朱元利, 刘云, 张春平. 基于软件的流量监测高阶间隔均值算法[J]. 云南大学学报(自然科学版), 2013, 35(6): 762-766. doi: 10.7540/j.ynu.20120708
引用本文: 朱元利, 刘云, 张春平. 基于软件的流量监测高阶间隔均值算法[J]. 云南大学学报(自然科学版), 2013, 35(6): 762-766. doi: 10.7540/j.ynu.20120708
ZHU Yuan-li, LIU Yun, ZHANG Chun-ping. The high inter-arrival means algorithm for network traffic monitoring based on the software[J]. Journal of Yunnan University: Natural Sciences Edition, 2013, 35(6): 762-766. DOI: 10.7540/j.ynu.20120708
Citation: ZHU Yuan-li, LIU Yun, ZHANG Chun-ping. The high inter-arrival means algorithm for network traffic monitoring based on the software[J]. Journal of Yunnan University: Natural Sciences Edition, 2013, 35(6): 762-766. DOI: 10.7540/j.ynu.20120708

基于软件的流量监测高阶间隔均值算法

The high inter-arrival means algorithm for network traffic monitoring based on the software

  • 摘要: 随着网络带宽及传输速率的不断提高,而以软件及硬件为基础的流量监测精度较低、系统延时较大.针对上述不足,该文提出一种在软件监测以及高带宽、高传输速率条件下的流量监测算法,即以低阶实测数据和不同阶间隔信息均等分布为基础的高阶间隔实时估计方法,并且利用相对熵对采样结果进行性能分析与估计.仿真结果表明随着高阶间隔的逐渐增大,流量监测的精度得到逐步提高,而系统延时显著减少.

     

    Abstract: With the continuous improvement of network bandwidth and transmission rate,the precision of traffic monitoring based on software and hardware is lower,and the system delay is bigger.In order to solve the above problem,we propose a software traffic monitoring algorithm under the condition of high bandwidth and high transmission rate.It is high order interval message estimation method based on the low-order measured data and interval message with different order.We analyze and estimate the sampling results using relative entropy.Simulation results show that the accuracy of traffic monitoring is gradually improved and system delay is further reduced with high order interval increased.

     

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