Green Cloud Computing: A Step Towards Minimizing Energy Consumption
Keywords:
Green Computing, Cloud Computing, Energy Efficiency, Power ConsumptionsAbstract
With the arrival of cloud computing, enormous quantity of energy is
consumed within the cloud day by day. So, there’s a requirement for an
efficient organization of energy within the cloud environment. Energy
efficiency is a crucial aspect of Green Cloud computing. Green computing
is an unindustrialized skill that is especially wont to improve the condition
and power consumption issues. Energy consumption can be reduced
by implementing green computing within the computer fields like CPU
servers and other peripheral devices. In this paper, we’ve discussed a
number of the green computing issues, solutions and initiatives taken
to extend energy efficiency.
References
Choudhary S. A Survey on Green Computing Techniques.
Department of Computer Science, Acropolis Institute of
Technology and Research Indore bypass road Mangliya
square, SonuChoudhary / (IJCSIT) International Journal
of Computer Science and Information Technologies
; 5(5): 6248-6252.
Anwar M, Qadri SF, Sattar AR. Green Computing and
Energy Consumption Issues in the Modern Age. IOSR
Journal of Computer Engineering (IOSR-JCE) e-ISSN:
-0661, pISSN: 2278-8727 2013; 12(6): 91-98 www.
iosrjournals.org www.iosrjournals.org 91.
Singh G, Singh G. Green computing initiatives for
environmental issues”, The 2015 WEI International
Academic Conference Proceedings.
Kaur S, Ritika, Rani M. Comparative Analysis upon
Energy Efficiency between Cloud Computing and Green
Computing”, International Journal of Advanced Research
in Computer Science and Software Engineering, 2014;
(9); ISSN: 2277 128X
Liu Z, Ma R, Zhou F et al. Power-aware I/OIntensive and
CPU-Intensive Applications Hybrid Deployment within
Virtualization Environments IEEE 2010.
The green grid consortium (2011).
Beloglazov A, Buyya RK, Lee YC et al. A Taxonomy and
Survey of Energy- Efficient data centers and cloud
computing system”, Advances in Computers, 82.
Aditya et al. International Journal of Advanced Research
in Computer Science and Software Engineering 2013;
(10).
http://www.intel.com/products/processor/core2duo/
specifi cations.htm
Liangli M, Yanshen C, Yufei S et al. Virtualization
Maturity Reference Model for Green Software. Control
Engineering and Communication Technology (ICCECT),
International Conference on, 2012; 573: 576.
Rodriguez MG, Ortiz Uriarte LE, Jia Y et al. Wireless
sensor network for data-center environmental
monitoring,” Sensing Technology (ICST), 2011 Fifth
International Conference on 2011; 533: 537.
Edenhofer OR, Pichs-Madruga Y, Sokona E et al.
Global Greenhouse Gas Emissions Data by EPA – US
Environmental Protection Agency ”. IPCC (2014). Climate
Change 2014: Mitigation of Climate Change. Contribution
of Working Group III to the Fifth Assessment Report
of the Intergovernmental Panel on Climate Change
[Cambridge University Press, Cambridge, United
Kingdom, and New York, NY, USA].
Qian L, Luo Z, Du Y et al. Cloud computing: An overview,
in Proceedings of 1st International Conference on Cloud
Computing (Beijing, China, 2009: 626-631 .
http://www.asigra.com/blog/cloud-types-privatepublic- and-hybrid. [17] Judith Hurwitz, Robin Bloor,
Marcia Kaufman, Fern Halper, “Comparing public,
private, and hybrid cloud computing options”, http://
www.dummies.com/programming/networking/comp
aring-public-private-andhybrid-cloud-computingoptions/
https://www.stratalux.com/blog/comparing-publicprivate- hybrid-clouds/
https://en.wikipedia.org/wiki/Communitycloud/
https://www.stratalux.com/blog/comparing-publicprivate- hybrid-clouds/
http://www.cra.org/ccc/files/docs/init/bigdatawhite
paper.p df
http://www.computerweekly.com/feature/Improvingdata- centre-power-consumption-and-efficiency.
