Orchestrating Mixed-Criticality Cloud Workloads in Reconfigurable Manufacturing Systems

Fuente: arXiv
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Main Authors: Barletta, Marco, Cinque, Marcello, De Vita, Davide
Format: Preprint
Published: 2024
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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