{"title":"虚拟化数据中心中基于工作负载预测的自动伸缩发放","authors":"Danqing Feng, Zhibo Wu, Decheng Zuo, Zhan Zhang","doi":"10.4018/ijghpc.2020010104","DOIUrl":null,"url":null,"abstract":"WiththedevelopmentintheClouddatacenters,thepurposeoftheefficientresourceallocationis tomeetthedemandoftheusersinstantlywiththeminimumrentcost.Thus,theelasticresource allocationstrategyisusuallycombinedwiththepredictiontechnology.Thisarticleproposesanovel predictmethodcombinationforecasttechnique,includingbothexponentialsmoothing(ES)andautoregressiveandpolynomialfitting(PF)model.Theaimofcombinationpredictionistoachievean efficientforecasttechniqueaccordingtotheperiodicandrandomfeatureoftheworkloadandmeet theapplicationservicelevelagreement(SLA)withtheminimumcost.Moreover,theESprediction withPSOalgorithmgivesafine-grainedscalingupanddowntheresourcescombiningtheheuristic algorithminthefuture.APWPwouldsolvetheperiodicalorhybridfluctuationoftheworkloadin theclouddatacenters.Finally,experimentsimprovethatthecombinedpredictionmodelmeetsthe SLAwiththebetterprecisionaccuracywiththeminimumrentingcost. KeyWoRDS ES, PF, Prediction, Provisioning, Scaling, SLA","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"76 1","pages":"53-69"},"PeriodicalIF":0.6000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Auto-Scaling Provision Basing on Workload Prediction in the Virtualized Data Center\",\"authors\":\"Danqing Feng, Zhibo Wu, Decheng Zuo, Zhan Zhang\",\"doi\":\"10.4018/ijghpc.2020010104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"WiththedevelopmentintheClouddatacenters,thepurposeoftheefficientresourceallocationis tomeetthedemandoftheusersinstantlywiththeminimumrentcost.Thus,theelasticresource allocationstrategyisusuallycombinedwiththepredictiontechnology.Thisarticleproposesanovel predictmethodcombinationforecasttechnique,includingbothexponentialsmoothing(ES)andautoregressiveandpolynomialfitting(PF)model.Theaimofcombinationpredictionistoachievean efficientforecasttechniqueaccordingtotheperiodicandrandomfeatureoftheworkloadandmeet theapplicationservicelevelagreement(SLA)withtheminimumcost.Moreover,theESprediction withPSOalgorithmgivesafine-grainedscalingupanddowntheresourcescombiningtheheuristic algorithminthefuture.APWPwouldsolvetheperiodicalorhybridfluctuationoftheworkloadin theclouddatacenters.Finally,experimentsimprovethatthecombinedpredictionmodelmeetsthe SLAwiththebetterprecisionaccuracywiththeminimumrentingcost. KeyWoRDS ES, PF, Prediction, Provisioning, Scaling, SLA\",\"PeriodicalId\":43565,\"journal\":{\"name\":\"International Journal of Grid and High Performance Computing\",\"volume\":\"76 1\",\"pages\":\"53-69\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Grid and High Performance Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/ijghpc.2020010104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Grid and High Performance Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijghpc.2020010104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 2
Auto-Scaling Provision Basing on Workload Prediction in the Virtualized Data Center
WiththedevelopmentintheClouddatacenters,thepurposeoftheefficientresourceallocationis tomeetthedemandoftheusersinstantlywiththeminimumrentcost.Thus,theelasticresource allocationstrategyisusuallycombinedwiththepredictiontechnology.Thisarticleproposesanovel predictmethodcombinationforecasttechnique,includingbothexponentialsmoothing(ES)andautoregressiveandpolynomialfitting(PF)model.Theaimofcombinationpredictionistoachievean efficientforecasttechniqueaccordingtotheperiodicandrandomfeatureoftheworkloadandmeet theapplicationservicelevelagreement(SLA)withtheminimumcost.Moreover,theESprediction withPSOalgorithmgivesafine-grainedscalingupanddowntheresourcescombiningtheheuristic algorithminthefuture.APWPwouldsolvetheperiodicalorhybridfluctuationoftheworkloadin theclouddatacenters.Finally,experimentsimprovethatthecombinedpredictionmodelmeetsthe SLAwiththebetterprecisionaccuracywiththeminimumrentingcost. KeyWoRDS ES, PF, Prediction, Provisioning, Scaling, SLA