# On the Controllability of Clustered Scale-Free Networks

## TL;DR

This paper compares the controllability of Scale-Free and Clustered Scale-Free networks, showing that clustering reduces control inputs needed but also limits recovery options due to smaller dilations.

## Contribution

It introduces a comparative analysis of network controllability metrics between Scale-Free and clustered variants, highlighting the impact of clustering.

## Key findings

- Clustered Scale-Free networks require fewer control inputs.
- Average dilation size is smaller in clustered networks.
- Clustering affects controllability recovery options.

## Abstract

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.