Stacked job scheduling on virtual machines with containers in cloud computing systems

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buir.advisorKörpeoğlu, İbrahim
dc.contributor.authorAkın, Mustafa
dc.date.accessioned2016-07-13T07:09:55Z
dc.date.available2016-07-13T07:09:55Z
dc.date.copyright2016-06
dc.date.issued2016-06
dc.date.submitted2016-07-12
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (M.S.): Bilkent University, Department of Computer Engineering, İhsan Doğramacı Bilkent University, 2016.en_US
dc.descriptionIncludes bibliographical references (leaves 61-65).en_US
dc.description.abstractVirtualization and use of virtual machines (VMs) is important for both public and private cloud systems and also for users. The allocation and use of virtual machines can be optimized by using knowledge about expectations of users, such as resource demands, network communication patterns, and total budget. However, both public and private cloud providers do not expose advanced configuration options to make use of custom needs of users. Adding upon to previous research, we propose a new approach for allocating and scheduling user jobs to virtual machines by use of container technologies like Docker, so that VM utilization can be increased and costs for users can be decreased. In our approach, by predicting resource demands, we can schedule different kinds of jobs on a single virtual machine without jobs affecting each other and without degrading performance to unacceptable levels. We also allow cost-performance tradeoff for users. We veri fied our approach in a real test-bed and evaluated it with extensive simulation experiments. We also adapted our approach into a real web-based application we developed, called PAGS (Programming Assignment Grading System), which enables efficient and convenient testing, submission and evaluation of programming assignments of a large number students in an interactive or batch manner in identical and isolated system environments. Our approach effectively schedules requests from teachers and students so that the system can horizontally scale in a cost efficient manner.en_US
dc.description.provenanceSubmitted by Betül Özen (ozen@bilkent.edu.tr) on 2016-07-13T07:09:55Z No. of bitstreams: 1 MustafaAkin_Tez.pdf: 1454038 bytes, checksum: f66ab09d2c7e4c021e33daa2cf8e8646 (MD5)en
dc.description.provenanceMade available in DSpace on 2016-07-13T07:09:55Z (GMT). No. of bitstreams: 1 MustafaAkin_Tez.pdf: 1454038 bytes, checksum: f66ab09d2c7e4c021e33daa2cf8e8646 (MD5) Previous issue date: 2016-06en
dc.description.statementofresponsibilityby Mustafa Akın.en_US
dc.format.extentx, 65 leaves : illustrations, charts.en_US
dc.identifier.itemidB153638
dc.identifier.urihttp://hdl.handle.net/11693/30132
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectClouden_US
dc.subjectSchedulingen_US
dc.subjectContainersen_US
dc.subjectVirtual machineen_US
dc.subjectAllocationen_US
dc.titleStacked job scheduling on virtual machines with containers in cloud computing systemsen_US
dc.title.alternativeBulut bilişim sistemlerinde sanal makineler üzerinde taşıyıcılar ile yığın iş çizelgelemesien_US
dc.typeThesisen_US
thesis.degree.disciplineComputer Engineering
thesis.degree.grantorBilkent University
thesis.degree.levelMaster's
thesis.degree.nameMS (Master of Science)

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