Utilizing Green Energy Prediction to Schedule Mixed Batch and Service Jobs in Data Centers

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Provided by: Association for Computing Machinery
Topic: Big Data
Format: PDF
As brown energy costs grow, renewable energy becomes more widely used. Previous paper focused on using immediately available green energy to supplement the non-renewable, or brown energy at the cost of canceling and rescheduling jobs whenever the green energy availability is too low. In this paper, the authors design an adaptive data center job scheduler which utilizes short term prediction of solar and wind energy production. This enables the user to scale the number of jobs to the expected energy availability, thus reducing the number of cancelled jobs by 4x and improving green energy usage efficiency by 3x over just utilizing the immediately available green energy.
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