Grid Task Scheduling Strategy Based on Particle Swarm Optimizationand Ant Colony Optimization Algorithm


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Based on particle swarm optimization algorithm, this paper presents a grid scheduling optimization algorithm combing the advantages of Ant Colony optimization algorithm. The algorithm processes task scheduling through particle swarm optimization algorithm to get a group of relatively optimal solutions, and then conducts small-area local search with Ant Colony optimization algorithm. Theoretical analysis and results of the simulation experiments show that this scheduling algorithm effectively achieves load balancing of resources with comprehensive advantages in time efficiency and solution accuracy compared to the traditional Ant Colony optimization algorithm and particle swarm optimizationalgorithm, and can be applied to task scheduling in grid computing.



Advanced Materials Research (Volumes 108-111)

Edited by:

Yanwen Wu




P. C. Wei and X. Shi, "Grid Task Scheduling Strategy Based on Particle Swarm Optimizationand Ant Colony Optimization Algorithm", Advanced Materials Research, Vols. 108-111, pp. 392-397, 2010

Online since:

May 2010




[1] Rajkumar Buyya, David Abramson, Jonathan Giddy. Grid Resource Management, Scheduling, and Computational Economy [C]. The 1st International Workshop on Grid and Cooperative Computing, Tokyo, Japan: IEEE Computer Society (2000), pp.1734-1739.

DOI: 10.1016/s0167-739x(02)00085-7

[2] Yao jun Han, Resource Scheduling Algorithm for Grid Computing and Its Modeling and Analysis Using Petri Net[C]. The 2nd International Workshop on Grid and Cooperative Computing, Shanghai, IEEE Computer Society (2003), pp.814-820.

DOI: 10.1007/978-3-540-24680-0_10

[3] ; . Using ant algorithm to schedule tasks in grid[J]. Computer Applications, 25(10) (2005), pp.2236-2238.

[4] Zhi hong Xu, Xiangdan Hou. Ant Algorithm-based Task Scheduling in Grid Computing[C]. Proc of Conf on Electrical and Computer Engineering, Quebec Canadian:IEEE Computer Society (2003), pp.1107-1110.

DOI: 10.1109/ccece.2003.1226090

[5] Vincenzo Di Martino. Schduling in a grid computing enviroment using genetic algorithm[C]. The 16th Int'1 Parallel and Distributed Processing Symp, Pittsburgh, USA:Kluwer Academic press (2002), P. 678-686.

[6] Wensheng Yao, Genetic Scheduling on Minimal Processing Elements in the Grid[M]. Springr-Verlag Heidelberg (2002).

[7] Ajith Abraham, Rajkumar Buyya. Nature's heuristics for scheduling jobs on computational grids[C]. The 8th Int'1 Conf on Advanced Computing and Communications, Cochin, India: IEEE Computer Society (2000)., pp.27-38.

[8] Naik V K, Garbacki P, Kummamuru K, et a. l On-line evolutionary re-sourcematching for job scheduling in heterogeneous grid environments[J]. Parallel andDistributed Systems, 2006. ICPADS 2006. 12th Inter-nationalConference on Volume 2 (2006), p.6.

DOI: 10.1109/icpads.2006.72

[9] LihuaA, i SiweiLuo. GridLocalityEnhanced by Job Schedule. Grid and Cooperative Computing, 2007. GCC 2007. Sixth International Confer-ence on Aug. (2007), pp.462-466.

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