Impact of Infection Rate on Scaling Law of Epidemic Routing

Performance modeling of epidemic routing is challenging because of the unguaranteed end-to-end connectivity and lack of global information in delay-tolerant scenarios. Existing works analyze the scaling law of epidemic protocol based on the assumption that each node has the same infectivity. Whereas, the most recent work indicates that the distribution of infected nodes has spatial-temporal correlation rather than homogeneity, i.e., nodes in different locations have different infectivities, which leads to defectiveness of the existing solutions.