Dynamic modeling approach to analyze user churn in a large P2P downloading system

Characterizing the features of user churn is crucial to the sustainable development of peer-to-peer (P2P) systems where peers join and leave at any arbitrary time. This paper analyzes the user churn in a P2P downloading system named QQXuanfeng by using the fine-grained log analysis over 60 days. It shows that the online and offline duration is related to up (arrive) time and down (depart) time respectively. A continuous ON/OFF process, which exhibits the diurnal patterns of users, is simulated using the churn model. In particular, the dynamic departure rate is proposed to give insight into the distribution of online duration. Further more, considering the heterogeneity of users, we cluster users based on the similarity of redefined user availability. As an example of application of this model, a high availability overlay is constructed and evaluated based on the clustering.