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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2501.14763 |
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| _version_ | 1866917902450425856 |
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| author | Dutta, Souvik Brahmaroutu, Suri |
| author_facet | Dutta, Souvik Brahmaroutu, Suri |
| contents | Job scheduling under various constraints to achieve global optimization is a well-studied problem. However, in scenarios that involve time-dependent constraints, such as scheduling backup jobs, achieving global optimization may not always be desirable. This paper presents a framework for scheduling new backup jobs in the presence of existing job schedules, focusing on satisfying intent-based constraints without disrupting current schedules. The proposed method accommodates various scheduling intents and constraints, and its effectiveness is validated through extensive testing against a variety of backup scenarios on real-world data from Veritas Netbackup customer policies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_14763 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Intent-driven scheduling of backup jobs Dutta, Souvik Brahmaroutu, Suri Distributed, Parallel, and Cluster Computing Performance C.4; E.2 Job scheduling under various constraints to achieve global optimization is a well-studied problem. However, in scenarios that involve time-dependent constraints, such as scheduling backup jobs, achieving global optimization may not always be desirable. This paper presents a framework for scheduling new backup jobs in the presence of existing job schedules, focusing on satisfying intent-based constraints without disrupting current schedules. The proposed method accommodates various scheduling intents and constraints, and its effectiveness is validated through extensive testing against a variety of backup scenarios on real-world data from Veritas Netbackup customer policies. |
| title | Intent-driven scheduling of backup jobs |
| topic | Distributed, Parallel, and Cluster Computing Performance C.4; E.2 |
| url | https://arxiv.org/abs/2501.14763 |