| Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
|---|---|---|
| Article Number | 09012 | |
| Number of page(s) | 8 | |
| Section | Artificial Intelligence and Machine Learning | |
| DOI | https://doi.org/10.1051/epjconf/202429509012 | |
| Published online | 06 May 2024 | |
https://doi.org/10.1051/epjconf/202429509012
Digital Twins for Storage Systems and RAID Pools: Enhancing Data Management in High Energy Physics
HSE University, Moscow, Russia
* e-mail: al-maeeni@hse.ru
Published online: 6 May 2024
In high-energy physics experiments, the acquisition of vast quantities of data poses formidable challenges in terms of efficient storage and management. We explore the application of the digital twin concept for SSD RAID pools, wherein digital replicas of physical systems are created to augment the efficiency of data storage within HEP experiments. By developing digital twins of storage systems, this research seeks to facilitate the continuous monitoring, comprehensive analysis, and strategic optimization of various workloads within the HEP domain. The key objectives of this study include the development of a digital twin for a data storage system and the formulation of generative models to assess the performance of the data storage system performance under specific configurations and data load parameters.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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