Visible to the public Energy Efficiency Evaluation Based on QoS Parameter Specification for Cloud Systems

TitleEnergy Efficiency Evaluation Based on QoS Parameter Specification for Cloud Systems
Publication TypeConference Paper
Year of Publication2020
AuthorsLong, Saiqin, Yu, Hao, Li, Zhetao, Tian, Shujuan, Li, Yun
Conference Name2020 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)
Date PublishedDec. 2020
ISBN Number978-1-7281-7649-9
Keywordsbelief rule base, Best Worst Method, cloud computing, cloud systems, compositionality, Conferences, energy consumption, Energy Efficiency Evaluation, High performance computing, Measurement, Metrics, pubcrawl, QoS, quality of service, resilience, Resiliency, Scientific Computing Security, System performance
AbstractEnergy 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.
Citation Keylong_energy_2020