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International Conference on Objects, Components, Models and Patterns

TOOLS 2019: Software Technology: Methods and Tools pp 313–325Cite as

Distributed Computing System on a Smartphones-Based Network

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Part of the Lecture Notes in Computer Science book series (LNPSE,volume 11771)

Abstract

The number of Smartphone users in the world is expected to pass the five billion in 2019. The major credit for this exponential growth is the competition between Smartphones manufacturing companies and increasing Internet availability in the world. Processing power considered to be one of the most important features in Smartphones and it is evolving year by year. Until now, building a distributed computing system done exclusively using PCs and other server infrastructure. In this paper we will propose a new architecture for a distributed computing system consists of a network of Smartphones and use their computation power to execute machine learning models on each Smartphone. As proof of concept, our solution will provide a stable layer to execute large data-sets using common machine learning algorithms such as Linear Regression.

Keywords

  • Distributed system
  • Computation power
  • JS-Regression

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Author information

Authors and Affiliations

  1. Innopolis University, Innopolis, Russia

    Hamza Salem

Authors
  1. Hamza Salem
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Correspondence to Hamza Salem .

Editor information

Editors and Affiliations

  1. Innopolis University, Innopolis, Russia

    Manuel Mazzara

  2. IUT de Blagnac , Blagnac, France

    Dr. Jean-Michel Bruel

  3. Innopolis University, Innopolis, Russia

    Prof. Bertrand Meyer

  4. Ivannikov Institute for System Programming, Russian Academy of Sciences, Moscow, Russia

    Alexander Petrenko

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Salem, H. (2019). Distributed Computing System on a Smartphones-Based Network. In: Mazzara, M., Bruel, JM., Meyer, B., Petrenko, A. (eds) Software Technology: Methods and Tools. TOOLS 2019. Lecture Notes in Computer Science(), vol 11771. Springer, Cham. https://doi.org/10.1007/978-3-030-29852-4_26

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  • DOI: https://doi.org/10.1007/978-3-030-29852-4_26

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