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Simulation Tools and Techniques. 12th EAI International Conference, SIMUtools 2020, Guiyang, China, August 28-29, 2020, Proceedings, Part I

Research Article

Workload Evaluation Tool for Metadata Distribution Method

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  • @INPROCEEDINGS{10.1007/978-3-030-72792-5_63,
        author={\^{E}lo\~{n}se Billa and Philippe Deniel and Soraya Zertal},
        title={Workload Evaluation Tool for Metadata Distribution Method},
        proceedings={Simulation Tools and Techniques. 12th EAI International Conference, SIMUtools 2020, Guiyang, China, August 28-29, 2020, Proceedings, Part I},
        proceedings_a={SIMUTOOLS},
        year={2021},
        month={4},
        keywords={Metadata distribution Load-balancing Evaluation tool},
        doi={10.1007/978-3-030-72792-5_63}
    }
    
  • Éloïse Billa
    Philippe Deniel
    Soraya Zertal
    Year: 2021
    Workload Evaluation Tool for Metadata Distribution Method
    SIMUTOOLS
    Springer
    DOI: 10.1007/978-3-030-72792-5_63
Éloïse Billa, Philippe Deniel, Soraya Zertal1
  • 1: Li-PaRAD

Abstract

In theHigh Performance Computingfield (HPC), metadata server cluster is a critical aspect of a storage system performance and with object storage growth, systems must now be able to distribute metadata across servers thanks to distributed metadata servers. Storage systems reach better performances if the workload remains balanced over time. Indeed, an unbalanced distribution can lead to frequent requests to a subset of servers while other servers are completely idle. To avoid this issue, different metadata distribution methods exist and each one has its best use cases. Moreover, each system has different usages and different workloads, which means that one distribution method could fit to a specific kind of storage system and not to another one. To this end, we propose a tool to evaluate metadata distribution methods with different workloads. In this paper, we describe this tool and we use it to compare state-of-the-art methods and one method we developed. We also show how outputs generated by our tool enable us to deduce distribution weakness and chose the most adapted method.

Keywords
Metadata distribution Load-balancing Evaluation tool
Published
2021-04-27
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-72792-5_63
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