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A Queueing Model to Achieve Proper Elasticity for Cloud Cluster Jobs
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Estimating service response time for elastic cloud applications
inferredcites →https://doi.org/10.1109/esciw.2009.5408002openalex-snapshot
Scientific workflow applications on Amazon EC2
inferredcites →https://doi.org/10.1109/i-span.2009.150openalex-snapshot
High-Performance Cloud Computing: A View of Scientific Applications
inferredcites →https://doi.org/10.1109/noms.2012.6211900openalex-snapshot
An adaptive hybrid elasticity controller for cloud infrastructures
inferredcites →https://doi.org/10.1109/tnsm.2009.04.090404openalex-snapshot
AppRAISE: application-level performance management in virtualized server environments
inferredcites →https://doi.org/10.1109/tpds.2011.199openalex-snapshot
Performance Analysis of Cloud Computing Centers Using M/G/m/m+r Queuing Systems
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inferredcites →https://doi.org/10.1145/1555271.1555277openalex-snapshot
Elastic management of cluster-based services in the cloud
inferredcites →https://doi.org/10.1145/1851476.1851535openalex-snapshot
Case study for running HPC applications in public clouds
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inferredcites →https://doi.org/10.1145/2188286.2188301openalex-snapshot
How a consumer can measure elasticity for cloud platforms
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Efficient provisioning of bursty scientific workloads on the cloud using adaptive elasticity control
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