Information propagation in stochastic networks

In this paper, a network-based stochastic information propagation model is developed. The flow modeled by probabilistic differential equation system. numerical solution of these equations leads to the expected number informed nodes as function time and reveals relationship between degrees their reception time. validity justified Monte Carlo network simulation through analysis in scale-free Erdos-Renyi networks. It has been found that developed provides more accurate results compared widely used SI mean-field model, especially sparse