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Self-regulated multi-criteria decision analysis: an autonomous brokerage-based approach for service provider ranking in the cloud
Type of publication
Straipsnis konferencijos medžiagoje Web of Science duomenų bazėje / Article in conference proceedings in Web of Science database (P1a1)
Author(s)
Wasim, Muhammad Umer | University of Luxembourg |
Abdallah, A. Z. A. Ibrahim | University of Luxembourg |
Bouvry, Pascal | University of Luxembourg |
Title
Self-regulated multi-criteria decision analysis: an autonomous brokerage-based approach for service provider ranking in the cloud
Date Issued
2017
Extent
p. 33-40
Is part of
Proceedings of the International Conference on Cloud Computing Technology and Science, CloudCom. 11-14 December 2017. Hong Kong : IEEE Computer Society, 2017. ISBN 9781538606926.
Field of Science
Abstract
The use of multi-criteria decision analysis (MCDA) by online broker to rank different service providers in the Cloud is based upon criteria provided by a customer. However, such ranking is prone to bias if the customer has insufficient domain knowledge. He/she may exclude relevant or include irrelevant criterion termed as 'misspecification of criterion'. This causes structural uncertainty within the MCDA leading to selection of suboptimal service provider by online broker. To cater such issue, we propose a self-regulatedMCDA, which uses notion of factor analysis from the field of statistics. Two QoS based datasets were used for evaluation of proposed model. The prior dataset i.e., feedback from customers, was compiled using leading review websites such as Cloud Hosting Reviews, Best Cloud Computing Providers, and Cloud Storage Reviews and Ratings. The later dataset i.e., feedback from servers, was generated from Cloud brokerage architecture that was emulated using high performance computing (HPC) cluster at University of Luxembourg (HPC @ Uni.lu). The results show better performance of proposed model as compared to its counterparts in the field. The beneficiary of the research would be enterprises that view insufficient domain knowledge as a limiting factor for acquisition of Cloud services.
Type of document
type::text::conference output::conference proceedings::conference paper
ISBN (of the container)
9781538606926
ISSN (of the container)
2330-2194
2330-2186
WOS
000427727800005
SCOPUS
2-s2.0-85044294352
eLABa
27145032
Coverage Spatial
Lietuva / Lithuania (LT)
Language
Anglų / English (en)
Bibliographic Details
20