Abstract
The identification of vital nodes that maintain the network connectivity is a long-standing challenge in network science. In this paper, we propose a so-called reverse greedy method where the least important nodes are preferentially chosen to make the size of the largest component in the corresponding induced subgraph as small as possible. Accordingly, the nodes being chosen later are more important in maintaining the connectivity. Empirical analyses on eighteen real networks show that the reverse greedy method performs remarkably better than well-known state-of-the-art methods.
Highlights
The identification of vital nodes that maintain the network connectivity is a long-standing challenge in network science
A smaller R means a quicker collapse and a better performance. Another metric is the number of nodes to be removed to make the size of the largest component in the remaining network being no more than 0.01N, denoted by, ρHmeinr.eOwbevuiosuesBlyC, a, CsmCa, lDleCr,ρmHin-imndeeaxn,sKaSb,ePttRe,r performance
Most previous methods directly identify the critical nodes by looking at the effects due to their removal[10]
Summary
The identification of vital nodes that maintain the network connectivity is a long-standing challenge in network science. We propose a so-called reverse greedy method where the least important nodes are preferentially chosen to make the size of the largest component in the corresponding induced subgraph as small as possible. Empirical analyses on eighteen real networks show that the reverse greedy method performs remarkably better than well-known state-of-the-art methods. CI performs remarkably better than some known methods in identifying the nodes’ importance for network connectivity[18,19]. Empirical analyses on eighteen real networks show that RG performs remarkably better than well-known state-of-the-art methods. The core of the RG algorithm is the reverse process, which adds nodes one by one to an empty network while minimizes the cost function until all nodes in the considered network are added.
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