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Performance Testing of Mass Distributed Abyss Storage Prototype for SMB

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Complex, Intelligent, and Software Intensive Systems (CISIS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 611))

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Abstract

The trends in ICT are concentrated in IoT, Bigdata, and Cloud Computing. These megatrends do not operate independently, and mass storage technology is essential as large computing technology is needed in the background to support them. In order to evaluate the performance of high-capacity storage based on open source Ceph, we carry out the demonstration test of abyss storage with domestic and overseas sites using educational network: KOREN. In addition, storage media and network bonding are tested to evaluate the performance of the storage itself.

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References

  1. Singh, K.: Learning Ceph, January 2015

    Google Scholar 

  2. Singh, K.: Ceph Cookbook, pp. 270–272, February 2016

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  3. SpeedoMeter. https://hub.docker.com/r/opennsm/speedometer/~/dockerfile/

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Acknowledgments

This work was supported by the Technology Development Project for Startup-Growth of SMBA. [No. S2385742, Development of open source-based mass volume distributed storage and network accelerator technology].

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Authors and Affiliations

  1. School of Electrical Engineering and Computer Science, GIST, Gwangju, Korea

    ByungRae Cha, Sun Park & JongWon Kim

  2. GenoTech Inc., Gwangju, Korea

    ByungRae Cha & YoonSeok Cha

Authors
  1. ByungRae Cha
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  2. YoonSeok Cha
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  3. Sun Park
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  4. JongWon Kim
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Corresponding author

Correspondence to ByungRae Cha .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Politècnico di Torino, Istituto Superiore Mario Boella, Turin, Italy

    Olivier Terzo

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Cha, B., Cha, Y., Park, S., Kim, J. (2018). Performance Testing of Mass Distributed Abyss Storage Prototype for SMB. In: Barolli, L., Terzo, O. (eds) Complex, Intelligent, and Software Intensive Systems. CISIS 2017. Advances in Intelligent Systems and Computing, vol 611. Springer, Cham. https://doi.org/10.1007/978-3-319-61566-0_71

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  • DOI: https://doi.org/10.1007/978-3-319-61566-0_71

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61565-3

  • Online ISBN: 978-3-319-61566-0

  • eBook Packages: EngineeringEngineering (R0)

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