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Enhanced ant colony optimization for grid resource scheduling

Abdul Nasir, Husna Jamal and Ku-Mahamud, Ku Ruhana (2010) Enhanced ant colony optimization for grid resource scheduling. In: International Conference on Engineering and ICT 2010 (ICEI 2010), 18 - 20 February 2010, Holiday Inn Hotel, Melaka.

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Scheduling jobs to resources in grid computing is complicated due to the distributed and heterogeneous nature of the resources. Stagnation in grid computing system may occur when all jobs require or are assigned to the same resources which will lead to the resources having high workload. Stagnation also may occur if the computational time of the processed job is high. An effective job scheduling algorithm is needed to avoid or reduce the stagnation problem. An Enhanced Ant Colony Optimization (EACO) technique for jobs and resources scheduling in grid computing is proposed in this paper. The proposed algorithm combines the techniques from Ant Colony System and Max - Min Ant System and focused on local pheromone trail update and trail limit. The agent concept is also integrated in this proposed technique for the purpose of updating the grid resource table. This facilitates in scheduling jobs to available resources efficiently which will enable jobs to be processed in minimum time and also balance all the resource in grid system.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Enhanced Ant Colony Optimization, Grid Resource Scheduling, Stagnation, System Architecture
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: College of Arts and Sciences
Depositing User: Prof. Dr. Ku Ruhana Ku Mahamud
Date Deposited: 31 Oct 2011 06:51
Last Modified: 14 Apr 2014 00:08

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