Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/8149
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dc.contributor.authorAçıkalın, U.U.-
dc.contributor.authorÇaşkurlu, B.-
dc.contributor.authorWojciechowski, P.-
dc.contributor.authorSubramani, K.-
dc.date.accessioned2022-01-15T12:58:46Z-
dc.date.available2022-01-15T12:58:46Z-
dc.date.issued2021-
dc.identifier.isbn9783030930424-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://doi.org/10.1007/978-3-030-93043-1_3-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/8149-
dc.description6th International Symposium on Algorithmic Aspects of Cloud Computing, ALGOCLOUD 2021 -- 6 September 2021 through 7 September 2021 -- 269749en_US
dc.description.abstractAn important ubiquitous task in modern cloud systems is the migration of databases from one location to another. In practical settings, the databases are migrated in several shifts in order to meet the quality of service requirements of the end-users [18]. Once a batch of databases is migrated in a shift, the applications that depend on the databases on that shift are to be immediately tested [8]. Testing an application is a costly procedure [25] and the number of times an application is to be tested throughout the migration process varies greatly depending on the migration schedule. An interesting algorithmic challenge is to find a schedule that minimizes the total testing cost of all the applications. This problem, referred to as the capacity constrained database migration (CCDM) problem, is known to be NP-hard and fixed-parameter intractable for various relevant parameters [24]. In this paper, we provide new approximability and inapproximability results as well as new conditional lower bounds for the running time of any exact algorithm for the CCDM problem. Also, we adapt heuristic algorithms devised for the Hypergraph Partitioning problem to the CCDM problem and give extensive experimental results. © 2021, Springer Nature Switzerland AG.en_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCloud computingen_US
dc.subjectCombinatorial optimizationen_US
dc.subjectHeuristic algorithmsen_US
dc.subjectQuality of serviceen_US
dc.subjectAlgorithmicsen_US
dc.subjectCloud systemsen_US
dc.subjectCost minimizationen_US
dc.subjectDatabase migrationsen_US
dc.subjectEnd-usersen_US
dc.subjectMigration processen_US
dc.subjectNew resultsen_US
dc.subjectQuality-of-serviceen_US
dc.subjectService requirementsen_US
dc.subjectTest costen_US
dc.subjectDatabase systemsen_US
dc.titleNew Results on Test-Cost Minimization in Database Migrationen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.identifier.volume13084 LNCSen_US
dc.identifier.startpage38en_US
dc.identifier.endpage55en_US
dc.identifier.wosWOS:000769651600003en_US
dc.identifier.scopus2-s2.0-85121931102en_US
dc.institutionauthorÇaşkurlu, Buğra-
dc.identifier.doi10.1007/978-3-030-93043-1_3-
dc.authorscopusid35309348400-
dc.authorscopusid35104543000-
dc.authorscopusid57205976247-
dc.authorscopusid8921210200-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
item.openairetypeConference Object-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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