Improving utility and recovery algorithms for adaptive real time system in multiprocessor environment

Among the issues in adaptive real time system is the efficiency of the scheduling algorithm to satisfy the predefined deadline and utility requirements. The design of real time scheduler to achieve an efficient utility and fault recovery algorithm in multiprocessor environment is the main problem f...

Full description

Saved in:

Bibliographic Details
Main Author:	Ahmad, Idawaty
Format:	Thesis
Language:	English
Published:	2012
Subjects:	Algorithms Real-time data processing Multiprocessors
Online Access:	http://psasir.upm.edu.my/id/eprint/32774/1/FSKTM%202012%2029R.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-upm-ir.32774
record_format	uketd_dc
spelling	my-upm-ir.327742015-01-13T01:53:18Z Improving utility and recovery algorithms for adaptive real time system in multiprocessor environment 2012-07 Ahmad, Idawaty Among the issues in adaptive real time system is the efficiency of the scheduling algorithm to satisfy the predefined deadline and utility requirements. The design of real time scheduler to achieve an efficient utility and fault recovery algorithm in multiprocessor environment is the main problem focused in this research. This thesis considers the independent tasks that are subject to deadline constraints specified in the TUF/UA scheduling environment. The algorithms for uniprocessor environment are known as Priority Inversion Utility Accrual Scheduling (PUAS) and Negation Oriented Utility Accrual Scheduling (NUAS). These algorithms solved the abortion problem in the existing General Utility Scheduling (GUS). PUAS implements a preemption strategy while NUAS negates the scheduling decision to abort by resuming the owner task. Simulation results reveal that the proposed algorithms outperforms the existing algorithm for the entire load range. The algorithm for multiprocessor environment is known as Global PUAS (GPUAS). GPUAS is adapted from the existing Greedy-Global Utility Accrual (G-GUA) and Non-Greedy Global Utility Accrual (NG-GUA) algorithms that considered task migration attribute for load sharing purposes. GPUAS enhanced the task placement mechanism in G-GUA and NGGUA algorithms. From the simulation results, GPUAS outperforms the existing G-GUA algorithm. The placement of task into a queue according to the value of utility in GPUAS has efficiently accrued at most 4.98% higher utility as compared to the existing G-GUA in dual core platform during overloaded condition in the system. GPUAS also tremendously outperforms NG-GUA in all platforms at most 12.44% higher utility accrued to the system. The scheduling algorithms with fault recovery are implemented in the uniprocessor and multiprocessor environment. The Backward Recovery (BR) mechanism is adapted from the Responsive Algorithm (RA) and works by re-executing of the erroneous request after its transient error period is over. The Backward Recovery PUAS (BRPUAS) and Backward Recovery NUAS (BRNUAS) algorithms are implemented for the uniprocessor scheduling environment. The Backward Recovery GPUAS (BR_GPUAS) algorithm is implemented in the multiprocessor environment. This thesis has proven that the BR mechanism is efficient to be used in the uniprocessor as BRPUAS saved at most 8.94% higher utility as compared to the abortion recovery. In multiprocessor environment, the BR_GPUAS saved at most 31.98% utility and thus enhanced the system performance in transient erroneous environment. Algorithms Real-time data processing Multiprocessors 2012-07 Thesis http://psasir.upm.edu.my/id/eprint/32774/ http://psasir.upm.edu.my/id/eprint/32774/1/FSKTM%202012%2029R.pdf application/pdf en public phd doctoral Universiti Putra Malaysia Algorithms Real-time data processing Multiprocessors
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
topic	Algorithms Real-time data processing Multiprocessors
spellingShingle	Algorithms Real-time data processing Multiprocessors Ahmad, Idawaty Improving utility and recovery algorithms for adaptive real time system in multiprocessor environment
description	Among the issues in adaptive real time system is the efficiency of the scheduling algorithm to satisfy the predefined deadline and utility requirements. The design of real time scheduler to achieve an efficient utility and fault recovery algorithm in multiprocessor environment is the main problem focused in this research. This thesis considers the independent tasks that are subject to deadline constraints specified in the TUF/UA scheduling environment. The algorithms for uniprocessor environment are known as Priority Inversion Utility Accrual Scheduling (PUAS) and Negation Oriented Utility Accrual Scheduling (NUAS). These algorithms solved the abortion problem in the existing General Utility Scheduling (GUS). PUAS implements a preemption strategy while NUAS negates the scheduling decision to abort by resuming the owner task. Simulation results reveal that the proposed algorithms outperforms the existing algorithm for the entire load range. The algorithm for multiprocessor environment is known as Global PUAS (GPUAS). GPUAS is adapted from the existing Greedy-Global Utility Accrual (G-GUA) and Non-Greedy Global Utility Accrual (NG-GUA) algorithms that considered task migration attribute for load sharing purposes. GPUAS enhanced the task placement mechanism in G-GUA and NGGUA algorithms. From the simulation results, GPUAS outperforms the existing G-GUA algorithm. The placement of task into a queue according to the value of utility in GPUAS has efficiently accrued at most 4.98% higher utility as compared to the existing G-GUA in dual core platform during overloaded condition in the system. GPUAS also tremendously outperforms NG-GUA in all platforms at most 12.44% higher utility accrued to the system. The scheduling algorithms with fault recovery are implemented in the uniprocessor and multiprocessor environment. The Backward Recovery (BR) mechanism is adapted from the Responsive Algorithm (RA) and works by re-executing of the erroneous request after its transient error period is over. The Backward Recovery PUAS (BRPUAS) and Backward Recovery NUAS (BRNUAS) algorithms are implemented for the uniprocessor scheduling environment. The Backward Recovery GPUAS (BR_GPUAS) algorithm is implemented in the multiprocessor environment. This thesis has proven that the BR mechanism is efficient to be used in the uniprocessor as BRPUAS saved at most 8.94% higher utility as compared to the abortion recovery. In multiprocessor environment, the BR_GPUAS saved at most 31.98% utility and thus enhanced the system performance in transient erroneous environment.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Ahmad, Idawaty
author_facet	Ahmad, Idawaty
author_sort	Ahmad, Idawaty
title	Improving utility and recovery algorithms for adaptive real time system in multiprocessor environment
title_short	Improving utility and recovery algorithms for adaptive real time system in multiprocessor environment
title_full	Improving utility and recovery algorithms for adaptive real time system in multiprocessor environment
title_fullStr	Improving utility and recovery algorithms for adaptive real time system in multiprocessor environment
title_full_unstemmed	Improving utility and recovery algorithms for adaptive real time system in multiprocessor environment
title_sort	improving utility and recovery algorithms for adaptive real time system in multiprocessor environment
granting_institution	Universiti Putra Malaysia
publishDate	2012
url	http://psasir.upm.edu.my/id/eprint/32774/1/FSKTM%202012%2029R.pdf
_version_	1747811676361588736

Improving utility and recovery algorithms for adaptive real time system in multiprocessor environment

Similar Items