Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
