CONTROLLABILITY ANALYSIS OF COMPLEX NETWORKS USING STATISTICAL RANDOM SAMPLING

Babak Ravandi, Forough S. Ansari () and Fatma Mili ()
Additional contact information
Babak Ravandi: Network Science Institute, Center for Complex Network Research, Northeastern University, Boston, MA 02115, USA
Forough S. Ansari: Department of Computer Science and Engineering, Georgia State University, Alpharetta, GA 30022, USA
Fatma Mili: College of Computing and Informatics, University of North Carolina at Charlotte, Charlotte, NC 28223, USA

Advances in Complex Systems (ACS), 2020, vol. 22, issue 07n08, 1-15

Abstract: Large complex dynamical systems behave in ways that reflect their structure. There are many applications where we need to control these systems by bringing them from their current state to a desired state. Affecting the state of these systems is done by communications with its key elements, called driver nodes, in reference to their representation as a network of nodes. Over the past decades, much focus has been paid on analytical approaches to derive optimal control configurations based on the concept of Minimum Driver node Sets (MDSs) for directed complex networks. However, the underlying control mechanisms of many complex systems rely on quickly controlling a major subspace of a system. In this work, we ask how complex networks behave if driver nodes are randomly selected? We seek to understand and employ the statistical characteristics of MDSs to randomly select driver nodes and analyze the controllability properties of complex network. We propose an algorithm to build Random Driver node Sets (RDSs) and analyze their controllable subspace, the minimum time needed to control, and the cardinality of RDSs. Through our evaluations on a variety of synthetic and real-world networks, we show RDSs can quickly and effectively control a major subspace of networks.

Keywords: Complex networks; controllability; driver nodes; random sampling; statistical characteristics; complex systems (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.worldscientific.com/doi/abs/10.1142/S0219525919500127
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:acsxxx:v:22:y:2020:i:07n08:n:s0219525919500127

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219525919500127

Access Statistics for this article

Advances in Complex Systems (ACS) is currently edited by Frank Schweitzer

More articles in Advances in Complex Systems (ACS) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().