New heuristic function in ant colony system for job scheduling in grid computing
Job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Ant colony system algorithm is a meta-heuristic al...
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my.uum.repo.69762013-01-21T01:08:43Z http://repo.uum.edu.my/6976/ New heuristic function in ant colony system for job scheduling in grid computing Ku-Mahamud, Ku Ruhana Alobaedy, Mustafa Muwafak QA76 Computer software Job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Ant colony system algorithm is a meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This paper focuses on enhancing the heuristic function where information about recent ants’ discoveries will be taken into account.Experiments were conducted using a simulator with dynamic environment features to mimic the grid environment.Results show that the proposed enhanced algorithm produce better output in term of utilization and make span. 2012-12-29 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/6976/1/P11_-_AMATHI_2012.pdf Ku-Mahamud, Ku Ruhana and Alobaedy, Mustafa Muwafak (2012) New heuristic function in ant colony system for job scheduling in grid computing. In: The 3rd International Conference on Applied Mathematic and Informatics, 29-31 December 2012, Montreux, Switzerland. |
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QA76 Computer software Ku-Mahamud, Ku Ruhana Alobaedy, Mustafa Muwafak New heuristic function in ant colony system for job scheduling in grid computing |
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Job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Ant colony system algorithm is a meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This paper focuses on enhancing the heuristic function where information about
recent ants’ discoveries will be taken into account.Experiments were conducted using a simulator with
dynamic environment features to mimic the grid environment.Results show that the proposed enhanced
algorithm produce better output in term of utilization and make span. |
format |
Conference or Workshop Item |
author |
Ku-Mahamud, Ku Ruhana Alobaedy, Mustafa Muwafak |
author_facet |
Ku-Mahamud, Ku Ruhana Alobaedy, Mustafa Muwafak |
author_sort |
Ku-Mahamud, Ku Ruhana |
title |
New heuristic function in ant colony system for job scheduling in grid computing |
title_short |
New heuristic function in ant colony system for job scheduling in grid computing |
title_full |
New heuristic function in ant colony system for job scheduling in grid computing |
title_fullStr |
New heuristic function in ant colony system for job scheduling in grid computing |
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New heuristic function in ant colony system for job scheduling in grid computing |
title_sort |
new heuristic function in ant colony system for job scheduling in grid computing |
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2012 |
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http://repo.uum.edu.my/6976/1/P11_-_AMATHI_2012.pdf http://repo.uum.edu.my/6976/ |
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1644279414047899648 |
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