Shima Sokout JAHROMI, Mansourr AMINILARI, Amin TOUSI
2.269 502


Abstract. Data centers are one of the major components of ICT field that have had significant growth to meet the needs of this area. In addition, the data centers are a computational resource for cloud computing and to have a good response time for a large number of their customers are often comprised of thousands of servers. In such a large scale, the energy consumption of data centers has increased extraordinarily. Increasing the power of consumption leads to increasing operational costs as well as greenhouse gas emissions. Thus, optimizing energy consumption in data centers is essential to reduce operational costs and protect the environment. Servers consume considerable amount of energy in cloud data center, thus optimizing the energy consumption of them has a significant role in reducing energy consumption. This paper provides a comprehensive study of the green metrics in the fields of energy efficiency in data centers, then classifies energy optimization approaches of servers in the data center and also provides a comprehensive review of techniques and their applications in each approach of   recent research.  


Cloud computing, data center, energy efficiency, performance metric

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Koomey, J.G. )2007(. “Estimating Total Power Consumption by Servers in the US and the World”. Final report. 2 (3): 1-31.

Barroso, L. (2005). “The Price of Performance”, ACM Press, 3(7): 48- 53.

Sokout jahromi, S., Aminilari, M., Toosi, A. (2014). “Approaches to energy consumption management in cloud computing data centers", 4th International Conference on Information Technology Management, Communication and Computer, Tehran, IRAN, pp-183-191.

Katz, R. H. (2009). “Tech Titans Building Boom.”. IEEE Spectrum, 46(2): 40–54.

Wadhwa, B., and Verma, A. (2014). “Energy Saving Approaches for Green Cloud Computing: A Review”, IEEE Recent Advances in Engineering and Computational Sciences, 2(3): 1-6.

Holzle, U., Clidaras, J., and Barroso, L. A.( 2013). The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines (2nd Ed.). New York: Morgan and Claypool Publishers.

Malone, C. Belady, C. (2006). “Metrics to Characterize Data Center & IT Equipment Energy Use”. Proceedings of 2006 Digital Power Forum, pp:34-45.

Kulseitova, A., and Fong , T. (2013). “A survey of energy-efficient techniques in cloud data centers”. IEEE International Conference on ICT for Smart Society, Jakarta ,June, pp. 1-5.

Dumitru. I., Fagarasan: I., Iliescu. S. Said, Y.H., and Ploix. S., 2011. “Increasing Energy Efficiency in Data Centers using Energy Management”, IEEE/ACM International Conference on Green Computing and Communications, Aug, pp. 159-165

Azevedo, D., Cooley, J., Patterson, M. and Blackburn, M., 2011. “Data Center Efficiency Metrics: mPUE, Partial PUE, ERE, DCcE”. The Green Grid Presentation, 2(3): 1-37

Sullivan. A. (2010). ENERGY STAR R for Data Centers. U.S. Environmental Protection Agency, presentation, on the WWW, URL development/downloads/DataCenters GreenGrid02042010.pdf

Stansberry, M., and Kudritzki, J.(2012). “Uptime Institute 2012 Data Center Industry Survey”. Technical

The Green Grid in its white paper. (2007). “The Green Grid Data Center Power Efficiency Metrics: PUE and DCiE”. pp. 1-16. See also URL content/uploads/TGG_Data_Center_Power_Efficiency_Metrics_PUE_and_DCiE.pdf

Belady, C.L., and Malone, CG. (2007).“Metrics and an Infrastructure Model to Evaluate Data Center Efficiency” ASME 2007 InterPACK Conference, 1, Vancouver, British Columbia, Canada, July, pp. 751-755.

Mathew, P., Ganguly, S., Greenberg, S., and Sartor, D.( 2009). “Self-benchmarking Guide for Data Centers: Metrics, Benchmarks, Actions”. Environmental Energy Technologies Division,2(4): 1-31.

Zhou, R., Shi, Y., and Zhu, C.(2013). “AxPUE: Application Level Metrics for Power Usage”. IEEE International Conference on Big data , 5(4): 110-117.

Wilde, T., Auweter, A., Pattersony. M.K., Shoukourian, H., Huber, H., Bodez, A., Labrenz, D., and Cavazzonix, C.(2014). “DWPE,a new data center energy-efficiency metric bridging the gap between infrastructure and workload”. IEEE International Conference on High Performance Computing & Simulation (HPCS), Bologna ,pp.893-901.

Thereska, E., Donnelly, A., Narayanan, D.( 2011). “Sierra: Practical Power-proportionality for Data Center Storage”. Proceedings of the sixth conference on Computer systems EuroSys '11, New York, NY, USA ,pp 169-182

Barroso, LA., and Holzle, U.(2007). “The case for energy proportional computing”. ComputerJournal, 40(12): 33–37.

Albers, S., Antoniadis, A.(2012). “Race to idle: new algorithms for speed scaling with a sleep state”. SODA '12 Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms, pp 1266-1285.

Beloglazov, A., Buyya, R., Choon Lee, Y., and Zomaya, A.(2011). “A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems”. Advances in computers, 8(82) 47-108.

Rizvandi, N.B., Taheri, J., Zomaya, A.Y., and Lee, Y.(2010). “Linear Combinations of DVFS- Enabled Processor Frequencies to Modify the Energy-Aware Scheduling Algorithms. Cluster, Cloud and Grid Computing”. 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGrid) , Melbourne, Australia, pp. 388-397.

Anagnostopoulou, V., Biswas, S., Saadeldeen, H., Savage, A., Bianchini, R., Yang, T., Franklin, D., and Chong. F.T.( 2012). “Barely alive memory servers: Keeping data active in a low power state”, Journal on Emerging Technologies in Computing Systems, 8(4), pp 1-20.

Gupta, V., Brett, P., Koufaty, D., Reddy, D., Hahn, S., Schwan, K. and Srinivasa, G.(2012). “HeteroMates: Providing high dynamic power range on client devices using heterogeneous core groups”. International Green Computing Conference, San Jose, CA, USA, pp 1-10.

Vasudevan, V., Andersen, D., Kaminsky, M., Tan, L., Franklin,. J. and Moraru, I.(2010). “Energy efficient cluster computing with FAWN: workloads and implications”. 1st International Conference on Energy Efficient Computing and Networking, pages Passau, Germany, pp 195- 204.

Meisner, D., Wenisch, T.F.(2011). “Does Low-Power Design Imply Energy Efficiency for Data Centers?”, International Symposium on Low Power Electronics and Design, Fukuoka, pp 109- 114.

Isci. C., McIntosh, S., Kephart, J., Das, R., Hanson, J., Piper,. S., Wolford, R,. Brey, T., Kanter, R., Ng, A., Norris, J., Traore, A., and Frissora, M.( 2013). “Agile Efficient Virtualization Power Management with Low-latency Server Power States”. ACM SIGARCH Computer Architecture News - ICSA '13, 41(3):96-107.

Song, Y., Zhang. Y., Sun. Y., Shi. W.(2009). “Utility analysis for Internet-oriented server consolidation in VM-based data centers”. IEEE International Conference on Cluster Computing and Workshops, New Orleans, LA, pp.1-10.

Bari, Md. F., Boutaba, R., Esteves, R., Granville. L. Z., Podlesny. M., Rabbani. M. G., Zhang, Q., and Zhani, M. F.(2013). “Data Center Network Virtualization: A Survey”. IEEE communications surveys & tutorials, 15(2): 909-928.

Li, Y., Li, W., Jiang, C.(2010). “A Survey of Virtual Machine System: Current Technology and Future Trends”. Third International Symposium on Electronic Commerce and Security, Guangzhou, pp. 332-336