Cover Image

Enhanced ant colony optimization for grid resource scheduling

Scheduling jobs to resources in grid computing is complicated due to the distributed and heterogeneous nature of the resources. Stagnation in grid computing system may occur when all jobs require or are assigned to the same resources which will lead to the resources having high workload. Stagnat...

Full description

Saved in:
Bibliographic Details
Main Authors: Abdul Nasir, Husna Jamal, Ku-Mahamud, Ku Ruhana
Format: Conference or Workshop Item
Language:English
Published: 2010
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://repo.uum.edu.my/3997/1/Husna_%26_Ku_Ruhana.pdf
http://repo.uum.edu.my/3997/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uum.repo.3997
record_format eprints
spelling my.uum.repo.39972014-04-14T00:08:42Z http://repo.uum.edu.my/3997/ Enhanced ant colony optimization for grid resource scheduling Abdul Nasir, Husna Jamal Ku-Mahamud, Ku Ruhana QA75 Electronic computers. Computer science Scheduling jobs to resources in grid computing is complicated due to the distributed and heterogeneous nature of the resources. Stagnation in grid computing system may occur when all jobs require or are assigned to the same resources which will lead to the resources having high workload. Stagnation also may occur if the computational time of the processed job is high. An effective job scheduling algorithm is needed to avoid or reduce the stagnation problem. An Enhanced Ant Colony Optimization (EACO) technique for jobs and resources scheduling in grid computing is proposed in this paper. The proposed algorithm combines the techniques from Ant Colony System and Max - Min Ant System and focused on local pheromone trail update and trail limit. The agent concept is also integrated in this proposed technique for the purpose of updating the grid resource table. This facilitates in scheduling jobs to available resources efficiently which will enable jobs to be processed in minimum time and also balance all the resource in grid system. 2010 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/3997/1/Husna_%26_Ku_Ruhana.pdf Abdul Nasir, Husna Jamal and Ku-Mahamud, Ku Ruhana (2010) Enhanced ant colony optimization for grid resource scheduling. In: International Conference on Engineering and ICT 2010 (ICEI 2010), 18 - 20 February 2010, Holiday Inn Hotel, Melaka.
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 QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Abdul Nasir, Husna Jamal
Ku-Mahamud, Ku Ruhana
Enhanced ant colony optimization for grid resource scheduling
description Scheduling jobs to resources in grid computing is complicated due to the distributed and heterogeneous nature of the resources. Stagnation in grid computing system may occur when all jobs require or are assigned to the same resources which will lead to the resources having high workload. Stagnation also may occur if the computational time of the processed job is high. An effective job scheduling algorithm is needed to avoid or reduce the stagnation problem. An Enhanced Ant Colony Optimization (EACO) technique for jobs and resources scheduling in grid computing is proposed in this paper. The proposed algorithm combines the techniques from Ant Colony System and Max - Min Ant System and focused on local pheromone trail update and trail limit. The agent concept is also integrated in this proposed technique for the purpose of updating the grid resource table. This facilitates in scheduling jobs to available resources efficiently which will enable jobs to be processed in minimum time and also balance all the resource in grid system.
format Conference or Workshop Item
author Abdul Nasir, Husna Jamal
Ku-Mahamud, Ku Ruhana
author_facet Abdul Nasir, Husna Jamal
Ku-Mahamud, Ku Ruhana
author_sort Abdul Nasir, Husna Jamal
title Enhanced ant colony optimization for grid resource scheduling
title_short Enhanced ant colony optimization for grid resource scheduling
title_full Enhanced ant colony optimization for grid resource scheduling
title_fullStr Enhanced ant colony optimization for grid resource scheduling
title_full_unstemmed Enhanced ant colony optimization for grid resource scheduling
title_sort enhanced ant colony optimization for grid resource scheduling
publishDate 2010
url http://repo.uum.edu.my/3997/1/Husna_%26_Ku_Ruhana.pdf
http://repo.uum.edu.my/3997/
_version_ 1644278646676914176
score 13.211869

Similar Items