Experiential probabilistic assessment of cloud services

Fahmideh, M; Beydoun, G; Low, G

Experiential probabilistic assessment of cloud services

Fahmideh, M Beydoun, G

Low, G

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Publication Type:: Journal Article
Citation:: Information Sciences, 2019, 502 pp. 510 - 524
Issue Date:: 2019-10-01

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Field	Value	Language
dc.contributor.author	Fahmideh, M	en_US
dc.contributor.author	Beydoun, G https://orcid.org/0000-0001-8087-5445	en_US
dc.contributor.author	Low, G	en_US
dc.date.accessioned	2020-03-24T03:32:40Z
dc.date.available	2020-03-24T03:32:40Z
dc.date.issued	2019-10-01	en_US
dc.identifier.citation	Information Sciences, 2019, 502 pp. 510 - 524	en_US
dc.identifier.issn	0020-0255	en_US
dc.identifier.uri	http://hdl.handle.net/10453/139491
dc.description.abstract	© 2019 Elsevier Inc. Substantial difficulties in adopting cloud services are often encountered during upgrades of existing software systems. A reliable early stage analysis can facilitate an informed decision process of moving systems to cloud platforms. It can also mitigate risks against system quality goals. Towards this, we propose an interactive goal reasoning approach which is supported by a probabilistic layer for the precise analysis of cloud migration risks to improve the reliability of risk control. The approach is illustrated using a commercial scenario of integrating a digital document processing system to Microsoft Azure cloud platform.	en_US
dc.relation.ispartof	Information Sciences	en_US
dc.relation.isbasedon	10.1016/j.ins.2019.06.027	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Experiential probabilistic assessment of cloud services	en_US
dc.type	Journal Article
utslib.citation.volume	502	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	09 Engineering	en_US
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/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
pubs.organisational-group	/University of Technology Sydney/Strength - PERSWADE - Centre on Persuasive Systems for Wise Adaptive Living
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US
pubs.volume	502	en_US

Abstract:

© 2019 Elsevier Inc. Substantial difficulties in adopting cloud services are often encountered during upgrades of existing software systems. A reliable early stage analysis can facilitate an informed decision process of moving systems to cloud platforms. It can also mitigate risks against system quality goals. Towards this, we propose an interactive goal reasoning approach which is supported by a probabilistic layer for the precise analysis of cloud migration risks to improve the reliability of risk control. The approach is illustrated using a commercial scenario of integrating a digital document processing system to Microsoft Azure cloud platform.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/139491