A scheduling analysis framework for predicting the weakly hard real-time systems

For real-time systems, hard real-time and soft real-time systems are based on “miss restriction” and “miss tolerance”, respectively. However, a weakly hard real-time system integrates both these requirements. The problem with these systems is the limitation of the scheduling analysis method which on...

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Main Author:	Ismail, Habibah
Format:	Thesis
Language:	English
Published:	2013
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/35890/5/HabibahIsmailMFSKSM2013.pdf
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spelling	my-utm-ep.358902017-07-16T04:27:06Z A scheduling analysis framework for predicting the weakly hard real-time systems 2013-06 Ismail, Habibah QA75 Electronic computers. Computer science For real-time systems, hard real-time and soft real-time systems are based on “miss restriction” and “miss tolerance”, respectively. However, a weakly hard real-time system integrates both these requirements. The problem with these systems is the limitation of the scheduling analysis method which only uses the traditional scheduling approach. Besides that, the current framework has problems with the complexity and predictability of the systems. This study proposed a scheduling analysis framework based on the suitability of scheduling algorithms, weakly hard real-time modelling and the combination of the deterministic and probabilistic schedulability analyses for predicting the weakly hard real-time tasks. Initially, the best fitting specification of a weakly hard real-time system was integrated into the proposed framework and tested in the Modeling and Analysis of Real-Time Embedded systems (MARTE) profile. The profile was enhanced because the current MARTE timing constraint restricted to the hard and soft real time timing requirement, thus some modifications were made to model the weakly hard real-time requirements. For complex systems, rather than only using scheduling algorithms to schedule the tasks, the algorithms were used with Unified Modeling Language (UML) modelling. Sequence diagram complexity factor metrics were used to measure the behavioural complexity. The proposed combination approach was applied on case studies and then evaluated with reference to the existing approaches. The results of the evaluations showed that the proposed framework is more predictable compared to the other frameworks and has addressed the problem posed in this research. In conclusion, the proposed scheduling analysis framework provides a less complex design through the behavioural complexity measurements, as well as increases the predictability of the systems. 2013-06 Thesis http://eprints.utm.my/id/eprint/35890/ http://eprints.utm.my/id/eprint/35890/5/HabibahIsmailMFSKSM2013.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:70027?site_name=Restricted Repository masters Universiti Teknologi Malaysia, Faculty of Computing Faculty of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Ismail, Habibah A scheduling analysis framework for predicting the weakly hard real-time systems
description	For real-time systems, hard real-time and soft real-time systems are based on “miss restriction” and “miss tolerance”, respectively. However, a weakly hard real-time system integrates both these requirements. The problem with these systems is the limitation of the scheduling analysis method which only uses the traditional scheduling approach. Besides that, the current framework has problems with the complexity and predictability of the systems. This study proposed a scheduling analysis framework based on the suitability of scheduling algorithms, weakly hard real-time modelling and the combination of the deterministic and probabilistic schedulability analyses for predicting the weakly hard real-time tasks. Initially, the best fitting specification of a weakly hard real-time system was integrated into the proposed framework and tested in the Modeling and Analysis of Real-Time Embedded systems (MARTE) profile. The profile was enhanced because the current MARTE timing constraint restricted to the hard and soft real time timing requirement, thus some modifications were made to model the weakly hard real-time requirements. For complex systems, rather than only using scheduling algorithms to schedule the tasks, the algorithms were used with Unified Modeling Language (UML) modelling. Sequence diagram complexity factor metrics were used to measure the behavioural complexity. The proposed combination approach was applied on case studies and then evaluated with reference to the existing approaches. The results of the evaluations showed that the proposed framework is more predictable compared to the other frameworks and has addressed the problem posed in this research. In conclusion, the proposed scheduling analysis framework provides a less complex design through the behavioural complexity measurements, as well as increases the predictability of the systems.
format	Thesis
qualification_level	Master's degree
author	Ismail, Habibah
author_facet	Ismail, Habibah
author_sort	Ismail, Habibah
title	A scheduling analysis framework for predicting the weakly hard real-time systems
title_short	A scheduling analysis framework for predicting the weakly hard real-time systems
title_full	A scheduling analysis framework for predicting the weakly hard real-time systems
title_fullStr	A scheduling analysis framework for predicting the weakly hard real-time systems
title_full_unstemmed	A scheduling analysis framework for predicting the weakly hard real-time systems
title_sort	scheduling analysis framework for predicting the weakly hard real-time systems
granting_institution	Universiti Teknologi Malaysia, Faculty of Computing
granting_department	Faculty of Computing
publishDate	2013
url	http://eprints.utm.my/id/eprint/35890/5/HabibahIsmailMFSKSM2013.pdf
_version_	1747816380805152768

A scheduling analysis framework for predicting the weakly hard real-time systems

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