2020/12/11 by Mohammadreza Doostmohammadian, Doostmohammadian, Mohammadreza, Hamid R. Rabiee +1
Computer Science · Engineering · Mathematics · Physics and Astronomy · #Actuator #Applied mathematics #Artificial intelligence #Cluster analysis #Clustering coefficient #Complex Network Analysis Techniques #Computer network #Computer science #Controllability #Distributed computing #Embedded system #FOS: Computer and information sciences #FOS: Electrical engineering #Internet of Things #Link (geometry) #Mathematics #Mobile Ad Hoc Networks #Networking and Internet Architecture (cs.NI) #Observability #Opportunistic and Delay-Tolerant Networks #Scale (ratio) #Social and Information Networks (cs.SI) #Systems and Control (eess.SY) #Topology (electrical circuits) #cs.NI #cs.SI #cs.SY #eess.SY #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2012.06198
arxiv created 2020/12/11 · openalex publication_date 2020/12/11 · arxiv updated 2020/12/14 · openalex created_date 2022/07/25 · openalex updated_date 2026/08/06
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 Barabási-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.