Study On Discret SIS Mode For Epidemic Propation In ADATPVE NETWORK Based ON Celluar Atuomata

In order to restrain the spread and the eruption of epidemic effectively, many models for epidemic propagation are established to analyze the evolution process, reveal the transmission mechanism and predict the change trend, which provides theory basis for defense and restrain of epidemic propagation. Actually, most network topology change adaptability according to the state of each node. It is adaptive networks that can reflect the interplay between node dynamics which regards each node as a dynamic system and network dynamics which regards network topology as a dynamic system.A model for epidemic propagation in adaptive networks based on cellular automata is analyzed and studied in this paper. The dissertation contains the following several parts: Firstly, the relational theory of adaptive networks and cellular automata are reviewed briefly, the present studies on them are analyzed.Secondly, considering the mechanism of interplay between node dynamics and network dynamics, a discrete SIS (susceptible-infected-susceptible) model in adaptive networks is proposed to investigate the average trend of epidemic propagation in adaptive networks.Finally, considering these networks including Erdos-Renyi(ER) random network, Watts-Strogatz (WS) small-world network and Barabasi-Albert (BA) scale-free network as the initial network respectively, a lot of simulations are made to analyze the proposed model for epidemic propagation in adaptive networks. The proposed model is compared with the traditional mean-field model in terms of spreading properties. The results show that the proposed model can effectively overcome the shortcomings that the average trend of spread is reflected only for differential equation model based on mean-field method and describe the phenomenon of bistability in spreading process for adaptive networks.