The Iterative Resource Allocation In Interconnected Networks

In the study of complex networks, identifying important nodes in propagation contributes a lot to the control of diffusion. Since real-world networks are often closely interacted, it seems promising to generalize the ranking algorithms of nodes to multi-layer networks. In this paper, the iterative resource allocation method is extended to interconnected networks for the identification of influential spreaders. The new method is verified by the SIR model in interconnected networks. Simulations show that the proposed model performs more accurately comparing the original IRA in monoplex networks.