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Home / A Review on Energy Efficiency and Demand Response With Focus on Small and Medium Data Centers

A Review on Energy Efficiency and Demand Response With Focus on Small and Medium Data Centers

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Abstract

Data centers are the courage of a growing number of activities in mod economies. Notwithstanding, the large increase of digital content, large data, eastward-commerce, and Cyberspace traffic is also making information centers one of the fastest-growing users of electricity. The total energy consumption of information centers corresponded to almost ane.5% of the global electricity consumption and has an approximated annual growth rate of four.3%. Therefore, information technology is very important to increase the energy efficiency in data centers with actions such as ability usage direction, server consolidation, free energy-efficient components and systems, equally well equally need response programs and renewable free energy sources. Modest and medium information centers account for more than 50% of the total electricity consumption in this sector. In fact, surveys signal that this information center profile waste more than energy than larger facilities. Nevertheless, existing studies tend to be focused on the free energy-related issues for big data centers rather than small and medium information centers. Therefore, through a meticulous land-of-the-art literature review of data centers energy efficiency and demand response perspectives, this paper aims to present how an intensive energy consumer, such every bit small and medium data centers, can go more efficient from the free energy point of view and how they can take advantage of demand response programs to decrease costs and to cooperate with the filigree to ensure higher reliability and sustainable development goals.

References

  • Aghaei, J., & Alizadeh, G. I. (2013). Demand response in smart electricity grids equipped with renewable energy sources: a review. Renewable and Sustainable Energy Reviews, 18, 64–72. https://doi.org/10.1016/j.rser.2012.09.019.

    Article  Google Scholar

  • Ahmad, R. Westward., Gani, A., Hamid, S. H. A., Shiraz, M., Yousafzai, A., & Xia, F. (2015). A survey on virtual machine migration and server consolidation frameworks for cloud data centers. Journal of Network and Computer Applications, pp., 52, eleven–25. https://doi.org/ten.1016/j.jnca.2015.02.002.

    Commodity  Google Scholar

  • Ahn, J. H., Jouppi, Northward. P., Kozyrakis, C., Leverich, J., & Schreiber, R. S. (2009). Future scaling of processor-retentivity interfaces. In Proceedings of the Conference on Loftier Performance Computing Networking, Storage and Analysis - SC '09 (p. 1). New York: ACM Press. https://doi.org/10.1145/1654059.1654102.

    Google Scholar

  • Alkharabsheh, South., Fernandes, J., Gebrehiwot, B., Agonafer, D., Ghose, Thou., Ortega, A., Joshi, Y., & Sammakia, B. (2015). A brief overview of contempo developments in thermal management in data centers. Journal of Electronic Packaging, 137(iv), 040801. https://doi.org/x.1115/1.4031326.

    Article  Google Scholar

  • Amur, H., Cipar, J., & Gupta, V. (2010). Robust and flexible power-proportional storage. In Proceedings of the 1st ACM symposium on Cloud computing - SoCC '10 (pp. 217–228). https://doi.org/ten.1145/1807128.1807164.

    Chapter  Google Scholar

  • Andrén, F. P., Strasser, T. and Kastner, Due west. (2016) 'Applying the SGAM methodology for rapid prototyping of smart grid applications', IECON Proceedings (Industrial Electronics Briefing), pp. 3812–3818. https://doi.org/ten.1109/IECON.2016.7794057.

  • Ardagna, D., Panicucci, B., Trubian, M., & Zhang, L. (2012). Energy-aware autonomic resource allocation in multitier virtualized environments. IEEE Transactions on Services Computing, 5(i), 2–19. https://doi.org/10.1109/TSC.2010.42.

    Commodity  Google Scholar

  • Arianyan, E., Taheri, H., & Khoshdel, 5. (2017). Novel fuzzy multi objective DVFS-enlightened consolidation heuristics for energy and SLA efficient resource management in cloud data centers. Journal of Network and Computer Applications, 78, 43–61. https://doi.org/10.1016/j.jnca.2016.09.016.

    Article  Google Scholar

  • ASHRAE (2011) '2011 Gaseous and particulate contagion guidelines for data centers', American Society of Heating, Refrigerating and Air-Conditioning Engineers, pp. 1–22.

  • Avgerinou, G., Bertoldi, P. and Castellazzi, L. (2017) 'Trends in data centre energy consumption under the European lawmaking of behave for information eye energy efficiency', Energies, 10(10). https://doi.org/10.3390/en10101470.

  • Barroso, L. A., & Hölzle, U. (2007). The example for energy-proportional computing. Computer, 40(12), 33–37. https://doi.org/10.1109/MC.2007.443.

    Article  Google Scholar

  • Basmadjian, R., Müller, L., & De Meer, H. (2015). Data centres' ability profile selecting policies for demand response: insights of green supply demand agreement. Advertizing Hoc Networks, 25(PB), 581–594. https://doi.org/10.1016/j.adhoc.2014.eleven.007.

    Article  Google Scholar

  • Beloglazov, A., & Buyya, R. (2013). Managing overloaded hosts for dynamic consolidation of virtual machines in cloud data centers under quality of service constraints. IEEE Transactions on Parallel and Distributed Systems, 24(7), 1366–1379. https://doi.org/10.1109/TPDS.2012.240.

    Article  Google Scholar

  • Bennett, D. and Delforge, P. (2012) 'Pocket-sized server rooms, big energy savings opportunities and barriers to energy efficiency on the small server room market', NRDC, (February).

  • Bonetto, Due east., Finamore, A., Mellia, M., & Fiandra, R. (2014). Energy efficiency in admission and aggregation networks: from current traffic to potential savings. Computer Networks, 65, 151–166. https://doi.org/ten.1016/j.comnet.2014.03.008.

    Article  Google Scholar

  • Bostoen, T., Mullender, S., & Berbers, Y. (2013). Power-reduction techniques for data-heart storage systems. ACM Calculating Surveys, 45(3), ane–38. https://doi.org/ten.1145/2480741.2480750.

    Article  Google Scholar

  • Boulos, S., Nuttall, C., Harrison, B., Moura, P. and Jehle, C. (2014) ErP lot 27—uninterruptible power supplies: preparatory written report—final report. Ricardo-AEA, Intertek, ISR – Academy of Coimbra.

  • Brocanelli Grand, Li South, Wang X, and Zhang W. (2014) 'Maximizing the revenues of data centers in regulation marketplace by coordinating with electric vehicles', Sustainable Computing: Informatics and Systems. Elsevier Inc., pp. 1–13. https://doi.org/ten.1016/j.suscom.2014.03.004, 2015.

  • Calheiros, R. Northward., Ranjan, R., De Rose, C. A. F. and Buyya, R. (2009) 'CloudSim: a novel framework for modeling and simulation of cloud calculating infrastructures and services', arXiv preprint arXiv:0903.2525, p. ix.

  • Camacho, J., Zhang, Y., Chen, One thousand. and Chiu, D. M. (2014) 'Balance your bids before your bits: the economics of geographic load-balancing', Proc. of the 5th Int. Conf. on Hereafter Energy Systems (ACM e-Free energy), pp. 75–85. https://doi.org/10.1145/2602044.2602068.

  • Capozzoli, A., Chinnici, Chiliad., Perino, M. and Serale, Chiliad. (2015) 'Review on operation metrics for energy efficiency in data center: the function of thermal management', Free energy Efficient Data Centers, pp. 135–151. https://doi.org/x.1007/978-3-319-15786-3_9.

  • Carreiro, A. M., Jorge, H. M., & Antunes, C. H. (2017). Energy management systems aggregators: a literature survey. Renewable and Sustainable Energy Reviews, 73, 1160–1172. https://doi.org/10.1016/j.rser.2017.01.179.

    Commodity  Google Scholar

  • Castro, P. H. P., Cardoso, K. 5 and Corrêa, S. (2013) 'Uma Abordagem Baseada no Consumo de CPU east RAM para a Eficiencia Energetica em Centros de Dados para Computação em Nuvem', Wscad-Ssc 2013, (February), p. viii. https://doi.org/10.13140/2.1.4681.0242.

  • Cecati, C., Mokryani, Thousand., Piccolo, A. and Siano, P. (2010) 'An overview on the smart grid concept', IECON Proceedings (Industrial Electronics Briefing), pp. 3322–3327. https://doi.org/x.1109/IECON.2010.5675310.

  • Chen, Northward., Ren, X., Ren, S. and Wierman, A. (2015) 'Greening multi-tenant data center demand response', Performance Evaluation. Elsevier B.V., 91, pp. 229–254. https://doi.org/10.1016/j.peva.2015.06.014.

  • Chen, T., Gao, X., & Chen, G. (2016a). The features, hardware, and architectures of data eye networks: a survey. Journal of Parallel and Distributed Calculating, 96, 45–74. https://doi.org/10.1016/j.jpdc.2016.05.009.

    Article  Google Scholar

  • Chen, T., Zhang, Y., Wang, X., & Giannakis, Yard. B. (2016b). Robust workload and free energy direction for sustainable information centers. IEEE Journal on Selected Areas in Communications, 34(3), 651–664. https://doi.org/ten.1109/JSAC.2016.2525618.

    Article  Google Scholar

  • Christantoni, D., Oxizidis, S., Flynn, D., & Finn, D. P. (2016). Implementation of demand response strategies in a multi-purpose commercial building using a whole-edifice simulation model arroyo. Energy and Buildings, 131, 76–86. https://doi.org/ten.1016/j.enbuild.2016.09.017.

    Article  Google Scholar

  • Cioara, T., Anghel, I., Bertoncini, Thousand., Salomie, I., Arnone, D., Mammina, M., Velivassaki, T.-H., & Antal, K. (2016). Optimized flexibility management enacting information centres participation in smart need response programs. Futurity Generation Computer Systems., 78, 330–342. https://doi.org/10.1016/j.futurity.2016.05.010.

    Article  Google Scholar

  • Craig-forest, K., Krause, P. and Mason, A. (2010) 'Green ICT: oxymoron or phone call to innovation?', Send, (Ict), pp. 978–981. https://doi.org/10.5176/978-981-08-7240-3.

  • Dai, J., Das, D., & Pecht, M. (2012a). A multiple stage approach to mitigate the risks of telecommunications equipment nether free air cooling weather. Energy Conversion and Management, 64, 424–432. https://doi.org/10.1016/j.enconman.2012.06.018.

    Article  Google Scholar

  • Dai, J., Das, D., & Pecht, Grand. (2012b). Prognostics-based risk mitigation for telecom equipment nether free air cooling atmospheric condition. Applied Free energy, 99, 423–429. https://doi.org/x.1016/j.apenergy.2012.05.055.

    Article  Google Scholar

  • Dai, J., Das, D., Ohadi, M., & Pecht, G. (2013). Reliability risk mitigation of free air cooling through prognostics and health management. Applied Energy, 111, 104–112. https://doi.org/10.1016/j.apenergy.2013.04.047.

    Article  Google Scholar

  • Dargie, W. (2014) 'Estimation of the cost of VM migration', Proceedings - International Conference on Computer Communications and Networks, ICCCN. https://doi.org/10.1109/ICCCN.2014.6911756.

  • Dayarathna, One thousand., Wen, Y., & Fan, R. (2016). Information center energy consumption modeling: a survey. IEEE Communications Surveys & Tutorials, eighteen(1), 732–794. https://doi.org/10.1109/COMST.2015.2481183.

    Commodity  Google Scholar

  • Delforge, P. (2014) 'America's data centers are wasting huge amounts of energy', Natural Resource Defence Council (NRDC), IB:14-08-a(baronial), pp. 1–v.

  • Deng, Y. (2011). What is the future of disk drives, expiry or rebirth? ACM Calculating Surveys, 43(3), 1–27. https://doi.org/x.1145/1922649.1922660.

    Article  Google Scholar

  • Dhiman, G., Marchetti, 1000., & Rosing, T. S. (2010). VGreen: a organisation for energy-efficient management of virtual machines. ACM Transactions on Pattern Automation of Electronic Systems, 16(1), 1–27. https://doi.org/10.1145/1870109.1870115.

    Commodity  Google Scholar

  • Dreibholz, T., Becke, M. and Adhari, H. (2007) 'Report to congress on server and data center free energy efficiency public constabulary 109-431', tdr.wiwi.uni-due.de, 109, p. 431.

  • Ebrahimi, Thousand., Jones, M. F., & Fleischer, A. S. (2014). A review of information center cooling technology, operating conditions and the respective depression-grade waste rut recovery opportunities. Renewable and Sustainable Free energy Reviews, 31, 622–638. https://doi.org/10.1016/j.rser.2013.12.007.

    Commodity  Google Scholar

  • Elnozahy, E. N., Kistler, Chiliad. and Rajamony, R. (2003) 'Energy-efficient server clusters', in, pp. 179–197. https://doi.org/x.1007/3-540-36612-1_12.

  • Emerson (2015) 'Energy logic: reducing data center free energy consumption by creating savings that cascade across systems', White Paper, Emerson Network Ability, pp. 1–21.

  • Fang, X., Misra, S., Xue, G., & Yang, D. (2012). Smart grid—the new and improved power grid: a survey. IEEE Communications Surveys & Tutorials, 14(four), 944–980. https://doi.org/ten.1109/SURV.2011.101911.00087.

    Commodity  Google Scholar

  • Flanagan, C. (2013) 'A data center perspective on demand response', Data Centers Dynamics.

  • Fridgen, G., Keller, R., Thimmel, M., & Wederhake, L. (2017). Shifting load through infinite—the economic science of spatial demand side management using distributed data centers. Energy Policy, 109, 400–413. https://doi.org/ten.1016/j.enpol.2017.07.018.

    Article  Google Scholar

  • Fulpagare, Y., & Bhargav, A. (2015). Advances in data center thermal direction. Renewable and Sustainable Energy Reviews, 43, 981–996. https://doi.org/x.1016/j.rser.2014.11.056.

    Article  Google Scholar

  • Garimella, S. V., Persoons, T., Weibel, J. and Yeh, L. T. (2013) 'Technological drivers in data centers and telecom systems: multiscale thermal, electric, and energy management', Practical Energy, pp. 66–80. https://doi.org/10.1016/j.apenergy.2013.02.047.

  • Ghatikar, G., Piette, Thou. A., Fujita, S., McKane, A., Dudley J. H., Radspieler, A., Mares, K. C. and Shroyer, D. (2010) Demand response and open automatic demand response opportunities for data centers, Lawrence Berkeley National Laboratory.

  • Ghatikar, G., Ganti, 5. and Matson, Due north. (2012) Demand response opportunities and enabling technologies for information centers: findings from field studies, Lawrence Berkeley National Laboratory.

  • Gils, H. C. (2014) Assessment of the theoretical demand response potential in Europe. Energy, 67, 1–18. https://doi.org/x.1016/j.energy.2014.02.019.

  • Grice, J. Westward., Dean, Northward. and Eddie, S. (2013) 'Sustainable site selection: the convergence of data centre site', The Green Grid. Enquiry Study, (Sustainable Site Selection), p. 20.

  • Güngör, V. C., Sahin, D., Kocak, T., Ergüt, Southward., Buccella, C., Cecati, C., & Hancke, G. P. (2011). Smart grid technologies: communication technologies and standards. IEEE Transactions on Industrial Informatics, 7(4), 529–539. https://doi.org/10.1109/TII.2011.2166794.

    Article  Google Scholar

  • Gupta, M. and Singh, S. (2003) 'Greening of the internet', Proceedings of the 2003 briefing on Applications, technologies, architectures, and protocols for estimator communications - SIGCOMM '03, pp. 19–26. https://doi.org/10.1145/863956.863959.

  • Gupta, G. and Singh, S. (2007) 'Using low-power modes for energy conservation in Ethernet LANs', In IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications, pp. 2451–2455. https://doi.org/ten.1109/INFCOM.2007.299.

  • Hammadi, A., & Mhamdi, L. (2014). A survey on architectures and energy efficiency in data heart networks. Figurer Communications, 40, i–21. https://doi.org/x.1016/j.comcom.2013.11.005.

    Article  Google Scholar

  • Härder, T., Hudlet, V., Ou, Y. and Schall, D. (2011) 'Energy efficiency is not enough, energy proportionality is needed!', DASFAA Workshops, pp. 226–239. https://doi.org/10.1007/978-iii-642-20244-5.

  • Heller, B., Seetharaman, S., Mahadevan, P., Yiakoumis, Y., Sharma, P., Banerjee, S. and McKeown, N. (2010) 'ElasticTree: saving free energy in data center networks', Proceedings of the 7th USENIX Conference on Networked Systems Design and Implementation, pp. 17–17. https://doi.org/10.1021/ci2004779.

  • Hermenier, F., Lorca, X., Menaud, J.-M., Muller, G. and Lawall, J. (2009) 'Entropy: a consolidation director for clusters', Proceedings of the 2009 ACM SIGPLAN/SIGOPS international conference on Virtual execution environments - VEE '09, p. 41. https://doi.org/x.1145/1508293.1508300.

  • Iec (2013) 'Uninterruptible power systems (UPS)—part i: full general and prophylactic requirements for UPS.' International Electrotechnical Commission. Reference number. IEC 62040–1.

  • International Free energy Agency (2014) 'Energy supply security 2014 Part 3', Energy supply security: the emergency response of IEA countries—2014 Edition, pp. 1–105.

  • Irwin, D., Sharma, N. and Shenoy, P. (2011) 'Towards continuous policy-driven demand response in data centers', Proceedings of the 2nd ACM SIGCOMM workshop on Green networking - GreenNets '11, p. 19. https://doi.org/10.1145/2018536.2018541.

  • Islam, M. A., Arafath, M. Y. and Hasan, Thou. J. (2015) 'Blueprint of DDR4 SDRAM controller', 8th International Conference on Electrical and Computer Engineering: Advancing Technology for a Better Tomorrow, ICECE 2014, pp. 148–151. https://doi.org/ten.1109/ICECE.2014.7026950.

  • JEDEC (2017) 'JEDEC DDR5 & NVDIMM-P standards under development', JEDEC's Server Forum.

  • Jiang, T., Yu, 50. and Cao, Y. (2015) Energy management of net data centers in smart grid. Springer. https://doi.org/10.1007/978-3-662-45676-vii.

  • Jin, M., Feng, W., Liu, P., Marnay, C., & Spanos, C. (2017a). Modern-DR: microgrid optimal dispatch with need response. Applied Energy, 187, 758–776. https://doi.org/x.1016/j.apenergy.2016.11.093.

    Commodity  Google Scholar

  • Jin, M., Feng, W., Marnay, C., & Spanos, C. (2017b). Microgrid to enable optimal distributed energy retail and end-user need response. Practical Free energy., 210, 1321–1335. https://doi.org/10.1016/j.apenergy.2017.05.103.

    Article  Google Scholar

  • Johannah, J. J., Korah, R., Kalavathy, Grand., & Sivanandham. (2017). Standby and dynamic ability minimization using enhanced hybrid power gating structure for deep-submicron CMOS VLSI. Microelectronics Journal, 62, 137–145. https://doi.org/10.1016/j.mejo.2017.02.003.

    Commodity  Google Scholar

  • Josh, Due west. and Delforge, P. (2014) Information center efficiency assessment: scaling upwardly energy efficiency across the data middle industry: evaluating key drivers and barriers. NRDC and Anthesis.

  • Judge, J., Pouchet, J., Ekbote, A. and Dixit, S. (2008) 'Reducing information heart energy consumption', ASHRAE Journal, 50(Nov).

  • Khan, 1000. U. S., & Khan, South. U. (2015). Smart data center. In Handbook on information centers (pp. 247–262). New York: Springer New York. https://doi.org/ten.1007/978-1-4939-2092-1_7.

    Google Scholar

  • Kim, J. (2016) Strong, thorough, and efficient memory protection against existing and emerging DRAM errors. University of Texas.

  • Kim, J., Sabry, M. Grand., Ruggiero, M., & Atienza, D. (2015). Ability-thermal modeling and control of free energy-efficient servers and datacenters. In Handbook on data centers (pp. 857–913). New York: Springer New York. https://doi.org/10.1007/978-1-4939-2092-1_29.

    Google Scholar

  • Koomey. (2011). Growth in data eye electricity use 2005 to 2010 (p. 3). Oakland: Analytics Press. https://doi.org/10.1088/1748-9326/three/iii/034008.

    Google Scholar

  • Krzywda, J., Ali-Eldin, A., Carlson, T. Eastward., Östberg, P.-O., & Elmroth, Eastward. (2017). Power-performance tradeoffs in data eye servers: DVFS, CPU pinning, horizontal, and vertical scaling. Future Generation Computer Systems., 81, 114–128. https://doi.org/10.1016/j.hereafter.2017.10.044.

    Article  Google Scholar

  • Lee, K. P., & Chen, H. 50. (2013). Analysis of free energy saving potential of air-side gratuitous cooling for data centers in worldwide climate zones. Energy and Buildings, 64, 103–112. https://doi.org/10.1016/j.enbuild.2013.04.013.

    Article  Google Scholar

  • Lei, H., Wang, R., Zhang, T., Liu, Y., & Zha, Y. (2016). A multi-objective co-evolutionary algorithm for energy-efficient scheduling on a green information center. Computers and Operations Research, 75, 103–117. https://doi.org/x.1016/j.cor.2016.05.014.

    MathSciNet  Article  MATH  Google Scholar

  • Li, J., Bao, Z., & Li, Z. (2015). Modeling demand response adequacy past internet data centers processing batch calculating jobs. IEEE Transactions on Smart Filigree, 6(ii), 737–747. https://doi.org/10.1109/TSG.2014.2363583.

    Commodity  Google Scholar

  • Lim, South.-H., Huh, J.-Southward., Kim, Y., & Das, C. R. (2011). Migration, consignment, and scheduling of jobs in virtualized surroundings. HotCloud, 2011, 1–5.

    Google Scholar

  • Liu, Z., Wierman, A., Chen, Y., Razon, B. and Chen, N. (2013) 'Data center demand response: avoiding the coincident height via workload shifting and local generation', Functioning Evaluation. Elsevier B.V., 70(10), pp. 770–791. https://doi.org/10.1016/j.peva.2013.08.014.

  • Liu, Z., Liu, I., Low, Southward., & Wierman, A. (2014). Pricing information center demand response. Acm Sigmetrics, 42, 111–123. https://doi.org/ten.1145/2591971.2592004.

    Article  Google Scholar

  • Lu, T., Pande, P. P., & Shirazi, B. (2016). A dynamic, compiler guided DVFS mechanism to achieve energy-efficiency in multi-core processors. Sustainable Computing: Computer science and Systems, 12, 1–9. https://doi.org/10.1016/j.suscom.2016.04.003.

    Google Scholar

  • Masanet, E. R., Brown, R. East., Shehabi, A., Koomey, J. K., & Nordman, B. (2011). Estimating the energy utilisation and efficiency potential of U.S. information centers. Proceedings of the IEEE, 99, 1440–1453. https://doi.org/10.1109/JPROC.2011.2155610.

    Article  Google Scholar

  • Mazumdar, S., & Pranzo, M. (2017). Ability efficient server consolidation for cloud information center. Future Generation Estimator Systems, lxx, four–16. https://doi.org/10.1016/j.time to come.2016.12.022.

    Article  Google Scholar

  • Moreno-Munoz, A., De La Rosa, J. J. G., Pallarés-Lopez, V., Real-Calvo, R. J., & Gil-De-Castro, A. (2011). Distributed DC-UPS for free energy smart buildings. Energy and Buildings, 43(1), 93–100. https://doi.org/10.1016/j.enbuild.2010.08.018.

    Commodity  Google Scholar

  • Moura, P., Nuttall, C., Harrison, B., Jehle, C., & de Almeida, A. (2016). Energy savings potential of uninterruptible power supplies in European Union. Free energy Efficiency, 9(v), 993–1013. https://doi.org/10.1007/s12053-015-9406-7.

    Commodity  Google Scholar

  • Nathuji, R. and Schwan, Yard. (2007) 'VirtualPower: coordinated power management in virtualized enterprise systems', Proceedings of twenty-outset ACM SIGOPS symposium on Operating systems principles - SOSP '07, p. 265. https://doi.org/10.1145/1294261.1294287.

  • Nedevschi, S., Popa, L., Iannaccone, K., Ratnasamy, S., & Wetherall, D. (2008). Reducing network energy consumption via sleeping and rate-accommodation. Symposium a quarterly journal in modern foreign literatures, 21(3), 323–336. https://doi.org/ten.11143/3471.

  • Ni, J., & Bai, X. (2017). A review of air conditioning energy performance in data centers. Renewable and Sustainable Free energy Reviews, 67, 625–640. https://doi.org/ten.1016/j.rser.2016.09.050.

    Commodity  Google Scholar

  • Oconnell, North., Pinson, P., Madsen, H., & Omalley, M. (2014). Benefits and challenges of electrical demand response: a critical review. Renewable and Sustainable Energy Reviews, 39, 686–699. https://doi.org/10.1016/j.rser.2014.07.098.

    Article  Google Scholar

  • Oró, E., Depoorter, V., Garcia, A., & Salom, J. (2015). Energy efficiency and renewable energy integration in information centres. Strategies and modelling review. Renewable and Sustainable Free energy Reviews, 429, 445–445. https://doi.org/10.1016/j.rser.2014.x.035.

    Google Scholar

  • Padala, P., Hou, K.-Y., Shin, K. G., Zhu, X., Uysal, Chiliad., Wang, Z., Singhal, S. and Merchant, A. (2009) 'Automated control of multiple virtualized resources', Proceedings of the quaternary ACM European briefing on Computer systems, pp. 13–26. https://doi.org/ten.1145/1519065.1519068.

  • Panajotovic, B., Jankovic, Yard. and Odadzic, B. (2011) 'ICT and smart filigree', 2011 10th International Conference on Telecommunications in Mod Satellite, Cablevision and Broadcasting Services, TELSIKS 2011 - Proceedings of Papers, pp. 118–121. https://doi.org/10.1109/TELSKS.2011.6112018.

  • Paterakis, Due north. G., Erdinç, O. and Catalão, J. P. S. (2017) 'An overview of demand response: key-elements and international experience', Renewable and Sustainable Energy Reviews, pp. 871–891. https://doi.org/10.1016/j.rser.2016.11.167.

  • Paul, D., De Zhong, W., & Bose, Due south. K. (2017). Need response in data centers through energy-efficient scheduling and simple incentivization. IEEE Systems Periodical, 11(2), 613–624. https://doi.org/10.1109/JSYST.2015.2476357.

    Commodity  Google Scholar

  • PIER (2008) 'Uninterruptible ability supplies: A data center efficiency opportunity. Technical brief. California Energy Commission's Public Interest Energy Research (PIER) Program'.

  • Pierson, J.-G. (Ed.). (2015). Big-scale distributed systems and energy efficiency. Hoboken, NJ, USA: John Wiley & Sons, Inc.. https://doi.org/x.1002/9781118981122.

    Google Scholar

  • Pore, One thousand., Abbasi, Z., Gupta, Southward. Thousand. South., & Varsamopoulos, G. (2015). Techniques to achieve energy proportionality in data centers: a survey. In Handbook on information centers (pp. 109–162). New York: Springer. https://doi.org/x.1007/978-1-4939-2092-1_4.

    Google Scholar

  • Reiss, C., Tumanov, A., and Ganger, G. (2012) 'Towards understanding heterogeneous clouds at scale: Google trace analysis', Center for Cloud.

  • Ristic, B., Madani, K., & Makuch, Z. (2015). The h2o footprint of data centers. Sustainability, 7(8), 11260–11284. https://doi.org/10.3390/su70811260.

    Article  Google Scholar

  • Rong, H., Zhang, H., Xiao, S., Li, C. and Hu, C. (2016) 'Optimizing energy consumption for information centers', Renewable and Sustainable Energy Reviews. Elsevier, 58, pp. 674–691. https://doi.org/10.1016/j.rser.2015.12.283.

  • Salom, J., Urbaneck, T. and Oró, Due east. (2017) Advanced concepts for renewable energy supply of data centres. River publishers. https://doi.org/ten.13052/rp-9788793519411.

  • Sanders, P., Sivadasan, N. and Skutella, 1000. (2004) 'Online scheduling with bounded migration', Automata , Languages and Programming, Proceedings, pp. 1111–1122. https://doi.org/ten.1287/moor.1090.0381.

  • Shehabi, A., Tschudi, W. and Gagdil, A. (2007) Data center economizer contamination and humidity written report. Lawrence Berkeley National Laboratory.

  • Shehabi, A., Horvath, A., Tschudi, Due west., Gadgil, A. J., & Nazaroff, W. W. (2008). Particle concentrations in data centers. Atmospheric Environment, 42(24), 5978–5990. https://doi.org/10.1016/j.atmosenv.2008.03.049.

    Article  Google Scholar

  • Shehabi, A., Smith, S. J., Sartor, D. A., Brownish, R. Eastward., Herrlin, Thou., Koomey, J. G., Masanet, E. R., Horner, North., Azevedo, I. 50. and Lintner, W. (2016) 'Us data center energy usage report', Ernest Orlando Lawrence Barkeley National Laboratory, (June)

  • Sheppy, M., Lobato, C., Van Geet, O., Pless, S., Donovan, M., & Chuck, P. (2011). Reducing data center loads for a big-scale, low-energy office edifice: NREL's research support facility. Colorado: Golden.

    Volume  Google Scholar

  • SIA (2015) 'Rebooting the IT revolution: a call to action. Semiconductor Industry Clan and the Semiconductor Research Corporation', p. 40.

  • Siriwardana, J., Jayasekara, S., & Halgamuge, Southward. K. (2013). Potential of air-side economizers for information centre cooling: a case study for key Australian cities. Applied Energy, 104, 207–219. https://doi.org/ten.1016/j.apenergy.2012.10.046.

    Article  Google Scholar

  • Sithimolada, Five. and Sauer, P. Westward. (2010) 'Facility-level DC vs. typical AC distribution for data centers: a comparative reliability study', IEEE Region x Annual International Briefing, Proceedings/TENCON, pp. 2102–2107. https://doi.org/10.1109/TENCON.2010.5686625.

  • Sohel Murshed, S. M., & Nieto de Castro, C. A. (2017). A critical review of traditional and emerging techniques and fluids for electronics cooling. Renewable and Sustainable Free energy Reviews, 78, 821–833. https://doi.org/x.1016/j.rser.2017.04.112.

    Commodity  Google Scholar

  • SPEC (2016) SPECpower_ssj2008 benchmark. http://www.spec.org/power_ssj2008/results/. Accessed fourteen-01-2016.

  • Bound, N., Peterson, L., Bavier, A., & Pai, V. (2006). Using PlanetLab for network research: myths, realities, and best practices. ACM SIGOPS Operating Systems Review, forty, 17–24. https://doi.org/10.1145/1113361.1113368.

    Article  Google Scholar

  • Sueur, E. 50. and Heiser, G. (2010) 'Dynamic voltage and frequency scaling: the laws of diminishing returns', Proceedings of the 2010 international conference on ability aware calculating and systems, pp. 1–8.

  • Tang, C., Dai, Thousand. and Chuang, C.-C. (2012) 'Need response control strategies for on-campus small information centers', in Ubiquitous Intelligence & Computing and ninth International Briefing on Autonomic & Trusted Calculating (UIC/ATC), 2012 9th International Conference on, pp. 217–224. https://doi.org/x.1109/UIC-ATC.2012.97.

  • Tang, C.-J., Dai, M.-R., Chuang, C.-C., Chiu, Y.-Due south. and Lin, Due west. Due south. (2014) 'A load command method for small-scale data centers participating in demand response programs', Time to come Generation Estimator Systems. Elsevier B.V., 32, pp. 232–245. https://doi.org/x.1016/j.hereafter.2013.07.020.

  • Tang, Y., Sun, H., Wang, X., & Liu, 10. (2017). Achieving convergent causal consistency and high availability for deject storage. Time to come Generation Figurer Systems, 74, 20–31. https://doi.org/10.1016/j.future.2017.04.016.

    Article  Google Scholar

  • Tesauro, Grand., Jong, N. K., Das, R. and Bennani, Thousand. N. (2006) 'A hybrid reinforcement learning arroyo to autonomic resource allotment', In Proceedings of the IEEE International Conference on Autonomic Computing, 2006. ICAC'06., pp. 65–73. https://doi.org/10.1109/ICAC.2006.1662383.

  • The Light-green Grid (2016) 'The green filigree'. http://www.thegreengrid.org.

  • Thekkilakattil, A., Pillai, A. S., Dobrin, R. and Punnekkat, S. (2010) 'Preemption control using frequency scaling in fixed priority scheduling', In 2010 IEEE/IFIP International Briefing on Embedded and Ubiquitous Computing. IEEE, pp. 281–288. https://doi.org/x.1109/EUC.2010.47.

  • Tran, Due north., Ren, South., Han, Z., Man Jang, Due south., Il Moon, S. and Seon Hong, C. (2014) 'Demand response of information centers: a existent-time pricing game between utilities in smart grid', 9th International Workshop on Feedback Computing.

  • Tsirogiannis, D., Harizopoulos, Southward. and Shah, G. a (2010) 'Analyzing the energy efficiency of a database server', the 2010 International Conference, p. 231. https://doi.org/10.1145/1807167.1807194.

  • Uddin, M., & Rahman, A. A. (2012). Energy efficiency and low carbon enabler light-green It framework for data centers considering green metrics. Renewable and Sustainable Energy Reviews, 16, 4078–4094. https://doi.org/10.1016/j.rser.2012.03.014.

    Article  Google Scholar

  • Uddin, M., Darabidarabkhani, Y., Shah, A., & Memon, J. (2015). Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: a review. Renewable and Sustainable Energy Reviews, 51, 1553–1563. https://doi.org/10.1016/j.rser.2015.07.061.

    Article  Google Scholar

  • Urgaonkar, B., Shenoy, P., Chandra, A., Goyal, P., & Wood, T. (2008). Active dynamic provisioning of multi-tier net applications. ACM Transactions on Autonomous and Adaptive Systems, 3(i), 1–39. https://doi.org/ten.1145/1342171.1342172.

    Article  Google Scholar

  • Van Heddeghem, W., Lambert, S., Lannoo, B., Colle, D., Pickavet, M. and Demeester, P. (2014) 'Trends in worldwide ICT electricity consumption from 2007 to 2012', Computer Communications Elsevier B.V., 50, pp. 64–76. https://doi.org/10.1016/j.comcom.2014.02.008.

  • Vanson-Bourne (2011) V-index: virtualization penetration charge per unit in the enterprise. Available at: http://www.five-alphabetize.com/full-study.html.

  • Varrette, Due south., Bouvry, P., Jarus, M., & Oleksiak, A. (2015). Free energy efficiency in HPC information centers: latest advances to build the path to Exascale. In Handbook on data centers (pp. 81–107). New York: Springer. https://doi.org/10.1007/978-1-4939-2092-1_3.

    Google Scholar

  • Vasques, T., Moura, P. and Almeida, A. de (2017) 'Energy efficiency insight into small and medium data centres: a comparative assay based on a survey', 13th European Council for an Free energy Efficient Economic system Summer Study on energy efficiency (ECEEE 2017), Presqu'île de Giens (France), 29th May - tertiary June.

  • Verma, A., Koller, R., Useche, 50. and Rangaswami, R. (2010) 'SRCMap: Energy proportional storage using dynamic consolidation', FAST'10 Proceedings of the eighth USENIX conference on File and storage technologies, (VM), p. xx.

  • vor dem Berge, M., Buchholz, J., Cupertino, L., Da Costa, Chiliad., Donoghue, A., Gallizo, One thousand., Jarus, One thousand., Lopez, 50., Oleksiak, A., Pages, E., Piątek, Due west., Pierson, J.-Thousand., Piontek, T., Rathgeb, D., Salom, J., Sisó, L., Volk, E., Wössner, U., & Zilio, T. (2015). CoolEmAll: models and tools for planning and operating energy efficient data Centres. In Handbook on information centers (pp. 191–245). New York: Springer New York. https://doi.org/ten.1007/978-ane-4939-2092-1_6.

    Google Scholar

  • Wang, C. and De Groot, M. (2013) 'Enabling demand response in a computer cluster', 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013, pp. 181–186. https://doi.org/10.1109/SmartGridComm.2013.6687954.

  • Wang, X., & Wang, Y. (2011). Coordinating power control and performance management for virtualized server clusters. IEEE Transactions on Parallel and Distributed Systems, 22(2), 245–259. https://doi.org/x.1109/TPDS.2010.91.

    Commodity  Google Scholar

  • Wang, P., Huang, J. Y., Ding, Y., Loh, P. and Goel, L. (2011) 'Demand side load management of smart grids using intelligent trading/metering/billing system', 2011 IEEE Trondheim PowerTech, pp. 1–6. https://doi.org/10.1109/PTC.2011.6019420.

  • Wang, D., Ren, C., Sivasubramaniam, A., Urgaonkar, B., & Fathy, H. (2012). Free energy storage in datacenters: what, where and how much. ACM SIGMETRICS Performance Evaluation Review, 40(one), 187. https://doi.org/x.1145/2318857.2254780.

    Article  Google Scholar

  • Wang, C., Urgaonkar, B., Wang, Q. and Kesidis, G. (2013) 'A hierarchical demand response framework for data center ability cost optimization nether real-earth electricity pricing', pp. 1–10.

  • Wang, H., Huang, J., Lin, X., & Mohsenian-Rad, H. (2016). Proactive demand response for data centers: a win-win solution. IEEE Transactions on Smart Grid, 7(three), 1584–1596. https://doi.org/10.1109/TSG.2015.2501808.

    Commodity  Google Scholar

  • Wang, B., Chen, C., He, L., Gao, B., Ren, J., Fu, Z., Fu, S., Hu, Y., & Li, C. T. (2017a). Modelling and developing conflict-aware scheduling on large-scale information centres. Future Generation Reckoner Systems., 86, 995–1007. https://doi.org/10.1016/j.time to come.2017.07.043.

    Article  Google Scholar

  • Wang, Y., Brun, E., Malvagi, F. and Calvin, C. (2017b) 'Competing energy lookup algorithms in Monte Carlo neutron transport calculations and their optimization on CPU and Intel MIC architectures', Periodical of Computational Science. https://doi.org/10.1016/j.jocs.2017.01.006.

  • Whitney, J. and Delforge, P. (2014) 'Data centre efficiency assessment scaling upwards energy efficiency beyond the information eye industry: evaluating key drivers and barriers', (August).

  • Wiboonrat, Grand. (2012) 'Adjacent generation data center design under smart grid', Ubiquitous and Hereafter Networks (ICUFN), 2012 Fourth International Conference on, pp. 103–108. https://doi.org/x.1109/ICUFN.2012.6261673.

  • Wierman, A., Liu, Z., Liu, I. and Mohsenian-Rad, H. (2014) 'Opportunities and challenges for information center demand response', International Green Computing Conference. IEEE, pp. 1–10. https://doi.org/x.1109/IGCC.2014.7039172.

  • Zakarya, M., & Gillam, L. (2017). Free energy efficient computing, clusters, grids and clouds: a taxonomy and survey. Sustainable Computing: Computer science and Systems, 14, 13–33. https://doi.org/ten.1016/j.suscom.2017.03.002.

    Google Scholar

  • Zhang, H., Shao, S., Xu, H., Zou, H., & Tian, C. (2014). Costless cooling of information centers: a review. Renewable and Sustainable Energy Reviews, 35, 171–182. https://doi.org/10.1016/j.rser.2014.04.017.

    Article  Google Scholar

  • Zhu, W., Garrett, D., Butkowski, J., & Wang, Y. (2012). Overview of distributive energy storage systems for residential communities', 2012 IEEE Energytech. Energytech, 2012(1), 1–half-dozen. https://doi.org/10.1109/EnergyTech.2012.6304671.

    Google Scholar

  • Zhu, K., Cui, Z., Wang, Y., Li, H., Zhang, 10., & Franke, C. (2017). Estimating the maximum energy-saving potential based on IT load and Information technology load shifting. Energy, 138, 902–909. https://doi.org/10.1016/j.energy.2017.07.092.

    Article  Google Scholar

  • Zhuravlev, S., Saez, J. C., Blagodurov, S., Fedorova, A., & Prieto, M. (2013). Survey of energy-cognizant scheduling techniques. Parallel and Distributed Systems, IEEE Transactions on, 24(vii), 1447–1464. https://doi.org/10.1109/TPDS.2012.20.

    Article  Google Scholar

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Funding

The present work was supported by CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brazil).

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  1. Establish of Systems and Robotics, Department of Electric and Computer Engineering, University of Coimbra, Coimbra, Portugal

    Thiago Lara Vasques, Pedro Moura & Aníbal de Almeida

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Vasques, T.L., Moura, P. & de Almeida, A. A review on energy efficiency and demand response with focus on small-scale and medium data centers. Energy Efficiency 12, 1399–1428 (2019). https://doi.org/10.1007/s12053-018-9753-2

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Keywords

  • Data centers
  • Data and advice technologies
  • Energy efficiency
  • Demand response

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