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    于 秦 毛玉明. 自相似参数辨识与汇聚无线业务尺度特性分析[J]. 计算机研究与发展, 2007, 44(1): 58-64.
    引用本文: 于 秦 毛玉明. 自相似参数辨识与汇聚无线业务尺度特性分析[J]. 计算机研究与发展, 2007, 44(1): 58-64.
    Yu Qin and Mao Yuming. Self-Similarity Parameter Estimation and Scaling Properties Analyses of Aggregated Wireless Traffic[J]. Journal of Computer Research and Development, 2007, 44(1): 58-64.
    Citation: Yu Qin and Mao Yuming. Self-Similarity Parameter Estimation and Scaling Properties Analyses of Aggregated Wireless Traffic[J]. Journal of Computer Research and Development, 2007, 44(1): 58-64.

    自相似参数辨识与汇聚无线业务尺度特性分析

    Self-Similarity Parameter Estimation and Scaling Properties Analyses of Aggregated Wireless Traffic

    • 摘要: Hurst参数是衡量网络流量自相似程度和突发性的重要参数,在时域R/S统计、方差-时间图法和频域周期图法的基础上,提出一种最优化线性回归小波模型,实现小波域内Hurst参数的准确有效快速辨识.研究了WLAN中多个输入业务源的汇聚过程以及汇聚的多输入自相似业务源统计特性.仿真实验比较了传统的以及基于最优化线性回归小波模型的Hurst参数辨识方法,验证了理论分析中汇聚自相似业务也呈现自相似性的结论,且仿真结果表明,汇聚业务的突发性得到加强而不是削弱.研究结论对网络流量的准确建模以及网络传输中流量控制和优化网络资源配置以及提高网络性能具有重要作用.

       

      Abstract: Hurst parameter is important to measure the self-similarity degree and bustiness of network traffic. Based on R/S statistic, variance-time plots and periodogram-based analysis methods, an optimal linear regression wavelet model is proposed to perform the accurate, quick and effective estimation of the Hurst parameter in wavelet field. The aggregating process and statistic characteristics of multiple input traffic sources in WLAN are studied. Simulation results compare the Hurst parameter estimation values of self-similar WLAN traffic by using the above statistical approaches. Furthermore, theoretical analyses and simulation results demonstrate that the aggregated traffic at WLAN also exhibits self-similarity, which actually intensifies rather than diminishes burstiness. These results can be very useful for accurate modeling, traffic control, resource allocation optimization and performance improvement of WLAN.

       

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