LAUSR

Identifying critical nodes in complex networks aims to fragment a graph $$G = (V, E)$$G=(V,E) by removing a set of vertices R with cardinality $$\left| R \right| \le $$R≤ k, such that the residual graph has minimum pairwise connectivity. Existing optimization algorithms are incapable of finding a good set R in complex networks. By investigating the role of nodes, a minimum dominating set approach is considered in controlling a network. This paper presents an algorithmic procedure to compute the critical nodes using a novel minimum connected dominating set, in which the critical nodes are identified based on the number of close subsequences. Through experimental verification on some randomly generated networks and comparing with the similar algorithms, the results showed that the proposed algorithm has high capability of identifying the critical nodes and low time complexity.