摘要
针对NetFlow抽样概率需手动配置的缺陷,提出了一种基于包速率自适应的分组抽样算法。通过测量包速率,采用预定义测量误差的方法,根据包速率的变化自适应地调整抽样概率,从而在有限资源情况下达到控制测量误差的目的。基于实际互联网数据进行了实验比较,结果显示:与传统的NetFlow算法相比,该方法易于实现,测量误差可控,具有高效性和准确性,同时具有资源节约性。
For the inflexibility of NetFlow＇s sampling probability,this paper proposed the algorithm based on packet rate adaptive for packet sampling.The algorithm measured the packet rate,employed the predefine measurement error,adaptively adjusted the sampling probability according to the change of packet rate and advanced to control the measurement error.Also conducted experiments based on real network traces.Results demonstrate that the proposed method can implement simplicity,controllability of measurement error with higher efficiency and without sacrificing accuracy,while memory consumption is lower compared with other methods.
出处
《计算机应用研究》
CSCD
北大核心
2010年第7期2727-2729,共3页
Application Research of Computers
基金
国家"863"计划资助项目(2008AA01A323)
关键词
流量测量
包速率
自适应
抽样
traffic measurement
packet rate
adaptive
sampling
