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An improved ant algorithm for job scheduling in grid computing

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4 Author(s)
Hui Yan ; Dept. of Comput., Zhejiang Univ. City Coll., Hangzhou, China ; Xue-Qin Shen ; Xing Li ; Ming-Hui Wu

In this paper, we propose an improved ant algorithm for job scheduling in grid computing. The new algorithm is based on the general ant adaptive scheduling heuristics and an added in load balancing guide component. The load balancing factor, related to the job finishing rate, is introduced to change the pheromone. That makes the job finishing rate at different resource being similar and the ability of the systematic load balancing improved. It has been successfully tested in a simulation grid environment. The experiments show that the new ant heuristic method can lead to significant performance in various applications.

Published in:

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on  (Volume:5 )

Date of Conference:

18-21 Aug. 2005