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Achieving Energy Aware Mechanism in Cloud Computing Environment

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Proceedings of International Conference on Communication and Networks

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 508))

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Abstract

Cloud Computing is an emerging technology and it provides pay-per-use computing model over the Internet without giving hassle of resource management to the users. With the increasing demand and usage of Cloud applications worldwide, the issues of energy consumption, carbon emission and operational cost require special attention. Many researchers have tried to address these issues in different facets. In this paper, we first explore few research carried out in the direction of energy efficiency. We further propose (a) architecture for energy-aware mechanism in Cloud and (b) pre-processing approach by considering Virtual Machine (VM) allocation and consolidation techniques as key factors to achieving energy efficiency in Cloud Computing.

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References

  1. P. Mell and T. Grance.: The NIST definition of cloud computing (draft), NIST special publication. vol. 800, p. 145.

    Google Scholar 

  2. R. Brown et. al.: Report to congress on server and data center energy efficiency: Public law 109-431, Lawrence Berkeley National Laboratory, 2008.

    Google Scholar 

  3. Green cloud Computing. Balancing Energy in processing, Storage and transport. Jayant Baliga W.A. Ayre, Kerry Hinton, and Rodney S. Tucker, Fellow IEEE, January 2011.

    Google Scholar 

  4. Arthi T, Shahul Hamead H.: Energy Aware Cloud Service Provisioning Approach For Green Computing Environment, in International Conference on Energy Efficient Technologies for Sustainability(ICEETS), Nagercoil, April, 2013, pp. 139–144.

    Google Scholar 

  5. Y. Han, S-S. Seo, C. Hwang, J-H. Yoo, and J.W.-K Homg.: Flow-level traffic matrix generation for various data center networks. Network IEEE Operations and Management Symposium (NOMS), pp. 1–6, 2014.

    Google Scholar 

  6. O. Fatmi, D. Pan.: Distributed multipath routing for data center networks based on stochastic traffic modeling, in Proceedings of the 2014 IEEE 11th International Conference on Networking, Sensing and Control (ICNSC), pp. 536–541,2014.

    Google Scholar 

  7. J. Loper and S. Parr. Energy efficiency in Data Centers: a new policy frontier. January 2007.[online]. Available: http://www.fypower.org/pdf/ASE_DataCenter_EE.pdf. [Accessed 10 May 2011].

  8. U.S. Environmental Protection Agency.: Report to Congress on server and Data Center energy efficiency. U.S. Environmental Protection Agency, Washington, 2007.

    Google Scholar 

  9. Kaplan, James M; Forrest, William; Kindler, Noah.: Revolutionising Data center Efficiency. McKinsey and Company, London, 2008.

    Google Scholar 

  10. The Climate Group.: SMART 2020: Enabling the low carbon economy in the information age. The Climate Group, New York, 2008.

    Google Scholar 

  11. L. Shang, L.-S. Peh, and N. K. Jha.: Dynamic voltage scaling with links for power optimization of interconnection networks, in the 9th International Symposium on High-Performance Computer Architecture (HPCA 2003), Anaheim, California, USA, 2003, pp. 91–102.

    Google Scholar 

  12. L. Benini, A. Bogliolo, and G. De Micheli.: a survey of design techniques for system-level dynamic power management. IEEE Transaction on Very Large Scale Integration(VLSI), San Jose, CA, April 2010.

    Google Scholar 

  13. C. Clark, K. Fraser, S. Hand, J. G. Hansen, E. Jul, C. Limpach, I. Pratt, and A. Warfield.: Live migration of virtual machines. In The 2nd Symposium on Networked Systems Design and Implementation (NSDI 2005), Boston, Massachusetts, USA, 2005, pp. 273–286.

    Google Scholar 

  14. Anton Beloglazov, Jemal Abawajy, Rajkumar Buyya.: Energy-aware resource allocation heuristics for efficient management of datacenters for Cloud computing. In Future Generation Computer Systems, 2012, pp. 755–768.

    Google Scholar 

  15. Chaima Ghribi, Makhlouf Hadji, Djamal Zeghlache.: Energy Efficient VM Scheduling for Cloud Data Centers: Exact allocation and migration algorithms. In 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, 2013, pp. 671–678.

    Google Scholar 

  16. Bharti Wadhwa, Amandeep Verma.: Energy saving approaches for Green Cloud Computing: A review. In Proc. of Recent Advances in Engineering and Computational Sciences, March 2014, pp. 1–6.

    Google Scholar 

  17. Anton Beloglazov, Jemal Abawajy, Rajkumar Buyya.: Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing. ELSEVIER 2012.

    Google Scholar 

  18. Anton Beloglazov, Jemal Abawajy, Rajkumar Buyya “Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing” ELSEVIER 2012

    Google Scholar 

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Correspondence to Komal Patel .

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Patel, K., Patel, H., Patel, N. (2017). Achieving Energy Aware Mechanism in Cloud Computing Environment. In: Modi, N., Verma, P., Trivedi, B. (eds) Proceedings of International Conference on Communication and Networks. Advances in Intelligent Systems and Computing, vol 508. Springer, Singapore. https://doi.org/10.1007/978-981-10-2750-5_13

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  • DOI: https://doi.org/10.1007/978-981-10-2750-5_13

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2749-9

  • Online ISBN: 978-981-10-2750-5

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