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Comparison of Various Data Center Frameworks

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Applications of Artificial Intelligence and Machine Learning

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 778))

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Abstract

Our world is now becoming more attached to IT technologies. With the growing use of the Internet, there is a store and process exponential data. Data centers gained importance due to the emergence of Internet services. Data centers are responsible for the storage, management, and dissemination of data. Since the data is exponentially increasing, the data centers are more overloaded with data and their size is increasing. Since the data centers are more overloaded to fulfill the growing demands of the customers, this in turn is indirectly contributing to global pollution in terms of heavy consumption of power. Data centers consume a lot of power that is why many organizations want to design their data center their operations as green as possible. Thus, an efficient green data center framework is needed for the efficient design of data centers. To achieve this, the comparison of green data centers frameworks is being done which evaluates each of the data centers. The contrast inferred that the frameworks have the chances for enhancement in terms of components, attributes, energy-effective metrics, and implementation procedure. A new data center framework is proposed which is implemented considering the disadvantages of the existing data center frameworks.

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References

  1. Mueen U, Azizah AR (2010) Server consolidation: an approach to make data centers energy efficient & green. Int J Sci Eng Res 1(1):1–7

    Google Scholar 

  2. Daim T, Justice J, Krampits M, Letts M, Subramanian G, Thirumalai M (2009) Data center metrics: an energy efficiency model for information technology managers. Manag Environ Qual Int J 20:712–731

    Article  Google Scholar 

  3. Kant K (2009) Data center evolution: a tutorial on state of the art, issues, and challenges. Comput Netw 53(17):2939–2965

    Article  Google Scholar 

  4. Shuja J, Madani SA, Bilal K, Hayat K, Khan SU, Sarwar S (2012) Energy-efficient data centers. Computing 94(12):973–994

    Article  Google Scholar 

  5. Norhashimi BMN, Mohammed HBS (2015) Green data center frameworks and guidelines review. Int J Comput Inform Syst Ind Manag Appl 7:094–105

    Google Scholar 

  6. Kaplan JM, Forrest W, Kindler N (2008) Revolutionizing data center efficiency. McKinsey & Company, pp 1–13

    Google Scholar 

  7. Schmidt M (2020) Total cost of ownership TCO for assets and acquisitions—how to uncover the hidden costs of ownership. Business Case Analysis. [Online]. Available: https://www.business-case-analysis.com/total-cost-of-ownership.html

  8. Handlin H (2013) Using a total cost ownership (TCO) four your data centers. DataCenter Knowledge. [Online]. Available: https://www.datacenterknowledge.com/archives/2013/10/01/using-a-total-cost-of-ownership-tco-model-for-your-data-center

  9. Torsten W, Axel A, Hayk S (2014) The 4 pillar framework for energy efficient HPC data centers. Comput Sci Res Dev 29:241–251

    Article  Google Scholar 

  10. Uddin M, Abdul Rahman A, Memon J (2012) Green information technology (IT) framework for energy efficient data centers using virtualization. Int J Phys Sci 7(13):2052–2065

    Google Scholar 

  11. Norhashimi BMN, Mohd HBS (2014) Review on green data center frameworks. In: 2014 4th world congress on information and communication technologies, pp 338–343

    Google Scholar 

  12. Google Inc. (2011) Google’s green data centers: network POP case study. Google User Content. [Online]. Available: https://static.googleusercontent.com/media/www.google.com/en//corporate/datacenter/dc-best-practices-google.pdf

  13. Google Inc. Efficiency. Google Inc. [Online]. Available: https://www.google.com/about/datacenters/efficiency/index.html

  14. European Commission (2008) Code of conduct on data centres energy efficiency version 1.0. [Online]. Available: https://ec.europa.eu/information_society/activities/sustainable_growth/docs/datacenter_code-conduct.pdf

  15. Ashwin S, Kaleem AU (2014) Understanding the maturity of EU code of conduct on data centres: a Mauritian case study. In: 2014 IST-Africa conference proceedings, pp 1–16

    Google Scholar 

  16. European Union (2016) Code of conduct for energy efficiency in data centres. EU Science Hub. [Online]. Available: https://ec.europa.eu/jrc/en/energy-efficiency/code-conduct/datacentres

  17. New York State (2015) Data centers. New York State Energy Research and Development Authority. [Online]. Available: https://www.nyserda.ny.gov/Business-and-Industry/Data-Centers

  18. Aljaberi MA, Khan SN, Muammar S (2016) Green computing implementation factors: UAE case study. In: 2016 5th international conference on electronic devices, systems and applications (ICEDSA), Ras Al Khaimah, pp 1–4. https://doi.org/10.1109/ICEDSA.2016.7818528

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Kushwaha, M., Singh, A., Raina, B.L., Raghunath, A.K. (2021). Comparison of Various Data Center Frameworks. In: Choudhary, A., Agrawal, A.P., Logeswaran, R., Unhelkar, B. (eds) Applications of Artificial Intelligence and Machine Learning. Lecture Notes in Electrical Engineering, vol 778. Springer, Singapore. https://doi.org/10.1007/978-981-16-3067-5_49

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  • DOI: https://doi.org/10.1007/978-981-16-3067-5_49

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-3066-8

  • Online ISBN: 978-981-16-3067-5

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