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Data Centers Job Scheduling with Deep Reinforcement Learning
Efficient job scheduling on data centers under heterogeneous complexity is crucial but challenging since it involves the allocation of multi-dimensional resources over time and space. To adapt the complex computing environment in data centers, we proposed an innovative Advantage Actor-Critic (A2C) d...
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| Publicado no: | Advances in Knowledge Discovery and Data Mining |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7206316/ https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-47436-2_68 |
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