Title
Nonasymptotic Connectivity of Random Graphs and Their Unions
Abstract
Graph-theoretic methods have seen wide use throughout the literature on multiagent control and optimization. When communication networks are intermittent and unpredictable, they have been modeled using random communication graphs. When graphs are time varying, it is common to assume that their unions are connected over time, yet, to the best of our knowledge, there are not any results that determine the number of finite-size random graphs needed to attain a connected union. Therefore, this article bounds the probability that individual random graphs are connected and bounds the same probability for connectedness of unions of random graphs. The random graph model used is a generalization of the classic Erdös-Rényi model, which allows some edges to never appear. Numerical results are presented to illustrate the analytical developments made.
Year
DOI
Venue
2021
10.1109/TCNS.2020.3013715
IEEE Transactions on Control of Network Systems
Keywords
DocType
Volume
Complex networks,multi-agent systems,networked control systems
Journal
8
Issue
ISSN
Citations 
1
2325-5870
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Beth Bjorkman111.03
Matthew F. Hale244.78
Thomas Lamkin300.34
Benjamin Robinson400.34
Craig Thompson500.34