Characterizing and modeling user behavior in a large-scale mobile live streaming system

Zhenyu Li, Mohamed Ali Kaafar, Kave Salamatian, Gaogang Xie

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


In mobile live streaming systems, users have fairly limited interactions with streaming objects due to the constraints coming from mobile devices and the event-driven nature of live content. The constraints could lead to unique user behavior characteristics, which have yet to be explored. This paper investigates over 9 million access logs collected from the PPTV live streaming system, with an emphasis on the discrepancies that might exist when users access the live streaming catalog from mobile and nonmobile terminals. We observe a much higher likelihood of abandoning sessions by mobile users and examine the structure of abandoned sessions from the perspectives of time of day, channel content, and mobile device types. Surprisingly, we find relatively low abandonment rates during peak-load time periods and a notable impact of mobile device type (i.e., Android or iOS) on the abandonment behavior. To further capture the intrinsic characteristics of user behavior, we develop a series of models for session duration, user activity, and time dynamics of user arrivals/departures. More importantly, we relate the model parameters to physical and real-life meanings. The observations and models shed light on a video delivery system, telco-content delivery networks, and mobile applications.

Original languageEnglish
Pages (from-to)2675-2686
Number of pages12
JournalIEEE Transactions on Circuits and Systems for Video Technology
Issue number12
Publication statusPublished - 1 Dec 2017
Externally publishedYes


  • Analysis
  • mobile live streaming
  • modeling
  • user behavior

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