Abstract
Cloud computing is a prototype for usage-based network. It is an Internet-based computing in which large groups of remote servers are networked so as to allow sharing of data-processing tasks, centralized data storage, and online access to computer services or resources. Data Center refers to the hardware that stores data within an organization’s local network. They are typically run by an in-house IT department. Cloud computing allows users to access secure and scalable networks of Data Centers and enables availability of virtually housed data, cloud-native and enterprise applications. The challenging problems in cloud data Center is the management of the load of different reconfigurable virtual machines. A mechanism for efficient resource management will be very significant to suite the need. The data Centers comprises of thousands of servers to provide services. The cost of maintaining this cloud data canters is extremely high. This paper focuses on the review of optimizing task load of different zone of data Center and users in the cloud environment.
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References
Geetha C. Megharaj, Dr. Mohan K.G. “Two Level Hierarchical Model of Load Balancing in Cloud”, International Journal of Emerging Technology and Advanced Engineering, ISSN 2250–2459, Volume 3 Issue 10, October2013.
Foster, I., Y. Zhao, I. Raicu and S. Lu, “Cloud computing and Grid Computing 360-degree compared,” in proc. Grid Computing Environments Workshop, pp: 99-106, 2008.
V.P. Narkhede, Prof. S. T. Khandare, “Fair Scheduling Algorithm with Dynamic Load Balancing Using In Grid Computing” International Journal Of Engineering And Science Vol. 2, Issue 10, 2013.
Mayanka Katyal, Atul Mishra “A Comparative Study of Load Balancing Algorithms in Cloud Computing Environment”, International Journal of Distributed and Cloud Computing, Volume 1, Issue 2, 2013.
Shridhar G. Domanal, G. Ram Mohana Reddy, “Optimal load balancing in cloud computing by efficient utilization of virtual machines”, IEEE, 2014.
Qiang Guo, “Task Scheduling Based on Ant Colony Optimization in Cloud Environment”, AIP Conference Proceedings 1834,040039 (2017)
Gaochao Xu, Junjie Pang, and Xiaodong Fu, “A Load Balancing Model Based on Cloud Partitioning for the Public Cloud”, Tsinghua Science and Technology, Volume 18, Number 1, February 2013
Gulshan Soni, Mala Kalra, “A Novel approach for Load Balancing in Cloud data Center”, 2014 IEEE.
Ambika Mishra, Prof. Susheel Jain, Prof. Anurag Jain, “ A Hierarchical Resource Switching and Load Assignment Algorithm for Load Balancing in Cloud System”, International Journal of Scientific & Engineering Research, Volume 5, Issue 3, March-2014 1179 ISSN 2229–5518.
Yongfei Zhu, Di Zhao, Wei Wang, and Haiwu He, “A Novel Load Balancing Algorithm Basedon Improved Particle Swarm Optimization in Cloud Computing Environment”, © Springer International Publishing Switzerland 2016, DOI: https://doi.org/10.1007/978-3-319-31854-7_57
Shu-Ching, Wang Kuo-Qin, Yan, Shun-Sheng, Wang Ching-Wei, Chen, “A Three-Phases Scheduling in a Hierarchical Cloud Computing Network”, 978-0-7695-4357-4/11 $26.00 © 2011 IEEE
Lekha Nema, Avinash Sharma, “Efficient Load Balancing Based on Improved Honey Bee Method in Cloud Computing”, IJCTA, 9(22), 2016, pp. 151-161, International Science Press.
Xin Xu and Huiqun Yu, “A Game Theory Approach to Fair and Efficient Resource Allocation in Cloud Computing”, Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 2014, Article ID 915878.
Kalpana Ettikyala, Y Rama Dev, “A Study on Cloud Simulation Tools”, International Journal of Computer Applications (0975–8887) Volume 115 – No. 14, April 2015
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Priya, B., Gnanasekaran, T. (2020). A Comprehensive Study on the Load Assessment Techniques in Cloud Data Center. In: Smys, S., Iliyasu, A.M., Bestak, R., Shi, F. (eds) New Trends in Computational Vision and Bio-inspired Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-41862-5_19
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DOI: https://doi.org/10.1007/978-3-030-41862-5_19
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