上则较为平稳.最后,应用季节乘积ARIMA模型对工业网络流量进行了实证分析.结果表明:应用该模型对工业网络流量进行建模预报是可行可靠的.

       

      Abstract: This paper collects network traffic of an industrial control system that is based on industrial Ethernet in a real environment. By analyzing the characteristics of the network, it is found that there is an obvious difference between the characteristics of industrial control network and ordinary IT network. The cause of the difference is carefully analyzed. The traffic of industrial control network has a relatively regularity. As a whole, the distribution packet intervals neither follow a Poisson distribution nor subject to heavy tailed distribution. In a small time scale, the traffic has a periodicity and it does not show self-similarity, while it is stationary in a large time scale. Finally, a multiple seasonal ARIMA model is used to make empirical analysis on the industrial network traffic. Results show that the model is feasible and reliable.

       

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