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Matching Renewable Energy Supply and Demand in Green Datacenters

Author

Listed:
  • Goiri, Inigo
  • Le, Kien
  • Beauchea, Ryan
  • Guitart, Jordi

Abstract

In this paper, we propose GreenSlot, a scheduler for parallel batch jobs in a datacenter powered by a photovoltaic solar array and the electrical grid (as a backup). GreenSlot predicts the amount of solar energy that will be available in the near future, and schedules the workload to maximize the green energy consumption while meeting the jobs’ deadlines. If grid energy must be used to avoid deadline violations, the scheduler selects times when it is cheap. Our results for both scientific computing workloads and data processing workloads demonstrate that GreenSlot can increase solar energy consumption by up to 117% and decrease energy cost by up to 39%, compared to conventional schedulers. Based on these positive results, we conclude that green datacenters and green-energy-aware scheduling can have a significant role in building a more sustainable IT ecosystem.

Suggested Citation

  • Goiri, Inigo & Le, Kien & Beauchea, Ryan & Guitart, Jordi, 2014. "Matching Renewable Energy Supply and Demand in Green Datacenters," MPRA Paper 104507, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:104507
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    File URL: https://mpra.ub.uni-muenchen.de/104507/1/MPRA_paper_104507.pdf
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    More about this item

    Keywords

    Green energy; energy-aware job scheduling; datacenters;
    All these keywords.

    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General

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