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.
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References
Koomey J (2011) Growth in data center electricity use 2005 to 2010. Report, Analytics Press, Oakland
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/
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
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
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
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
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
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
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
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
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
The Green Grid (2014) Harmonizing global metrics for data center energy efficiency. Statement. http://www.thegreengrid.org/~/media/Regulatory/HarmonizingGlobalMetricsforDataCenterEnergyEfficiency.pdf
Intel Corporation: Intelligent Platform Management Interface (IPMI). http://www.intel.com/content/www/us/en/servers/ipmi/ipmi-home.html
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
The Carbon Trust (2013) Energy and carbon conversion factors. Tech. Rep. CTL 153. http://www.carbontrust.com/media/18223/ctl153_conversion_factors.pdf
Ganglia Monitoring System. http://ganglia.sourceforge.net/
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
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
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
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
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
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
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
Alpaydin E (2014) Introduction to machine learning, 3rd edn. The MIT Press, Cambridge
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
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
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
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
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
Brockwell P, Davis R (2002) Introduction to time series and forecasting, 2nd edition. Springer, New York. doi:10.1007/b97391
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
UEFI Forum (2013) Advanced configuration and power interface specification revision 5.0a. http://www.acpi.info/spec50a.htm
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
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
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
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
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
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
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
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
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
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
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
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
Hatcher J (2013) Follow the moon. Data centre management magazine. http://datacentremanagement.com/news/view/follow-the-moon
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
United States Environmental Protection Agency (EPA) Renewable Energy Certificates (RECs). http://www.epa.gov/greenpower/gpmarket/rec.htm
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
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
The Green Grid (2015) Data center maturity model. White Paper n.56. http://www.thegreengrid.org/en/Global/Content/Tools/DataCenterMaturityModel
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
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
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
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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).
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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
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DOI: https://doi.org/10.1007/s00607-016-0501-1
Keywords
- Green computing
- Energy efficiency
- Energy management
- Energy measurement
- Sustainability
- Resource management
- Data centers