Detailed Information

Cited 0 time in webofscience Cited 3 time in scopus
Metadata Downloads

Cascading critical nodes detection with load redistribution in complex systems

Full metadata record
DC Field Value Language
dc.contributor.authorMishra, S.-
dc.contributor.authorLi, X.-
dc.contributor.authorThai, M.T.-
dc.contributor.authorSeo, J.-
dc.date.accessioned2021-09-15T06:40:04Z-
dc.date.available2021-09-15T06:40:04Z-
dc.date.created2021-09-15-
dc.date.issued2014-11-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/82163-
dc.description.abstractIn complex networked systems, the failures of a few critical components will cause a large cascade of component failures because of operational dependencies between components, resulting in the breakdown of the network. Therefore, it is crucial to identify these critical nodes in the study of complex network vulnerability under cascading failure. Unfortunately, we show that this problem is NP-hard to be approximated within a ratio of O(n1−Ɛ). Accordingly, we design two approaches to solve this problem. The first one estimates the cascading potential of each node while the second one measures the cooperated impact of node failures under an ordered attack. Since smart-grids is an important complex networked infrastructure, we also demonstrate some safety setting for power grids using the designed algorithms. © Springer International Publishing Switzerland 2014.-
dc.language영어-
dc.language.isoen-
dc.publisherSpringer Verlag-
dc.relation.isPartOfLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.titleCascading critical nodes detection with load redistribution in complex systems-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.doi10.1007/978-3-319-12691-3_29-
dc.identifier.bibliographicCitationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.8881, pp.379 - 394-
dc.description.isOpenAccessN-
dc.identifier.scopusid2-s2.0-84921480132-
dc.citation.endPage394-
dc.citation.startPage379-
dc.citation.titleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.citation.volume8881-
dc.contributor.affiliatedAuthorSeo, J.-
dc.type.docTypeArticle-
dc.subject.keywordAuthorCascading failure-
dc.subject.keywordAuthorComplex network vulnerability-
dc.subject.keywordAuthorInapproximability-
dc.subject.keywordAuthorSmart grids-
dc.subject.keywordPlusElectric power transmission networks-
dc.subject.keywordPlusIndium compounds-
dc.subject.keywordPlusNetwork security-
dc.subject.keywordPlusOutages-
dc.subject.keywordPlusSmart power grids-
dc.subject.keywordPlusCascading failures-
dc.subject.keywordPlusComplex networked systems-
dc.subject.keywordPlusComponent failures-
dc.subject.keywordPlusCritical component-
dc.subject.keywordPlusInapproximability-
dc.subject.keywordPlusLoad redistribution-
dc.subject.keywordPlusNetwork vulnerability-
dc.subject.keywordPlusSmart grid-
dc.subject.keywordPlusComplex networks-
dc.description.journalRegisteredClassscopus-
Files in This Item
There are no files associated with this item.
Appears in
Collections
IT융합대학 > 컴퓨터공학과 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher SEO, JUNGTAEK photo

SEO, JUNGTAEK
College of IT Convergence (컴퓨터공학부(스마트보안전공))
Read more

Altmetrics

Total Views & Downloads

BROWSE