基于M值概率分布的网络视频流分类  

Network Video Traffic Classification Based on Probability Distribution of M Value

作　　者：杨凌云 董育宁[1] 王再见[2] 汤萍萍[1,2] YANG Lingyun;DONG Yuning;WANG Zaijian;TANG Pingping(College of Communication and Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210003,China;College of Physics and Electronic Information,Anhui Normal University,Wuhu 241000,China)

机构地区：[1]南京邮电大学通信与信息工程学院,南京210003 [2]安徽师范大学物理与电子信息学院,芜湖241000

出　　处：《电子与信息学报》2018年第5期1094-1100,共7页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(61271233;61401004;61601005);华为HIRP创新项目;安徽师范大学博士科研启动金项目(2016XJJ129)~~

摘　　要：为了改善网络视频流的细粒度分类效果,该文分析视频流传输过程中的特征变化与流分类之间的关系。根据不同类型的视频流具有不同的下行传输速率变化模式,提出一种新的基于下行速率传输的视频流分类特征—M值概率分布,并使用支持向量机(SVM)实现网络视频流的分类。实验结果表明,M值概率分布相比较于已有的常见流特征,可以更好地实现6种典型的网络视频流分类。To obtain better results for fine-grained video traffic classification, this paper analyzes the relationship between the feature variations during transmission and video traffic classification. According to the nature that different types of video services contain different downlink transmission rate variation patterns, a new video flow feature M value probability distribution, based on downlink byte rate variation is proposed, and video classification is realized by Support Vector Machine （SVM）. The experimental results show that the probability distribution of M value is a better feature for classification of six kinds of common network video applications than other commonly used flow features.

关 键 词：网络视频流 流分类 M值概率分布 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]