摘要
基于信息熵的理论提出了一种大规模、高速IPv6网络流量抽样测量方法,对实际IPv6网络流量数据进行了统计分析,比较了IPv6数据报文头的各个字段比特位的随机性,选择出随机性好的字段作为抽样的匹配字段输入,满足了抽样样本的随机性要求。通过软件编程实现了该抽样测量方法,并抽样采集了实际IPv6网络流量,实验数据表明其结果具有良好的均匀性,且总体和样本的数据报文大小的分布函数曲线吻合。
A novel traffic sampling measurement method in high speed IPv6 networks is proposed. The method is to sample IPv6 traffic based on the information entropy theory. Firstly, we present a distributed IPv6 network sampling measurement framework including communication and sampling modules. Secondly, through computing the bit entropy in real IPv6 traffic traces, we discuss the randomicity of each byte in lPv6 packet headers, and select those bytes having a good randomicity as the input of our traffic sampling method. Finally, an experiment is performed to prove that the output of our method has sufficiently uniform and the sample＇s curve of cumulative distribution function of packet size is fully conformed to the parent＇s.
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2009年第5期1337-1341,共5页
Journal of Jilin University:Engineering and Technology Edition
基金
国家自然科学基金项目(60572147
60132030)
陕西省科技攻关项目(2006k04-G33)
关键词
计算机应用
网络流量
抽样测量
信息熵
哈希函数
高速网络
computer application
network traffic
sampling measurement
entropy
hash function
highspeed networks
