Heterogeneous Epidemic Model for Assessing Data Dissemination in Opportunistic Networks

In this paper we apply a susceptible-infected-susceptible (SIS) epidemic model to analyse data dissemination in opportunistic networks with heterogeneous setting of transmission parameters, as established in author's previous paper? . We obtained the estimation of the final epidemic size assuming that amount of data transferred between network nodes possesses a Pareto distribution, implying scale-free properties. In this context, more heterogeneity in susceptibility means the less severe epidemic progression, and, on the contrary, more heterogeneity in infectivity leads to more severe epidemics — assuming that the other parameter (either heterogeneity or susceptibility) stays fixed. The results are general enough to be useful for estimating the epidemic progression with no significant acquired immunity — in the cases where Pareto distribution holds.