挖掘算法在高速网络流频繁项计算中的实验应用

Experiment Application of Frequent Items Mining Algorithm in High-Speed Network Flow Calculation

近年来,计算机网络技术发展迅速,且为社会各项生产、生活领域的发展提供必要的信息和技术支持。网络管理与网络安全,特别是在当前骨干网络链路呈几何倍数增长的背景下,网络安全与管理就显得尤其重要。为了进一步确保网络安全并实现网络的规范化管理,通过对网络流的特性进行分析,进而引入IWFIM和CBF-IWFIM算法,通过对二者的原理及算法进行分析,在结合IWFIM算法的基础上,以网络流重尾分布特性为依据,利用IWFIM实现对高速网络流量频繁项的挖掘。通过对网络流量的实际测试表明,IWFIM算法与CBF-IWFIM算法具有较高的空间准确率及利用率。

In recent years,computer network technology has developed rapidly,and for the development of various social production and life provides the necessary information and technical support.Network management and network security,especially in the current backbone link geometric multiples growth background,the network security and management is particularly important.In order to further ensure the security of the network and to realize the standardization of the network management,through analysis of the characteristics of the network flow,and then introduces the IWFIM and CBF-IWFIM algorithm,through the analysis of the principle and algorithm of both,on the basis of combining IWFIM algorithm,based on network flowheavy-tailed distribution characteristics,uses IWFIM to realize high-speed network traffic mining frequent items.Through the network traffic practical test shows that IWFIM algorithm and CBF-IWFIM algorithm has high accuracy and efficiency.