@inproceedings{5c17bfd2c6f247dbbd257aa39caadee1,
title = "Energy Consumption of IT System in Cloud Data Center: Architecture, Factors and Prediction",
abstract = "In recent years, as cloud data center has grown constantly in size and quantity, the energy consumption of cloud data center has increased dramatically. Therefore, it is of great significance to study the energy-saving issues of cloud data centers in depth. Therefore, this paper analyzes the architecture of energy consumption of IT system in cloud data centers and proposes a new framework for collecting energy consumption. Based on this framework, the factors affecting energy consumption are studied, and various parameters closely related to energy consumption are selected. Finally, the RBF neural network is used to model and predict the energy consumption of the cloud data centers, which is aim to prove the accuracy of the framework for collecting energy consumption and influencing factors. The experimental results show that these parameters under the framework for collecting energy consumption have better accuracy and adaptability to the prediction of energy consumption in cloud data centers than the previous model of energy consumption prediction.",
keywords = "Architecture, Cloud computing, Cloud data center, Energy consumption, Prediction",
author = "Haowei Lin and Xiaolong Xu and Xinheng Wang",
note = "Funding Information: This work was jointly supported by National Key Research and Development Program of China under Grant 2018YFB1003702, Jiangsu Key Laboratory of Big Data Security & Intelligent Processing, and the Talent Project in Six Fields of Jiangsu Province under Grant 2015-JNHB-012. Funding Information: Acknowledgement. This work was jointly supported by National Key Research and Development Program of China under Grant 2018YFB1003702, Jiangsu Key Laboratory of Big Data Security & Intelligent Processing, and the Talent Project in Six Fields of Jiangsu Province under Grant 2015-JNHB-012. Publisher Copyright: {\textcopyright} 2019, IFIP International Federation for Information Processing.; 16th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2019 ; Conference date: 23-08-2019 Through 24-08-2019",
year = "2019",
doi = "10.1007/978-3-030-30709-7_25",
language = "English",
isbn = "9783030307080",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "311--315",
editor = "Xiaoxin Tang and Quan Chen and Pradip Bose and Weiming Zheng and Jean-Luc Gaudiot",
booktitle = "Network and Parallel Computing - 16th IFIP WG 10.3 International Conference, NPC 2019, Proceedings",
}