A Hybrid Fuzzy Framework for Cloud Service Selection

被引：21

作者：

Le, Sun ^{[1
]}

Dong, Hai ^{[2
]}

Hussain, Farookh Khadeer ^{[3
]}

Hussain, Omar Khadeer ^{[4
]}

Ma, Jiangang ^{[1
]}

Zhang, Yanchun ^{[1
]}

机构：

[1] Victoria Univ, Ctr Appl Informat, Melbourne, Vic 8001, Australia

[2] RMIT Univ, Sch Comp Sci & Informat Technol, Melbourne, Vic, Australia

[3] Univ Technol Sydney, Sch Software, Sydney, NSW 2007, Australia

[4] Univ New S Wales, Australian Def Force Acad, Canberra, ACT, Australia

来源：

2014 IEEE 21ST INTERNATIONAL CONFERENCE ON WEB SERVICES (ICWS 2014) | 2014年

关键词：

Multi-criteria decision making; fuzzy AHP; fuzzy TOPSIS; fuzzy ontology; Cloud service selection; DECISION-MAKING; NUMBERS; SIMILARITY; TOPSIS; AHP;

D O I：

10.1109/ICWS.2014.53

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：313 / 320

页数：8

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