This project advances the boundaries of network theory by analyzing spreading processes over multilayer and interconnected networks, which abound in nature and man-made infrastructures, and about which many interesting questions remain unanswered. Multilayer networks are an abstract representation where multiple types of links exist among nodes. Interconnected networks are an abstract representation where two or more simple networks, possibly with different and separate dynamics, are coupled to each other. The rationale for this project is that viral-spreading dynamics over multilayer and interconnected networks exhibit behaviors that cannot be attributed to single-network characteristics and play a highly relevant role in practice. The first part of the project extends the concept of the epidemic threshold value, which determines the conditions for outbreak, to the threshold curve for interconnected and multilayer networks. This research further develops measures for quantification of coupling strength in interconnected networks and seeks optimal interconnection designs for them. The second part of the project aims at predicting competitive spreading over multilayer networks and possible emergent phenomena. This research analyzes transient dynamics and steady-state behavior of multiple-virus competitive spreading in multilayer networks, and investigates competition policy in a game-theoretic framework. This project will use rigorous mathematical tools from network science, spectral graph theory, nonlinear dynamics, stochastic processes, control theory, game theory, and optimization.

Successful completion of this project will greatly advance the state of the art in network theory, with specific, relevant applications in communications and information technologies leading to more efficient and robust design of these complex networked systems. In a broader view, this research will contribute positively to society through a better understanding of how to prevent large-scale catastrophes, including cascading failures in power grids, financial contagions in market trading, infectious disease pandemics, and outbreaks of computer malware. Furthermore, the investigators will put forth significant effort to involve students from under-represented groups, and disseminate project outcomes in both general society and academia through publications, webinars, and public webpages.

Project Start
Project End
Budget Start
2014-07-15
Budget End
2018-06-30
Support Year
Fiscal Year
2014
Total Cost
$522,042
Indirect Cost
Name
Kansas State University
Department
Type
DUNS #
City
Manhattan
State
KS
Country
United States
Zip Code
66506