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Lifetime-Aware Cloud Data Centers: Models and Performance Evaluation

Author

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  • Luca Chiaraviglio

    (Department of Information, Electronics and Telecommunications, University of Rome Sapienza, Rome 00185, Italy)

  • Antonio Cianfrani

    (Department of Information, Electronics and Telecommunications, University of Rome Sapienza, Rome 00185, Italy)

  • Marco Listanti

    (Department of Information, Electronics and Telecommunications, University of Rome Sapienza, Rome 00185, Italy)

  • William Liu

    (Department of Information Technology and Software Engineering, School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, 55 Wellesley Street East, Auckland 1010, New Zealand)

  • Marco Polverini

    (Department of Information, Electronics and Telecommunications, University of Rome Sapienza, Rome 00185, Italy)

Abstract

We present a model to evaluate the server lifetime in cloud data centers (DCs). In particular, when the server power level is decreased, the failure rate tends to be reduced as a consequence of the limited number of components powered on. However, the variation between the different power states triggers a failure rate increase. We therefore consider these two effects in a server lifetime model, subject to an energy-aware management policy. We then evaluate our model in a realistic case study. Our results show that the impact on the server lifetime is far from negligible. As a consequence, we argue that a lifetime-aware approach should be pursued to decide how and when to apply a power state change to a server.

Suggested Citation

  • Luca Chiaraviglio & Antonio Cianfrani & Marco Listanti & William Liu & Marco Polverini, 2016. "Lifetime-Aware Cloud Data Centers: Models and Performance Evaluation," Energies, MDPI, vol. 9(6), pages 1-17, June.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:6:p:470-:d:72307
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    References listed on IDEAS

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    1. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 4.
    2. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 3.
    3. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 2.
    4. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 2.
    5. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 4.
    6. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 3.
    7. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 1.
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    Citations

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    Cited by:

    1. Maria Avgerinou & Paolo Bertoldi & Luca Castellazzi, 2017. "Trends in Data Centre Energy Consumption under the European Code of Conduct for Data Centre Energy Efficiency," Energies, MDPI, vol. 10(10), pages 1-18, September.
    2. Xiao-Fang Liu & Zhi-Hui Zhan & Jun Zhang, 2017. "An Energy Aware Unified Ant Colony System for Dynamic Virtual Machine Placement in Cloud Computing," Energies, MDPI, vol. 10(5), pages 1-15, May.
    3. Yeliang Qiu & Congfeng Jiang & Yumei Wang & Dongyang Ou & Youhuizi Li & Jian Wan, 2019. "Energy Aware Virtual Machine Scheduling in Data Centers," Energies, MDPI, vol. 12(4), pages 1-21, February.
    4. Pio Alessandro Lombardi & Kranthi Ranadheer Moreddy & André Naumann & Przemyslaw Komarnicki & Carmine Rodio & Sergio Bruno, 2019. "Data Centers as Active Multi-Energy Systems for Power Grid Decarbonization: A Technical and Economic Analysis," Energies, MDPI, vol. 12(21), pages 1-14, November.

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