Renewable and cooling aware workload management for sustainable data centers

  • Authors:

  • Zhenhua Liu;Yuan Chen;Cullen Bash;Adam Wierman;Daniel Gmach;Zhikui Wang;Manish Marwah;Chris Hyser

  • Affiliations:

  • California Institute of Technology, Pasadena, CA, USA;HP Labs, Palo Alto, CA, USA;HP Labs, Palo Alto, CA, USA;California Institute of Technology, Pasadena, CA, USA;HP Labs, Palo Alto, CA, USA;HP Labs, Palo Alto, CA, USA;HP Labs, Palo Alto, CA, USA;HP Labs, Palo Alto, CA, USA

  • Venue:
  • Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
  • Year:
  • 2012

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Abstract

Recently, the demand for data center computing has surged, increasing the total energy footprint of data centers worldwide. Data centers typically comprise three subsystems: IT equipment provides services to customers; power infrastructure supports the IT and cooling equipment; and the cooling infrastructure removes heat generated by these subsystems. This work presents a novel approach to model the energy flows in a data center and optimize its operation. Traditionally, supply-side constraints such as energy or cooling availability were treated independently from IT workload management. This work reduces electricity cost and environmental impact using a holistic approach that integrates renewable supply, dynamic pricing, and cooling supply including chiller and outside air cooling, with IT workload planning to improve the overall sustainability of data center operations. Specifically, we first predict renewable energy as well as IT demand. Then we use these predictions to generate an IT workload management plan that schedules IT workload and allocates IT resources within a data center according to time varying power supply and cooling efficiency. We have implemented and evaluated our approach using traces from real data centers and production systems. The results demonstrate that our approach can reduce both the recurring power costs and the use of non-renewable energy by as much as 60% compared to existing techniques, while still meeting the Service Level Agreements.