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International Conference on Future Data and Security Engineering

FDSE 2017: Future Data and Security Engineering pp 3–22Cite as

Eco Models of Distributed Systems

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10646))

Abstract

It is critical to reduce electric energy consumed in information systems, especially servers in scalable clusters, in order to realize eco society. In this paper, we take the macro-level approach to reducing the electric energy consumption of servers. Here, we aim at reducing the total energy consumed by a server to perform application processes. First, we discuss power consumption models which give electric power to be consumed by a server to perform application processes. We also discuss computation models of a server which give execution time of application processes. Based on the models, we discuss algorithms to select an energy-efficient server to perform an application process issued by a client. We also discuss algorithms to migrate processes on host servers to more energy-efficient servers by using virtual machines.

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Acknowledgements

This work was supported by JSPS KAKENHI grant number 15H0295.

Author information

Authors and Affiliations

  1. Hosei University, Tokyo, Japan

    Dilawaer Duolikun, Ryo Watanabe & Makoto Takizawa

Authors
  1. Dilawaer Duolikun
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  2. Ryo Watanabe
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  3. Makoto Takizawa
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Corresponding author

Correspondence to Makoto Takizawa .

Editor information

Editors and Affiliations

  1. HCMC University of Technology, Ho Chi Minh City, Vietnam

    Tran Khanh Dang

  2. Johannes Kepler University Linz, Linz, Austria

    Roland Wagner

  3. Johannes Kepler University Linz, Linz, Austria

    Josef Küng

  4. Ho Chi Minh City University of Technolog , Ho Chi Minh City, Vietnam

    Nam Thoai

  5. Hosei University, Koganei, Tokyo, Japan

    Makoto Takizawa

  6. University of Vienna, Vienna, Austria

    Erich J. Neuhold

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Duolikun, D., Watanabe, R., Takizawa, M. (2017). Eco Models of Distributed Systems. In: Dang, T., Wagner, R., Küng, J., Thoai, N., Takizawa, M., Neuhold, E. (eds) Future Data and Security Engineering. FDSE 2017. Lecture Notes in Computer Science(), vol 10646. Springer, Cham. https://doi.org/10.1007/978-3-319-70004-5_1

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  • DOI: https://doi.org/10.1007/978-3-319-70004-5_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70003-8

  • Online ISBN: 978-3-319-70004-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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