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dc.contributor.advisor Varman, Peter J.
dc.creatorWang, Hui
dc.date.accessioned 2013-03-08T00:39:49Z
dc.date.available 2013-03-08T00:39:49Z
dc.date.issued 2012
dc.identifier.urihttps://hdl.handle.net/1911/70483
dc.description.abstract The increasing popularity of storage and server consolidation introduces new challenges for resource management, capacity provisioning, and application performance guaranteeing. In addition, the bursty nature of storage workloads results in a large gap between the peak and the average capacity required to meet response time bounds, leading to low overall server utilization and high cost. This situation is driving the development of elastic QoS models that allow clients greater flexibility in adopting SLAs tailored to their workload characteristics and performance requirements, while allowing the service provider opportunities to optimize provisioning and scheduling decisions. This thesis presents a novel service model, called the Nested QoS model, for multiplexing concurrent bursty workloads in shared storage systems. The solution employs two strategies together: systematically classifying requests with a graduated QoS and flexibly scheduling the classified portions. The results show that the Nested QoS model provides (i) performance isolation and strong performance guarantees for both well-behaved and misbehaving workloads; (2) a flexible and auditable elastic SLA definition; and (3) improved server utilization.
dc.format.extent 81 p.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.subjectApplied sciences
Computer engineering
Electrical engineering
Computer science
dc.title Nested QoS: Providing flexible SLAs in shared storage systems
dc.identifier.digital WangH
dc.type.genre Thesis
dc.type.material Text
thesis.degree.department Electrical and Computer Engineering
thesis.degree.discipline Engineering
thesis.degree.grantor Rice University
thesis.degree.level Masters
thesis.degree.name Master of Science
dc.identifier.citation Wang, Hui. "Nested QoS: Providing flexible SLAs in shared storage systems." (2012) Master’s Thesis, Rice University. https://hdl.handle.net/1911/70483.


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