Optimization of Network Robustness to Random Breakdowns
classification
❄️ cond-mat.stat-mech
keywords
networknodessqrtdegreebreakdownsgivennetworksnumber
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We study network configurations that provide optimal robustness to random breakdowns for networks with a given number of nodes $N$ and a given cost--which we take as the average number of connections per node $\kav$. We find that the network design that maximizes $f_c$, the fraction of nodes that are randomly removed before global connectivity is lost, consists of $q=[(\kav-1)/\sqrt\kav]\sqrt N$ high degree nodes (``hubs'') of degree $\sqrt{\kav N}$ and $N-q$ nodes of degree 1. Also, we show that $1-f_c$ approaches 0 as $1/\sqrt N$--faster than any other network configuration including scale-free networks. We offer a simple heuristic argument to explain our results.
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