摘要：

为适应高速网络环境并实现对网络流量的准确测量,提出一种将计数型布隆过滤器结构与基于报文的流抽样技术相结合的网络流等概率抽样算法。利用4 bit的Counter向量识别是否有新流出现,通过实时调整抽样频率弥补新流判定中的错误率,从而对网络流进行等概率抽样 并获取较真实的网络流分布情况。实验结果表明,该算法的测量结果与网络流真实值较接近,且具有可扩展性,可以满足当前复杂多变的高速网络环境下的流量测量需求。

关键词: 高速网络, 流抽样, 计数型布隆过滤器, 等概率抽样, 哈希函数, Counter向量

Abstract:

In order to adapt to the high-speed network environment and realize the accurate measurement of network traffic,a network algorithm of flow equal probability sampling based on the combination of Counting Bloom Filter and packet-based flow sampling technique is proposed.It identifies whether there is a new flow by the 4 bit Counter vector,and realizes the equal probability sampling of the network flow by adjusting the sampling frequency constantly to compensate for the error rate of the new flow judgement.Then,it makes an equal probability sampling of network flow and obtains a more realistic distribution of network traffic.Experimental results show that the algorithm’s measurement results are close to the real value of network flow,and it has scalability,which can meet the current demand of traffic measurement in the complex and changeable high-speed network environment.

Key words: high-speed network, flow sampling, Counting Bloom Filter, equal probability sampling, hash function, Counter vector

中图分类号: 

• TP391