TY - GEN
T1 - Renewable and cooling aware workload management for sustainable data centers
AU - Liu, Zhenhua
AU - Chen, Yuan
AU - Bash, Cullen
AU - Wierman, Adam
AU - Gmach, Daniel
AU - Wang, Zhikui
AU - Marwah, Manish
AU - Hyser, Chris
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - cooling optimization
KW - demand shaping
KW - renewable energy
KW - scheduling
KW - sustainable data center
UR - https://www.scopus.com/pages/publications/84864700984
U2 - 10.1145/2254756.2254779
DO - 10.1145/2254756.2254779
M3 - Conference contribution
AN - SCOPUS:84864700984
SN - 9781450310970
T3 - Performance Evaluation Review
SP - 175
EP - 186
BT - SIGMETRICS/Performance 2012 - Proceedings of the 2012 ACM SIGMETRICS/Performance, Joint International Conference on Measurement and Modeling of Computer Systems
T2 - 12th Joint International Conference on Measurement and Modeling of Computer Systems, ACM SIGMETRICS/Performance 2012
Y2 - 11 June 2012 through 15 June 2012
ER -