Skip to main content
SpringerLink
Log in
Book cover

Handbook on Data Centers pp 915–943Cite as

Thermal Modeling and Management of Storage Systems in Data Centers

  • Chapter
  • First Online:

Abstract

Thermal modeling and management techniques have been widely investigated in recent years. Prior studies show thermal management could increase energy efficiency of data centers. The thermal impacts of CPUs on data storage have been extensively studied; however, disk thermal models are still in their infancy. In our study, we aim at building thermal models that take into account both CPUs and disks. We propose an approach to developing thermal models to estimate a data node’s outlet temperature based on its CPU and disk activities. Integrating our thermal model into an energy consumption model, we can evaluate the total energy cost of a data center. We apply our models to study the impact of various thermal management strategies on energy efficiency.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    ftp://ftp.ncbi.nih.gov/genomes/H_sapiens.

References

  1. P. Thibodeau, “Data centers use 2 % of U.S. energy, below forecast,” 2011. [Online]. Available: http://blogs.computerworld.com/18738/data_centers_use_2_of_u_s_energy_below_forecast.

  2. IDC, “Annual it spending by Western European utilities to reach 12.7 billion by 2017, says IDC energy insights,” 2013. [Online]. Available: http://www.idc-ei.com/getdoc.jsp?containerId=prUS24251013.

  3. M. Baile, “The economics of virtualization: Moving toward an application-based cost mode,” 2009. [Online]. Available: http://www.vmware.com/files/pdf/Virtualization-application-based-cost-model-WP-EN.pdf.

  4. J. He, “Datacenter power management: Power consumption trend,” 2008. [Online]. Available: http://communities.intel.com/community/datastack/blog/2008/02/20/datacenter-power-management-power-consumption-trend.

  5. Statista, “Number of monthly active Facebook users worldwide from 3rd quarter 2008 to 2nd quarter 2013 (in millions),” 2013. [Online]. Available: http://www.statista.com/statistics/264810/number-of-monthly-active-facebook-users-worldwide/.

  6. “What happens on Facebook in each day?” 2012. [Online]. Available: http://visual.ly/what-happens-facebook-each-day.

  7. “Whetstone,” http://www.netlib.org/benchmark/whetstones.

  8. J. Katcher, “Postmark: A new file system benchmark,” System, no. 3022, pp. 1–8, 1997. [Online]. Available: http://www.netapp.com/tech_library/3022.html.

  9. P. Jones, “Industry census 2012: Emerging data center markets,” 2012. [Online]. Available: http://www.datacenterdynamics.com/blogs/industry-census-2012-emerging-data-center-markets.

  10. Y. Lee and A. Zomaya, “EnglishEnergy efficient utilization of resources in cloud computing systems,” EnglishThe Journal of Supercomputing, vol. 60, no. 2, pp. 268–280, 2012. [Online]. Available: http://dx.doi.org/10.1007/s11227-010-0421-3.

  11. Z. Liu, Y. Chen, C. Bash, A. Wierman, D. Gmach, Z. Wang, M. Marwah, and C. Hyser, “Renewable and cooling aware workload management for sustainable data centers,” SIGMETRICS Perform. Eval. Rev., vol. 40, no. 1, pp. 175–186, Jun. 2012. [Online]. Available: http://doi.acm.org/10.1145/2318857.2254779.

  12. M. AlAssaf, X. Jiang, M. Abid, and X. Qin, “EnglishEco-storage: A hybrid storage system with energy-efficient informed prefetching,” EnglishJournal of Signal Processing Systems, vol. 72, no. 3, pp. 165–180, 2013. [Online]. Available: http://dx.doi.org/10.1007/s11265-013-0784-9.

  13. D. Colarelli and D. Grunwald, “Massive arrays of idle disks for storage archives,” in Proceedings of the 2002 ACM/IEEE conference on Supercomputing, ser. Supercomputing '02. Los Alamitos, CA, USA: IEEE Computer Society Press, 2002, pp. 1–11. [Online]. Available: http://dl.acm.org/citation.cfm?id=762761.762819.

  14. E. Pinheiro and R. Bianchini, “Energy conservation techniques for disk array-based servers,” in Proceedings of the 18th annual international conference on Supercomputing, ser. ICS '04. New York, NY, USA: ACM, 2004, pp. 68–78. [Online]. Available: http://doi.acm.org/10.1145/1006209.1006220.

  15. A. Beloglazov and R. Buyya, “Energy efficient resource management in virtualized cloud data centers,” in Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, ser. CCGRID '10. Washington, DC, USA: IEEE Computer Society, 2010, pp. 826–831. [Online]. Available: http://dx.doi.org/10.1109/CCGRID.2010.46

  16. A. Beloglazov, J. Abawajy, and R. Buyya, “Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing,” Future Generation Computer Systems, vol. 28, no. 5, pp. 755–768, 2012, <ce:title>Special Section: Energy efficiency in large-scale distributed systems</ce:title>. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0167739X11000689.

  17. B. Aksanli, J. Venkatesh, L. Zhang, and T. Rosing, “Utilizing green energy prediction to schedule mixed batch and service jobs in data centers,” SIGOPS Oper. Syst. Rev., vol. 45, no. 3, pp. 53–57, Jan. 2012. [Online]. Available: http://doi.acm.org/10.1145/2094091.2094105.

  18. “7 strategies to optimize data centre cooling,” http://www.biztechmagazine.com/article/2011/01/keep-your-cool/.

  19. J. Moore, J. Chase, P. Ranganathan, and R. Sharma, “Making scheduling “cool”: temperature-aware workload placement in data centers,” in Proceedings of the annual conference on USENIX Annual Technical Conference, ser. ATEC '05. Berkeley, CA, USA: USENIX Association, 2005, pp. 5–5. [Online]. Available: http://dl.acm.org/citation.cfm?id=1247360.1247365.

  20. Q. Tang, S. Gupta, and G. Varsamopoulos, “Thermal-aware task scheduling for data centers through minimizing heat recirculation,” in Cluster Computing, 2007 IEEE International Conference on, sept. 2007, pp. 129–138.

    Google Scholar 

  21. Q. Tang, S. K. S. Gupta, and G. Varsamopoulos, “Energy-efficient thermal-aware task scheduling for homogeneous high-performance computing data centers: A cyber-physical approach,” IEEE Trans. Parallel Distrib. Syst., vol. 19, no. 11, pp. 1458–1472, Nov. 2008. [Online]. Available: http://dx.doi.org/10.1109/TPDS.2008.111.

  22. K. Skadron, M. R. Stan, K. Sankaranarayanan, W. Huang, S. Velusamy, and D. Tarjan, “Temperature-aware microarchitecture: Modeling and implementation,” ACM Trans. Archit. Code Optim., vol. 1, no. 1, pp. 94–125, Mar. 2004. [Online]. Available: http://doi.acm.org/10.1145/980152.980157.

  23. P. Eibeck and D. Cohen, “Modeling thermal characteristics of a fixed disk drive,” Components, Hybrids, and Manufacturing Technology, IEEE Transactions on, vol. 11, no. 4, pp. 566–570, dec 1988.

    Google Scholar 

  24. C. Tan, J. Yang, J. Mou, and E. Ong, “Three dimensional finite element model for transient temperature prediction in hard disk drive,” in Magnetic Recording Conference, 2009. APMRC '09. Asia-Pacific, jan. 2009, pp. 1–2.

    Google Scholar 

  25. S. Gurumurthi, A. Sivasubramaniam, and V. K. Natarajan, “Disk drive roadmap from the thermal perspective: A case for dynamic thermal management,” SIGARCH Comput. Archit. News, vol. 33, no. 2, pp. 38–49, May 2005. [Online]. Available: http://doi.acm.org/10.1145/1080695.1069975.

  26. Y. Kim, S. Gurumurthi, and A. Sivasubramaniam, “Understanding the performance-temperature interactions in disk i/o of server workloads,” in High-Performance Computer Architecture, 2006. The Twelfth International Symposium on, feb. 2006, pp. 176–186.

    Google Scholar 

  27. X. Jiang, M. Alghamdi, J. Zhang, M. Assaf, X. Ruan, T. Muzaffar, and X. Qin, “Thermal modeling and analysis of storage systems,” in Performance Computing and Communications Conference (IPCCC), 2012 IEEE 31st International, 2012, pp. 31–40.

    Google Scholar 

  28. X. Jiang, M. AlAssaf, J. Zhang, M. Alghamdi, X. Ruan, T. Muzaffar, and X. Qin, “EnglishThermal modeling of hybrid storage clusters,” EnglishJournal of Signal Processing Systems, vol. 72, no. 3, pp. 181–196, 2013. [Online]. Available: http://dx.doi.org/10.1007/s11265-013-0787-6.

  29. J. Lin, H. Zheng, Z. Zhu, and Z. Zhang, “Thermal modeling and management of dram systems,” IEEE Transactions on Computers, vol. 99, no. PrePrints, 2012.

    Google Scholar 

  30. A. Shah, V. Carey, C. Bash, C. Patel, and R. Sharma, “EnglishExergy analysis of data center thermal management systems,” in EnglishEnergy Efficient Thermal Management of Data Centers, Y. Joshi and P. Kumar, Eds. Springer US, 2012, pp. 383–446. [Online]. Available: http://dx.doi.org/10.1007/978-1-4419-7124-1_9.

  31. R. Sharma, C. Bash, C. Patel, R. Friedrich, and J. Chase, “Balance of power: dynamic thermal management for internet data centers,” Internet Computing, IEEE, vol. 9, no. 1, pp. 42–49, jan.-feb. 2005.

    Google Scholar 

  32. O. Sarood, A. Gupta, and L. Kale, “Temperature aware load balancing for parallel applications: Preliminary work,” in Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), 2011 IEEE International Symposium on, may 2011, pp. 796–803.

    Google Scholar 

  33. O. Sarood and L. V. Kale, “A `cool' load balancer for parallel applications,” in Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis, ser. SC '11. New York, NY, USA: ACM, 2011, pp. 21:1–21:11. [Online]. Available: http://doi.acm.org/10.1145/2063384.2063412.

  34. J. Li, M. Qiu, J.-W. Niu, L. T. Yang, Y. Zhu, and Z. Ming, “Thermal-aware task scheduling in 3d chip multiprocessor with real-time constrained workloads,” ACM Trans. Embed. Comput. Syst., vol. 12, no. 2, pp. 24:1–24:22, Feb. 2013. [Online]. Available: http://doi.acm.org/10.1145/2423636.2423642.

  35. J. Srinivasan and S. V. Adve, “Predictive dynamic thermal management for multimedia applications,” in Proceedings of the 17th annual international conference on Supercomputing, ser. ICS '03. New York, NY, USA: ACM, 2003, pp. 109–120. [Online]. Available: http://doi.acm.org/10.1145/782814.782831.

  36. L. Ramos and R. Bianchini, “C-oracle: Predictive thermal management for data centers,” in High Performance Computer Architecture, 2008. HPCA 2008. IEEE 14th International Symposium on, feb. 2008, pp. 111–122.

    Google Scholar 

  37. X.-F. Jiang, J. Zhang, M. I. Alghamdi, X. Qin, M.-H. Jiang, and J.-F. Zhang, “Peam: Predictive energy-aware management for storage systems,” in Proceedings of 8th IEEE International Conference on Networking, Architecture, and Storage.

    Google Scholar 

  38. “Wd1600aajs specification,” http://www.wdc.com/wdproducts/library/SpecSheet/ENG/2879-701277.pdf.

  39. “What happens on line in 60 seconds?” http://www.mediabistro.com/alltwitter/online-60-seconds_b46813.

  40. “Dropbox statistics,” http://techcrunch.com/2012/11/13/dropbox-100-million/.

Download references

Acknowledgments

This research was supported by the U.S. National Science Foundation under Grants CCF-0845257 (CAREER), CNS-0917137 (CSR), CNS-0757778 (CSR), CCF-0742187 (CPA), CNS-0831502 (CyberTrust), CNS-0855251 (CRI), OCI-0753305 (CI-TEAM), DUE-0837341 (CCLI), and DUE-0830831 (SFS). Meikang Qiu’s research was support by NSF CNS-1359557 and NSFC 61071061.

Author information

Authors and Affiliations

  1. Department of Computer Science, Earlham College, Richmond, IN, USA

    Xunfei Jiang PhD

  2. Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA

    Ji Zhang PhD & Xiao Qin PhD

  3. Computer Engineering, San Jose State University, San Jose, CA, USA

    Meikang Qiu PhD

  4. College of Mathematics and Computer Science, Wuhan Textile University, Wuhan, China

    Minghua Jiang PhD

  5. Taiyuan University of Science and Technology, Taiyuan, China

    Jifu Zhang PhD

Authors
  1. Xunfei Jiang PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ji Zhang PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiao Qin PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Meikang Qiu PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Minghua Jiang PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jifu Zhang PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xunfei Jiang PhD .

Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, North Dakota State University, Fargo, North Dakota, USA

    Samee U. Khan

  2. School of Information Technologies, The University of Sydney, Sydney, New South Wales, Australia

    Albert Y. Zomaya

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Science+Business Media New York

About this chapter

Cite this chapter

Jiang, X., Zhang, J., Qin, X., Qiu, M., Jiang, M., Zhang, J. (2015). Thermal Modeling and Management of Storage Systems in Data Centers. In: Khan, S., Zomaya, A. (eds) Handbook on Data Centers. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2092-1_30

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-2092-1_30

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4939-2091-4

  • Online ISBN: 978-1-4939-2092-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation