ABSTRACT
The sharp rise in energy usage in data centers, fueled by increased IT workload and high server density, and coupled with a concomitant increase in the cost and volatility of the energy supply, have triggered urgent calls to improve data center energy efficiency. In response, researchers have developed energy-aware IT systems that slow or shut down servers without sacrificing performance objectives. Several authors have shown that utility functions are a natural and advantageous framework for self-management of servers to joint power and performance objectives. We demonstrate that utility functions are a similarly powerful framework for flexibly managing entire data centers to joint power and temperature objectives. After showing how utility functions can capture a wide range of objectives and tradeoffs that an operator might wish to specify, we illustrate the resulting range in behavior and energy savings using experimental results from a real data center that is cooled by two computer room air-conditioning (CRAC) units equipped with variable-speed fan drives.
- ASHRAE Publication. 2008 ASHRAE environment guidelines for datacom equipment: Expanding the recommended environmental envelope. Technical report, American Society of Heating, Regrigerating and Air-Conditioning Engineers, Inc., 2008.Google Scholar
- R. Ayoub and T. Rosing. Cool and save: cooling aware dynamic workload scheduling in multi-socket cpu systems. In Proceedings of ASPDAC 2010, 2010. Google ScholarDigital Library
- C. E. Bash, C. D. Patel, and R. K. Sharma. Dynamic thermal management of air cooled data centers. In Proc. of the 10th Int'l Conf. on Thermal and Thermomechanical Phenomena in Electronics Systems (ITHERM), pages 445--452, San Diego, CA, May 2006.Google ScholarCross Ref
- T. Boucher, D. Auslander, C. Bash, C. Federspiel, and C. Patel. Viability of dynamic cooling control in a data center environment. In Proc. of the 9th Int'l Conf. on Thermal and Thermomechanical Phenomena in Electronics Systems (ITHERM), pages 445--452, Las Vegas, NV, August 2004.Google ScholarCross Ref
- R. G. Brown and J. Hughes. Skimp on server room air conditioning? At your peril. http://www.openxtra.co.uk/articles/skimp-server-room-ac, 2009.Google Scholar
- J. S. Chase, D. C. Anderson, P. N. Thakar, A. N. Vahdat, and R. P. Doyle. Managing energy and server resources in hosting centers. In Proc. 18th Symposium on Operating Systems Principles (SOSP), 2001. Google ScholarDigital Library
- D. Chess, G. Pacifici, M. Spreitzer, M. Steinder, A. Tantawi, and I. Whalley. Experience with collaborating managers: Node group manager and provisioning manager. In Proc. 2nd Int'l Conference on Autonomic Computing, 2005. Google ScholarDigital Library
- G. Cole. Estimating drive reliability in desktop computers and consumer electronics systems. Technical report, Seagate TP-338.1, 2000.Google Scholar
- Gartner Inc. Gartner Says 50 Percent of Data Centers Will Have Insufficient Power and Cooling Capacity by 2008. Press Release, November 29, 2006.Google Scholar
- H. Hamann, T. van Kessel, M. Iyengar, J.-Y. Chung, W. Hirt, M. A. Schappert, A. Claassen, J. M. Cook, W. Min, Y. Amemiya, V. Lopez, J. A. Lacey, and M. O'Boyle. Uncovering energy efficiency opportunities in data centers. IBM Journal of Research and Development, 53(3):10:1--10:12, 2009. Google ScholarDigital Library
- H. F. Hamann, M. Schappert, M. Iyengar, T. van Kessel, and A. Claassen. Methods and techniques for measuring and improving data center best practices. In Proceedings of 11th Intersociety Conference on Thermomechanical Phenomena in Electronic Systems, pages 1146--1152, May 2008.Google ScholarCross Ref
- J. O. Kephart, H. Chan, R. Das, D. W. Levine, G. Tesauro, F. L. R. III, and C. Lefurgy. Coordinating multiple autonomic managers to achieve specified power-performance tradeoffs. In Proc. 4th Int'l Conf. on Autonomic Computing, pages 24--33, 2007. Google ScholarDigital Library
- J. O. Kephart and D. M. Chess. The vision of autonomic computing. Computer, 36(1):41--52, 2003. Google ScholarDigital Library
- J. O. Kephart and R. Das. Achieving self-management via utility functions. IEEE Internet Computing, 11:40--48, 2007. Google ScholarDigital Library
- B. Khargharia, S. Hariri, and M. S. Yousif. Autonomic power and performance management for computing systems. In Proc. Third Int'l Conference on Autonomic Computing, pages 145--154, 2006. Google ScholarDigital Library
- J. G. Koomey. Estimating total power consumption by servers in the U.S. and the world. http://enterprise.amd.com/Downloads/svrpwrusecompletefinal.pdf, 2007.Google Scholar
- V. Kumar, B. Cooper, and K. Schwan. Distributed stream management using utility-driven self-adaptive middleware. In Proc. 2nd Int'l Conference on Autonomic Computing, pages 3--14, 2005. Google ScholarDigital Library
- D. Kusic, J. O. Kephart, J. E. Hanson, N. Kandasamy, and G. Jiang. Power and performance management of virtualized computing environments via lookahead control. In Proc. Fifth Int'l Conference on Autonomic Computing, pages 3--12, 2008. Google ScholarDigital Library
- J. Moore, J. Chase, and P. Ranganathan. Making scheduling "cool": Temperature-aware workload placement in data centers. In Proc. 2005 USENIX Annual Technical Conference (USENIX '05), 2005. Google ScholarDigital Library
- R. Nathuji, C. Isci, and E. Gorbatov. Exploiting platform heterogeneity for power efficient data centers. In Proc. Fourth Int'l Conference on Autonomic Computing, pages 5--14, Washington, DC, USA, 2007. IEEE Computer Society. Google ScholarDigital Library
- L. Parolini, B. Sinopoli, and B. H. Krogh. Reducing data center energy consumption via coordinated cooling and load management. HotPower S08: Workshop on Power Aware Computing and Systems, December 2008. Google ScholarDigital Library
- C. Patel, C. Bash, and C. Belady. Computational fluid dynamics modeling of high compute density data centers to assure system inlet air specifications. Proc. ASME Int'l Electronic Packaging Technical Conference and Exhibition, 2001.Google Scholar
- C. Patel, C. Bash, R. Sharma, A. Beitelmal, and R. Friedrich. Smart cooling of datacenters. Proc. IPACK'03 -- The PacificRim/ASME Int'l Electronics Packaging Tech. Conference and Exhibition, July 2003.Google Scholar
- E. Pinheiro, W.-D. Weber, and L. A. Barroso. Failure trends in a large disk drive population. In Proc. of the 5th USENIX Conference on File and Storage Technologies (FAST07), pages 17--29, 2007. Google ScholarDigital Library
- N. Rasmussen. Electrical efficiency modeling of data centers, document 113 version 1, 2006.Google Scholar
- R. Sharma, C. Bash, C. Patel, R. Friedrich, and J. Chase. Balance of power: Dynamic thermal management for internet data centers. IEEE Internet Computing, 9(1):42--49, January 2005. Google ScholarDigital Library
- H. W. Stanford III. HVAC Water Chillers and Cooling towers: Fundamentals, Application, and Operation. Dekker Mechanical Engineering, 2003.Google Scholar
- G. Tesauro, R. Das, W. E. Walsh, and J. O. Kephart. Utility-function-driven resource allocation in autonomic systems. In 2nd Int'l Conference on Autonomic Computing, 2005. Google ScholarDigital Library
- W. E. Walsh, G. Tesauro, J. O. Kephart, and R. Das. Utility functions in autonomic systems. In First Int'l Conference on Autonomic Computing, 2004. Google ScholarDigital Library
Index Terms
- Utility-function-driven energy-efficient cooling in data centers
Recommendations
A unified approach to coordinated energy-management in data centers
CNSM '11: Proceedings of the 7th International Conference on Network and Services ManagementEnergy consumption has become a critical issue for data centers, triggered by the rise in energy costs, volatility in the supply and demand of energy and the widespread proliferation of power-hungry information technology (IT) equipment. In response, ...
Energy Efficient Free Cooling System for Data Centers
CLOUDCOM '11: Proceedings of the 2011 IEEE Third International Conference on Cloud Computing Technology and ScienceA data center is a facility used to keep computer related equipments. It is estimated that heat production rate of the data center is doubled in every two years and hence the inevitability of the cooling system gets increased. In due course power ...
Trade-off between Performance and Energy Management in Autonomic and Green Data Centers
NISS '19: Proceedings of the 2nd International Conference on Networking, Information Systems & SecurityIn recent years, energy optimization of cloud data centers got important consideration since data centers in activity frequently expend huge energy rates. In fact, the expanding processing capacity of data centers and its complexity, increases ...
Comments