Research On Information And Virus Transmission Mechanism On Complex Networks

The transmission dynamics on complex networks provides an important analytical framework for the study of a large number of social phenomena,such as the spread of infectious diseases,information transmission,computer virus transmission and so on.Communication dynamics on complex networks can be divided into three types according to the research objects:biological communication,social communication and social biological communication.Biological communication mainly includes relatively simple communication processes such as computer virus transmission and infectious disease transmission.Social communication refers to the behavior adoption process with social reinforcement effect,while social biological communication mainly refers to the process of coupling the two,influencing each other and evolving together.This thesis is mainly divided into two parts,which makes an in-depth study on the transmission mechanism of information and virus on complex networks.The first part of this thesis studies the information dissemination process on complex networks.Firstly,it explores the impact of limited contact on the information dissemination mechanism;On this basis,the impact of the heterogeneity of adoption threshold on the mechanism of information dissemination is analyzed.Firstly,this thesis proposes a contact constrained information propagation model on double-layer complex networks and the corresponding edge based partition theory.It is found that increasing the contact capacity can promote the dissemination of information on double-layer strongly heterogeneous networks.On two-layer strongly heterogeneous scale-free networks and two-layer random networks,the propagation range of information changes from continuous growth to discontinuous phase transition with the increase of information propagation probability.When the propagation probability is small,increasing the heterogeneity of degree distribution is conducive to information dissemination,while when the propagation probability is large,increasing the heterogeneity of degree distribution is not conducive to information dissemination.On this basis,considering that the adoption threshold is affected by individual heterogeneity,this thesis constructs a two-layer network model.The adoption threshold of a node in the network is related to the degree of the node and a parameter subject to truncated normal distribution.At the same time,the corresponding edge division theory is improved to quantitatively analyze the information dissemination mechanism.It is found that increasing the mean value of parameters can inhibit the propagation of information,and the range of information propagation first increases and then decreases with the increase of parameter standard deviation.The influence of the standard deviation of parameters on the phase transition mode of information transmission range depends on the mean value of parameters.The above research methods expand new ideas for the research of individual heterogeneity on information dissemination mechanism on complex networks.The second part discusses the virus resource transmission process on complex networks.In this thesis,a two-layer network model is proposed,in which the virus transmission process and the resource allocation process for disease recovery are considered respectively.On this basis,this thesis proposes a hybrid resource allocation scheme:part of the resources of each healthy node are directly provided to its infected neighbor nodes,and the remaining resources will be equally distributed to all infected nodes in the network as public resources.At the same time,this thesis uses a generalized discrete Markov chain method to quantitatively analyze the mechanism of virus transmission,mainly considering the effects of initial seed fraction,network edge coincidence degree,degree distribution heterogeneity and public resource allocation ratio on the mechanism of virus transmission.It is found that when the initial seed fraction is small,the diffusion range of the virus first increases continuously with the increase of transmission probability,and then produces discontinuous phase transition.When the edge coincidence degree of the two-layer network is high,local propagation is more likely to occur.When the edges of the two-layer networks do not coincide at all,it is easier to cause the phenomenon of cascade infection.When the heterogeneity of network degree distribution is weak and the initial seed score is small,there is a critical value for the proportion of public resource allocation.When the proportion of public resource allocation exceeds this value,the hybrid resource allocation strategy is better than the neighbor resource allocation strategy.In other cases,increasing the proportion of resource allocation can effectively improve the critical probability of system collapse.However,accordingly,this will reduce the critical probability of infected nodes in the network.This research method provides a new idea for the study of virus transmission mechanism on complex networks.