ECDX: Energy consumption prediction model based on distance correlation and XGBoost for edge data center

Chuang Li, Dan Zhu, Chunhua Hu, Xiaolong Li, Suqin Nan, Hua Huang

Abstract: Highlights•Distance correlation aims to effectively extract a representative low-dimensional feature dataset from the original high-dimensional feature dataset.•We introduce an energy consumption prediction model named ECDX. For four workloads, the XGBoost algorithm is used for modeling to improve the model adaptability.•We conduct several simulation experiments using real server performance data to verify the effectiveness and adaptability of the ECDX model with different load types.