Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.1925
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DC FieldValueLanguage
dc.contributor.authorTurau, Volker-
dc.date.accessioned2018-12-13T09:07:23Z-
dc.date.available2018-12-13T09:07:23Z-
dc.date.issued2018-05-03-
dc.identifierdoi: 10.3390/a11050058-
dc.identifier.citationAlgorithms 11 (2018), 5 : 58de_DE
dc.identifier.issn1999-4893de_DE
dc.identifier.urihttp://tubdok.tub.tuhh.de/handle/11420/1928-
dc.description.abstractThe analysis of self-stabilizing algorithms is often limited to the worst case stabilization time starting from an arbitrary state, i.e., a state resulting from a sequence of faults. Considering the fact that these algorithms are intended to provide fault tolerance in the long run, this is not the most relevant metric. A common situation is that a running system is an a legitimate state when hit by a single fault. This event has a much higher probability than multiple concurrent faults. Therefore, the worst case time to recover from a single fault is more relevant than the recovery time from a large number of faults. This paper presents techniques to derive upper bounds for the mean time to recover from a single fault for self-stabilizing algorithms based on Markov chains in combination with lumping. To illustrate the applicability of the techniques they are applied to a new self-stabilizing coloring algorithm.en
dc.description.sponsorshipDeutsche Forschungsgemeinschaftde_DE
dc.language.isoende_DE
dc.publisherMultidisciplinary Digital Publishing Institutede_DE
dc.relation.ispartofAlgorithmsde_DE
dc.rightsCC BY 4.0de_DE
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.subjectdistributed algorithmsde_DE
dc.subjectfault-tolerancede_DE
dc.subjectself-stabilizationde_DE
dc.subjectMarkov chainde_DE
dc.subjectlumpingde_DE
dc.subject.ddc510: Mathematikde_DE
dc.titleComputing Fault-Containment Times of Self-Stabilizing Algorithms Using Lumped Markov Chainsde_DE
dc.typeArticlede_DE
dc.date.updated2018-11-22T14:21:57Z-
dc.identifier.urnurn:nbn:de:gbv:830-882.023854-
dc.identifier.doi10.15480/882.1925-
dc.type.diniarticle-
dc.subject.ddccode510-
dcterms.DCMITypeText-
tuhh.identifier.urnurn:nbn:de:gbv:830-882.023854de_DE
tuhh.oai.showtrue-
dc.identifier.hdl11420/1928-
tuhh.abstract.englishThe analysis of self-stabilizing algorithms is often limited to the worst case stabilization time starting from an arbitrary state, i.e., a state resulting from a sequence of faults. Considering the fact that these algorithms are intended to provide fault tolerance in the long run, this is not the most relevant metric. A common situation is that a running system is an a legitimate state when hit by a single fault. This event has a much higher probability than multiple concurrent faults. Therefore, the worst case time to recover from a single fault is more relevant than the recovery time from a large number of faults. This paper presents techniques to derive upper bounds for the mean time to recover from a single fault for self-stabilizing algorithms based on Markov chains in combination with lumping. To illustrate the applicability of the techniques they are applied to a new self-stabilizing coloring algorithm.de_DE
tuhh.publisher.doidoi: 10.3390/a11050058-
tuhh.publication.instituteTelematik E-17de_DE
tuhh.identifier.doi10.15480/882.1925-
tuhh.type.opus(wissenschaftlicher) Artikelde
tuhh.institute.germanTelematik E-17de
tuhh.institute.englishTelematik E-17de_DE
tuhh.gvk.hasppnfalse-
openaire.rightsinfo:eu-repo/semantics/openAccessde_DE
dc.type.driverarticle-
dc.rights.ccbyde_DE
dc.rights.ccversion4.0de_DE
dc.type.casraiJournal Articleen
tuhh.container.volume11.2018, 5de_DE
tuhh.container.startpageArtikelnummer: 58de_DE
dc.relation.projectDFG (TU 221/6-2)de_DE
dc.rights.nationallicensefalsede_DE
item.fulltextWith Fulltext-
item.creatorOrcidTurau, Volker-
item.creatorGNDTurau, Volker-
item.grantfulltextopen-
crisitem.author.deptTelematik E-17-
crisitem.author.orcid0000-0001-9964-8816-
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