Orchestrating Mixed-Criticality Cloud Workloads in Reconfigurable Manufacturing Systems
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
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| _version_ | 1866917624672157696 |
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| author | Barletta, Marco Cinque, Marcello De Vita, Davide |
| author_facet | Barletta, Marco Cinque, Marcello De Vita, Davide |
| contents | The adoption of cloud computing technologies in the industry is paving the way to new manufacturing paradigms. In this paper we propose a model to optimize the orchestration of workloads with differentiated criticality levels on a cloud-enabled factory floor. Preliminary results show that it is possible to optimize the guarantees to deployed jobs without penalizing the number of schedulable jobs. We indicate future research paths to quantitatively evaluate job isolation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_19042 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Orchestrating Mixed-Criticality Cloud Workloads in Reconfigurable Manufacturing Systems Barletta, Marco Cinque, Marcello De Vita, Davide Distributed, Parallel, and Cluster Computing The adoption of cloud computing technologies in the industry is paving the way to new manufacturing paradigms. In this paper we propose a model to optimize the orchestration of workloads with differentiated criticality levels on a cloud-enabled factory floor. Preliminary results show that it is possible to optimize the guarantees to deployed jobs without penalizing the number of schedulable jobs. We indicate future research paths to quantitatively evaluate job isolation. |
| title | Orchestrating Mixed-Criticality Cloud Workloads in Reconfigurable Manufacturing Systems |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2403.19042 |