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In this paper we investigate a susceptible-infected-susceptible (SIS)epidemic model describing data dissemination in opportunistic networks withheterogeneous setting of transmission parameters. We obtained the estimation ofthe final epidemic size assuming that amount of data transferred betweennetwork nodes possesses a Pareto distribution, implying scale-free properties.In this context, more heterogeneity in susceptibility means the less severeepidemic progression, and, on the contrary, more heterogeneity in infectivityleads to more severe epidemics -- assuming that the other parameter (eitherheterogeneity or susceptibility) stays fixed. The results are general enoughand can be useful in general epidemic theory for estimating the epidemicprogression for diseases with no significant acquired immunity -- in the caseswhere Pareto distribution holds.

Heterogeneous epidemic model for assessing data dissemination in opportunistic networks