72. UTILIZING GREEN ENERGY PREDICTION TO SCHEDULE MIXED BATCH AND SERVICE JOBS IN DATA CENTERS

Department: Computer Science & Engineering
Research Institute Affiliation: Center for Networked Systems (CNS)
Faculty Advisor(s): Tajana Simunic-Rosing
Award(s): Honorable Mention

Primary Student
Name: Jagannathan Venkatesh
Email: jvenkate@ucsd.edu
Phone: 865-566-8377
Grad Year: 2014

Abstract
As brown energy costs grow, renewable energy becomes more widely used. Previous work 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 poster we design an adaptive data center job scheduler which utilizes short-term prediction of solar and wind energy production. This enables us to scale the number of jobs to the expected energy availability, thus reducing the number of cancelled jobs by 4x, improving green energy usage efficiency by 3x over utilizing the available green energy immediately, and providing over 90% green energy efficiency.

Related Links:

  1. http://dl.acm.org/citation.cfm?id=2039257

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