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Reseach on Immunization Strategy Based on Random Walk Mechanism in Temporal Networks

ZHU Yi-xin;ZHANG Feng-li;WANG Rui-jin;QIN Zhi-guang;School of Computer Science and Engineering,Xinjiang University of Finance and Economics;Network and Data Security key Laboratory of Sichuan Province,University of Electronic Science and Technology of China;  
For the problems of traditional immune models arising in collectingand analyzing network topology information in temporal networks, an immune strategy based on random walk mechanism is put forward and itcan be implemented withoutcollectingnetwork topology information. A certain number of immune particles were randomly assigned to the network nodes.When a nodewith immune particles has one or more activated links,the immune particles on the node will walk to another node along anactivated link of the node.The nodes with immune particlesacquire the immunity,but thenodes losingimmune particleswill betransformed into the susceptible state. Considering whether the random walkers exert impact upon each other when they move, the dependent random walk immune model and the P_independent random walk immune model are established,respectively, in which the network transmission overhead of the immune particle is limited by a given immune particle density. Experiments show the two random walk immune models are characterized by their better immune effects with lower immune particle density and the network overhead when compared with acquaintances immune model. In addition, the comparative result with the target immune model depends on heterogeneity of network topology.
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