Exploration based Genetic Algorithm for Job Scheduling on Grid Computing

Hanaa Abdelrahman; Mohammed Bakri Bashir; Adil Yousif

doi:10.18495/comengapp.v5i3.181

[1] C. K. Ian Foster , Steven Tuecke â€¢, "The Anatomy of the GridEnabling Scalable Virtual Organizations," {foster, tuecke}@mcs.anl.gov, carl@isi.edu.
[2] R. B. a. B. N. Ajith Abraham, "Natureâ€™s Heuristics for Scheduling Jobs on Computational Grids."
[3] H. JIN, X. S. â€ a) , â€ , W. Q. , â€ , a. D. Z. , â€ , and N. , "DRIC: Dependable Grid Computing Framework," IEICE TRANS. INF. & SYST.,, vol. .E89â€“D, FEBRUARY 2006.
[4] M. P. M. Dipti Sharma "Job Scheduling Algorithm for Computational Grid in Grid Computing Environment," International Journal of Advanced Research in Computer Science and Software Engineering, vol. 3, May 2013.
[5] F. D. a. S. G. Ak, "Scheduling Algorithms for Grid Computing: State of the Art and Open Problems " January 2006
[6] H. S. Maryam Rabiee "Job Scheduling in Grid Computing with Cuckoo Optimization Algorithm " International Journal of Computer Applications vol. 62, January 2013
[7] F. D. a. S. G. Akl, "Scheduling Algorithms for Grid Computing: State of the Art and Open Problems " 2006.
[8] A. Yousif, S. M. Nor, A. H. Abdullah, and M. B. Bashir, "A Discrete Firefly Algorithm for Scheduling Jobs on Computational Grid," in Cuckoo Search and Firefly Algorithm, ed: Springer, 2014, pp. 271-290.
[9] A. Yousif, A. H. Abdullah, S. M. Nor, and A. Abdelaziz, "Intelligent Task Scheduling for Computational Grid," presented at the 1st Taibah University International Conference on Computing and Information Technology, 2012.
[10] P. Brucker, Scheduling algorithms: Springer Verlag, 2007.
[11] A. Abraham, R. Buyya, and B. Nath, "Natureâ€™s heuristics for scheduling jobs on computational grids," in The 8th IEEE International Conference on Advanced Computing and Communications (ADCOM 2000), 2000, pp. 45â€“52.
[12] S. Li, Y. Li, Y. Liu, and Y. Xu, "A GA-based NN approach for makespan estimation," Applied Mathematics and Computation, vol. 185, pp. 1003-1014, 2007.
[13] A. Abraham, R. Buyya, and B. Nath, "Natureâ€™s heuristics for scheduling jobs on computational grids," 2000, pp. 45-52.
[14] R. Entezari-Maleki and A. Movaghar, "A genetic algorithm to increase the throughput of the computational grids," International Journal of Grid and Distributed Computing, vol. 4, 2011.
[15] H. Liu, A. Abraham, and A. E. Hassanien, "Scheduling jobs on computational grids using a fuzzy particle swarm optimization algorithm," Future Generation Computer Systems, vol. 26, pp. 1336-1343, 2010.
[16] M. Dorigo and T. StÃ¼tzle, Ant colony optimization: the MIT Press, 2004.
[17] A. Abraham, H. Liu, W. Zhang, and T. G. Chang, "Scheduling jobs on computational grids using fuzzy particle swarm algorithm," 2006, pp. 500-507.
[18] V. Di Martino and M. Mililotti, "Scheduling in a grid computing environment using genetic algorithms," 2002, p. 297.
[19] S. Sanyal, A. Jain, S. K. Das, and R. Biswas, "A hierarchical and distributed approach for mapping large applications to heterogeneous grids using genetic algorithms," in Cluster Computing, 2003. Proceedings. 2003 IEEE International Conference on, 2003, pp. 496-499.
[20] V. Hamscher, U. Schwiegelshohn, A. Streit, and R. Yahyapour, "Evaluation of job-scheduling strategies for grid computing," Grid Computingâ€”GRID 2000, pp. 191-202, 2000.
[21] Y. Gao, H. Rong, and J. Z. Huang, "Adaptive grid job scheduling with genetic algorithms," Future Generation Computer Systems, vol. 21, pp. 151-161, 2005.
[22] S. Lorpunmanee, M. Sap, M. Noor, and A. H. Abdullah, "Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid," Jurnal Teknologi Maklumat, vol. 18, pp. 1-13, 2006.
[23] G. Singh, 1, a. M. S. Manna, and 2, "Genetic Algorithms: An Unbiased Optimization Technique for Image Segmentation."
[24] W. AbdElrouf, A. Yousif, and M. B. Bashir, "High Exploitation Genetic Algorithm for Job Scheduling on Grid Computing," International Journal of Grid and Distributed Computing, vol. 9, pp. 221-228, 2016.

Abstract viewed - 1232 times
PDF downloaded - 988 times

Affiliations

Hanaa Abdelrahman
University Science & Technology

Mohammed Bakri Bashir
Shendi University

Adil Yousif
University of Science and Technology, Khartoum

Content Top

Exploration based Genetic Algorithm for Job Scheduling on Grid Computing

Hanaa Abdelrahman ,
Mohammed Bakri Bashir ,
Adil Yousif

Vol 5 No 3 (2016)

DOI 10.18495/comengapp.v5i3.181

Submitted: Jan 12, 2001

Published: Oct 12, 2016

Abstract

Grid computing presents a new trend to distribute and Internet computing to coordinate large scale heterogeneous resources providing sharing and problem solving in dynamic, multi- institutional virtual organizations. Scheduling is one of the most important problems in computational grid to increase the performance. Genetic Algorithm is adaptive method that can be used to solve optimization problems, based on the genetic process of biological organisms. The objective of this research is to develop a job scheduling algorithm using genetic algorithm with high exploration processes. To evaluate the proposed scheduling algorithm this study conducted a simulation using GridSim Simulator and a number of different workload. The research found that genetic algorithm get best results when increasing the mutation and these result directly proportional with the increase in the number of job. The paper concluded that, the mutation and exploration process has a good effect on the final execution time when we have large number of jobs. However, in small number of job mutation has no effects.