Application of Bayesian networks to architectural optimisation

Parakhine, A; O'Neill, T; Leaney, J

Application of Bayesian networks to architectural optimisation

Parakhine, A O'Neill, T Leaney, J

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the International Symposium and Workshop on Engineering of Computer Based Systems, 2007, pp. 37 - 44
Issue Date:: 2007-06-18

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Field	Value	Language
dc.contributor.author	Parakhine, A	en_US
dc.contributor.author	O'Neill, T	en_US
dc.contributor.author	Leaney, J https://orcid.org/0000-0001-5009-0401	en_US
dc.date.issued	2007-06-18	en_US
dc.identifier.citation	Proceedings of the International Symposium and Workshop on Engineering of Computer Based Systems, 2007, pp. 37 - 44	en_US
dc.identifier.isbn	0769527728	en_US
dc.identifier.isbn	9780769527727	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2452
dc.description.abstract	The field of optimisation covers a great multitude of principles, methods and frameworks aimed at maximisation of an objective under constraints. However, the classical optimisation can not be easily applied in the context of computer-based systems architecture as there is not enough knowledge concerning the dependencies between non-functional qualities of the system. Out approach is based on the simulation optimisation methodology where the system simulation is first created to assess the current state of the design with respect to the objectives. The results of the simulation are used to construct a Bayesian Belief Network which effectively becomes a base for an objective function and serves as the main source of the decision support pertaining to the guidance of the optimisation process. The potential effects of each proposed change or combination of changes is then examined by updating and re-evaluating the system simulation. © 2007 IEEE.	en_US
dc.relation.ispartof	Proceedings of the International Symposium and Workshop on Engineering of Computer Based Systems	en_US
dc.relation.isbasedon	10.1109/ECBS.2007.19	en_US
dc.title	Application of Bayesian networks to architectural optimisation	en_US
dc.type	Conference Proceeding
utslib.for	0803 Computer Software	en_US
dc.location.activity	Tucson, Arizona	en_US
dc.location.activity	San Jose
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - HCTD - Human Centred Technology Design
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

The field of optimisation covers a great multitude of principles, methods and frameworks aimed at maximisation of an objective under constraints. However, the classical optimisation can not be easily applied in the context of computer-based systems architecture as there is not enough knowledge concerning the dependencies between non-functional qualities of the system. Out approach is based on the simulation optimisation methodology where the system simulation is first created to assess the current state of the design with respect to the objectives. The results of the simulation are used to construct a Bayesian Belief Network which effectively becomes a base for an objective function and serves as the main source of the decision support pertaining to the guidance of the optimisation process. The potential effects of each proposed change or combination of changes is then examined by updating and re-evaluating the system simulation. © 2007 IEEE.

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http://hdl.handle.net/10453/2452