Cloud Marginal Resource Allocation: A Decision Support Model

Hussain, W; Sohaib, O; Naderpour, M; Gao, H

Cloud Marginal Resource Allocation: A Decision Support Model

Hussain, W

Sohaib, O

Naderpour, M

Gao, H

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Publication Type:: Journal Article
Citation:: Mobile Networks and Applications, 2019
Issue Date:: 2019-01-01

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Field	Value	Language
dc.contributor.author	Hussain, W https://orcid.org/0000-0003-0610-4006	en_US
dc.contributor.author	Sohaib, O https://orcid.org/0000-0001-9287-5995	en_US
dc.contributor.author	Naderpour, M https://orcid.org/0000-0002-3549-3875	en_US
dc.contributor.author	Gao, H https://orcid.org/0000-0001-6861-9684	en_US
dc.date.issued	2019-01-01	en_US
dc.identifier.citation	Mobile Networks and Applications, 2019	en_US
dc.identifier.issn	1383-469X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/137399
dc.description.abstract	© 2019, Springer Science+Business Media, LLC, part of Springer Nature. One of the significant challenges for cloud providers is how to manage resources wisely and how to form a viable service level agreement (SLA) with consumers to avoid any violation or penalties. Some consumers make an agreement for a fixed amount of resources, these being the required resources that are needed to execute its business. Consumers may need additional resources on top of these fixed resources, known as– marginal resources that are only consumed and paid for in case of an increase in business demand. In such contracts, both parties agree on a pricing model in which a consumer pays upfront only for the fixed resources and pays for the marginal resources when they are used. A marginal resource allocation is a challenge for service provider particularly small- to medium-sized service providers as it can affect the usage of their resources and consequently their profits. This paper proposes a novel marginal resource allocation decision support model to assist cloud providers to manage the cloud SLAs before its execution, covering all possible scenarios, including whether a consumer is new or not, and whether the consumer requests the same or different marginal resources. The model relies on the capabilities of the user-based collaborative filtering method with an enhanced top-k nearest neighbor algorithm and a fuzzy logic system to make a decision. The proposed framework assists cloud providers manage their resources in an optimal way and avoid violations or penalties. Finally, the performance of the proposed model is shown through a cloud scenario which demonstrates that our proposed approach can assists cloud providers to manage their resources wisely to avoid violations.	en_US
dc.relation.ispartof	Mobile Networks and Applications	en_US
dc.relation.isbasedon	10.1007/s11036-019-01457-7	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	Networking & Telecommunications	en_US
dc.title	Cloud Marginal Resource Allocation: A Decision Support Model	en_US
dc.type	Journal Article
utslib.for	0805 Distributed Computing	en_US
utslib.for	0999 Other 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 Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US

Abstract:

© 2019, Springer Science+Business Media, LLC, part of Springer Nature. One of the significant challenges for cloud providers is how to manage resources wisely and how to form a viable service level agreement (SLA) with consumers to avoid any violation or penalties. Some consumers make an agreement for a fixed amount of resources, these being the required resources that are needed to execute its business. Consumers may need additional resources on top of these fixed resources, known as– marginal resources that are only consumed and paid for in case of an increase in business demand. In such contracts, both parties agree on a pricing model in which a consumer pays upfront only for the fixed resources and pays for the marginal resources when they are used. A marginal resource allocation is a challenge for service provider particularly small- to medium-sized service providers as it can affect the usage of their resources and consequently their profits. This paper proposes a novel marginal resource allocation decision support model to assist cloud providers to manage the cloud SLAs before its execution, covering all possible scenarios, including whether a consumer is new or not, and whether the consumer requests the same or different marginal resources. The model relies on the capabilities of the user-based collaborative filtering method with an enhanced top-k nearest neighbor algorithm and a fuzzy logic system to make a decision. The proposed framework assists cloud providers manage their resources in an optimal way and avoid violations or penalties. Finally, the performance of the proposed model is shown through a cloud scenario which demonstrates that our proposed approach can assists cloud providers to manage their resources wisely to avoid violations.

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http://hdl.handle.net/10453/137399