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Energy Consumption Issues of a Data Center

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Machine Intelligence and Emerging Technologies (MIET 2022)

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Abstract

Nowadays, local or private data centers are a revolution that is developing rapidly. Many companies and educational organizations are building local data centers for security reasons. However, the energy consumption issues of data centers are rapidly increasing which needs to be addressed to develop green data centers. Many methods and techniques had been developed for minimizing the energy consumption of data centers. In this paper, an energy-efficient proposed model has been suggested for East West university’s local data center for upgrading to a green data center. It is found that approximately 20% to 30% of energy will be saved after redesigning the data center.

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References

  1. Cholli, N.G.: Green Cloud computing: redefining the future of cloud computing. Int. Res. J. Adv. Sci. Hub 3, 12–19 (2021)

    Article  Google Scholar 

  2. Depavath, H., Ramesh, K.B., Chithra, B., Ramana, M.V.: Green computing-an efficient eco friendly computing, vol. 2, no. 08, August 2015

    Google Scholar 

  3. Atrey, A., Jain, N., Iyengar, N.: A study on green cloud computing. Int. J. Grid Distrib. Comput. 6(6), 93–102 (2013)

    Article  Google Scholar 

  4. Managıng and Understandıng On-Premıses and Cloud Spend. https://www.softwareone.com/en-ie/downloads/global/research-report-on-premises-and-cloud-spend. Accessed 11 Jan 2022

  5. Yang, J., Xiao, W., Jiang, C., Hossain, M.S., Muhammad, G., Amin, S.U.: AI-powered green cloud and data center. IEEE Access 7, 4195–4203 (2018)

    Article  Google Scholar 

  6. Yadav, A.K., Garg, M.L, Ritika: The ıssues of energy efficiency in cloud computing based data centers. Oryzae. Biosc. Biotech. Res. Comm. 12(2) (2019)

    Google Scholar 

  7. Diouani, S., Medromi, H.: Survey: an optimized energy consumption of resources in cloud data centers. Int. J. Comput. Sci. Inf. Secur. (IJCSIS) 16(2) (2018)

    Google Scholar 

  8. Buyya, R., Gill, S.S.: Sustainable cloud computing: foundations and future directions. arXiv preprint arXiv:1805.01765 (2018)

  9. Derdus, K.M., Omwenga, V.O., Ogao, P.J.: Causes of energy wastage in cloud data centre servers: a survey (2019)

    Google Scholar 

  10. Helfert, M., Desprez, F., Ferguson, D., Leymann, F. (eds.): CLOSER 2013. CCIS, vol. 453. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11561-0

    Book  Google Scholar 

  11. Diaconescu, D., Pop, F., Cristea, V.: Energy-aware placement of VMs in a datacenter. In: 2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP), pp. 313–318. IEEE (2013)

    Google Scholar 

  12. Li, L.: Energy consumption management of virtual cloud computing platform. IOP Conf. Ser. Earth Environ. Sci. 94(1) (2017)

    Google Scholar 

  13. Dumitrescu, C., Plesca, A., Dumitrescu, L., Adam, M., Nituca, C., Dragomir, A.: Assessment of data center energy efficiency methods and metrics. In: 2018 International Conference and Exposition on Electrical And Power Engineering (EPE), pp. 0487–0492. IEEE (2018)

    Google Scholar 

  14. Yadav, R., Zhang, W., Chen, H., Guo, T.: Mums: energy-aware VM selection scheme for cloud data center. In: 2017 28th International Workshop on Database and Expert Systems Applications (DEXA), pp. 132–136. IEEE (2017)

    Google Scholar 

  15. Ali, R., Shen, Y., Huang, X., Zhang, J., Ali, A.: VMR: virtual machine replacement algorithm for QoS and energy-awareness in cloud data centers. In: 2017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC), vol. 2, pp. 230–233. IEEE (2017)

    Google Scholar 

  16. Khoshkholghi, M.A., Derahman, M.N., Abdullah, A., Subramaniam, S., Othman, M.: Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers. IEEE Access 5, 10709–10722 (2017)

    Article  Google Scholar 

  17. Berl, A., et al.: Energy-efficient cloud computing. Comput. J. 53(7), 1045-1051 (2010)

    Google Scholar 

  18. Adhikary, T., Das, A.K., Razzaque, M.A., Sarkar, A.J.: Energy-efficient scheduling algorithms for data center resources in cloud computing. In: 2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing, pp. 1715–1720. IEEE (2013)

    Google Scholar 

  19. Babu, G.P., Tiwari, A.K.: Energy efficient scheduling algorithm for cloud computing systems based on prediction model. Int. J. Adv. Network. Appl. 10(5), 4013–4018 (2019)

    Google Scholar 

  20. Basmadjian, R., Meer, H.D., Lent, R., Giuliani, G.: Cloud computing and its interest in saving energy: the use case of a private cloud. J. Cloud Comput. Adv. Syst. Appl. 1(1), 1–25 (2012)

    Article  Google Scholar 

  21. Singh, S., Sharma, P.K., Moon, S.Y., Park, J.H.: EH-GC: an efficient and secure architecture of energy harvesting Green cloud infrastructure. Sustainability 9(4), 673 (2017)

    Article  Google Scholar 

  22. Madani, N., Lebbat, A., Tallal, S., Medromi, H.: Power-aware virtual Machines consolidation architecture based on CPU load scheduling. In: 2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA), pp. 361–365. IEEE (2014)

    Google Scholar 

  23. Gao, J.: Machine learning applications for data center optimization (2014)

    Google Scholar 

  24. Wang, J., Zhou, B., Liu, W., Hu, S.: Research progress and development trend of cross-layer energy efficiency optimization in data centers. SCIENTIA SINICA Inf. 50(1), 1–24 (2020)

    Article  Google Scholar 

  25. Pries, R., Jarschel, M., Schlosser, D., Klopf, M., Tran-Gia, P.: Power consumption analysis of data center architectures. In: Rodrigues, J.J.P.C., Zhou, L., Chen, M., Kailas, A. (eds.) GreeNets 2011. LNICSSITE, vol. 51, pp. 114–124. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33368-2_10

    Chapter  Google Scholar 

  26. Rais, M.Z.: Design of green data center. Int. J. Res. Eng. Technol. (IJRET) 03(05) (2014)

    Google Scholar 

  27. Kass, S., Ravagni, A.: Designing and building the next generation of sustainable data centers. Sustain. Dev. Goals, 1–21 (2019)

    Google Scholar 

  28. Mukherjee, D., Chakraborty, S., Sarkar, I., Ghosh, A., Roy, S.: A detailed study on data centre energy efficiency and efficient cooling techniques. Int. J. 9(5) (2020)

    Google Scholar 

  29. Peoples, C., Parr, G., McClean, S., Morrow, P., Scotney, B.: Energy aware scheduling across ‘green’ cloud data centres. In: IEEE International Symposium on Integrated Network Management, pp. 876–879 (2013)

    Google Scholar 

  30. https://www.42u.com/measurement/pue-dcie.htm

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Authors and Affiliations

  1. Department of Computer Science and Engineering, East West University, Dhaka, Bangladesh

    Nabila Islam, Lubaba Alam Chhoa & Ahmed Wasif Reza

Authors
  1. Nabila Islam
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  2. Lubaba Alam Chhoa
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  3. Ahmed Wasif Reza
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Corresponding author

Correspondence to Ahmed Wasif Reza .

Editor information

Editors and Affiliations

  1. Noakhali Science and Technology University, Noakhali, Bangladesh

    Md. Shahriare Satu

  2. The University of Queensland, St. Lucia, QLD, Australia

    Mohammad Ali Moni

  3. Jahangirnagar University, Dhaka, Bangladesh

    M. Shamim Kaiser

  4. Daffodil International University, Dhaka, Bangladesh

    Mohammad Shamsul Arefin

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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Islam, N., Chhoa, L.A., Reza, A.W. (2023). Energy Consumption Issues of a Data Center. In: Satu, M.S., Moni, M.A., Kaiser, M.S., Arefin, M.S. (eds) Machine Intelligence and Emerging Technologies. MIET 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 491. Springer, Cham. https://doi.org/10.1007/978-3-031-34622-4_55

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  • DOI: https://doi.org/10.1007/978-3-031-34622-4_55

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-34621-7

  • Online ISBN: 978-3-031-34622-4

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