Towards Extension of Data Centre Modelling Toolbox with Parameters Estimation

• Main Authors: Berezovskaya, Yulia, Yang, Chen-Wei, Vyatkin, Valeriy
• Other Authors: Department of Computer science, Electrical and Space engineering, Luleå University of Technology = Luleå Tekniska Universitet (LUT), Department of Electrical Engineering and Automation Aalto University, Aalto University, Luis M. Camarinha-Matos, Pedro Ferreira, Guilherme Brito, TC 5, WG 5.5
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2021
• Subjects: Data centre; Modelling; Power consumption; Parameter estimation; Matlab/Simulink; [INFO]Computer Science [cs]; Luleå
• Online Access: https://inria.hal.science/hal-03685940; https://inria.hal.science/hal-03685940/document; https://inria.hal.science/hal-03685940/file/512066_1_En_18_Chapter.pdf; https://doi.org/10.1007/978-3-030-78288-7_18

Part 5: Smart Energy Management International audience Modern data centres consume a significant amount of electricity. Therefore, they require techniques for improving energy efficiency and reducing energy waste. The promising energy-saving methods are those, which adapt the system energy use based on resource requirements at run-time. These techniques require testing their performance, reliability and effect on power consumption in data centres. Generally, real data centres cannot be used as a test site because of such experiments may violate safety and security protocols. Therefore, examining the performance of different energy-saving strategies requires a model, which can replace the real data centre. The model is expected to accurately estimate the energy consumption of data centre components depending on their utilisation. This work presents a toolbox for data centre modelling. The toolbox is a set of building blocks representing individual components of a typical data centre. The paper concentrates on parameter estimation methods, which use data, collected from a real data centre and adjust parameters of building blocks so that the model represents the data centre most accurately. The paper also demonstrates the results of parameters estimation on an example of EDGE module of SICS ICE data centre located in Luleå, Sweden.