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Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid

Lorpunmanee, Siriluck and Md Sap, Mohd Noor and Abdullah, Abdul Hanan (2006) Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid. Jurnal Teknologi Maklumat, 18 (2). pp. 1-13. ISSN 0128-3790

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Abstract

The concept of Grid computing is becoming the most important research area in the high performance computing. Under this concept, the jobs scheduling in Grid computing has more complicated problems to discover a diversity of available resources, select the appropriate applications and map to suitable resources. However, the major problem is the optimal job scheduling, which Grid nodes need to allocate the appropriate resources for each job. In this paper, we combine Fuzzy C-Mean and Genetic Algorithms which are popular algorithms, the Grid can be used for scheduling. Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. In the experiments, we used the workload historical information and put it into our simulator. We get the better result when compared to the traditional algorithms for scheduling policies. Finally, the paper also discusses approach of the jobs classifications and the optimization engine in Grid scheduling.

Item Type:Article
Uncontrolled Keywords:Jobs scheduling, Grid Computing, Fuzzy C-Mean algorithm, Genetic algorithm, High performance computing
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:3279
Deposited By: Mrs Rozilawati Dollah @ Md Zain
Deposited On:22 May 2007 04:08
Last Modified:01 Jun 2010 03:08

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