Abstract/Description
Since the grid is a dynamic environment, the prediction and detection of available resources in near future is important for resource scheduling. Economic-based grid management has been viewed as a feasible approach to carry out fair, efficient and reliable scheduling. One key issue in economic-based grid strategy is to inform about available resources. In this paper, we present a novel predictable method to specify available resource in economic-based grid. This method use a rough set analysis by scheduler to divide resources in groups and then grant a priority to each group based on cost price and efficiency of nodes. The result show that our proposed method has an acceptable performance and it try to use cheaper and suitable resources for each job to decrease cost price of computation.
Keywords
Component, Economic-base grid, Availability, Resource scheduling, Scheduler, Rough set
Location
Eiffel 3
Session Theme
Networks - II
Session Type
Other
Session Chair
Dr. Sayeed Ghani
Start Date
16-8-2009 12:40 PM
End Date
16-8-2009 1:00 PM
Recommended Citation
Bouyer, A., SAP, M. n., & Abdullah, A. H. (2009). Networks - II: A new rough set based approach for optimized detection of available resources in Grid computing. International Conference on Information and Communication Technologies. Retrieved from https://ir.iba.edu.pk/icict/2009/2009/11
Networks - II: A new rough set based approach for optimized detection of available resources in Grid computing
Eiffel 3
Since the grid is a dynamic environment, the prediction and detection of available resources in near future is important for resource scheduling. Economic-based grid management has been viewed as a feasible approach to carry out fair, efficient and reliable scheduling. One key issue in economic-based grid strategy is to inform about available resources. In this paper, we present a novel predictable method to specify available resource in economic-based grid. This method use a rough set analysis by scheduler to divide resources in groups and then grant a priority to each group based on cost price and efficiency of nodes. The result show that our proposed method has an acceptable performance and it try to use cheaper and suitable resources for each job to decrease cost price of computation.
