Allocating optimized resources in the cloud by a viable SLA xodel

Hussain, W; Hussain, F; Hussain, O

Allocating optimized resources in the cloud by a viable SLA xodel

Hussain, W

Hussain, F

Hussain, O

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Publication Type:: Conference Proceeding
Citation:: 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016, 2016, pp. 1282 - 1287
Issue Date:: 2016-11-07

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Field	Value	Language
dc.contributor.author	Hussain, W https://orcid.org/0000-0003-0610-4006	en_US
dc.contributor.author	Hussain, F https://orcid.org/0000-0003-1513-8072	en_US
dc.contributor.author	Hussain, O	en_US
dc.date.issued	2016-11-07	en_US
dc.identifier.citation	2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016, 2016, pp. 1282 - 1287	en_US
dc.identifier.isbn	9781509006250	en_US
dc.identifier.uri	http://hdl.handle.net/10453/121816
dc.description.abstract	© 2016 IEEE. A cloud business environment comprises service providers and service consumers. Services are supplied through a Service Level Agreement (SLA) which defines all deliverables, commitments, obligations, QoS, violation penalties etc. that help a service provider and a service consumer to execute their business transactions. The primary aim of a service provider is to fulfill its commitment to a consumer by forming a viable SLA that wisely assigns the appropriate amount of resources to a requesting consumer. In this paper, we propose a viable SLA model that helps a service provider form a viable agreement with a consumer, based on its previous resource usage profile. The model uses a Fuzzy Inference System and takes the reliability and the contract duration of a consumer as input to calculate the suitability of this consumer, which is also used as input along with the risk propensity of a service provider to determine the amount of resources to offer to a consumer. We evaluate our approach and find that by using an optimized viable SLA model, providers are able to allocate an appropriate amount of resources to avoid an SLA violation.	en_US
dc.relation.ispartof	2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016	en_US
dc.relation.isbasedon	10.1109/FUZZ-IEEE.2016.7737836	en_US
dc.title	Allocating optimized resources in the cloud by a viable SLA xodel	en_US
dc.type	Conference Proceeding
utslib.for	080301 Bioinformatics Software	en_US
utslib.for	080109 Pattern Recognition and Data Mining	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 - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2016 IEEE. A cloud business environment comprises service providers and service consumers. Services are supplied through a Service Level Agreement (SLA) which defines all deliverables, commitments, obligations, QoS, violation penalties etc. that help a service provider and a service consumer to execute their business transactions. The primary aim of a service provider is to fulfill its commitment to a consumer by forming a viable SLA that wisely assigns the appropriate amount of resources to a requesting consumer. In this paper, we propose a viable SLA model that helps a service provider form a viable agreement with a consumer, based on its previous resource usage profile. The model uses a Fuzzy Inference System and takes the reliability and the contract duration of a consumer as input to calculate the suitability of this consumer, which is also used as input along with the risk propensity of a service provider to determine the amount of resources to offer to a consumer. We evaluate our approach and find that by using an optimized viable SLA model, providers are able to allocate an appropriate amount of resources to avoid an SLA violation.

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

http://hdl.handle.net/10453/121816