Abstract

This paper studies the problem of robustifying an interdependent network by rewiring a small number of links in realtime during a cascading attack. Interdependent networks have been widely used to model interconnected complex systems such as a critical infrastructure network including both the power grid and the Internet. Realtime robustification of interdependent networks, therefore, has significant practical importance. This paper formulates the problem using the Markov decision process (MDP) framework. We first show the problem is NP-hard and then develop an effective and efficient greedy algorithm, named REALWIRE, to robustify the network in realtime. REALWIRE scores each link (and each node) based on the expected number of links failures resulted from the failure of the link (or the node), and rewires the links greedily according to the scores. Extensive experimental results show that REALWIRE outperforms other algorithms on multiple trobustness metrics.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018
EditorsNaoki Abe, Huan Liu, Calton Pu, Xiaohua Hu, Nesreen Ahmed, Mu Qiao, Yang Song, Donald Kossmann, Bing Liu, Kisung Lee, Jiliang Tang, Jingrui He, Jeffrey Saltz
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1347-1356
Number of pages10
ISBN (Electronic)9781538650356
DOIs
StatePublished - Jul 2 2018
Event2018 IEEE International Conference on Big Data, Big Data 2018 - Seattle, United States
Duration: Dec 10 2018Dec 13 2018

Publication series

NameProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018

Conference

Conference2018 IEEE International Conference on Big Data, Big Data 2018
Country/TerritoryUnited States
CitySeattle
Period12/10/1812/13/18

Keywords

  • Interdependent networks
  • Markov decision processes
  • cascading failures
  • network robustness

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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