Probing the robustness of nested multi-layer networks (1911.03277v1)
Abstract: We consider a multi-layer network with two layers, $\mathcal{L}{1}$, $\mathcal{L}{2}$. Their intra-layer topology shows a scale-free degree distribution and a core-periphery structure. A nested structure describes the inter-layer topology, i.e., some nodes from $\mathcal{L}{1}$, the generalists, have many links to nodes in $\mathcal{L}{2}$, specialists only have a few. This structure is verified by analyzing two empirical networks from ecology and economics. To probe the robustness of the multi-layer network, we remove nodes from $\mathcal{L}{1}$ with their inter- and intra-layer links and measure the impact on the size of the largest connected component, $F{2}$, in $\mathcal{L}_{2}$, which we take as a robustness measure. We test different attack scenarios by preferably removing peripheral or core nodes. We also vary the intra-layer coupling between generalists and specialists, to study their impact on the robustness of the multi-layer network. We find that some combinations of attack scenario and intra-layer coupling lead to very low robustness values, whereas others demonstrate high robustness of the multi-layer network because of the intra-layer links. Our results shed new light on the robustness of bipartite networks, which consider only inter-layer, but no intra-layer links.
Collections
Sign up for free to add this paper to one or more collections.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.