AN IMPLEMENTATION OF CARBON EFFICIENT VM PLACEMENT AND MIGRATION TECHNIQUE IN CLOUD ENVIRONMENT
DOI:
https://doi.org/10.24297/ijct.v15i10.4521Keywords:
Cloud Computing, Power Data Center, Carbon Footprint, Load Balacing, Virtual Machine, Energy, Data Center BrokerAbstract
Electricity consumption is set to rise 76% from 2007 to 2030 and datacenters are the main contributors of an important portion of this increase, emphasizes the importance of reducing energy consumption in clouds. Increase in the level of carbon dioxide in our ecosystem is another consequence of this increasing amount of energy consumption by the datacenters. According to Gartner, the Information and communication industry produces 2% of global carbon dioxide
emission [10]. Hence, there is a great requirement of making use of more environmentally friendly computing called “Green Cloud Computing†to minimize operational and energy consumption costs and also to reduce the environmental
impact. In this paper, we have implemented the carbon efficient VM placement and migration technique in cloud sim simulator.
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References
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[3] Jianzhe Tai Juemin Zhang Jun Li Waleed Meleis Ningfang Mi “ARA: Adaptive Resource Allocation for Cloud Computing Environment under Bursty workloadâ€.
[4] Xiaolong Xu, Lingling Cao, and Xinheng Wang, Senior Member, IEEE “Adaptive Task Scheduling Strategy Based on Dynamic Workload Adjustment for Heterogeneous Hadoop Clusters.â€
[5] L. Dhivya, Ms. K. Padmave “Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environmentâ€
IJREAT International Journal of Research in Engineering & Advanced Technology, Volume 2, Issue 1,2014.
[6] Bhupendra Panchal, Prof. R. K. Kapoor “Dynamic VM Allocation Algorithm usingClustering in Cloud Computing†International Journal of Advanced Research in Computer Science and SoftwareEngineering 2013.
[7] Joseph L. Hellerstein “HARMONY: Dynamic Heterogeneity−Aware Resource Provisioning in the Cloudâ€.
[8] Malgorzata Steinder, Ian Whalley, David Carrera, Ilona Gaweda and David Chess “Server virtualization in autonomic
Management of heterogeneous workloads’.
[9] Atefeh Khosravi, Saurabh Kumar Garg, and Rajkumar Buyya“ Energy and Carbon-Efficient Placement of Virtual Machines in Distributed Cloud Data Centersâ€.
[10] Rajkumar Buyya, Anton Beloglazov1, and Jemal Abawajy “Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challengesâ€.
[11] Hong Xu, Student Member, IEEE, andBaochunLi, Senior Member, IEEE“Anchor: A Versatile and Efficient Framework for Resource Management in the Cloudâ€.
[12] Christopher Clark, Ying Song, Yuzhong Sun, Member, IEEE, andWeisong Shi, Senior Member, IEEE “A Two-Tiered On- Demand Resource Allocation Mechanism for VM-Based Data Centers†.
[13] R Suchithra “Heuristic Based Resource Allocation Using Virtual Machine Migration: A Cloud Computing Perspective†International Refereed Journal of Engineering and Science
[14] Marvin McNett, Diwaker Gupta, Amin Vahdat, and Geoffrey M. Voelker “Usher: An Extensible Framework For Managing Clusters of Virtual Machinesâ€,University of California, San Diego
[15] Zhen Xiao, Senior member, IEEE, weijia song and Qi chen “Dynamic Resource allocation using Virtual Machines For Cloud Computing Environment ,†IEEE Transaction on parallel and distributed systems, vol.24, No.6 june 2013.
[16] Alex Delis‘Nefeli: Hint-based Execution of Workloads in Clouds†International Conference on Distributed Computing Systems,2010.
[17] Kyle Chard, Member, IEEE, Kris Bubendorfer, Member, IEEE, “Social Cloud Computing: A Vision for Socially Motivated Resource Sharing†IEEE Transactions on Services Computing, VOL. 5, NO. 4, Oct-Dec 2012
[18] Weisong Shi, Senior Member, IEEE, ChuliangWeng, WenyaoZhang, and XiutaoZang“Cost-Aware Cooperative
Resource Provisioning for Heterogeneous Workloads in Data Centers†Vol. 62, NO. 11, Nov 2013.
[19] Michael Cardosa, Aameek Singh, HimabinduPucha Exploiting Spatio-Temporal “Tradeoffs for Energy-Aware
MapReduce in the Cloudâ€Vol. 61, NO. 12, Dec 2012.
[20] Anthony A. Maciejewski, Fellow, IEEE and Howard Jay Siegel, Fellow, IEEE“Power and Thermal-Aware Workload Allocation in Heterogeneous Data Centersâ€.
[21] Seematai S. Patil, KogantiBhavani“Dynamic Resource Allocation using Virtual Machines for Cloud Computing Environment†International Journal of Engineering and
Advanced Technology (IJEAT) ISSN: 2249 – 8958, Volume-3 Issue-6, August 2014
[22] Sukhpal Singh and InderveerChana“Energy based Efficient Resource Scheduling: A Step Towards Green Computing†International Journal of Energy, Information and Communications Vol.5, Issue 2 (2014), pp.35-52
[23] Jianfeng Zhan, Lei Wang, Weisong Shi, Shimin Gong “PhoenixCloud: Provisioning Resources for Heterogeneous Cloud Workloadsâ€. IEEE transaction service on cloud computing.
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Published
2016-10-15
How to Cite
Grover, S., & Ghumman, M. N. S. (2016). AN IMPLEMENTATION OF CARBON EFFICIENT VM PLACEMENT AND MIGRATION TECHNIQUE IN CLOUD ENVIRONMENT. INTERNATIONAL JOURNAL OF COMPUTERS &Amp; TECHNOLOGY, 15(10), 7169–7174. https://doi.org/10.24297/ijct.v15i10.4521
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