Solving Task Scheduling Problems in Dew Computing via Deep Reinforcement Learning
Due to mobile and IoT devices’ ubiquity and their ever-growing processing potential, Dew computing environments have been emerging topics for researchers. These environments allow resource-constrained devices to contribute computing power to others in a local network. One major challenge in these en...
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| Principais autores: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
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MDPI AG
2022-07-01
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| Colecção: | Applied Sciences |
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| Acesso em linha: | https://www.mdpi.com/2076-3417/12/14/7137 |
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