DocumentCode
115176
Title
On the strengths of connectivity and robustness in general random intersection graphs
Author
Jun Zhao ; Yagan, Osman ; Gligor, Virgil
Author_Institution
Dept. of ECE, Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear
2014
fDate
15-17 Dec. 2014
Firstpage
3661
Lastpage
3668
Abstract
Random intersection graphs have received much attention for nearly two decades, and currently have a wide range of applications ranging from key predistribution in wireless sensor networks to modeling social networks. In this paper, we investigate the strengths of connectivity and robustness in a general random intersection graph model. Specifically, we establish sharp asymptotic zero-one laws for k-connectivity and k-robustness, as well as the asymptotically exact probability of k-connectivity, for any positive integer k. The k-connectivity property quantifies how resilient is the connectivity of a graph against node or edge failures. On the other hand, k-robustness measures the effectiveness of local diffusion strategies (that do not use global graph topology information) in spreading information over the graph in the presence of misbehaving nodes. In addition to presenting the results under the general random intersection graph model, we consider two special cases of the general model, a binomial random intersection graph and a uniform random intersection graph, which both have numerous applications as well. For these two specialized graphs, our results on asymptotically exact probabilities of k-connectivity and asymptotic zero-one laws for k-robustness are also novel in the literature.
Keywords
graph theory; probability; random processes; wireless sensor networks; asymptotic zero-one laws; asymptotically exact probability; binomial random intersection graph model; connectivity strengths; edge failures; global graph topology information; k-connectivity; k-connectivity property; k-robustness; key predistribution; local diffusion strategies; social network modeling; uniform random intersection graph model; wireless sensor networks; Cryptography; Probability distribution; Random variables; Robustness; Silicon; Topology; Wireless sensor networks; Connectivity; consensus; random graph; random intersection graph; random key graph; robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location
Los Angeles, CA
Print_ISBN
978-1-4799-7746-8
Type
conf
DOI
10.1109/CDC.2014.7039959
Filename
7039959
Link To Document