Epidemic Information Dissemination in Mobile Social Networks with Opportunistic Links

With the advancement of smartphones, mobile social networks (MSNs) have emerged where information can be shared among mobile users via opportunistic peer-to-peer links. Since the social ties and users' behaviors in MSNs have diverse characteristics, the information dissemination in MSNs becomes a new challenge. In particular, mobile users' interested information may vary, which can significantly affect the information dissemination. In this paper, we develop an analytical model to analyze the epidemic information dissemination in MSNs. We first adopt preimmunity and immunity to represent the features of mobile nodes when they change their interests. Then, the information dissemination mechanism is introduced with four proposed dissemination rules according to the process of the epidemic information dissemination. We develop the analytical model through ordinary differential equations to mimic epidemic information dissemination in MSNs. The trace-driven simulation demonstrates that our analytical model is more accurate to mimic epidemic information dissemination than other existing ones.