Cloud-FuSeR: Fuzzy ontology and MCDM based cloud service selection
- Publication Type:
- Journal Article
- Citation:
- Future Generation Computer Systems, 2016, 57 pp. 42 - 55
- Issue Date:
- 2016-04-01
Closed Access
| Filename | Description | Size | |||
|---|---|---|---|---|---|
| 1-s2.0-S0167739X15003829-main.pdf | Published Version | 1.82 MB |
Copyright Clearance Process
- Recently Added
- In Progress
- Closed Access
This item is closed access and not available.
© 2015 Elsevier B.V. All rights reserved. With the rapidly growing number of available Cloud services, to fulfill the need for ordinary users to select accurate services has become a significant challenge. However, as a Cloud service environment encompasses many uncertainties that may hinder users to make sound decisions, it is highly desirable to handle fuzzy information when choosing a suitable service in an uncertain environment. In this paper, we present a novel fuzzy decision-making framework that improves the existing Cloud service selection techniques. In particular, we build a fuzzy ontology to model uncertain relationships between objects in databases for service matching, and present a novel analytic hierarchy process approach to calculate the semantic similarity between concepts. We also present a multi-criteria decision-making technique to rank Cloud services. Furthermore, we conduct extensive experiments to evaluate the performance of the fuzzy ontology-based similarity matching. The experimental results show the efficiency of the proposed method.
Please use this identifier to cite or link to this item: