基于sla的云资源分配模型-研究与优化

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1、万方数据东北大学硕士学位论文AbstractTheResearchandOptimizationofCloudResourceAllocationCloudresourcesinModelBasedonSLAAbstractcomputingisanewwayofInternet-basedcomputing，itcanprovideaccordancewithcustomer’Sdemand．Inrecentyears，cloudcomputinghasbecomethemainstreamofthe

2、developmenttrendoftheinformationindustry,andalsobecomeahotacademicresearch．Butwiththeexpansionofthescaleoftheuser,theuser’Srequestshowingincreasingdiversity,dynamic，complexfeatures，andaswellastheenergyconsumptionofdatacenterhasbecomeincreasinglyprominent

3、，theseallbringchallengestotheschedulingassignmentofcloudresources．Atthesametime，users’requirementsofqualityofservicesuchasresponsetimearegettinghigher,whileSLAcanprovideaguaranteeofqualityofservice．Therefore，theresearchofresourcesallocationbasedonSLAisne

4、cessary．Basedontheanalysisofcurrentresearch，thisthesispresentsanimprovedcloudcomputingresourceallocationmodel，andadoptesaswarmintelligencealgorithmforitssolution．Themaincontentsareasfollows：(1)Thismodelfullyconsiderstheneedsofusersonthequalityofservices，

5、meanwhileestablishestheobjectivefunctiononthegoalthatcloudserviceproviderscanobtainemaximizeprofits．Thefunctionmodulesinthecloudresourcemanagementplatformareintroducedfirst，andtheflowofinformationbetweenthemareanalyzed．Secondthismodelusesqueuingtheorytom

6、odeltheprocessofrequestsareservedandevaluatetheresponsetime，andusesalayeredapproachtohandleusers’requests，considerstheloadstatusofcloudcomputingsystem．accordingtothepredictednumberofrequeststodecidetheallocationofvirtualresources．(2)Multiplevariableswith

7、bindingrelationshipexistintheaboveresourceallocationmodel，anditbelongstoNP—hardproblem．Traditionalsolutionisdividethisproblemintoseveralsub—problemsbygreedyalgorithmforsolvingtheproblem，buttheresultsofsub-dividingobtainedaftersummingneedtoproveistheoptim

8、alsolutionoftheoriginalproblem，andtheproveisacomplexprocess．Therefore，thistheisuses·III·万方数据东北大学硕士学位论文Abstractswarmintelligencealgorithmtosolvethemodel．Theparticleswarmoptimazitonalgorithmasoneofintelligencealgorithmhaseas