Improving Cluster Scheduling Resiliency to Network Faults

dc.contributor.advisorAl-Kiswany, Samer
dc.contributor.authorQunaibi, Sara
dc.date.accessioned2023-05-31T15:46:06Z
dc.date.available2024-05-31T04:50:04Z
dc.date.issued2023-05-31
dc.date.submitted2023-05-25
dc.description.abstractWe present a comprehensive empirical study of the impact partial network partitions have on cluster managers in data analysis frameworks. Our study shows that modern scheduling approaches are vulnerable to partial network partitions. Partial partitions can lead to a complete cluster pause or a significant loss of performance. To overcome the shortcoming of the state-of-the-art schedulers, we design the topology-aware scheduler (TAS). TAS incorporates the current network connectivity information when making a scheduling decision, to allocate fully connected nodes for a given application. TAS effectively hides partial partitions from applications. Our evaluation of a TAS prototype shows that it can tolerate partial network partitions, eliminate application halting or significant loss of performance.en
dc.identifier.urihttp://hdl.handle.net/10012/19515
dc.language.isoenen
dc.pendingfalse
dc.publisherUniversity of Waterlooen
dc.subjectfault toleranceen
dc.subjectnetwork partitionsen
dc.subjectcomputer networksen
dc.subjectcloud computingen
dc.titleImproving Cluster Scheduling Resiliency to Network Faultsen
dc.typeMaster Thesisen
uws-etd.degreeMaster of Mathematicsen
uws-etd.degree.departmentDavid R. Cheriton School of Computer Scienceen
uws-etd.degree.disciplineComputer Scienceen
uws-etd.degree.grantorUniversity of Waterlooen
uws-etd.embargo.terms1 yearen
uws.contributor.advisorAl-Kiswany, Samer
uws.contributor.affiliation1Faculty of Mathematicsen
uws.peerReviewStatusUnrevieweden
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

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