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dc.contributor.authorWłodzimierz, Funika-
dc.contributor.authorPaweł, Koperek-
dc.contributor.authorJacek, Kitowski-
dc.date.accessioned2023-03-31T01:27:16Z-
dc.date.available2023-03-31T01:27:16Z-
dc.date.issued2023-
dc.identifier.urihttps://link.springer.com/article/10.1007/s11227-022-04924-3-
dc.identifier.urihttps://dlib.phenikaa-uni.edu.vn/handle/PNK/7354-
dc.descriptionCC BYvi
dc.description.abstractMany modern applications, both scientific and commercial, are deployed to cloud environments and often employ multiple types of resources. That allows them to efficiently allocate only the resources which are actually needed to achieve their goals. However, in many workloads the actual usage of the infrastructure varies over time, which results in over-provisioning and unnecessarily high costs. In such cases, automatic resource scaling can provide significant cost savings by provisioning only the amount of resources which are necessary to support the current workload. Unfortunately, due to the complex nature of distributed systems, automatic scaling remains a challenge.vi
dc.language.isoenvi
dc.publisherSpringervi
dc.subjectmodern applicationsvi
dc.subjectscientific and commercialvi
dc.subjectcomplex nature of distributed systemsvi
dc.titleAutomated cloud resources provisioning with the use of the proximal policy optimizationvi
dc.typeBookvi
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