How to make a fragile network robust and vice versa

Abstract

We investigate topologically biased failure in scale-free networks with degree distribution $P(k) \propto k^{-\gamma}$. The probability $p$ that an edge remains intact is assumed to depend on the degree $k$ of adjacent nodes $i$ and $j$ through $p_{ij}\propto(k_{i}k_{j})^{-\alpha}$. By varying the exponent $\alpha$, we interpolate between random ($\alpha=0$) and systematic failure. For $\alpha >0 $ ($<0$) the most (least) connected nodes are depreciated first. This topological bias introduces a characteristic scale in $P(k)$ of the depreciated network, marking a crossover between two distinct power laws. The critical percolation threshold, at which global connectivity is lost, depends both on $\gamma$ and on $\alpha$. As a consequence, network robustness or fragility can be controlled through fine tuning of the topological bias in the failure process.