Research On Virus Spreading And Control Strategy In Complex Networks

In recent years, the discoveries of complex networks have attracted a lot of interest which has been applied extensively in many fields, such as graph theory, statistical physics, computer networks, ecology, sociology and economics. Many behaviors, such as the spread of the virus in computer networks, the prevalence of infectious diseases in the crowd, diffusion of canard in society and so on, can be viewed as the communication on the networks which is subjected to a certain law. The characteristics of small world and scale free in real complex networks have profound effects on the virus spreading. Therefore, it is of great importance to study the virus spreading on complex networks and explore the diffusing mechanism as well as preventive measures. In this paper, we have a pilot study on the behavior of virus spreading on complex networks. The content is as follows:At first, we sum up the recent development and achievement of researches on virus spreading on complex networks, and discuss the special conclusion and some analyze method on different networks briefly.Secondly, by use of the mean-field theory, the two-factor virus spreading model in small-world networks is introduced which considers two key factors: artificial control and virus itself interference. The spreading behavior of the virus is analyzed and some spreading conditions are given. Through analysis, we conclude that the initial conditions of virus spreading and the spreading threshold relate to the network topology. Also, the existence of stable states of the system and its steady state stability are discussed. Through simulation, we prove that artificial control and virus itself interference have significant influence on virus spreading. In addition, some corresponding preventive measures are given.Thirdly, the delay virus spreading model is introduced, which is used to study the influence of the delay. Through analysis, we conclude that the delay has less effect on equilibrium state. Through simulation, at the initial stage of virus spreading, the delay has large influence on virus spreading course. We prove that the reconnection probability p has influence on the spreading speed, and it has lessinfluence on the equilibrium state of the virus spreading curve. Also, we prove that small world networks can speed the virus spreading.Finally, we point out the insufficiency about this thesis, propose some problems that need to be solved further and prospect the development of complex networks.