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Renewable and Cooling Aware Workload Management for Sustainable Data Centers

Liu, Zhenhua and Cheng, Yuan and Bash, Cullen and Wierman, Adam and Gmach, Daniel and Wang, Zhikui and Marwah, Manish and Hyser, Chris (2012) Renewable and Cooling Aware Workload Management for Sustainable Data Centers. ACM SIGMETRICS Performance Evaluation Review, 40 (1). pp. 175-186. ISSN 0163-5999. doi:10.1145/2318857.2254779.

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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.

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Additional Information:© 2012 ACM, Inc. SIGMETRICS '12. Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems, Pages 175-186. This work is done during Zhenhua Liu’s internship at HP Labs. Zhenhua Liu and Adam Wierman are partly supported by NSF grant CNS 0846025 and DoE grant DE-EE0002890. We are grateful to many members of Sustainable Ecosystem Research Group at HP Labs. Chandrakant Patel has provided great support and guidance at various stages of this work. Niru Kumari provided valuable information on chiller cooling models. Martin Arlitt, Amip Shah, Sergey Blagodurov and Alan McReynolds offered helpful feedback. We also thank the anonymous reviewers and our shepherd, Christopher Stewart, for their valuable comments and help.
Funding AgencyGrant Number
Department of Energy (DOE)DE-EE0002890
Subject Keywords:sustainable data center; renewable energy; demand shaping; scheduling; cooling optimization
Issue or Number:1
Record Number:CaltechAUTHORS:20130108-115043744
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:36237
Deposited On:08 Jan 2013 22:27
Last Modified:09 Nov 2021 23:20

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