Improved Dynamic Load Balance Model on Gametheory for the Public Cloud
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Abstract
Cloud computing is an enhancing technology in the field of computer science. Cloud computing is an efficient and scalable but maintaining the stability of processing several jobs in the cloud computing environment is a very complex problem with load balancing receiving much attention for researchers. Load balancing in the cloud computing surroundings has an imperative impact on the performance. Excellent load balancing makes cloud computing more efficient and improves user satisfaction. At present cloud computing is one of the utmost platforms which deliver storage of data in very lowers cost and accessible for all time over the internet. But it has more serious issue like security, load management and fault tolerance. Load balancing in the cloud computing environment has a significant influence on the presentation. The algorithm relates the game theory to the load balancing approach to increase the proficiency in the public cloud environment. This article announces an improved load balance model for the public cloud centered on the cloud segregating concept with a switch mechanism to select different approaches for different circumstances.
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References
R. Hunter, The why of cloud, http://www.gartner.com/DisplayDocument?do c cd=226469&ref= g noreg, 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/whitepapers/ Load-Balancingin-the-Cloud.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, N. Nitin, and R. Rastogi, Load balancing of nodes in cloud using ant colony optimization, in Proc. 14th International Conference on Computer Modelling and Simulation (UKSim), Cambridgeshire, 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 InformationNetworking and Applications, Perth, Australia, 2010, pp. 551- 556.
A. Rouse, Public cloud, http://searchcloudcomputing.techtarget.com/d efinition/public-cloud, 2012.
D. MacVittie, Intro to load balancing for developers —The algorithms, https://devcentral.f5.com/blogs/us/introtoloadbalancing-for-developers-ndash-the- algorithms, 2012.
S. Penmatsa and A. T. Chronopoulos, Gametheoretic static load balancing for distributed systems, Journal of Parallel and Distributed Computing, vol. 71, no. 4, pp. 537-555, Apr. 2011.
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. Gaochao Xu received his BEng degree