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Survey the Storage Systems Used in HPC and BDA Ecosystems

Received: 25 March 2022     Accepted: 28 April 2022     Published: 19 May 2022
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Abstract

The advancement in HPC and BDA ecosystem demands a better understanding of the storage systems to plan effective solutions. The amount of data being generated from the ever-growing devices over years have increased tremendously. To make applications access data more efficiently for computation, HPC and BDA ecosystems adopt different storage systems. Each storage system has its pros and cons. Therefore, it is worthwhile and interesting to explore the storage systems used in HPC and BDA respectively. Also, it’s inquisitive to understand how such storage systems can handle data consistency and fault tolerance at a massive scale. In this paper, we’re surveying four storage systems: Lustre, Ceph, HDFS, and CockroachDB. Lustre and HDFS are some of the most prominent file systems in HPC and BDA ecosystem. Ceph is an upcoming filesystem and is being used by supercomputers. CockroachDB is based on NewSQL systems a technique that is being used in the industry for BDA applications. The study helps us to understand the underlying architecture of these storage systems and the building blocks used to create them. The protocols and mechanisms used for data storage, data access, data consistency, fault tolerance, and recovery from failover are also overviewed. The comparative study will help system designers to understand the key features and architectural goals of these storage systems to select better storage system solutions.

Published in Internet of Things and Cloud Computing (Volume 10, Issue 1)
DOI 10.11648/j.iotcc.20221001.12
Page(s) 12-28
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

HPC, BDA, Storage Systems, CockroachDB, HDFS, Ceph, Lustre

References
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Cite This Article
  • APA Style

    Priyam Shah, Jie Ye, Xian-He Sun. (2022). Survey the Storage Systems Used in HPC and BDA Ecosystems. Internet of Things and Cloud Computing, 10(1), 12-28. https://doi.org/10.11648/j.iotcc.20221001.12

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    ACS Style

    Priyam Shah; Jie Ye; Xian-He Sun. Survey the Storage Systems Used in HPC and BDA Ecosystems. Internet Things Cloud Comput. 2022, 10(1), 12-28. doi: 10.11648/j.iotcc.20221001.12

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    AMA Style

    Priyam Shah, Jie Ye, Xian-He Sun. Survey the Storage Systems Used in HPC and BDA Ecosystems. Internet Things Cloud Comput. 2022;10(1):12-28. doi: 10.11648/j.iotcc.20221001.12

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  • @article{10.11648/j.iotcc.20221001.12,
      author = {Priyam Shah and Jie Ye and Xian-He Sun},
      title = {Survey the Storage Systems Used in HPC and BDA Ecosystems},
      journal = {Internet of Things and Cloud Computing},
      volume = {10},
      number = {1},
      pages = {12-28},
      doi = {10.11648/j.iotcc.20221001.12},
      url = {https://doi.org/10.11648/j.iotcc.20221001.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.iotcc.20221001.12},
      abstract = {The advancement in HPC and BDA ecosystem demands a better understanding of the storage systems to plan effective solutions. The amount of data being generated from the ever-growing devices over years have increased tremendously. To make applications access data more efficiently for computation, HPC and BDA ecosystems adopt different storage systems. Each storage system has its pros and cons. Therefore, it is worthwhile and interesting to explore the storage systems used in HPC and BDA respectively. Also, it’s inquisitive to understand how such storage systems can handle data consistency and fault tolerance at a massive scale. In this paper, we’re surveying four storage systems: Lustre, Ceph, HDFS, and CockroachDB. Lustre and HDFS are some of the most prominent file systems in HPC and BDA ecosystem. Ceph is an upcoming filesystem and is being used by supercomputers. CockroachDB is based on NewSQL systems a technique that is being used in the industry for BDA applications. The study helps us to understand the underlying architecture of these storage systems and the building blocks used to create them. The protocols and mechanisms used for data storage, data access, data consistency, fault tolerance, and recovery from failover are also overviewed. The comparative study will help system designers to understand the key features and architectural goals of these storage systems to select better storage system solutions.},
     year = {2022}
    }
    

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    AB  - The advancement in HPC and BDA ecosystem demands a better understanding of the storage systems to plan effective solutions. The amount of data being generated from the ever-growing devices over years have increased tremendously. To make applications access data more efficiently for computation, HPC and BDA ecosystems adopt different storage systems. Each storage system has its pros and cons. Therefore, it is worthwhile and interesting to explore the storage systems used in HPC and BDA respectively. Also, it’s inquisitive to understand how such storage systems can handle data consistency and fault tolerance at a massive scale. In this paper, we’re surveying four storage systems: Lustre, Ceph, HDFS, and CockroachDB. Lustre and HDFS are some of the most prominent file systems in HPC and BDA ecosystem. Ceph is an upcoming filesystem and is being used by supercomputers. CockroachDB is based on NewSQL systems a technique that is being used in the industry for BDA applications. The study helps us to understand the underlying architecture of these storage systems and the building blocks used to create them. The protocols and mechanisms used for data storage, data access, data consistency, fault tolerance, and recovery from failover are also overviewed. The comparative study will help system designers to understand the key features and architectural goals of these storage systems to select better storage system solutions.
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Author Information
  • Computer Department, Illinois Institute of Technology, Chicago, USA

  • Computer Department, Illinois Institute of Technology, Chicago, USA

  • Computer Department, Illinois Institute of Technology, Chicago, USA

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