The prevalence of smart phone and improvement of wireless net promote the usage of crowdsourced live streaming,where individual users act as live streaming sources to broadcast themselves online. Characterizing the performance and identifying its bottleneck in such systems can shed light on the system design and performance optimization. TCP performance of a commercial crowdsourced live streaming system is examined by analyzing packet-level traces collected at streaming servers. TCP stalls that heavily hurt the Qo E of user have been identified. In particular,the TCP stalls account for as much as 31. 6% of the flow completion time for upload flows and result in abandonment of upload on the corresponding channels. Stalls caused by timeout retransmissions are further dissected and timeout retransmission characteristics are revealed to be dependent on the video encoding methods. These findings provide new insights in crowdsourced live streaming systems and can guide designers to improve the TCP efficiency. The prevalence of smart phone and improvement of wireless net promote the usage of crowdsourced live streaming, where individual users act as live streaming sources to broadcast themselves online. Characterizing the performance and identifying its bottleneck in such systems can shed light on the system design and performance TCP performance of a commercial crowdsourced live streaming system is examined by analyzing packet-level traces collected at streaming servers. TCP stalls that heavily hurt the Qo E of user have been identified. In particular, the TCP stalls account for as much as 31 . 6% of the flow completion time for upload flows and result in abandonment of upload on the corresponding channels. Stalls caused by timeout retransmissions are further dissected and timeout retransmission characteristics are revealed to be dependent on the video encoding methods. in crowdsourced live streaming systems and can guide designers to improve t he TCP efficiency.