Green Cloud Computing: Some Studies on Energy Usage Reduction Methods


V. Venkata Sai Lakshmi,Dept. of Computer Science & Engineering, Vignan’s Institute of Information Technology, Visakhapatnam, AP, India
N.Thirupathi Rao,


Distributed computing center around the information figuring proficiency where as green distributed computing is another reasoning which depends on distributed computing design and concentrates on the vitality productivity of gadget and processing. Green Cloud Computing is an approach used to enhance the usage of figuring assets those are being utilized as a part of distributed computing system, for example, stockpiling, servers, its application, and benefits and decrease vitality utilization of these assets which enhances control proficiency. This is finished by different innovations, for example, virtualization and virtual machines movement. This paper surveys the different systems purposed by the distinctive creators to make distributed computing more vitality proficient. The primary target of this paper is to think about and break down the idea of vitality proficient server farm engineering, asset allotment and streamlining.



Cloud computing, Energy efficiency, Virtualization


[1]    J. Liu, F. Zhao, X. Liu, and W. He, “Challenges towards elastic power management in internet data centers,” in Distributed Computing Systems Workshops, 2009. ICDCS Workshops’ 09. 29th IEEE International Conference on 2009, pp.65-72, (2009)
[2]    G. Chen, W. He, J. Liu, S. Nath, L. Rigas, L. Xiao, et al., “Energy-Aware Server Provisioning and Load Dispatching for Connection-Intensive Internet Services,” in NSDI, pp.337-350, (2008)
[3]    J. Chabarek, J. Sommers, P. Barford, C. Estan, D. Tsiang, and S. Wright, “Power awareness in network design and routing,” in INFOCOM 2008. The 27th Conference on Computer Communications. IEEE, (2008).
[4]    C. Gunaratne, K. Christensen, B. Nordman, and S. Suen, “Reducing the energy consumption of Ethernet with adaptive link rate (ALR),” Computers, IEEE Transactions on, vol.57, pp.448-461, (2008)
[5]    J. F. Botero, X. Hesselbach, M. Duelli, D. Schlosser, A. Fischer, and H. De Meer, “Energy efficient virtual network embedding,” Communications Letters, IEEE, vol.16, pp.756-759, (2012)
[6]    A. Fischer, J. F. Botero, M. Till Beck, H. De Meer, and X. Hesselbach, “Virtual network embedding: A survey,” Communications Surveys & Tutorials, IEEE, vol.15, pp.1888- 1906, (2013)
[7]    Y. Shang, D. Li, and M. Xu, “Energy-aware routing in data center network,” in Proceedings of the first ACM SIGCOMM workshop on Green networking, pp.1-8, (2010)
[8]    P. Mahadevan, P. Sharma, S. Banerjee, and P. Ranganathan, “Energy aware network operations,” in INFOCOM Workshops 2009, IEEE, pp.1-6, (2009)
[9]    Apple. Apple Facilities Environmental Footprint Report. Available: /reports/do cs/Apple_Facilities_Report_2013.pdf, (2012)
[10]  Gandhi, M. Harchol-Balter, R. Das, and C. Lefurgy, “Optimal power allocation in server farms,” in ACM SIGMETRICS Performance Evaluation Review, pp.157-168, (2009)
[11]  R. V. Aroca and L. M. G. Goncalves, “Towards green data centers: A comparison of x86 and ARM architectures power efficiency,” Journal of Parallel and Distributed Computing, vol.72, pp.1770- 1780, (2012)
[12]  C. Guo, G. Lu, H. J. Wang, S. Yang, C. Kong, P. Sun, et al., “Secondnet: a data center network virtualization architecture with bandwidth guarantees,” in Proceedings of the 6th International COnference, pp.15, (2010)
[13]  J. Torres, D. Carrera, K. Hogan, R. Gavalda, V. Beltran, and N. Poggi, “Reducing wasted resources to help achieve green data centers,” in Parallel and Distributed Processing, IPDPS 2008. IEEE International Symposium on 2008, pp.1-8, (2008)
[14]  R. Subrata, A. Y. Zomaya, and B. Landfeldt, “Cooperative power-aware scheduling in grid computing environments,” Journal of Parallel and Distributed Computing, vol.70, pp.84-91, (2010)
[15]  M. Mazzucco, D. Dyachuk, and R. Deters, “Maximizing cloud providers’ revenues via energy aware allocation policies,” in Cloud Computing (CLOUD), 2010 IEEE 3rd International Conference on 2010, pp.131-138, (2010)
[16]  I. Fujiwara, K. Aida, and I. Ono, “Marketbased Resource Allocation for Distributed Computing,” vol.2009, pp.1-6, (2009)
[17]  B. Li, J. Li, J. Huai, T. Wo, Q. Li, and L. Zhong, “Enacloud: An energy-saving application live placement approach for cloud computing environments,” in Cloud Computing, 2009, CLOUD’09. IEEE International Conference on 2009, pp.17-24, (2009)
[18]  L. Liu, H. Wang, X. Liu, X. Jin, W. B. He, Q. B. Wang, et al., “GreenCloud: a new architecture for green data center,” in Proceedings of the 6th international conference industry session on Autonomic computing and communications industry session, pp.29-38, (2009)


  • APA:
    Lakshmi,V.V.S.& Rao,N.T.(2018). Green Cloud Computing: Some Studies on Energy Usage Reduction Methods . International Journal of Smart Home , 12(2), 7-16. 10.21742/IJSH.2018.12.2.02
  • Harvard:
    Lakshmi,V.V.S., Rao,N.T.(2018). "Green Cloud Computing: Some Studies on Energy Usage Reduction Methods ". International Journal of Smart Home , 12(2), pp.7-16. doi:10.21742/IJSH.2018.12.2.02
  • IEEE:
    [1] V.V.S.Lakshmi, N.T.Rao, "Green Cloud Computing: Some Studies on Energy Usage Reduction Methods ". International Journal of Smart Home , vol.12, no.2, pp.7-16, Jun. 2018
  • MLA:
    Lakshmi V. Venkata Sai and Rao N.Thirupathi. "Green Cloud Computing: Some Studies on Energy Usage Reduction Methods ". International Journal of Smart Home , vol.12, no.2, Jun. 2018, pp.7-16, doi:10.21742/IJSH.2018.12.2.02


  • Volume 12, No. 2, 2018
  • ISSN(p):1975-4094
  • ISSN(e):2383-725X
  • Published:Jun. 2018