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Long, Saiqin, Yu, Hao, Li, Zhetao, Tian, Shujuan, Li, Yun.  2020.  Energy Efficiency Evaluation Based on QoS Parameter Specification for Cloud Systems. 2020 IEEE 22nd International Conference on High Performance Computing and Communications; IEEE 18th International Conference on Smart City; IEEE 6th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). :27–34.
Energy efficiency evaluation (EEE) is a research difficulty in the field of cloud computing. The current research mainly considers the relevant energy efficiency indicators of cloud systems and weights the interrelationship between energy consumption, system performance and QoS requirements. However, it lacks a combination of subjective and objective, qualitative and quantitative evaluation method to accurately evaluate the energy efficiency of cloud systems. We propose a novel EEE method based on the QoS parameter specification for cloud systems (EEE-QoS). Firstly, it reduces the metric values that affect QoS requirements to the same dimension range and then establishes a belief rule base (BRB). The best-worst method is utilized to determine the initial weights of the premise attributes in the BRB model. Then, the BRB model parameters are optimized by the mean-square error, the activation weight is calculated, and the activation rules of the evidence reasoning algorithm are integrated to evaluate the belief of the conclusion. The quantitative and qualitative evaluation of the energy efficiency of cloud systems is realized. The experiments show that the proposed method can accurately and objectively evaluate the energy efficiency of cloud systems.
Setyono, R. Puji, Sarno, R..  2018.  Vendor Track Record Selection Using Best Worst Method. 2018 International Seminar on Application for Technology of Information and Communication. :41–48.
Every company will largely depend on other companies. This will help unite a large business process. Risks that arise from other companies will affect the business performance of a company. Because of this, the right choice for suppliers is crucial. Each vendor has different characteristics. Everything is not always suitable basically the selection process is quite complex and risky. This has led to a new case study which has been studied for years by researchers known as Supplier Selection Problems. Selection of vendors with multi-criteria decision making has been widely studied over years ago. The Best Worst Method is a new science in Multi-Criteria Decision Making (MCDM) determination. In this research, taking case study at XYZ company is in Indonesia which is engaged in mining and industry. The research utilized the transaction data that have been recorded by the XYZ company and analyzed vendor valuation. The weighting of Best Worst Method is calculated based on vendor assessment result. The results show that XYZ company still focuses on Price as its key criteria.