Towards a trust evaluation middleware for cloud service selection

Tang, M; Dai, X; Liu, J; Chen, J

Towards a trust evaluation middleware for cloud service selection

Tang, M Dai, X Liu, J Chen, J

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Publication Type:: Journal Article
Citation:: Future Generation Computer Systems, 2017, 74 pp. 302 - 312
Issue Date:: 2017-09-01

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Field	Value	Language
dc.contributor.author	Tang, M	en_US
dc.contributor.author	Dai, X	en_US
dc.contributor.author	Liu, J	en_US
dc.contributor.author	Chen, J	en_US
dc.date.issued	2017-09-01	en_US
dc.identifier.citation	Future Generation Computer Systems, 2017, 74 pp. 302 - 312	en_US
dc.identifier.issn	0167-739X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/97227
dc.description.abstract	© 2016 Elsevier B.V. With the advent of cloud computing, employing various cloud services to build highly reliable cloud applications has become increasingly popular. The trustworthiness of cloud services is a critical issue that hinders the development of cloud applications, and thus is an urgently-required research problem. Previous studies evaluate trustworthiness of services via either QoS monitoring mechanisms or user feedback ratings, while seldom they combine both of them for enhancing service trust evaluation. This paper proposes a trustworthy selection framework for cloud service selection, named TRUSS. Aiming at developing an effective trust evaluation middleware for TRUSS, we propose an integrated trust evaluation method via combining objective trust assessment and subjective trust assessment. The objective trust assessment is based on QoS monitoring, while the subjective trust assessment is based on user feedback ratings. Experiments conducted using a synthesized dataset show that our proposed method significantly outperforms the other trust and reputation methods.	en_US
dc.relation.ispartof	Future Generation Computer Systems	en_US
dc.relation.isbasedon	10.1016/j.future.2016.01.009	en_US
dc.subject.classification	Distributed Computing	en_US
dc.title	Towards a trust evaluation middleware for cloud service selection	en_US
dc.type	Journal Article
utslib.citation.volume	74	en_US
utslib.for	0805 Distributed Computing	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	0803 Computer Software	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 Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	74	en_US

Abstract:

© 2016 Elsevier B.V. With the advent of cloud computing, employing various cloud services to build highly reliable cloud applications has become increasingly popular. The trustworthiness of cloud services is a critical issue that hinders the development of cloud applications, and thus is an urgently-required research problem. Previous studies evaluate trustworthiness of services via either QoS monitoring mechanisms or user feedback ratings, while seldom they combine both of them for enhancing service trust evaluation. This paper proposes a trustworthy selection framework for cloud service selection, named TRUSS. Aiming at developing an effective trust evaluation middleware for TRUSS, we propose an integrated trust evaluation method via combining objective trust assessment and subjective trust assessment. The objective trust assessment is based on QoS monitoring, while the subjective trust assessment is based on user feedback ratings. Experiments conducted using a synthesized dataset show that our proposed method significantly outperforms the other trust and reputation methods.

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http://hdl.handle.net/10453/97227