Weighted double deep Q-network based reinforcement learning for bi-objective multi-workflow scheduli...
Weighted double deep Q-network based reinforcement learning for bi-objective multi-workflow scheduling in the cloud
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Publisher
New York: Springer US
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Language
English
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Publisher
New York: Springer US
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Scope and Contents
Contents
As a promising distributed paradigm, cloud computing provides a cost-effective deploying environment for hosting scientific applications due to its provisioning elastic, heterogeneous resources in a pay-per-use model. More and more applications modeled as workflows are being moved to the cloud, and time and cost become important for workflow execut...
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Full title
Weighted double deep Q-network based reinforcement learning for bi-objective multi-workflow scheduling in the cloud
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Author / Creator
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Record Identifier
TN_cdi_proquest_journals_2918253172
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2918253172
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ISSN
1386-7857
E-ISSN
1573-7543
DOI
10.1007/s10586-021-03454-6
