On the Effectiveness of Standard Centrality Metrics for Interdependent Networks

Nathaniel Hudson, Matthew Turner, Asare Nkansah, Hana Khamfroush

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper investigates the effectiveness of standard centrality metrics for interdependent networks (IDN) in identifying important nodes in preventing catastrophic failure propagation. To show the need for designing specialized centrality metrics for IDNs, we compare the performance of these metrics in an IDN under two different scenarios: i) the nodes with highest centrality of networks composing an IDN are selected separately and ii) the nodes with highest centrality of the entire IDN represented as one single network are calculated. To investigate the resiliency of an IDN, a threshold-based failure propagation model is used to simulate the evolution of failure propagation over time. The nodes with highest centrality are chosen and are assumed to be resistant w.r.t failure. Extensive simulation is conducted to compare the usefulness of standard metrics to stop or slow down the failure propagation in an IDN. Finally a new metric of centrality tailored for interdependent networks is proposed and evaluated. Also, useful guidelines on designing new metrics are presented.

Original languageEnglish (US)
Title of host publication2019 International Conference on Computing, Networking and Communications, ICNC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages842-846
Number of pages5
ISBN (Electronic)9781538692233
DOIs
StatePublished - Apr 8 2019
Event2019 International Conference on Computing, Networking and Communications, ICNC 2019 - Honolulu, United States
Duration: Feb 18 2019Feb 21 2019

Publication series

Name2019 International Conference on Computing, Networking and Communications, ICNC 2019

Conference

Conference2019 International Conference on Computing, Networking and Communications, ICNC 2019
Country/TerritoryUnited States
CityHonolulu
Period2/18/192/21/19

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software
  • Hardware and Architecture

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