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dc.contributor.authorNguyen, Thuy L.
dc.contributor.authorNou Castell, Ramon
dc.contributor.authorLebre, Adrien
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2019-09-17T10:05:19Z
dc.date.available2019-09-17T10:05:19Z
dc.date.issued2019
dc.identifier.citationNguyen, T. L.; Nou, R.; Lebre, A. YOLO: Speeding Up VM and Docker Boot Time by Reducing I/O Operations. A: "Euro-Par 2019: Parallel Processing". Springer, 2019.
dc.identifier.isbn978-3-030-29399-4
dc.identifier.urihttp://hdl.handle.net/2117/168305
dc.description.abstractAlthough this comes as a surprise, the time to boot a Docker-based container can last as long as a virtual machine in high consolidated cloud scenarios. Because this time is critical as boot duration defines how an application can react w.r.t. demands’ fluctuations (horizontal elasticity), we present in this paper the YOLO mechanism (You Only Load Once). YOLO reduces the number of I/O operations generated during a boot process by relying on a boot image abstraction, a subset of the VM/container image that contains data blocks necessary to complete the boot operation. Whenever a VM or a container is booted, YOLO intercepts all read accesses and serves them directly from the boot image, which has been locally stored on fast access storage devices (e.g., memory, SSD, etc.). In addition to YOLO, we show that another mechanism is required to ensure that files related to VM/container management systems remain in the cache of the host OS. Our results show that the use of these two techniques can speed up the boot duration 2–13 times for VMs and 2 times for containers. The benefit on containers is limited due to internal choices of the docker design. We underline that our proposal can be easily applied to other types of virtualization (e.g., Xen) and containerization because it does not require intrusive modifications on the virtualization/container management system nor the base image structure.
dc.description.sponsorshipAll experiments presented in this paper were carried out using the Grid'5000 testbed, supported by a scientific interest group hosted by Inria and including CNRS, RENATER and several Universities as well as other organizations (see https://www.grid5000.fr). This work is also a part of the BigStorage project, H2020-MSCA-ITN-2014-642963, funded by the European Commission within the Marie Skodowska-Curie Actions framework. This work was partially supported by the Spanish Ministry of Science and Innovation under the TIN2015-65316 grant, the Generalitat de Catalunya under contract 2014-SGR-1051.
dc.format.extent14 p.
dc.language.isoeng
dc.publisherSpringer
dc.subjectÀrees temàtiques de la UPC::Enginyeria elèctrica
dc.subject.lcshHigh performance computing
dc.subject.otherVirtualization
dc.subject.otherContainerization
dc.subject.otherBoot duration
dc.titleYOLO: Speeding Up VM and Docker Boot Time by Reducing I/O Operations
dc.typePart of book or chapter of book
dc.subject.lemacSupercomputadors
dc.identifier.doi10.1007/978-3-030-29400-7_20
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.springerprofessional.de/en/yolo-speeding-up-vm-and-docker-boot-time-by-reducing-i-o-operati/17080644
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/642963/EU/BigStorage: Storage-based Convergence between HPC and Cloud to handle Big Data/BigStorage
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/PE2013-2016/TIN2015-65316
local.citation.publicationNameEuro-Par 2019: Parallel Processing


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