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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Main Authors: Ku-Mahamud, Ku Ruhana, Alobaedy, Mustafa Muwafak
格式: Conference or Workshop Item
語言:English
出版: 2012
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在線閱讀:http://repo.uum.edu.my/6976/1/P11_-_AMATHI_2012.pdf
http://repo.uum.edu.my/6976/
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spelling 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.
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA76 Computer software
spellingShingle QA76 Computer software
Ku-Mahamud, Ku Ruhana
Alobaedy, Mustafa Muwafak
New heuristic function in ant colony system for job scheduling in grid computing
description 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
title_full_unstemmed 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
publishDate 2012
url http://repo.uum.edu.my/6976/1/P11_-_AMATHI_2012.pdf
http://repo.uum.edu.my/6976/
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score 13.149126