CFP last date
22 April 2024
Reseach Article

Job Scheduling in Grid Computing with Fast Artificial Fish Swarm Algorithm

by M. A. Awad El-bayoumy, M. Z. Rashad, M. A. Elsoud, M. A. El-dosuky
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 96 - Number 14
Year of Publication: 2014
Authors: M. A. Awad El-bayoumy, M. Z. Rashad, M. A. Elsoud, M. A. El-dosuky
10.5120/16859-6741

M. A. Awad El-bayoumy, M. Z. Rashad, M. A. Elsoud, M. A. El-dosuky . Job Scheduling in Grid Computing with Fast Artificial Fish Swarm Algorithm. International Journal of Computer Applications. 96, 14 ( June 2014), 1-5. DOI=10.5120/16859-6741

@article{ 10.5120/16859-6741,
author = { M. A. Awad El-bayoumy, M. Z. Rashad, M. A. Elsoud, M. A. El-dosuky },
title = { Job Scheduling in Grid Computing with Fast Artificial Fish Swarm Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 96 },
number = { 14 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume96/number14/16859-6741/ },
doi = { 10.5120/16859-6741 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:21:42.896404+05:30
%A M. A. Awad El-bayoumy
%A M. Z. Rashad
%A M. A. Elsoud
%A M. A. El-dosuky
%T Job Scheduling in Grid Computing with Fast Artificial Fish Swarm Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 96
%N 14
%P 1-5
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

One of the problems in grid computing is job scheduling. It is known that the job scheduling is NP-complete, and thus the use of heuristics is the de facto approach to deal with this practice in its difficulty. The proposed is an apply FAFSA in job scheduling and comparison between FASFA and normal AFSA

References
  1. Arora, J. , Introduction to Optimum Design, McGraw-Hill,1989
  2. Deb, K. , Optimisation for Engineering Design, Prentice-Hall, New Delhi.
  3. Glover, F. "Future Paths for Integer Programming and Links to Artificial Intelligence". Computers and Operations Research 13 (5): 533–549, 1986
  4. Farmer, J. D. ; Packard, N. ; Perelson, A. , "The immune system, adaptation and machine learning". Physica D 22 (1-3): 187–204. 1986
  5. Goldberg, D. E. , Genetic Algorithms in Search, Optimisation and Ma- chine Learning, Reading, Mass. , Addison Wesley, 1989. .
  6. Chu XiaoLi; Zhu Ying; Shi JunTao; Song JiQing, "Method of image segmentation based on Fuzzy C-Means Clustering Algorithm and Artificial Fish Swarm Algorithm," Intelligent Computing and Integrated Systems (ICISS), 2010 International Conference on , vol. , no. , pp. 254,257, 22-24 Oct. 2010
  7. Tang Xueqin; DuanmuJingshun; Jin Liya; XuZongchang, "WNN optimization design based on Artificial Fish-Swarm Algorithm," Computer Science and Network Technology (ICCSNT), 2011 International Conference on , vol. 4, no. , pp. 2747,2750, 24-26 Dec. 2011
  8. GaoZhong-hui; Ding Jian-yong; Liu Heng, "Hybrid algorithm based on artificial fish swarm algorithm and tabu search in distribution network reconfiguration," Computer Design and Applications (ICCDA), 2010 International Conference on , vol. 5, no. , pp. V5-415,V5-418, 25-27 June 2010
  9. Hai Ma; Yanjiang Wang, "An Artificial Fish Swarm Algorithm Based on Chaos Search," Natural Computation, 2009. ICNC '09. Fifth International Conference on , vol. 4, no. , pp. 118,121, 14-16 Aug. 2009
  10. M A Awad, M Z Rashad, M AElsoud and M A El-dosuky. Article: Visualization of Job Scheduling in Grid Computers. International Journal of Computer Applications 74(8):37-40, July 2013. Published by Foundation of Computer Science, New York, USA
  11. Jiang, M. Y. , Yuan, D. F. : Artificial Fish Swarm Algorithm and Its Applications. Proc. Of International Conference on Sensing, Computing and Automation, Chongqing China, 2006, pp. 1782-1787.
  12. Xiao, J. M. , Zheng , X. M. , Wang , X. H. : A Modified Artificial Fish-Swarm Algorithm. Proc. of IEEE the 6th World Congress on Intelligent Control and Automation, Dalian China, 2006, pp. 3456-3460.
  13. Jiang, M. Y. , Yuan, D. F. : Wavelet Threshold Optimization with Artificial Fish Swarm Algorithm. Proc. of IEEE International Conference on Neural Networks and Brain, Beijing China, 2005,pp. 569 -572.
  14. Li, X. L. : A New Intelligent Optimization-Artificial Fish Swarm Algorithm. Doctor thesis, Zhejiang University of Zhejiang, China , 2003.
  15. MrSaeedFarzi "Efficient Job Scheduling in Grid Computing with Modified Artificial Fish Swarm Algorithm" International Journal of Computer Theory and Engineering, Vol. 1, No. 1, April 2009 1793-821X.
  16. Peter Mörters, Yuval Peres, Brownian Motion, Cambridge University Press, Mar 25, 2010.
  17. Andrej N. Borodin, PaavoSalminen, Handbook of Brownian Motion: Facts and Formulae, Springer, 2002.
  18. Brian H. Kaye,A Random Walk Through Fractal Dimensions, Second Edition, John Wiley & Sons, Jul 11, 2008.
  19. Hans C. Foged by "Langevin equations For continuous time L´evy flights" 2008.
  20. Schoen, F. , 'A wide class of test functions for global optimization', J. Global Optimization, 3, 133-137, 1993
  21. Shang, Y. W. , Qiu Y. H. , 'A note on the extended rosenrbock function', Evolutionary Computation, 14, 119-126. , 2006
  22. Whitley, L. D. , Mathias, K. E. , Rana, S. , &Dzubera, J. , Building better test functions, In Eshelman, L. J. (Ed), Proceeding of the Sixth International Conference on Genetic Algorithms, PP 239-246, Morgan Kaufmann, California, 1995.
  23. De Jong, K. A. , An analysis of the behavior of a class of genetic adaptive systems, Doctoral dissertation, University of Michigan, Ann Arbor, University Microfilms No 76-9381, 1975.
  24. Rosenbrock, H. H. , An Automatic method for finding the greatest or least value of a function, The Computer Journal, Vol. 3, No. 3, PP 175-184, 1960.
  25. Dorigo, M,. Optimization, Learning and Natural Algorithms (Phd Thesis). Politecnico di Milano, Italie, 1992
  26. Karaboga, D. , "An Idea Based On Honey Bee Swarm For Numerical Numerical Optimization". Technical Report-TR06 (Erciyes University, Engineering Faculty, Computer Engineering Department), 2005
  27. Kennedy, J. ; Eberhart, R. "Particle Swarm Optimization". Proceedings of IEEE International Conference on Neural Networks. IV. pp. 1942–1948, 1995
  28. Gazi, K. , and Passino, K. M. , Stability analysis of social foraging swarms, IEEE Trans. Sys. Man. Cyber. Part B - Cybernetics, 34, 539-557, 2004.
  29. Glover, F. and M. Laguna. Tabu Search. Kluwer Academic Publishers, 1997.
  30. Hoos, H. H. and T. Stützle. Stochastic Local Search. Morgan Kaufmann, 2005
  31. M A Awad, M Z Rashad, M A Elsoud and M A El-dosuky. Article: FAFSA: Fast Artificial Fish Swarm Algorithm. International Journal of Information Science and Intelligent System, Vol. 2, No. 1, 2013
  32. M A Awad, M Z Rashad, M AElsoud and M A El-dosuky. Article: Implementation of a New Visualization Framework of Job Scheduling in Grid Computers. International Journal of Computer Applications Volume 86 – No 5, January 2014. Published by Foundation of Computer Science, New York, USA
Index Terms

Computer Science
Information Sciences

Keywords

AFSA Levy Fast Artificial Fish Swarm Algorithm FAFSA