A Fuzzy-Multi Attribute Decision Making approach for efficient service selection in cloud environments

作者：

Highlights：

• FMADM, a hybrid trust prediction model for efficient cloud service selection.

• Picture fuzzy set-MARCOS to address uncertainty in the cloud service assessment data.

• Naïve Bayes determine the weights of the QoS parameters.

• Random forest classifier predicts the trust values of cloud services.

• The efficiency of FMADM was evaluated using QWS dataset.

摘要

•FMADM, a hybrid trust prediction model for efficient cloud service selection.•Picture fuzzy set-MARCOS to address uncertainty in the cloud service assessment data.•Naïve Bayes determine the weights of the QoS parameters.•Random forest classifier predicts the trust values of cloud services.•The efficiency of FMADM was evaluated using QWS dataset.

论文关键词：Cloud service selection,Multi-Attribute Decision Making,Naïve Bayes,Picture Fuzzy Sets,Trust Prediction

论文评审过程：Received 6 September 2021, Revised 22 February 2022, Accepted 5 May 2022, Available online 21 May 2022, Version of Record 22 June 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117526