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A Platform for Edge Computing Based on Raspberry Pi Clusters

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Data Analytics (BICOD 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10365))

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Abstract

Small credit-card-sized single-board computers, such as the Raspberry Pi, are becoming ever more popular in areas unrelated to the education of children, for which they were originally intended. So far, these computers have mainly been used in small-scale projects focusing very often on hardware aspects. We want to take single-board computer architectures a step further by showing how to deploy part of an orchestration platform (OpenStack Swift) on a Raspberry Pi cluster to make it a useful platform for more sophisticated data collection and analysis applications located at the edge of a cloud. Our results illustrate that this is indeed possible, but that there are still shortcomings in terms of performance. Nevertheless, with the next generation of small single-board computers that have been introduced recently, we believe that this is a viable approach for certain application domains, such as private clouds or edge computing in harsh environments.

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Notes

  1. 1.

    http://coen.boisestate.edu/ece/raspberry-pi/.

  2. 2.

    Available at https://github.com/unibz-bobo.

  3. 3.

    Swift distinguishes four different types of nodes: account, container, object, and proxy nodes.

  4. 4.

    http://www.broadcom.com/docs/support/videocore/VideoCoreIV-AG100-R.pdf.

  5. 5.

    http://www.jeffgeerling.com/blogs/jeff-geerling/getting-gigabit-networking.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano, Italy

    Lorenzo Miori, Julian Sanin & Sven Helmer

Authors
  1. Lorenzo Miori
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  2. Julian Sanin
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  3. Sven Helmer
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Corresponding author

Correspondence to Sven Helmer .

Editor information

Editors and Affiliations

  1. Birkbeck, University of London, London, United Kingdom

    Andrea Calì

  2. Birkbeck, University of London, London, United Kingdom

    Peter Wood

  3. Birkbeck, University of London, London, United Kingdom

    Nigel Martin

  4. Birkbeck, University of London, London, United Kingdom

    Alexandra Poulovassilis

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Miori, L., Sanin, J., Helmer, S. (2017). A Platform for Edge Computing Based on Raspberry Pi Clusters. In: Calì, A., Wood, P., Martin, N., Poulovassilis, A. (eds) Data Analytics. BICOD 2017. Lecture Notes in Computer Science(), vol 10365. Springer, Cham. https://doi.org/10.1007/978-3-319-60795-5_16

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  • DOI: https://doi.org/10.1007/978-3-319-60795-5_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60794-8

  • Online ISBN: 978-3-319-60795-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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