Research Of Epidemic Spreading Based On Complex Networks

Many natural and technological networks we seen are complex networks. For example, Internet network, WWW network, social network, etc. These networks have affinity in our life, therefore it is necessary for us to profound research and get comprehend understanding of the topology, dynamics action of complex network, for the better to design and manage these fact networks. Among the many studies of complex networks, the qualitative and quantitative research of the dynamics of complex networks become the research hotspot. As one mainstream of the complex networks study, the study of epidemic dynamics has a long history and has achieved fruitfull results. The concern about the spreading behavior is often self-evident because of the danger: Infectious diseases prevalent among organisms, computer viruses spreading of the Internet, rumors transforming in the population. These can be regarded as subject to certain rules of complex network propagation. But in the real world behavior of the virus spreading propagation model is more complex than the existing studied network, it is necessary to build more appropriate model to study in greater depth the reality of the virus spreading behavior, and study its dynamics and its preventive measures. In this paper, we have a preliminary study on the behavior of virus spreading on complex networks. The content is as follow:First, this paper introduces the basic theory of complex networks and the current progress of the study, given the basic definition of complex networks, introduced some basic concepts of complex network, such as the concept of degree as well as degree distribution, average path length, clustering coefficient; and classical spreading model of the complex networks, such as the SI model, SIS model and the SIR model, as well as the immunization technologies, such as random immunization, target immunization and acquaintance immunization .Second, we devote in studying the spreading behavior of social networks. Due to different characteristic of social networks from the technological network, it is necessary to study the spreading behavior of the social network in order to study the real network theory. Study found that social networks with assortativity coefficientt affect the spreading behavior. After that, we study the spreading behavior in multi local weighted networks. The immunization behavior of the virus on the network, in fact, equivalent to disconnect the connection edges between nodes, but for multi local world network disconnecting the link between the local word will affect the entire network connectivity. So for the inner nodes and linking nodes of different local words, we set the different transmission rate , to have effective control over the spreading behavior of multi local world network.Then, we study the epidemic spreading model joining with feedback mechanism .We experiment the feedback mechanism on inhomogeneous networks. Experimental results show that feedback mechanisms can be an effective mechanism for controlling epidemic spreading.Finally, we summarized the work of this paper, and put forward the future work and research topics needed to further exploreing.