OptiTuner: On Performance Composition and Server Farm Energy Minimization Application

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dc.contributor.authorHeo, Jko
dc.contributor.authorJayachandran, Pko
dc.contributor.authorShin, Insikko
dc.contributor.authorWang, Dko
dc.contributor.authorAbdelzaher, Tko
dc.contributor.authorLiu, Xko
dc.date.accessioned2013-03-09T09:06:14Z-
dc.date.available2013-03-09T09:06:14Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2011-11-
dc.identifier.citationIEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, v.22, no.11, pp.1871 - 1878-
dc.identifier.issn1045-9219-
dc.identifier.urihttp://hdl.handle.net/10203/95947-
dc.description.abstractThis paper develops a software service for dynamic performance optimization and control in performance-sensitive systems. The next generation of performance-sensitive systems is expected to be more distributed and dynamic. They will have multiple "knobs" that affect performance and resource allocation. However, relying on the conglomeration of independent knob controls can become increasingly suboptimal. The problem lies in performance composability or lack thereof; a challenge that arises because individual optimizations in performance-sensitive systems generally do not compose well when combined. Performance adaptation in such systems needs to be carefully designed and implemented by holistically considering performance composability in order to achieve desired system performance. A flexible supporting software layer is therefore needed to easily apply different holistic performance management techniques. In this paper, we develop a software service, called OptiTuner, that monitors the current performance and the resource availability in performance-sensitive systems and allows easy implementation of different performance management schemes based on theoretical concepts of constrained optimization and feedback control. In order to show the efficacy of OptiTuner, we apply it to implement three holistic energy minimization techniques in a real-time web server farm comprising 18 machines. Using an industry standard e-Business benchmark, TPC-W, we demonstrate that the three approaches save up to 40 percent of total energy cost compared to the baseline approaches that do not holistically optimize the cost.-
dc.languageEnglish-
dc.publisherIEEE COMPUTER SOC-
dc.subjectOPTIMIZATION-
dc.titleOptiTuner: On Performance Composition and Server Farm Energy Minimization Application-
dc.typeArticle-
dc.identifier.wosid000295163500012-
dc.identifier.scopusid2-s2.0-80053561452-
dc.type.rimsART-
dc.citation.volume22-
dc.citation.issue11-
dc.citation.beginningpage1871-
dc.citation.endingpage1878-
dc.citation.publicationnameIEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS-
dc.contributor.localauthorShin, Insik-
dc.contributor.nonIdAuthorHeo, J-
dc.contributor.nonIdAuthorJayachandran, P-
dc.contributor.nonIdAuthorWang, D-
dc.contributor.nonIdAuthorAbdelzaher, T-
dc.contributor.nonIdAuthorLiu, X-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorPerformance composability-
dc.subject.keywordAuthorsoftware service-
dc.subject.keywordAuthorenergy minimization-
dc.subject.keywordAuthordata center-
dc.subject.keywordAuthorserver farm-
dc.subject.keywordPlusOPTIMIZATION-
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