The effect of interdependence on the percolation of interdependent networks

Two stochastic models are proposed to generate a system composed of two interdependent scale-free (SF) or Erdős-Rényi (ER) networks where interdependent nodes are connected with exponential or power-law relation, as well as different dependence strength, respectively. Each subnetwork grows through the addition of new nodes with constant accelerating random attachment in the first model but with preferential attachment in the second model. Two subnetworks interact with multi-support and undirectional dependence links. The effect of dependence relations and strength between subnetworks are analyzed in the percolation behavior of fully interdependent networks against random failure, both theoretically and numerically, and as a result, for both relations: interdependent SF networks show a secondorder percolation phase transition and increased dependence strength decreases the robustness of the system, whereas, interdependent ER networks show the opposite results. In addition, power-law relation between networks yields greater robustness than exponential one at given dependence strength.