Improved genetic algorithm for scheduling divisible data grid application
Data Grid technology promises geographically distributed scientists to access and share physically distributed resources such as computing resources, networks, storages, and most importantly data collections for large scale data intensive problems. In many Data Grid applications, Data can be decompo...
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Online Access: | http://psasir.upm.edu.my/id/eprint/48202/1/Improved%20genetic%20algorithm%20for%20scheduling%20divisible%20data%20grid%20application.pdf http://psasir.upm.edu.my/id/eprint/48202/ |
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my.upm.eprints.482022016-08-04T05:17:13Z http://psasir.upm.edu.my/id/eprint/48202/ Improved genetic algorithm for scheduling divisible data grid application Kaid, Monir Abdullah Abduh Othman, Mohamed Ibrahim, Hamidah K. Subramaniam, Shamala Data Grid technology promises geographically distributed scientists to access and share physically distributed resources such as computing resources, networks, storages, and most importantly data collections for large scale data intensive problems. In many Data Grid applications, Data can be decomposed into multiple independent sub datasets and distributed for parallel execution and analysis. In this paper, we exploit this property and propose an Improved Genetic Algorithm (IGA) for scheduling divisible data grid applications. A good heuristic approach used to generate the initial population. Experimental results show that the proposed IGA gives better performance compared to the Genetic Algorithm (GA). IEEE 2007 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/48202/1/Improved%20genetic%20algorithm%20for%20scheduling%20divisible%20data%20grid%20application.pdf Kaid, Monir Abdullah Abduh and Othman, Mohamed and Ibrahim, Hamidah and K. Subramaniam, Shamala (2007) Improved genetic algorithm for scheduling divisible data grid application. In: IEEE International Conference on Telecommunications and Malaysia International Conference on Communications (ICT-MICC 2007), 14-17 May 2007, Penang, Malaysia. (pp. 461-465). 10.1109/ICTMICC.2007.4448680 |
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Data Grid technology promises geographically distributed scientists to access and share physically distributed resources such as computing resources, networks, storages, and most importantly data collections for large scale data intensive problems. In many Data Grid applications, Data can be decomposed into multiple independent sub datasets and distributed for parallel execution and analysis. In this paper, we exploit this property and propose an Improved Genetic Algorithm (IGA) for scheduling divisible data grid applications. A good heuristic approach used to generate the initial population. Experimental results show that the proposed IGA gives better performance compared to the Genetic Algorithm (GA). |
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Conference or Workshop Item |
author |
Kaid, Monir Abdullah Abduh Othman, Mohamed Ibrahim, Hamidah K. Subramaniam, Shamala |
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Kaid, Monir Abdullah Abduh Othman, Mohamed Ibrahim, Hamidah K. Subramaniam, Shamala Improved genetic algorithm for scheduling divisible data grid application |
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Kaid, Monir Abdullah Abduh Othman, Mohamed Ibrahim, Hamidah K. Subramaniam, Shamala |
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Kaid, Monir Abdullah Abduh |
title |
Improved genetic algorithm for scheduling divisible data grid application |
title_short |
Improved genetic algorithm for scheduling divisible data grid application |
title_full |
Improved genetic algorithm for scheduling divisible data grid application |
title_fullStr |
Improved genetic algorithm for scheduling divisible data grid application |
title_full_unstemmed |
Improved genetic algorithm for scheduling divisible data grid application |
title_sort |
improved genetic algorithm for scheduling divisible data grid application |
publisher |
IEEE |
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2007 |
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http://psasir.upm.edu.my/id/eprint/48202/1/Improved%20genetic%20algorithm%20for%20scheduling%20divisible%20data%20grid%20application.pdf http://psasir.upm.edu.my/id/eprint/48202/ |
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