Virus Spreading In Adaptive Networks And Nodes Protection Immunization Strategy

With the accelerating and deepening of the process of world networking, the movements ofpersonnel and supplies are also becoming more and more frequent and convenient. This makes thespread of infectious diseases diffusion speed greatly increase. A variety of typical epidemicpropagation models have been proposed to study and analyze the spread of the disease. Consideringthe complexity of real networks, based on the existing studies of spread of the virus and itsprevention, virus propagation and controlling have been discussed and analyzed in two differentangles in this paper. The main contents of dissertation include the following three components:Firstly, the related background, research status and significance of virus spreading in complexnetwork are briefly introduced. The epidemic dynamics and virus controlling strategies are studiedand analyzed.Secondly, from the perspective of individuals, considering individuals virus awareness andavoidance behavior is dynamic changing as time varying. In order to represent strengtheningindividual risk awareness, the time-varying rewiring functions are used in network propagationmodels. And its impact on the spread of the virus is studied. And then from the perspective of thewhole network system, we proposed the nodes-protection immunization strategy based on differentidentifying influential nodes methods, and meanwhile, comparative analysis on the effect ofdifferent identifying influential nodes methods in network models with single characteristics isshown. These methods are applied in the virus immunization process, and the impacts of the mostinfluential nodes on virus spreading will be studied and analyzed.Finally, we use the real world networks data, on the one hand, to verify the validity of the resultsof previous studies, on the other hand, to analyze the process of transmission of the virus andimmunization strategies in the real world networks. The results show that the strengthening riskawareness and avoidance behavior can effectively slow down virus spreading. In different networks,the nodes-protection immunization strategy based on different identifying influential nodes methodsperforms different. The results of immunizing on the real networks are much closer to BA scale-freenetwork than other network structures. Preferentially immunizing on the nodes with high closenessvalue is a very effective immunization strategy in real world networks.