Robustness of interdependent geometric networks under inhomogeneous failures
Name
CV_C_210.pdf
Description
Accepted version
Size
1.16 MB
Format
Adobe PDF
Checksum (MD5)
a31a3aa0b72830eabeaafb9240acc6ac
Author(s)
Kamran, Khashayar
Zhang, Jianan
Yeh, Edmund M
Modiano, Eytan H
Date Issued
May 2018
Journal
2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Kamran, Khashayar, Zhang, Jianan, Yeh, Edmund M and Modiano, Eytan H. 2018. "Robustness of interdependent geometric networks under inhomogeneous failures." 2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), 2018.
Version
Author's final manuscript
Abstract
© 2018 IFIP. Complex systems such as smart cities and smart power grids rely heavily on their interdependent components. The failure of a component in one network may lead to the failure of the supported component in another network. Components which support a large number of interdependent components may be more vulnerable to attacks and failures. In this paper, we study the robustness of two interdependent networks under node failures. By modeling each network using a random geometric graph (RGG), we study conditions for the percolation of two interdependent RGGs after in-homogeneous node failures. We derive analytical bounds on the interdependent degree thresholds (k1,k2), such that the interdependent RGGs percolate after removing nodes in Gi that support more than kj nodes in Gj (Vi, j {1,2},i ≠ j). We verify the bounds using numerical simulation, and show that there is a tradeoff between k1 and k2 for maintaining percolation after the failures.
MIT Department
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.23919/WIOPT.2018.8362877
