  In this paper, we study large-scale networks in terms of observability and
controllability. In particular, we compare the number of unmatched nodes in two
main types of Scale-Free (SF) networks: the Barab{\'a}si-Albert (BA) model and
the Holme-Kim (HK) model. Comparing the two models based on theory and
simulation, we discuss the possible relation between clustering coefficient and
the number of unmatched nodes. In this direction, we propose a new algorithm to
reduce the number of unmatched nodes via link addition. The results are
significant as one can reduce the number of unmatched nodes and therefore
number of embedded sensors/actuators in, for example, an IoT network. This may
significantly reduce the cost of controlling devices or monitoring cost in
large-scale systems.
