One immunization strategy of complex networks
Aiming at improving respective shortcoming of target immunization and acquaintance immunization strategy, we present an immunization strategy which consists of two steps: choosing some node randomly and then adopting strengthened acquaintance immunization or improved target immunization according to different circumstances. This synthesis strategy retains the advantage of making decision based on pure local information, without needing information of global network structure or identification of the highest degree nodes. When the percentage of required vaccinations for immunity is the same as the targeted immunization, we get better results. Compare with other efficient strategies on a scale-free network model, the proposed strategy is significantly more effective and adaptive.