Epidemic Spreading On Complex Networks Considering Communication Flow

People know well of the infectious mechanisms of large-scale biology and computer viruses with the rapid development of complex network theory. At present, the research of epidemic spreading on complex networks mostly focused on differential equation model established by mean-field method, which reflects the average trend of epidemic spreading, but such model is not suitable to describe the dynamic evolution characteristics of epidemic spreading. Moreover, the existing epidemic spreading models mainly considered that the infected nodes infect all its neighbors in the same probability in unit time, but actual situation is not so.To overcome the deficiencies of the existing epidemic spreading models and propose more accurate epidemic spreading model, the paper studies the following aspects:First, the development of complex networks, important concepts and the network topologies are reviewed briefly, and the current models of virus propagation and the basic knowledge of the threshold theory are introduced.Then, considering the features of the global interaction of information network's nodes and the unbalances of communication flow, a new susceptible-infected-susceptible (SIS) model based on the one-dimensional cellular automata is proposed to study epidemic spreading in a variety of network topologies and to overcome the shortages of the current mean-field models.Furthermore, based on the proposed SIS model, considering some infectious diseases, in which the infected individuals who have been cured have permanent immunity, a new susceptible-infected-removed (SIR) model is proposed to study epidemic spreading in complex networks.Finally, the proposed models and existing models are compared, and the proposed two models are compared as well. The results show that the propagation velocity increases obviously in different network topologies with the increase of the communication flow, the threshold of epidemic spreading increases and the possibility of epidemic outbreak reduces with the communication flow decreasing. For some infectious diseases, in which the infected individuals who have been cured have permanent immunity, increasing network traffic can accelerate the extinction of the virus and improve the proportion of the immunity node.