东南大学学报（英文版）2002，Vol.18Issue(1)：40-45,6.
大规模高速IP网络分布式抽样测量模型
Distributed Sampling Measurement Model in a Large-Scale High-Speed IP Networks
摘要
Abstract
The distributed passive measurement is an important technology for network behavior research. To achieve a consistent measurement, the same packets should be sampled at distributed measurement points. And in order to estimate the character of traffic statistics, the traffic sample should be random in statistics. A distributed sampling mask measurement model is introduced to tackle the difficulty of measuring the full trace of high-speed networks. The key point of the model is to choose some bits that are suitable to be sampling mask. In the paper, the bit entropy and bit flow entropy of IP packet headers in CERNET backbone are analyzed, and we find that the 16 bits of identification field in IP packet header are fit to the matching field of sampling mask. Measurement traffic also can be used to analyze the statistical character of measurement sample and the randomicity of the model. At the same time the experiment results indicate that the model has a good sampling performance.关键词
抽样测量/位熵/匹配字段/标识字段Key words
sampling measurement/bit entropy/matching field/identification field分类
信息技术与安全科学引用本文复制引用
龚俭,程光..大规模高速IP网络分布式抽样测量模型[J].东南大学学报（英文版）,2002,18(1):40-45,6.基金项目
The project supported by the National Natural Science Foundation of China(90104031), and 863 program of China(2001AA112060). （90104031）
