Abstract

For a decade swarm Intelligence deals with the design of intelligent multi-agent systems by taking inspiration from the collective behaviors of social insects and other animal societies. They are characterized by a decentralized way of working that mimics the behavior of the swarm. Swarm Intelligence is a successful paradigm for the algorithm with complex problems. The aim of this review paper is to analyze and compare various swarm intelligence evolutionary techniques of load balancing and conclude the best optimum technique among them. A brief introduction of load balancing and its various evolutionary techniques are presented and summarized.

References

• Songnian Zhou, Domenico Ferrari, " An Empirical investigation of Load Indices for Load Balancing Applications", Performance '87, Proc. Of the 12th IFIP WG7. 3, International Symposium on Computer Performance Modeling Measurement and Evaluation, Brussels, Belgium,pp. 515-528, 1987.
• Songnian Zhou, Domenico Ferrari, " An Experimental Study of Load Balancing Performance", Tech. Rept, No. UCB/CSD 87/336, January 1987.
• Gururaj S. Rao, Harold S. Stone And T. C. Hu", Assignment of Tasks in A Distributed Processor System With Limited Memory", IEEE Trans. On Computers, Vol. C-28, No. 4, April 1979.
• Lionel M. Ni, Chong-Wei, Xu And Thomas B. Gendreau " A Distributed Drafting Algorithm for Load Balancing", IEEE Trans. on Software Engineering, Vol. SE -11, No. 10, October 1985.
• Asser N. Tantawi And Don Towsley, " Optimal Static Load Balancing in Distributed Computer Systems",Journal of the Association for Computing Machinery, Vol. 32, No. 2 , April 1985.
• Kang G. Shin And Yi-Chien Chang, "Load Sharing in Distributed Real - Time Systems with State-Change Broadcasts", IEEE Trans. on Computers, Vol. 38 , No. 8, August 1989.
• Shlomit S Pinter And Yaron Woltstahl, "On Mapping Processes to Processor in Distributed Systems", International Journal of Parallel Programming, Vol. 16, No. 1, 1987.
• Ming-Syan Chen And Kand G. Shin," Subcube Allocation and Task Migration in Hypercube Multiprocessor", IEEE Trans. on Computers, Vol. 39, No. 9,September 1990.
• Derek L. Eager And Edward D. Lazowska And John Zahorjan, " Adaptive Load Sharing in Homogeneous Distributed Systems", IEEE Trans. On Software Engineering, Vol. SE- 12, No. 5, May 1986.
• Jian Xu And Kai Hwang," Heuristic Methods for Dynamic Load Balancing in A Message -Passing Multicomputer", Journal of Parallel and Distributed Computing 18, 1-13(1993).
• Mourad Kara, "Using Dynamic Load Balancing in Distributed Information systems", University of Leeds School of Computer Studies Research Report Series, Report 94. 18, May 1994.
• J. H. Holland, Adaptation in Natural and Artificial Systems. Univ. of Michigan Press, 1975.
• M. D. Kidwell And D. J. Cook, ªGenetic Algorithm for Dynamic Task Scheduling,º Proc. IEEE 13th Ann. Int'l Phoenix Conf. Computers and Comm. , pp. 61-67, 1994.
• D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, Mass. : Addison-Wesley, 1989.
• Z. Michalewicz, Genetic Algorithms + Data Structures= Evolution Programs, second ed. Berlin: Springer-Verlag, 1994.
• Albert Y. Zomaya, Senior Member, IEEE, and Yee- Hwei, The Observations on Using Genetic Algorithms for Dynamic Load-Balancing,IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 12, NO. 9, SEPTEMBER 2001.
• M. Dorigo,V. Maniezzo,Et A. Colorni,Ant system:optimization by a colony of cooperating agents,IEEE Transactions on systems,Mna and Cybernetics—Part B,volume 26,numero 1,pages 29- 41,1996.
• D. Ramesh, A. Krishnan, Optimal Parameter Identification in Ant Colony Optimization for Load Balancing in Grid Computing. European Journal of Scientific Research ISSN 1450-216X Vol. 75 No. 3 (2012), pp. 370-376© EuroJournals Publishing, Inc. 2012.
• Al-Dahoud Ali And Mohamed A. Belal, Multiple Ant Colonies Optimization for Load Balancing in Distributed Systems". ICTA'07, April 12-14, Hammamet, Tunisia.
• V. Selvi Dr. R. Umarani, Comparative Analysis of Ant Colony and Particle Swarm Optimization Techniques. International Journal of Computer Applications (0975-8887) Volume 5– No. 4, August 2010.
• G. Cybenko, Load balancing for distributed memory multiprocessors. Journal of Parallel and Distributed Computing, 7:279-301, 1989.
• Berenbrink, P. and Friedetzky, T. and Martin, R. (2005) ,Dynamic diffusion load balancing. ', in Automata, languages and programming : 32nd International Colloquium, ICALP 2005, 11-15 July 2005, Lisbon, Portugal ; proceedings. Berlin: Springer, pp. 1386-1398.
• P. Neelakantan Department of CSE, SVUCE, Tirupati, India Load Balancing in Distributed Systems using Diffusion Technique International Journal of Computer Applications (0975 – 8887) Volume 39– No. 4, February 2012.
• Glover F. 1986. Future Paths for Integer Programming and Links to Artificial Intelligence. Computers and Operations Research. Vol. 13,pp. 533-549.
• Hansen,P. 1986. The Steepest Ascent Mildest Descent Heuristic for Combinatorial Programming. Congress on Numerial Methods in Combinatorial Optimization,Capri,Italy.
• Fred Glover, Manuel Laguna, Principles of Tabu Search. Dpto. de Estadística e Investigación Operativa, Facultad de Matemáticas, Universidad de Valencia, Dr. Moliner 50, 46100 Burjassot (Valencia) Spain.
• Karaboga, Dervis (2010)Artificial bee colony algorithmScholarpedia, 5(3): 6915.
• Artificial Bee Colony Dervis Karaboga*, Bahriye Akay A comparative study of Artificial Bee Colony algorithm,0096-3003/$-see front matter_Elsevier inc. Doi:10. 1016/j. amc. 2009. 03. 090
• Shah-Hosseini, Hames (2009). "The intelligent water drops algorithm: a nature-inspired swarm-based optimization algorithm". International Journal of Bio- Inspired Computation 1 (1/2) : 71-79.
• Liu, H. , Abraham, A. , Zhang, W. : A Fuzzy Adaptive Turbulent Particle Swarm Optimization. International Journal of Innovative Computing and Applications 1(1),39–47 (2007).
• S. Rao Rayapudi, An Intelligent Water Drop Algorithm for Solving Economic Load Dispatch Problem. International Journal of Electrical and Electronics Engineering 5:1 2011.
• Kennedy, J. , Eberhart, R. C. : Particle Swarm Optimization. In: IEEE International Conference on Neural Networks (Perth, Australia), IEEE Service Center, Piscataway,NJ, pg. IV, pp. 1942–1948 (1995).
• Millie Pant, Radha Thangaraj, and Ajith Abraham, Particle Swarm Optimization: Performance Tuning and Empirical Analysis. A. Abraham et al. (Eds. ): Foundations of Comput. Intel. Vol. 3, SCI 203, pp. 101–128© Springer-Verlag Berlin Heidelberg 2009.
• P. Visalakshi,S. N. Sivanandan,Dynamic Task Scheduling with Load Balancing using Hybrid Particle Swarm Optimization. Int. J. Open Problems Compt. Math. ,Vol. 2,No. 3,September 2009,ISSN 1998- 6262;Copyright©ICSRS Publication2009.
• Peng-Yeng Yin, Shiuh-Sheng Yu, Pei-Pei Wang, and Yi-Te Wang, "A hybrid particle swarm optimization algorithm for optimal task assignment in distributed systems", Computer Standards & Interfaces , Vol. 28(2006), pp. 441-450.
• C. Kalpana,U. Karthick Kumar and R. Gogulan, Max- Min Particle Swarm Optimization Algorithm with Load Balancing for Distributed Task Scheduling on the Grid Environment. JCSI International Journal of Computer Science Issues, Vol. 9, Issue 3, No 1, May 2012 ISSN (Online): 1694-0814.
• C. Kalpana,U. Karthick Kumar and R. Gogulan,A Randomized load balancing algorithm in grid using Max Min PSO Algorithm. International Journal of Research in Computer ScienceeISSN 2249-8265
• Volume 2 Issue 3 (2012) pp. 17-23© White Globe Publications.
• C. Kalpana,U. Karthick Kumar and R. Gogulan,A Randomized load balancing algorithm in grid using Max Min PSO Algorithm. International Journal of Research in Computer ScienceeISSN 2249-8265
• Volume 2 Issue 3 (2012) pp. 17-23© White Globe Publications.
• Adil Baykaso lu, Lale Özbak?r and P?nar Tapkan Artificial Bee Colony Algorithm and Its Application to Generalized Assignment Problem Source: Swarm Intelligence: Focus on Ant and Particle Swarm Optimization, Book edited by: Felix T. S. Chan and Manoj Kumar Tiwari, ISBN 978-3-902613-09-7, pp. 532, December 2007, Itech Education and Publishing, Vienna, Austria.