Abstract:
Although viral spreading processes taking place in networks are often analyzed using Markovian models, in which both the transmission and the recovery times follow expone...Show MoreMetadata
Abstract:
Although viral spreading processes taking place in networks are often analyzed using Markovian models, in which both the transmission and the recovery times follow exponential distributions, empirical studies show that, in many real scenarios, the distribution of these times is not necessarily exponential. To overcome this limitation, we first introduce a generalized susceptible-infected-susceptible spreading model that allows transmission and recovery times to follow phase-type distributions. In this context, we derive a lower bound on the exponential decay rate toward the infection-free equilibrium of the spreading model without relying on mean-field approximations. Based on our results, we illustrate how the particular shape of the transmission/recovery distribution influences the exponential rate of convergence toward the equilibrium.
Published in: IEEE Transactions on Control of Network Systems ( Volume: 7, Issue: 1, March 2020)