Open AccessThe Power Control Method of Data Center Based on Cloud- Edge Collaboration
Author(s) -
Junjie Zhao,
Yucheng Hou,
Liu Liu,
Feng Xie,
Xiang Mao,
Ping Luo,
Jinxin Wang,
Zhiqiang Zhang,
Jie Deng
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1754/1/012094
Subject(s) - data center , cloud computing , computer science , enhanced data rates for gsm evolution , smoothing , distributed computing , grid , server farm , power (physics) , control (management) , real time computing , server , computer network , operating system , client–server model , telecommunications , geometry , mathematics , physics , quantum mechanics , artificial intelligence , computer vision
Data centers have the characteristics of huge energy consumption and strong power fluctuations. To solve the problem of unstable supply and demand such as frequent power fluctuations in the micro-grid of the data center using renewable energies, this paper establishes a controllable load model of server clusters based on the task migration mechanism by analyzing the various tasks and characteristics of large cloud data centers, as well as edge computing nodes. Through the collaborative optimization control of edge and cloud computing tasks, and dynamically adjusting and migrating the server cluster load, a new data center tie-line power control method is proposed. The results of calculation examples show that the method can achieve power smoothing of large-scale cloud data center tie lines through cloud-edge collaborative control.