Energy efficiency improvement method for data centers based on hybrid proximal policy optimization algorithm

Heping Fang; Shihang Yang; Shuhong Peng; Shuguang Liu

doi:10.1117/12.3011982

7 December 2023 Energy efficiency improvement method for data centers based on hybrid proximal policy optimization algorithm

Heping Fang, Shihang Yang, Shuhong Peng, Shuguang Liu

Author Affiliations +

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 1294104 (2023) https://doi.org/10.1117/12.3011982
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

As an essential support for technology applications such as cloud computing and artificial intelligence, data centers face a pressing need to balance their demand with their own high energy consumption. Since the energy consumption of the Information Technology (IT) systems and cooling systems accounts for the majority of total energy consumption in data centers, a collaborative optimization framework called COHPPO based on a Hybrid Proximal Policy Optimization algorithm (HPPO) is proposed, which controls IT system and cooling system in a coordinated manner, fully compressing the resource redundancy of the IT system and cooling redundancy of the cooling system. The HPPO algorithm is trained and verified using a task dataset and a simulation platform that simulates the environmental state inside the data center. The experimental results demonstrate that the COHPPO collaborative optimization framework proposed in this paper can effectively improve the energy efficiency of the data center and the stability of its internal environment.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Heping Fang, Shihang Yang, Shuhong Peng, and Shuguang Liu "Energy efficiency improvement method for data centers based on hybrid proximal policy optimization algorithm", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 1294104 (7 December 2023); https://doi.org/10.1117/12.3011982

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available