Sangam: A Confluence of Knowledge Streams

Robustness of interdependent random geometric networks

Show simple item record

dc.contributor Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
dc.contributor Zhang, Jianan
dc.contributor Modiano, Eytan H
dc.creator Yeh, Edmund
dc.creator Zhang, Jianan
dc.creator Modiano, Eytan H
dc.date 2017-12-29T15:22:05Z
dc.date 2017-12-29T15:22:05Z
dc.date 2017-02
dc.date 2016-09
dc.date.accessioned 2023-03-01T18:09:44Z
dc.date.available 2023-03-01T18:09:44Z
dc.identifier 978-1-5090-4550-1
dc.identifier http://hdl.handle.net/1721.1/112963
dc.identifier Zhang, Jianan, Edmund Yeh and Eytan Modiano. "Robustness of Interdependent Random Geometric Networks." 2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 27-30 September, 2016, Monticello, IL, IEEE, 2016, pp. 172–79.
dc.identifier https://orcid.org/0000-0003-3318-2165
dc.identifier https://orcid.org/0000-0001-8238-8130
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/278984
dc.description We propose an interdependent random geometric graph (RGG) model for interdependent networks. Based on this model, we study the robustness of two interdependent spatially embedded networks where interdependence exists between geographically nearby nodes in the two networks. We study the emergence of the giant mutual component in two interdependent RGGs as node densities increase, and define the percolation threshold as a pair of node densities above which the mutual giant component first appears. In contrast to the case for a single RGG, where the percolation threshold is a unique scalar for a given connection distance, for two interdependent RGGs, multiple pairs of percolation thresholds may exist, given that a smaller node density in one RGG may increase the minimum node density in the other RGG in order for a giant mutual component to exist. We derive analytical upper bounds on the percolation thresholds of two interdependent RGGs by discretization, and obtain 99% confidence intervals for the percolation thresholds by simulation. Based on these results, we derive conditions for the interdependent RGGs to be robust under random failures and geographical attacks.
dc.description United States. Defense Threat Reduction Agency (Grant HDTRA1-14-1-0058)
dc.format application/pdf
dc.language en_US
dc.publisher Institute of Electrical and Electronics Engineers (IEEE)
dc.relation http://dx.doi.org/10.1109/ALLERTON.2016.7852226
dc.relation 2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton)
dc.rights Creative Commons Attribution-Noncommercial-Share Alike
dc.rights http://creativecommons.org/licenses/by-nc-sa/4.0/
dc.source Prof. Modiano
dc.title Robustness of interdependent random geometric networks
dc.type Article
dc.type http://purl.org/eprint/type/ConferencePaper


Files in this item

Files Size Format View
Allerton16_Jianan copy.pdf 339.3Kb application/pdf View/Open

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse