Cloud Partitioning of Load Balancing Using Round Robin Model
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Abstract
The purpose of load balancing is to look up the performance of a cloud environment through an appropriate circulation strategy. Good load balancing will construct cloud computing for more stability and efficiency. This paper introduces a better round robin model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. Load balancing is the process of giving out of workload among different nodes or processor. It will introduces a enhanced approach for public cloud load distribution using screening and game theory concept to increase the presentation of the system.
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References
R. Hunter, The why of cloud, http://www.gartner.com/DisplayDocument?doc cd=226469&ref= gnoreg, 2012.
M. D. Dikaiakos, D. Katsaros, P. Mehra, G. Pallis, and A. Vakali, Cloud computing: Distributed internet computing for IT and scientific research, Internet Computing, vol.13, no.5, pp.10-13, Sept.- Oct. 2009.
P. Mell and T. Grance, The NIST definition of cloud computing, http://csrc.nist.gov/ publications/nistpubs/800-145/SP800-145.pdf, 2012.
Microsoft Academic Research, Cloud computing, http:// libra.msra.cn/Keyword/6051/cloudcomputing? query = cloud%20computing, 2012.
Google Trends, Cloud computing, http://www.google.com/trends/explore#q=cloud %20computing, 2012.
N. G. Shivaratri, P. Krueger, and M. Singhal, Load distributing for locally distributed systems, Computer, vol. 25, no. 12, pp. 33-44, Dec. 1992.
B. Adler, Load balancing in the cloud: Tools, tips and techniques, http://www.rightscale. com/info center/white-papers/Load-Balancing-in-theCloud.pdf, 2012
Z. Chaczko, V. Mahadevan, S. Aslanzadeh, and C. Mcdermid, Availability and load balancing in cloud computing, presented at the 2011 International Conference on Computer and Software Modeling, Singapore, 2011.
K. Nishant, P. Sharma, V. Krishna, C. Gupta, K. P. Singh, International Conference on Computer Modeling and Simulation (UKSim), Cambridge shire, United Kingdom, Mar. 2012, pp. 28-30.
M. Randles, D. Lamb, and A. Taleb-Bendiab, A comparative study into distributed load balancing algorithms for cloud computing, in Proc. IEEE 24th International Conference on Advanced Information Networking and Applications, Perth, Australia, 2010, pp. 551-556.
A. Rouse, Public cloud, http://searchcloudcomputing.techtarget.com/defi nition/public-cloud, 2012.
D. MacVittie, Intro to load balancing for developers — the algorithms, https://devcentral.f5.com/blogs/us/intro-to-loadbalancing-for-developers-ndash-the-algorithms, 2012.
S. Penmatsa and A. T. Chronopoulos, Gametheoretic static balancing for distributed systems, load journal of Distributed computing pp.502-11- 42.
D. Grosu, A. T. Chronopoulos, and M. Y. Leung, Load balancing in distributed systems: An approach using cooperative games, in Proc. 16th IEEE Intl. Parallel and Distributed Processing Symp., Florida, USA, Apr. 2002, pp. 52-61.
S. Aote and M. U. Kharat, A game-theoretic model for dynamic load balancing in distributed systems, in Proc. the International Conference on Advances in Computing, Communication and Control (ICAC3 ’09), New York, USA, 2009, pp. 235-238.