Skip to main content

Advertisement

Log in

Toward sustainable data centers: a comprehensive energy management strategy

  • Published:
Computing Aims and scope Submit manuscript

Abstract

Data centers are major contributors to the emission of carbon dioxide to the atmosphere, and this contribution is expected to increase in the following years. This has encouraged the development of techniques to reduce the energy consumption and the environmental footprint of data centers. Whereas some of these techniques have succeeded to reduce the energy consumption of the hardware equipment of data centers (including IT, cooling, and power supply systems), we claim that sustainable data centers will be only possible if the problem is faced by means of a holistic approach that includes not only the aforementioned techniques but also intelligent and unifying solutions that enable a synergistic and energy-aware management of data centers. In this paper, we propose a comprehensive strategy to reduce the carbon footprint of data centers that uses the energy as a driver of their management procedures. In addition, we present a holistic management architecture for sustainable data centers that implements the aforementioned strategy, and we propose design guidelines to accomplish each step of the proposed strategy, referring to related achievements and enumerating the main challenges that must be still solved.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Koomey J (2011) Growth in data center electricity use 2005 to 2010. Report, Analytics Press, Oakland

    Google Scholar 

  2. Greenpeace International (2010) Make IT green: cloud computing and its contribution to climate change. Report. http://www.greenpeace.org/international/en/publications/reports/make-it-green-cloudcomputing/

  3. Belady CL (2007) In the data center, power and cooling costs more than the IT equipment it supports. Electronics cooling. http://www.electronics-cooling.com/2007/02/in-the-data-center-power-and-cooling-costs-more-than-the-it-equipment-it-supports

  4. The Climate Group (2008) SMART 2020: enabling the low carbon economy in the information age. Report. http://www.smart2020.org/_assets/files/02_Smart2020Report.pdf

  5. Kava J (2011) Google’s three steps for a zero carbon green data center. Data center Dynamics London. http://www.greenm3.com/gdcblog/2011/12/6/googles-three-steps-for-a-zero-carbon-green-data-center.html

  6. Arlitt M, Bash C, Blagodurov S, Chen Y, Christian T, Gmach D, Hyser C, Kumari N, Liu Z, Marwah M, Mcreynolds A, Patel R, Shah A, Wang Z, Zhou R (2012) Towards the design and operation of net-zero energy data centers. In: Proceedings of 13th IEEE intersociety conference on thermal and thermomechanical phenomena in electronic systems (ITherm’12), San Diego, USA, pp 552–561. doi:10.1109/ITHERM.2012.6231479

  7. Wang L, Khan SU (2013) Review of performance metrics for green data centers: a taxonomy study. J Supercomput 63(3):639–656. doi:10.1007/s11227-011-0704-3

    Article  Google Scholar 

  8. The Green Grid (2012) PUE: a comprehensive examination of the metric. Tech. Rep. White Paper n.49. https://www.thegreengrid.org/en/Global/Content/white-papers/WP49-PUEAComprehensiveExaminationoftheMetric

  9. The Green Grid (2010) Carbon usage effectiveness (CUE): a green grid data center sustainability metric. Tech. Rep. White Paper n.32. http://www.thegreengrid.org/Global/Content/white-papers/Carbon_Usage_Effectiveness_White_Paper

  10. The Green Grid (2008) A framework for data center energy productivity. Tech. Rep. White Paper n.13. http://www.thegreengrid.org/Global/Content/white-papers/Framework-for-Data-Center-Energy-Productivity

  11. Bekas C, Curioni A (2010) A new energy aware performance metric. Comput Sci Res Dev 25(3–4):187–195. doi:10.1007/s00450-010-0119-z

    Article  Google Scholar 

  12. The Green Grid (2014) Harmonizing global metrics for data center energy efficiency. Statement. http://www.thegreengrid.org/~/media/Regulatory/HarmonizingGlobalMetricsforDataCenterEnergyEfficiency.pdf

  13. Intel Corporation: Intelligent Platform Management Interface (IPMI). http://www.intel.com/content/www/us/en/servers/ipmi/ipmi-home.html

  14. Intel Corporation (2015) Intel 64 and IA-32 architectures software developer’s manual. Volume 3B: system programming guide, Part 2. http://www.intel.es/content/dam/www/public/us/en/documents/manuals/64-ia-32-architectures-software-developer-vol-3b-part-2-manual.pdf

  15. The Carbon Trust (2013) Energy and carbon conversion factors. Tech. Rep. CTL 153. http://www.carbontrust.com/media/18223/ctl153_conversion_factors.pdf

  16. Ganglia Monitoring System. http://ganglia.sourceforge.net/

  17. Kansal A, Zhao F, Liu J, Kothari N, Bhattacharya, AA (2010) Virtual machine power metering and provisioning. In: Proceedings of 1st ACM symposium on cloud computing (SoCC’10), Indianapolis, USA, pp 39–50. doi:10.1145/1807128.1807136

  18. Yang H, Zhao Q, Luan Z, Qian D (2014) iMeter: an integrated VM power model based on performance profiling. Fut Gen Comput Syst 36:267–286. doi:10.1016/j.future.2013.07.008

    Article  Google Scholar 

  19. Mobius C, Dargie W, Schill A (2014) Power consumption estimation models for processors, virtual machines, and servers. IEEE Trans Parall Distrib Syst 25(6):1600–1614. doi:10.1109/TPDS.2013.183

    Article  Google Scholar 

  20. Reiss C, Tumanov A, Ganger GR, Katz RH, Kozuch MA (2012) Heterogeneity and dynamicity of clouds at scale: google trace analysis. In: Proceedings 3rd ACM symposium on cloud computing (SoCC’12), San Jose, USA, pp 7:1–7:13. doi:10.1145/2391229.2391236

  21. Jarus M, Oleksiak A, Piontek T, Weglarz J (2014) Runtime power usage estimation of HPC servers for various classes of real-life applications. Fut Gen Comput Syst 36:299–310. doi:10.1016/j.future.2013.07.012

    Article  Google Scholar 

  22. Bircher WL, John LK (2012) Complete system power estimation using processor performance events. IEEE Trans Comput 61(4):563–577. doi:10.1109/TC.2011.47

    Article  MathSciNet  Google Scholar 

  23. Varrette S, Guzek M, Plugaru V, Besseron X, Bouvry P (2013) HPC performance and energy-efficiency of Xen, KVM and VMware Hypervisors. In: Proceedings of 25th international symposium on computer architecture and high performance computing (SBAC-PAD’13), Porto de Galinhas, Brazil, pp 89–96, IEEE (2013). doi:10.1109/SBAC-PAD.2013.18

  24. Alpaydin E (2014) Introduction to machine learning, 3rd edn. The MIT Press, Cambridge

    MATH  Google Scholar 

  25. Cupertino L, Da Costa G, Pierson JM (2015) Towards a generic power estimator. Comput Sci Res Dev 30(2):145–153. doi:10.1007/s00450-014-0264-x

    Article  Google Scholar 

  26. McCullough JC, Agarwal Y, Chandrashekar J, Kuppuswamy S, Snoeren AC, Gupta RK (2011) Evaluating the effectiveness of model-based power characterization. In: Proceedings 2011 USENIX annual technical conference (ATC’11), Portland, USA, pp 159–172

  27. Zhang Q, Zhani MF, Boutaba R, Hellerstein JL (2014) Dynamic heterogeneity-aware resource provisioning in the cloud. IEEE Trans Cloud Comput 2(1):14–28. doi:10.1109/TCC.2014.2306427

    Article  Google Scholar 

  28. Kousiouris G, Cucinotta T, Varvarigou T (2011) The effects of scheduling, workload type and consolidation scenarios on virtual machine performance and their prediction through optimized artificial neural networks. J Syst Softw 84(8):1270–1291. doi:10.1016/j.jss.2011.04.013

    Article  Google Scholar 

  29. Lewis AW, Tzeng NF, Ghosh S (2012) Runtime energy consumption estimation for server workloads based on chaotic time-series approximation. ACM Trans Arch Code Optim 9(3):15:1–15:26. doi:10.1145/2355585.2355588

    Google Scholar 

  30. Brockwell P, Davis R (2002) Introduction to time series and forecasting, 2nd edition. Springer, New York. doi:10.1007/b97391

  31. Subirats J, Guitart J (2015) Assessing and forecasting energy efficiency on cloud computing platforms. Fut Gen Comput Syst 45:70–94. doi:10.1016/j.future.2014.11.008

    Article  Google Scholar 

  32. UEFI Forum (2013) Advanced configuration and power interface specification revision 5.0a. http://www.acpi.info/spec50a.htm

  33. Etinski M, Corbalan J, Labarta J, Valero M (2012) Understanding the future of energy-performance trade-off via DVFS in HPC environments. J Parall Distrib Comput 72(4):579–590. doi:10.1016/j.jpdc.2012.01.006

    Article  Google Scholar 

  34. Mann ZA (2015) Allocation of virtual machines in cloud data centers: a survey of problem models and optimization algorithms. ACM Comput Surv 48(1):11:1–11:34. doi:10.1145/2797211

    Article  Google Scholar 

  35. Kim SG, Eom H, Yeom HY (2013) Virtual machine consolidation based on interference modeling. J Supercomput 66(3):1489–1506. doi:10.1007/s11227-013-0939-2

    Article  Google Scholar 

  36. Xiao Z, Song W, Chen Q (2013) Dynamic resource allocation using virtual machines for cloud computing environment. IEEE Trans Parall Distrib Syst 24(6):1107–1117. doi:10.1109/TPDS.2012.283

    Article  Google Scholar 

  37. Beloglazov A, Abawajy J, Buyya R (2012) Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Fut Gen Comput Syst 28(5):755–768. doi:10.1016/j.future.2011.04.017

    Article  Google Scholar 

  38. Tesfatsion S, Wadbro E, Tordsson J (2014) A combined frequency scaling and application elasticity approach for energy-efficient cloud computing. Sustain Comput Inf Syst 4(4):205–214. doi:10.1016/j.suscom.2014.08.007

    Google Scholar 

  39. Bilal K, Khan S, Madani S, Hayat K, Khan M, Min-Allah N, Kolodziej J, Wang L, Zeadally S, Chen D (2013) A survey on green communications using adaptive link rate. Cluster Comput 16(3):575–589. doi:10.1007/s10586-012-0225-8

    Article  Google Scholar 

  40. Zhang Y, Ansari N (2015) HERO: hierarchical energy optimization for data center networks. IEEE Syst J 9(2):406–415. doi:10.1109/JSYST.2013.2285606

    Article  Google Scholar 

  41. Addis B, Ardagna D, Capone A, Carello G (2014) Energy-aware joint management of networks and cloud infrastructures. Comput Netw 70:75–95. doi:10.1016/j.comnet.2014.04.011

    Article  Google Scholar 

  42. Chun BG, Iannaccone G, Iannaccone G, Katz R, Lee G, Niccolini L (2010) An energy case for hybrid datacenters. SIGOPS Oper Syst Rev 44(1):76–80. doi:10.1145/1740390.1740408

    Article  Google Scholar 

  43. Ferrer AJ, Hernandez F, Tordsson J, Elmroth E, Ali-Eldin A, Zsigri C, Sirvent R, Guitart J, Badia RM, Djemame K, Ziegler W, Dimitrakos T, Nair SK, Kousiouris G, Konstanteli K, Varvarigou T, Hudzia B, Kipp A, Wesner S, Corrales M, Forg N, Sharif T, Sheridan C (2012) OPTIMIS: a holistic approach to cloud service provisioning. Fut Gen Comput Syst 28(1):66–77. doi:10.1016/j.future.2011.05.022

    Article  Google Scholar 

  44. Le K, Bianchini R, Martonosi M, Nguyen TD (2009) Cost- and energy-aware load distribution across data centers. In: Proceedings of 2009 SOSP workshop on power aware computing and systems (HotPower’09), Big Sky, USA, USENIX Association

  45. Hatcher J (2013) Follow the moon. Data centre management magazine. http://datacentremanagement.com/news/view/follow-the-moon

  46. Abbasi Z, Pore M, Gupta S (2013) Impact of workload and renewable prediction on the value of geographical workload management. In: Energy-efficient data centers: 2nd internationl on workshop, E2DC 2013. Revised selected papers, Lecture notes in computer science, Springer, vol 8343, pp 1–15. doi:10.1007/978-3-642-55149-9_1

  47. Kecskemeti G, Kertesz A, Cs Marosi A, Nemeth Z (2014) Strategies for increased energy awareness in cloud federations. In: High-performance computing on complex environments, chap. 19, pp 365–382. Wiley, New York. doi:10.1002/9781118711897.ch19

  48. Xu J, Fortes JAB (2010) Multi-objective virtual machine placement in virtualized data center environments. In: Proceedings of 2010 international conference on green computing and communications and international conference on cyber, physical and social computing, Hangzhou, China, IEEE 2010, pp 179–188. doi:10.1109/GreenCom-CPSCom.2010.137

  49. Goiri I, Berral JL, Fitó JO, Julià F, Nou R, Guitart J, Gavaldà R, Torres J (2012) Energy-efficient and multifaceted resource management for profit-driven virtualized data centers. Fut Gen Comput Syst 28(5):718–731. doi:10.1016/j.future.2011.12.002

    Article  Google Scholar 

  50. Vitali M, Pernici B, OReilly UM (2015) Learning a goal-oriented model for energy efficient adaptive applications in data centers. Inf Sci 319:152–170. doi:10.1016/j.ins.2015.01.023

    Article  Google Scholar 

  51. Gao Y, Guan H, Qi Z, Hou Y, Liu L (2013) A multi-objective ant colony system algorithm for virtual machine placement in cloud computing. J Comput Syst Sci 79(8):1230–1242. doi:10.1016/j.jcss.2013.02.004

    Article  MathSciNet  MATH  Google Scholar 

  52. Wada H, Suzuki J, Yamano Y, Oba K (2012) E\({^3}\): a multiobjective optimization framework for SLA-aware service composition. IEEE Trans Serv Comput 5(3):358–372. doi:10.1109/TSC.2011.6

    Article  Google Scholar 

  53. Guenter B, Jain N, Williams C (2011) Managing cost, performance, and reliability tradeoffs for energy-aware server provisioning. In: Proceedings on IEEE INFOCOM 2011, Shanghai, China, IEEE 2011, pp 1332–1340. doi:10.1109/INFCOM.2011.5934917

  54. Shi L, Furlong J, Wang R (2013) Empirical evaluation of vector bin packing algorithms for energy efficient data centers. In: Proceedings 18th IEEE symposium on computers and communications (ISCC’13), Split, Croatia, IEEE 2013, pp 9–15. doi:10.1109/ISCC.2013.6754915

  55. Mann ZA (2015) Approximability of virtual machine allocation: much harder than bin packing. In: Proceedings of 9th Hungarian-Japanese symposium on discrete mathematics and its applications, Fukuoka, Japan, pp 21–30

  56. Lee EK, Kulkarni I, Pompili D, Parashar M (2012) Proactive thermal management in green datacenters. J Supercomput 60(2):165–195. doi:10.1007/s11227-010-0453-8

    Article  Google Scholar 

  57. Chrobak M, Durr C, Hurand M, Robert J (2011) Algorithms for temperature-aware task scheduling in microprocessor systems. Sustain Comput Inf Syst 1(3):241–247. doi:10.1016/j.suscom.2011.05.009

    MATH  Google Scholar 

  58. Chen Y, Gmach D, Hyser C, Wang Z, Bash C, Hoover C, Singhal S (2010) Integrated management of application performance, power and cooling in data centers. In: Proceedings of 2010 IEEE network operations and management symposium (NOMS’10), Osaka, Japan, IEEE 2010,pp 615–622. doi:10.1109/NOMS.2010.5488433

  59. Banerjee A, Mukherjee T, Varsamopoulos G, Gupta SK (2011) Integrating cooling awareness with thermal aware workload placement for HPC data centers. Sustain Comput Inf Syst 1(2):134–150. doi:10.1016/j.suscom.2011.02.003

    Google Scholar 

  60. Ahmad F, Vijaykumar TN (2010) Joint optimization of idle and cooling power in data centers while maintaining response time. In: Proceedings of 15th international conference on architectural support for programming languages and operating systems (ASPLOS’10), Pittsburgh, USA, ACM 2010, pp 243–256. doi:10.1145/1736020.1736048

  61. Vasic N, Scherer T, Schott W (2010) Thermal-aware workload scheduling for energy efficient data centers. In: Proceedings of 7th internationl conference on autonomic computing (ICAC’10), Washington, USA, ACM 2010, pp 169–174. doi:10.1145/1809049.1809076

  62. Belady CL (208) Does efficiency in the data center give us what we need? Mission critical magazine. http://www.missioncriticalmagazine.com/articles/does-efficiency-in-the-data-center-give-us-what-we-need

  63. Gmach D, Rolia J, Bash C, Chen Y, Christian T, Shah A, Sharma R, Wang Z (2010) Capacity planning and power management to exploit sustainable energy. In: Proceedings of 2010 international conference on network and service management (CNSM’10), Niagara Falls, Canada, IEEE 2010, pp 96–103. doi:10.1109/CNSM.2010.5691329

  64. Goiri I, Haque ME, Le K, Beauchea R, Nguyen TD, Guitart J, Torres J, Bianchini R (2015) Matching renewable energy supply and demand in green datacenters. Ad Hoc Netw 25(Part B):520–534. doi:10.1016/j.adhoc.2014.11.012

    Article  Google Scholar 

  65. Liu Z, Lin M, Wierman A, Low SH, Andrew LL (2011) Geographical load balancing with renewables. SIGMETRICS Perf Eval Rev 39(3):62–66. doi:10.1145/2160803.2160862

    Article  Google Scholar 

  66. Zhang Y, Wang Y, Wang X (2011) GreenWare: greening cloud-scale data centers to maximize the use of renewable energy. In: Proceedings of 12th ACM/IFIP/USENIX international middleware conference, Lisbon, Portugal, Lecture notes in computer science, Springer, vol 7049, pp 143–164. doi:10.1007/978-3-642-25821-3_8

  67. Cappiello C, Melia P, Pernici B, Plebani P, Vitali M (2014) Sustainable choices for cloud applications: a focus on CO2 emissions. In: Proceedings of 2nd international conference on ICT for sustainability (ICT4S’14), Stockholm, Sweden, Atlantis Press, pp 352–358. doi:10.2991/ict4s-14.2014.43

  68. Goiri I, Katsak W, Le K, Nguyen TD, Bianchini R (2013) Parasol and greenswitch: managing datacenters powered by renewable energy. In: Proceedings of 18th international conference on architectural support for programming languages and operating systems (ASPLOS’13), Houston, USA, ACM 2013, pp 51–64. doi:10.1145/2451116.2451123

  69. Erden HS, Khalifa HE (2012) Energy and environmental assessment of on-site power and cooling for data centers. HVAC & R Res 18(1–2):51–66. doi:10.1080/10789669.2011.585422

    Google Scholar 

  70. Kirby B, Hirst E (2000) Customer-specific metrics for the regulation and load-following ancillary services. Tech. Rep. CON-474, Oak Ridge National Laboratory (ORNL). http://web.ornl.gov/~webworks/cpr/rpt/105927.pdf

  71. Li C, Zhou R, Li T (2013) Enabling distributed generation powered sustainable high-performance data center. In: Proceedings of 19th international symposium on high performance computer architecture (HPCA’13), Shenzhen, China, IEEE 2013, pp 35–46. doi:10.1109/HPCA.2013.6522305

  72. United States Environmental Protection Agency (EPA) Renewable Energy Certificates (RECs). http://www.epa.gov/greenpower/gpmarket/rec.htm

  73. Deng N, Stewart C, Gmach D, Arlitt M, Kelley J (2012) Adaptive green hosting. In: Proceedings of 9th international conference on autonomic computing (ICAC’12), San Jose, USA, ACM 2012, pp 135–144. doi:10.1145/2371536.2371561

  74. Ren C, Wang D, Urgaonkar B, Sivasubramaniam A (2012) Carbon-aware energy capacity planning for datacenters. In: Proceedings of 20th international symposium on modeling, analysis and simulation of computer and telecommunication systems (MASCOTS’12), Arlington, USA, IEEE 2012, pp 391–400. doi:10.1109/MASCOTS.2012.51

  75. The Green Grid (2015) Data center maturity model. White Paper n.56. http://www.thegreengrid.org/en/Global/Content/Tools/DataCenterMaturityModel

  76. Macias M, Guitart J (2014) SLA negotiation and enforcement policies for revenue maximization and client classification in cloud providers. Fut Gen Comput Syst 41:19–31. doi:10.1016/j.future.2014.03.004

    Article  Google Scholar 

  77. Sedaghat M, Hernandez F, Elmroth E (2011) Unifying cloud management: towards overall governance of business level objectives. In: Proceedings of 11th IEEE/ACM international symposium on cluster, cloud and grid computing (CCGrid’11), Newport Beach, USA, IEEE 2011, pp 591–597. doi:10.1109/CCGrid.2011.65

  78. Kousiouris G, Menychtas A, Kyriazis D, Gogouvitis S, Varvarigou T (2014) Dynamic, behavioral-based estimation of resource provisioning based on high-level application terms in cloud platforms. Fut Gen Comput Syst 32:27–40. doi:10.1016/j.future.2012.05.009

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jordi Guitart.

Additional information

This work is supported by the Ministry of Science and Technology of Spain under contract TIN2015-65316-P, by the Generalitat de Catalunya under contract 2014-SGR-1051, and by the European Commission under FP7-SMARTCITIES-2013 contract 608679 (RenewIT) and FP7-ICT-2013-10 contracts 610874 (ASCETiC) and 610456 (EuroServer).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Guitart, J. Toward sustainable data centers: a comprehensive energy management strategy. Computing 99, 597–615 (2017). https://doi.org/10.1007/s00607-016-0501-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00607-016-0501-1

Keywords

Mathematics Subject Classification

Navigation