Acquaintance immunization with limited knowledge of network structure

Abstract Optimal and efficient immunization of large networks remains a challenging task. Many theories approaches have been suggested, however most them require complete knowledge the underlying network structure. Here, we study targeted strategy that incorporates fact there is often limited on Previous work has suggested ‘acquaintance’ immunization, where rather than selecting random individual to immunize, an selected then one their acquaintances immunized. generalize acquaintance case acquaintance, examine degrees n immunize with highest degree. We develop solve analytic framework for this model verify our extensive numerical simulations. determine critical percolation threshold p c size giant component, P ∞ , arbitrary degree distributions. also consider real-world variation increasing . find new approach improves both using knowledge.