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dc.identifier.urihttp://hdl.handle.net/11401/77265
dc.description.sponsorshipThis work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.en_US
dc.formatMonograph
dc.format.mediumElectronic Resourceen_US
dc.language.isoen_US
dc.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dc.typeThesis
dcterms.abstractContainers or OS-based virtualization have seen a recent resurgence in deployment. Containers have low memory footprint and start-up time but provide weaker security isolation than Virtual Machines (VMs). Incapability to load kernel modules and support multiple OS, and platform-dependence limits the functionality of containers. On the other hand, VMs or hardware-based virtualization are platform-independent and are more secure, but have higher overheads. A data centre operator chooses among these two virtualization technologies —VMs and containers—when setting up guests on cloud infrastructure. Density and Latency are two critical factors for a data centre operator because they determine the efficiency of cloud computing. Therefore, this thesis contributes updated density and latency measurements of KVM VMs and Linux Containers with a recent kernel version and best practices. This work also studies the memory footprint of KVM VMs and Linux Containers. In addition, it identifies three ways to improve the density of KVM VMs by lowering the memory footprint: improving existing memory deduplication techniques, removing unused devices emulated by QEMU, and removing unused pages from the guest address space.
dcterms.abstractContainers or OS-based virtualization have seen a recent resurgence in deployment. Containers have low memory footprint and start-up time but provide weaker security isolation than Virtual Machines (VMs). Incapability to load kernel modules and support multiple OS, and platform-dependence limits the functionality of containers. On the other hand, VMs or hardware-based virtualization are platform-independent and are more secure, but have higher overheads. A data centre operator chooses among these two virtualization technologies —VMs and containers—when setting up guests on cloud infrastructure. Density and Latency are two critical factors for a data centre operator because they determine the efficiency of cloud computing. Therefore, this thesis contributes updated density and latency measurements of KVM VMs and Linux Containers with a recent kernel version and best practices. This work also studies the memory footprint of KVM VMs and Linux Containers. In addition, it identifies three ways to improve the density of KVM VMs by lowering the memory footprint: improving existing memory deduplication techniques, removing unused devices emulated by QEMU, and removing unused pages from the guest address space.
dcterms.available2017-09-20T16:52:19Z
dcterms.contributorPorter, Donald Een_US
dcterms.contributorStoller, Scotten_US
dcterms.contributorFerdman, Mike.en_US
dcterms.creatorAgarwal, Kavita
dcterms.dateAccepted2017-09-20T16:52:19Z
dcterms.dateSubmitted2017-09-20T16:52:19Z
dcterms.descriptionDepartment of Computer Science.en_US
dcterms.extent55 pg.en_US
dcterms.formatApplication/PDFen_US
dcterms.formatMonograph
dcterms.identifierhttp://hdl.handle.net/11401/77265
dcterms.issued2015-12-01
dcterms.languageen_US
dcterms.provenanceMade available in DSpace on 2017-09-20T16:52:19Z (GMT). No. of bitstreams: 1 Agarwal_grad.sunysb_0771M_12504.pdf: 1010080 bytes, checksum: 4feba47f8a43388bacf753e7362fbec7 (MD5) Previous issue date: 1en
dcterms.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dcterms.subjectEngineering
dcterms.subjectcloud computing, containers, deduplication, overheads, virtualization, VMs
dcterms.titleA Study of Virtualization Overheads
dcterms.typeThesis


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