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PLDAD—An Algorihm to Reduce Data Center Energy Consumption

Author

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  • Joao Ferreira

    (Informatics Center, Federal University of Pernambuco, Recife 50740-560, Brazil
    Federal University of Pernambuco, Informatics Center, Cidade Universitária-50740-560-Recife/PE-Brazil.
    These authors contributed equally to this work.)

  • Gustavo Callou

    (Departament of Computing, Federal Rural University of Pernambuco, Recife 52171-900, Brazil
    These authors contributed equally to this work.)

  • Dietmar Tutsch

    (Automation Technologye, Bergische Universität Wuppertal, D-42119 Wuppertal, Germany
    These authors contributed equally to this work.)

  • Paulo Maciel

    (Informatics Center, Federal University of Pernambuco, Recife 50740-560, Brazil
    Federal University of Pernambuco, Informatics Center, Cidade Universitária-50740-560-Recife/PE-Brazil.
    These authors contributed equally to this work.)

Abstract

Due to the demands of new technologies such as social networks, e-commerce and cloud computing, more energy is being consumed in order to store all the produced data. While these new technologies require high levels of availability, a reduction in the cost and environmental impact is also expected. The present paper proposes a power balancing algorithm (power load distribution algorithm-depth (PLDA-D)) to optimize the energy distribution of data center electrical infrastructures. The PLDA-D is based on the Bellman and Ford–Fulkerson flow algorithms that analyze energy-flow models (EFM). EFM computes the power efficiency, sustainability and cost metrics of data center infrastructures. To demonstrate the applicability of the proposed strategy, we present a case study that analyzes four power infrastructures. The results obtained show about a 3.8% reduction in sustainability impact and operational costs.

Suggested Citation

  • Joao Ferreira & Gustavo Callou & Dietmar Tutsch & Paulo Maciel, 2018. "PLDAD—An Algorihm to Reduce Data Center Energy Consumption," Energies, MDPI, vol. 11(10), pages 1-24, October.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2821-:d:176810
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    References listed on IDEAS

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    1. Gustavo Callou & João Ferreira & Paulo Maciel & Dietmar Tutsch & Rafael Souza, 2014. "An Integrated Modeling Approach to Evaluate and Optimize Data Center Sustainability, Dependability and Cost," Energies, MDPI, vol. 7(1), pages 1-40, January.
    2. João Ferreira & Gustavo Callou & Paulo Maciel, 2013. "A Power Load Distribution Algorithm to Optimize Data Center Electrical Flow," Energies, MDPI, vol. 6(7), pages 1-22, July.
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    Cited by:

    1. Syed Naeem Haider & Qianchuan Zhao & Xueliang Li, 2020. "Cluster-Based Prediction for Batteries in Data Centers," Energies, MDPI, vol. 13(5), pages 1-17, March.
    2. Francisco G. Montoya & Raúl Baños & Alfredo Alcayde & Francisco Manzano-Agugliaro, 2019. "Optimization Methods Applied to Power Systems," Energies, MDPI, vol. 12(12), pages 1-8, June.

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