Local immunization algorithm on complex networks

We present a review on some local immunization algorithm, including community networks, adaptive networks, and coupled networks. For community networks, through the empirical analysis of five empirical networks we find that the distribution of weak ties is heterogeneous, which indicates that some bridge-nodes with more weak links play a more important role in information diffusion. We propose an efficient local algorithm to identify bridge-nodes. For adaptive networks, we study the effects of community-based control strategies on disease spreading and find that it is not 'the earlier, the better' to control diseases. For coupled networks, we present a facilitate-restrain asymmetric interacting spreading model, and investigate the impact of local disperse awareness on disease spreading. The presented results contribute to improving the understanding of key nodes in complex networks and offer beneficial reference and enlightenment for disease control and prevention.