期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2019
卷号：252
期号：4
页码：1-6
DOI：10.1088/1755-1315/252/4/042036
出版社：IOP Publishing
摘要：With the development of network and streaming media technology, network video traffic is growing rapidly. In order to better control and manage network traffic and guarantee the quality of service of network video, it is necessary to classify network video services effectively. In traffic identification and classification, feature analysis and acquisition of better features are the key points to achieve efficient classification. Starting with the characteristics of packet size distribution, rate, IP alternation, byte number ratio between downstream and upstream, number of sub-stream fragments and average packet arrival time interval, this paper uses Support Vector Machine (SVM) to verify the classification effect of this feature, and achieves a high classification accuracy
