Toward Stronger Robustness of Network Controllability: A Snapback Network Model
For researchers studying network controllability, this work proposes a new network model with improved robustness, though the improvement is incremental over existing models.
The paper introduces a q-snapback network model and demonstrates that it exhibits the strongest robustness of controllability against targeted and random attacks compared to multiplex congruence and scale-free networks, due to its chain- and loop-motif structure.
A new complex network model, called q-snapback network, is introduced. Basic topological characteristics of the network, such as degree distribution, average path length, clustering coefficient and Pearson correlation coefficient, are evaluated. The typical 4-motifs of the network are simulated. The robustness of both state and structural controllabilities of the network against targeted and random node- and edge-removal attacks, with comparisons to the multiplex congruence network and the generic scale-free network, are presented. It is shown that the q-snapback network has the strongest robustness of controllabilities due to its advantageous inherent structure with many chain- and loop-motifs.