P2P-based IPTV (P2P-TV) is one of the Internet applications grown dramatically currently. It is the key to identify P2P-TV video streaming in real-time for managing the P2P-TV traffic and understanding the networking behaviors. Analyzing the architecture, communications processes, message frames and system characteristics of P2P-TV represented by PPLive, a Crawler-based Identifying Video Flows (CIVF) algorithm and a Protocol characteristic-based Identifying Video Flows (PIVF) algorithm identifying video flows in real-time are proposed. CIVF identifies P2P-TV flows based on the peer information, which is obtained from crawler program, while PIVF makes use of the communication sequence and payload characteristic in P2P-TV applications to achieve real-time identification. The results of experiments in Internet environment shows that CIVF algorithm has features such as ease to realize, not high accurateness and long outdated peer information, and PIVF algorithm has features such as high accurateness, fast working and high expansibility.%基于P2P的IPTV(P2P-TV)是当前发展最为迅速的因特网应用之一,实时识别P2P-TV视频流是管理网络P2P-TV流量和理解网络行为的关键一步.通过分析以PPLive为代表的P2P-TV体系结构、通信过程、报文结构以及系统特征,该文提出了一种实时的基于爬虫的识别视频流CIVF算法和一种实时的基于协议特征的识别视频流PIVF算法,CIVF算法通过爬虫程序获取P2P-TV节点信息来识别P2P-TV视频流,而PIVF算法则基于视频流的通信时序和应用层负载特征实现实时识别.在因特网环境的试验分析结果表明,CIVF算法具有实现便捷但识别率不够高且节点信息残存时间较长的特点,PIVF算法则具有准确率较高、识别速度较快和扩展性强的特点.
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