On the Controllability of Clustered Scale-Free Networks
For network scientists and control engineers, this work provides insights into how clustering affects controllability, though it is an incremental extension of known network controllability analysis.
This paper compares controllability of Scale-Free and Clustered Scale-Free networks, finding that clustered networks require fewer control inputs but offer fewer recovery options due to smaller dilations.
In this paper, we compare the number of unmatched nodes and the size of dilations in two main random network models, the Scale-Free and Clustered Scale-Free networks. The number of unmatched nodes determines the necessary number of control inputs and is known to be a measure for network controllability, while the size of dilation is a measure of controllability recovery in case of control input failure. Our results show that clustered version of Scale-Free networks require fewer control inputs for controllability. Further, the average size of dilations is smaller in clustered Scale-Free networks, implying that potentially fewer options for controllability recovery are available.