Progressive recovery from failure in multi-layered interdependent network using a new model of interdependency

Anisha Mazumder, Chenyang Zhou, Arun Das, Arunabha Sen

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

1 Citation (Scopus)

Abstract

A number of models have been proposed to analyze interdependent networks in recent years. However most of the models are unable to capture the complex interdependencies between such networks. To overcome the limitations, we have recently proposed a new model. Utilizing this model, we provide techniques for progressive recovery from failure. The goal of the progressive recovery problem is to maximize the system utility over the entire duration of the recovery process. We show that the problem can be solved in polynomial time in some special cases, whereas for some others, the problem is NP-complete. We provide two approximation algorithms with performance bounds of 2 and 4 respectively. We provide an optimal solution utilizing Integer Linear Programming and a heuristic. We evaluate the efficacy of our heuristic with both synthetic and real data collected from Phoenix metropolitan area. The experiments show that our heuristic almost always produces near optimal solution.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages368-380
Number of pages13
Volume8985
ISBN (Print)9783319316635
DOIs
StatePublished - 2016
Event9th International Conference on Critical Information Infrastructures Security, CRITIS 2014 - Limassol, Cyprus
Duration: Oct 13 2014Oct 15 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8985
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other9th International Conference on Critical Information Infrastructures Security, CRITIS 2014
CountryCyprus
CityLimassol
Period10/13/1410/15/14

Fingerprint

Interdependencies
Recovery
Heuristics
Optimal Solution
Performance Bounds
Integer Linear Programming
Approximation algorithms
Model
Linear programming
Efficacy
Approximation Algorithms
Computational complexity
Polynomial time
NP-complete problem
Maximise
Polynomials
Entire
Evaluate
Experiment
Experiments

Keywords

  • Analysis
  • Critical infrastructure
  • Inter-dependence
  • Modeling
  • Multi-layer networks
  • Progressive recovery

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Mazumder, A., Zhou, C., Das, A., & Sen, A. (2016). Progressive recovery from failure in multi-layered interdependent network using a new model of interdependency. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8985, pp. 368-380). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8985). Springer Verlag. https://doi.org/10.1007/978-3-319-31664-2_38

Progressive recovery from failure in multi-layered interdependent network using a new model of interdependency. / Mazumder, Anisha; Zhou, Chenyang; Das, Arun; Sen, Arunabha.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8985 Springer Verlag, 2016. p. 368-380 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8985).

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

Mazumder, A, Zhou, C, Das, A & Sen, A 2016, Progressive recovery from failure in multi-layered interdependent network using a new model of interdependency. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 8985, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8985, Springer Verlag, pp. 368-380, 9th International Conference on Critical Information Infrastructures Security, CRITIS 2014, Limassol, Cyprus, 10/13/14. https://doi.org/10.1007/978-3-319-31664-2_38
Mazumder A, Zhou C, Das A, Sen A. Progressive recovery from failure in multi-layered interdependent network using a new model of interdependency. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8985. Springer Verlag. 2016. p. 368-380. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-31664-2_38
Mazumder, Anisha ; Zhou, Chenyang ; Das, Arun ; Sen, Arunabha. / Progressive recovery from failure in multi-layered interdependent network using a new model of interdependency. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8985 Springer Verlag, 2016. pp. 368-380 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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