On the Observability and Controllability of Large-Scale IoT Networks: Reducing Number of Unmatched Nodes via Link Addition

In this letter, 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 Barabasi-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.

Automated summary

This study compares the number of unmatched nodes in Barabasi-Albert and Holme-Kim models of Scale-Free networks, discussing the potential relationship between clustering coefficient and unmatched nodes. A new algorithm is proposed to reduce the number of unmatched nodes through link addition, potentially reducing the cost of controlling devices or monitoring in large-scale systems.