In December 2013, after a systematic and comprehensive technical evaluation and testing, Hangzhou Telecom finally chose EVA video analyzer as a test tool for troubleshooting IPTV. In 2011, Zhejiang Telecom Provincial Company deployed IPTV platform multicast source and IPTV service quality assurance system based on set-top box QoS soft probe. Although the system can monitor the overall IPTV service quality and handle common IPTV user complaints, it is still unable to accurately locate some difficult IPTV faults. Therefore, in recent years, Hangzhou Telecom is also constantly exploring and looking for more suitable testing means and tools for troubleshooting and accurate fault location of difficult IPTV. After a series of evaluations and tests, some unique technical advantages of EVA video analyzer were finally recognized by technical experts of Hangzhou Telecom Network Transportation Department, video operation center and network operation and maintenance center, including the following features:

（1） The original data of IP video stream for a specific user is stored on disk for a long time, so that the fault point data packet can be analyzed in detail by Wireshark protocol analyzer.

（2） The correlation analysis between VOD media stream KPI index and RTSP signaling events (such as fast forward, fast backward, pause, etc.) can automatically eliminate the media stream KPI index alarm caused by user behavior, thus improving the test accuracy.

（3） Through correlation analysis of QoS/QoE indicators in multi-protocol layers (such as MPEG-TS media layer, RTP layer, TCP layer), IPTV faults can be located by single-point monitoring (such as distinguishing IPTV platform faults, upstream or downstream network node loss, etc.), thus improving test efficiency.

In this project, Hangzhou Telecom purchased EVA-HS high-performance Gigabit probes to monitor and troubleshoot IPTV multicast streams and unicast streams of IP bearer network backbone links, and equipped with a number of EVA portable instrumentation software for detailed data analysis of user side failures.