WF-C4.5:WiFi环境下基于C4.5决策树的手持终端流量识别方法

目前移动数据流量已占全球IP流量的47%,其中WiFi流量已占整个移动数据流量的90%以上。WiFi环境下移动终端流量的识别对互联网流量管理具有重要意义。传统基于HTTP用户代理(User Agent,UA)的流量识别方法存在识别率不高的问题。分析了WiFi环境下移动终端连接持续时间、数据包大小、有效载荷大小等流量特征,提出一种WiFi环境下基于C4.5决策树的手持终端设备流量识别方法WF-C4.5,通过计算各属性值的信息增益率构建决策树模型,实现手持终端与非手持终端流量的区分。实验表明,相比UA方法65%的准确率,所提方法的准确率高达95%。

WF-C4.5:Handheld Terminal Traffic Identification Method Based on C4.5 Decision Tree in WiFi Environment

It was reported that mobile terminals account for about 47% global IP traffic while WiFi traffic account for over 90% mobile traffic.Identification of mobile terminal traffic is important for efficient network traffic management.In order to solve the low identification rate problem of traditional HTTP user agent (UA) method,we analyzed the features of mobile terminal traffic in WiFi environment,including the connection persist time,packet size and payload size,etc.We proposed WF-C4.5:a handheld terminal traffic identification method based on C4.5 decision tree in WiFi environment.The method distinguishes handheld terminal traffic from non-handheld traffic by decision tree model which is created by calculating the information gain ratio of each attribute value.The experiments show that the identification rate of WF-C4.5 can reach 95%,while the identification rate of UA is about 65%.