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Article: Online Speed Scaling Based on Active Job Count to Minimize Flow Plus Energy

TitleOnline Speed Scaling Based on Active Job Count to Minimize Flow Plus Energy
Authors
KeywordsCompetitive analysis
Dynamic speed scaling
Energy efficiency
Flow time
Online algorithms
Scheduling
Sleep management
Issue Date2012
PublisherSpringer New York LLC. The Journal's web site is located at http://link.springer.de/link/service/journals/00453/index.htm
Citation
Algorithmica (New York), 2013, v. 65 n. 3, p. 605-633 How to Cite?
AbstractThis paper is concerned with online scheduling algorithms that aim at minimizing the total flow time plus energy usage. The results are divided into two parts. First, we consider the well-studied "simple" speed scaling model and show how to analyze a speed scaling algorithm (called AJC) that changes speed discretely. This is in contrast to the previous algorithms which change the speed continuously. More interestingly, AJC admits a better competitive ratio, and without using extra speed. In the second part, we extend the study to a more general speed scaling model where the processor can enter a sleep state to further save energy. A new sleep management algorithm called IdleLonger is presented. This algorithm, when coupled with AJC, gives the first competitive algorithm for minimizing total flow time plus energy in the general model. © 2012 Springer Science+Business Media, LLC.
Persistent Identifierhttp://hdl.handle.net/10722/152491
ISSN
2015 Impact Factor: 0.795
2015 SCImago Journal Rankings: 0.898
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLam, TWen_HK
dc.contributor.authorLee, LKen_HK
dc.contributor.authorTo, IKKen_HK
dc.contributor.authorWong, PWHen_HK
dc.date.accessioned2012-06-26T06:39:37Z-
dc.date.available2012-06-26T06:39:37Z-
dc.date.issued2012en_HK
dc.identifier.citationAlgorithmica (New York), 2013, v. 65 n. 3, p. 605-633en_HK
dc.identifier.issn0178-4617en_HK
dc.identifier.urihttp://hdl.handle.net/10722/152491-
dc.description.abstractThis paper is concerned with online scheduling algorithms that aim at minimizing the total flow time plus energy usage. The results are divided into two parts. First, we consider the well-studied "simple" speed scaling model and show how to analyze a speed scaling algorithm (called AJC) that changes speed discretely. This is in contrast to the previous algorithms which change the speed continuously. More interestingly, AJC admits a better competitive ratio, and without using extra speed. In the second part, we extend the study to a more general speed scaling model where the processor can enter a sleep state to further save energy. A new sleep management algorithm called IdleLonger is presented. This algorithm, when coupled with AJC, gives the first competitive algorithm for minimizing total flow time plus energy in the general model. © 2012 Springer Science+Business Media, LLC.en_HK
dc.languageengen_US
dc.publisherSpringer New York LLC. The Journal's web site is located at http://link.springer.de/link/service/journals/00453/index.htmen_HK
dc.relation.ispartofAlgorithmica (New York)en_HK
dc.subjectCompetitive analysisen_HK
dc.subjectDynamic speed scalingen_HK
dc.subjectEnergy efficiencyen_HK
dc.subjectFlow timeen_HK
dc.subjectOnline algorithmsen_HK
dc.subjectSchedulingen_HK
dc.subjectSleep managementen_HK
dc.titleOnline Speed Scaling Based on Active Job Count to Minimize Flow Plus Energyen_HK
dc.typeArticleen_HK
dc.identifier.emailLam, TW: hresltk@hkucc.hku.hken_HK
dc.identifier.emailLee, LK: lklee@cs.hku.hken_HK
dc.identifier.authorityLam, TW=rp00135en_HK
dc.identifier.authorityLee, LK=rp00140en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1007/s00453-012-9613-yen_HK
dc.identifier.scopuseid_2-s2.0-84884339110en_HK
dc.identifier.hkuros221681-
dc.identifier.volume65-
dc.identifier.issue3-
dc.identifier.spage605en_HK
dc.identifier.epage633en_HK
dc.identifier.eissn1432-0541-
dc.identifier.isiWOS:000314359200007-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLam, TW=7202523165en_HK
dc.identifier.scopusauthoridLee, LK=12646190100en_HK
dc.identifier.scopusauthoridTo, IKK=23398547200en_HK
dc.identifier.scopusauthoridWong, PWH=9734871500en_HK
dc.identifier.citeulike10314524-

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