DocumentCode :
125400
Title :
A Hybrid Fuzzy Framework for Cloud Service Selection
Author :
Le Sun ; Hai Dong ; Hussain, Farookh Khadeer ; Hussain, Omar K. ; Jiangang Ma ; Yanchun Zhang
Author_Institution :
Centre for Appl. Inf., Victoria Univ., Melbourne, VIC, Australia
fYear :
2014
fDate :
June 27 2014-July 2 2014
Firstpage :
313
Lastpage :
320
Abstract :
QoS-based service rating has made positive contributions to the area of service selection. Especially for Cloud service users, the right decision when choosing suitable Cloud services can help them improve user satisfaction and trading revenues. This work aims to address the issue of uncertainty in service requests, service descriptions, user and expert preferences, as well as evaluation criteria in a MCDM-based service selection procedure. A hybrid fuzzy framework for Cloud service selection is proposed, addressing the challenge using three approaches: a fuzzy-ontology-based approach for function matching and service filtering, a fuzzy AHP technique for informed criterion weighting, and, a fuzzy TOPSIS approach for service ranking.
Keywords :
analytic hierarchy process; cloud computing; fuzzy set theory; ontologies (artificial intelligence); user interfaces; MCDM-based service selection procedure; QoS-based service rating; cloud service selection; evaluation criteria; expert preferences; function matching; fuzzy AHP technique; fuzzy TOPSIS approach; fuzzy-ontology-based approach; hybrid fuzzy framework; informed criterion weighting; multicriteria decision making; service descriptions; service filtering; service ranking; service requests; trading revenue improvement; user preferences; user satisfaction improvement; Cloud computing; Computational modeling; Finite impulse response filters; Ontologies; Quality of service; Time complexity; Vectors; Cloud service selection; Multi-criteria decision making; fuzzy AHP; fuzzy TOPSIS; fuzzy ontology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Services (ICWS), 2014 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4799-5053-9
Type :
conf
DOI :
10.1109/ICWS.2014.53
Filename :
6928913
Link To Document :
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