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http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/10021| Title: | Astrea: Auto-Serverless Analytics Towards Cost-Efficiency and QoS-Awareness |
| Authors: | Jananie, J. LiChen FeiXu BoLi |
| Keywords: | Cloud computing;Serverless computing;Resource provisioning;Modeling;Optimization |
| Issue Date: | 2022 |
| Publisher: | IEEE |
| Abstract: | Withtheabilitytosimplifythecodedeploymentwithone-clickuploadandlightweightexecution,serverlesscomputinghas emergedasapromisingparadigmwithincreasingpopularity.However,thereremainopenchallengeswhenadaptingdata-intensive analyticsapplicationstotheserverlesscontext,inwhichusersofserverlessanalyticsencounterthedifficultyincoordinatingcomputation acrossdifferentstagesandprovisioningresourcesinalargeconfigurationspace.Thispaperpresentsourdesignandimplementationof Astrea,whichconfiguresandorchestratesserverlessanalyticsjobsinanautonomousmanner,whiletakingintoaccountflexibly-specified userrequirements.Astreareliesonthemodelingofperformanceandcostwhichcharacterizestheintricateinterplayamongmultidimensionalfactors(e.g.,functionmemorysize,degreeofparallelismateachstage).Weformulateanoptimizationproblembasedon user-specificrequirementstowardsperformanceenhancementorcostreduction,anddevelopasetofalgorithmsbasedongraph theorytoobtaintheoptimaljobexecution.WedeployAstreaintheAWSLambdaplatformandconductreal-worldexperimentsover representativebenchmarks,includingBigDataanalyticsandmachinelearningworkloads,atdifferentscales.Extensiveresults demonstratethatAstreacanachievetheoptimalexecutiondecisionforserverlessdataanalytics,incomparisonwithvariousprovisioning anddeploymentbaselines.Forexample,whencomparedwiththreeprovisioningbaselines,Astreamanagestoreducethejobcompletion timeby21%to69%underagivenbudgetconstraint,whilesavingcostby20%to84%withoutviolatingperformancerequirements. |
| URI: | http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/10021 |
| Appears in Collections: | Computer Engineering |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| AstreaAuto-ServerlessAnalyticsTowards Cost-EfficiencyandQoS-Awareness.pdf | 2.73 MB | Adobe PDF | View/Open |
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