Review of Energy Minimization Strategies for Eco friendly cloud in IT
Keywords:
Cloud,optimizatio, energy efficiencyAbstract
The usage of cloud is increasing in day to day life which leads to consumption of energy.Cloud Computing with reduced energy consumption has been an important topic for the era of researchers and different computer users of computing systems. Cloud IT is an egressing technology which provides information about communication technologies, proposing new challenges for environmental protection. Green Cloud computing is a component of Green IT. The amount of carbon will be reduced with low energy consumption. This paper outlines the methods to reduce energy consumption in the cloud. To reduce the power in cloud, huge numbers of evaluations and optimizations have been done for successful energy efficiency. There are different methods to implement the cloud with minimum energy consumption like hardware, software and firmware. Hardware method includes reduction of energy in various components of cloud like server, etc. Software includes virtualization techniques, DVFS techniques, etc. Energy has to be reduced to create Eco-friendly environment.
References
[1] Jonathan Koomey, “Implications of historical trends in the electrical efficiency of computing”, IEEE Annals of the History of Computing”, vol-33, 2011.
[2] A. Elgelany, “Integrated framework for green ICT: Energy efficiency by using effective metric and efficient techniques for green data centres”, Ph.D. dissertation, Comp. Sci., Sudan University of Science & Technology, 2015.
[3] Shaden M Alismail,”Review of Energy reduction Techniques for Green Cloud Computing”, IJACSA, Vol 7,No.1,2016.
[4] Altar Ur Rahman, “Energy efficiency techniques in cloud Computing”, International Journal of CSIS, vol.14, No.6, June 2016.
[5] H. Rong,H, H.Zhang, s.xiao, c.Li and c.Hu, “optimizing energy consumption for data centers”,vole 58, pp. 674-691, 2016.
[6] R.M. Calheiros, R. Ranjan, “CloudSim: A tool kit for modelling and simulation of cloud computing environment & evaluation of resource Provisioning nalgorithms”, Journal – Software Practice & Experience, vole 41, no.1, pp. 23-50, Jan 2011.
[7] N. Kord and H. Haghighi, “An energy-efficient approach for virtual machine placement in cloud based data centers,” in Proc. 5th Information and Knowledge Technology Conf., 2013, pp. 44–49.
[8] K.H Kim, A Beloglazov,” Power aware Provisioning of virtual machines for real time cloud service”,vol.23,pp. 1491-1505, 2011.
[9] Vrunda J Patel, Hitesh Bheda,” Reducing Energy Consumption with DVFS for Real time services in Cloud Computing”,IOSR Journal of Computer Engineering, e-ISSN:2278-0661,p-ISSN:2278-8727.
[10] Liang-Teh Lee, Kang-Yuan Liu, Hui-Yang Huang and Chia-Ying Tseng “A Dynamic Resource Management with Energy Saving Mechanism for Supporting Cloud Computing” Department of Computer Science and Engineering, Tatung University, Taiwan.
[11] Florence AP, shanthi V,” Energy Conservation using Dynamic voltage frequency scaling for computational cloud”, Article, Scientific World Journal, 2016.
[12] Abdul Majeed, Munam Ali shah, “Energy Efficiency in big data Complex systems”, Article, 2194-3206, 2015.
[13] R. Shinmonski, “Windows 2000 & win server 2003 clustering & load Balancing”, CA, USA (2003), P2, 2003.
[14] Hesham Hassan,Ahmed Shawky Moussa,” Power Aware Computing Survey”, International Journal of Computer Applications,Vol -90, 2013.
[15] Dmitry Zhurikhin, Andrey Belevantsev, Arutyun Avetisyan, Kirill Batuzov, and Semun Lee, 2009, ―Evaluating power-aware optimizations within GCC compiler‖, GCC Research Opportunities workshop, GROW.
[16] Gary Cook, 2012, ―How Clean is Your Cloud? ‖ catalysing an energy revolution.
[17] Dagfinn Bach, 2012, ―MusicTank Report- Dark Side of the Tune - The Hidden Energy Cost of Digital Music.
[18] Navneet Singh, Dr Vijay Dhir, “A Literature Review: Efficient VM migration techniques for energy reduction in cloud computing”, International Journal of Advanced Research in Computer Science, Volume 8, No. 9,2017
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