Aggregating Fuzzy Sentiments with Customized QoS Parameters for Cloud Provider Selection Using Fuzzy Best Worst and Fuzzy TOPSIS

Hussain, W; Merigó, JM; Rabhi, F; Gao, H

Aggregating Fuzzy Sentiments with Customized QoS Parameters for Cloud Provider Selection Using Fuzzy Best Worst and Fuzzy TOPSIS

Hussain, W

Merigó, JM Rabhi, F Gao, H

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Publisher:: Springer International Publishing
Publication Type:: Chapter
Citation:: Lecture Notes in Networks and Systems, 2022, 337, pp. 81-92
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Hussain, W https://orcid.org/0000-0003-0610-4006
dc.contributor.author	Merigó, JM
dc.contributor.author	Rabhi, F
dc.contributor.author	Gao, H
dc.date.accessioned	2023-02-10T06:59:09Z
dc.date.available	2023-02-10T06:59:09Z
dc.date.issued	2022-01-01
dc.identifier.citation	Lecture Notes in Networks and Systems, 2022, 337, pp. 81-92
dc.identifier.isbn	9783030961497
dc.identifier.uri	http://hdl.handle.net/10453/166052
dc.description.abstract	Consumers often get confused to select the best cloud providers from the huge marketplace. The hesitancy of consumers further escalates when multiple service providers offer the same type and quality of services. To deal with such an uncertainty, the decision-makers always combine multiple factors to make an informed choice. Sentiment mining is one of the key parameters to determine the service quality and get an insight into the business. It assists service providers in precisely deduce consumer's emotions regarding the product. The analysis helps providers fine-tune the product based on consumer's sentiment and accommodates the consumer's request to find an optimal service provider. Several existing literature for cloud service selection mainly focuses on the Quality of Service (QoS) of the offered services. However, very few of them have considered the user experience of a consumer in the decision-making process. Moreover, there is minimal literature that amalgamates Quality of Experience (QoE) with customized Quality of Service (QoS) requirements to decide on a complex framework. The paper addresses the issue by aggregating consumer’s sentiments with customized QoS parameters to choose an optimal service provider. The paper uses the fuzzy Best Worst Method (BWM) to determine the weights of selection criteria and use the fuzzy TOPSIS to handle the uncertain linguistic preference. Analysis results demonstrate the applicability and effectiveness of the framework.
dc.language	en
dc.publisher	Springer International Publishing
dc.relation.ispartof	Lecture Notes in Networks and Systems
dc.relation.isbasedon	10.1007/978-3-030-96150-3_6
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Aggregating Fuzzy Sentiments with Customized QoS Parameters for Cloud Provider Selection Using Fuzzy Best Worst and Fuzzy TOPSIS
dc.type	Chapter
utslib.citation.volume	337
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
utslib.copyright.status	closed_access	*
dc.date.updated	2023-02-10T06:59:07Z
pubs.publication-status	Published
pubs.volume	337

Abstract:

Consumers often get confused to select the best cloud providers from the huge marketplace. The hesitancy of consumers further escalates when multiple service providers offer the same type and quality of services. To deal with such an uncertainty, the decision-makers always combine multiple factors to make an informed choice. Sentiment mining is one of the key parameters to determine the service quality and get an insight into the business. It assists service providers in precisely deduce consumer's emotions regarding the product. The analysis helps providers fine-tune the product based on consumer's sentiment and accommodates the consumer's request to find an optimal service provider. Several existing literature for cloud service selection mainly focuses on the Quality of Service (QoS) of the offered services. However, very few of them have considered the user experience of a consumer in the decision-making process. Moreover, there is minimal literature that amalgamates Quality of Experience (QoE) with customized Quality of Service (QoS) requirements to decide on a complex framework. The paper addresses the issue by aggregating consumer’s sentiments with customized QoS parameters to choose an optimal service provider. The paper uses the fuzzy Best Worst Method (BWM) to determine the weights of selection criteria and use the fuzzy TOPSIS to handle the uncertain linguistic preference. Analysis results demonstrate the applicability and effectiveness of the framework.

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http://hdl.handle.net/10453/166052