基于TCBF算法的网络流信息统计

Network flows' information statistics based on TCBF algorithm

针对传统的网络流信息统计算法容易溢出、频繁更新等特点,提出一种基于TCBF(time bloom filter&counting bloom filter)的网络流信息统计算法用于实时在线统计高速网络流信息。算法一方面利用短流超时特点使用time bloom filter抽取短流信息;另一方面利用网络流量分布呈现重尾分布的特性使用counting bloom filter过滤长流报文。分析了算法的复杂度和误判率,并通过模拟数据分析了算法参数配置对于流信息统计准确性和抽样率的影响。理论分析和仿真结果表明,与标准counting bloom filter相比,TCBF算法可以在使用较少的存储空间的条件下,及时、准确地对网络流量信息进行统计,满足实际测量需要。

Aiming at the problems of traditional network traffic record algorithm is easy to overflow and update frequently,this paper proposed a new algorithm based on time bloom filter ＆ counting bloom filter（ TCBF） to record hight speed network traffic information in time. On the one hand,time bloom filter sampled the mice flows by using of the timeout characteristics,on the other hand,counting bloom filter filtrated the packets of large flows by using of network traffic distribution showed heavytailed characteristics. It analyzed the complexity and false positive rate of the algorithm. It analyzed the effect of flow information statistical accuracy and sampling rate for parameter configuration through simulation. The theoretical analysis and the simulation result indicate that compare to bloom filter,the TCBF agorithm can generate the statistics of the network flows immediately and accurately under the condition of using less storage space,and satisfies the need of actual measurement.