An efficient algorithm for independent tasks scheduling in heterogeneous computing systems
Task scheduling is critical in heterogenous systems, especially with the huge number of tasks transmitted over grid. Since heuristics are proposing methods for solving heterogenous computing systems, several techniques were proposed for the scheduling on grid computing systems to get better ex...
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my-upm-ir.696682022-04-04T03:13:23Z An efficient algorithm for independent tasks scheduling in heterogeneous computing systems 2016-06 Al-Qadhi, Abdulrahman Khaldoon Mahmood Task scheduling is critical in heterogenous systems, especially with the huge number of tasks transmitted over grid. Since heuristics are proposing methods for solving heterogenous computing systems, several techniques were proposed for the scheduling on grid computing systems to get better execution time. In this thesis, a proposed new heuristic algorithm named Two Stages TasksTransfer (TSTT) algorithm introduced as an enhancement of state of TPB scheduling algorithm. Scheduling problem addressed Heterogeneous Computing Scheduling Problem (HCSP) mathematical model, where the independent tasks assigned to heterogenous processors with different characteristics. Twelve datasets with different heterogeneity level examined using different heuristic algorithms to compare the performance with the new algorithm. The proposed algorithm showed its efficiency in term of makespan, resource utilization and load balancing metrics for set of tasks. Heterogeneous distributed computing systems Computer algorithms 2016-06 Thesis http://psasir.upm.edu.my/id/eprint/69668/ http://psasir.upm.edu.my/id/eprint/69668/1/fsktm%202017%2016%20ir.pdf text en public masters Universiti Putra Malaysia Heterogeneous distributed computing systems Computer algorithms Ariffin, Ahmad Alauddin |
institution |
Universiti Putra Malaysia |
collection |
PSAS Institutional Repository |
language |
English |
advisor |
Ariffin, Ahmad Alauddin |
topic |
Heterogeneous distributed computing systems Computer algorithms |
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Heterogeneous distributed computing systems Computer algorithms Al-Qadhi, Abdulrahman Khaldoon Mahmood An efficient algorithm for independent tasks scheduling in heterogeneous computing systems |
description |
Task scheduling is critical in heterogenous systems, especially with the huge
number of tasks transmitted over grid. Since heuristics are proposing methods for
solving heterogenous computing systems, several techniques were proposed for the
scheduling on grid computing systems to get better execution time. In this thesis, a
proposed new heuristic algorithm named Two Stages TasksTransfer (TSTT)
algorithm introduced as an enhancement of state of TPB scheduling algorithm.
Scheduling problem addressed Heterogeneous Computing Scheduling Problem
(HCSP) mathematical model, where the independent tasks assigned to
heterogenous processors with different characteristics. Twelve datasets with
different heterogeneity level examined using different heuristic algorithms to
compare the performance with the new algorithm. The proposed algorithm showed
its efficiency in term of makespan, resource utilization and load balancing metrics for
set of tasks. |
format |
Thesis |
qualification_level |
Master's degree |
author |
Al-Qadhi, Abdulrahman Khaldoon Mahmood |
author_facet |
Al-Qadhi, Abdulrahman Khaldoon Mahmood |
author_sort |
Al-Qadhi, Abdulrahman Khaldoon Mahmood |
title |
An efficient algorithm for independent tasks scheduling in heterogeneous computing systems |
title_short |
An efficient algorithm for independent tasks scheduling in heterogeneous computing systems |
title_full |
An efficient algorithm for independent tasks scheduling in heterogeneous computing systems |
title_fullStr |
An efficient algorithm for independent tasks scheduling in heterogeneous computing systems |
title_full_unstemmed |
An efficient algorithm for independent tasks scheduling in heterogeneous computing systems |
title_sort |
efficient algorithm for independent tasks scheduling in heterogeneous computing systems |
granting_institution |
Universiti Putra Malaysia |
publishDate |
2016 |
url |
http://psasir.upm.edu.my/id/eprint/69668/1/fsktm%202017%2016%20ir.pdf |
_version_ |
1747812720155033600 |