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GreenSlot: Scheduling Energy Consumption in Green Datacenters
Technical documentation   Open access

GreenSlot: Scheduling Energy Consumption in Green Datacenters

Inigo Goiri, Kien Le, Md E. Haque, Ryan Beauchea, Thu Nguyen, Jordi Guitart, Jordi Torres and Ricardo Bianchini
Rutgers University
2011
DOI:
https://doi.org/10.7282/T3XK8K29

Abstract

Green energy Energy-aware job scheduling Datacenters Clean energy Data libraries
In this paper, we propose GreenSlot, a parallel batch job scheduler for 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 brown energy must be used to avoid deadline violations, the scheduler selects times when brown electricity is cheap. Our results for production scientific workloads demonstrate that GreenSlot can increase green energy consumption by up to 117% and decrease energy cost by up to 39%, compared to EASY backfilling. 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.
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