Decarbonisation of Data Centre Networks through Computing Power Migration

With the rapid development of Internet technologies and the widespread application of large-scale models, the computational load demand of data centers (DCs) continues to increase, exacerbating issues such as high energy consumption and operational costs. To address these challenges, DCs can improve their power and computing resource adjustment capabilities by migrating computational loads or incorporating energy storage systems to reduce operational costs. This paper aims to explore the economic impact of these two approaches on DCs. First, a computing power scheduling model for DCs is constructed. Then, we consider three different cases and use Yalmip and Cplex to solve the data migration strategy. Finally, the results demonstrate that the combination of energy storage and computing power migration not only facilitates the integration of renewable energy, but also yields better economic benefits.

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Publication Details

Published
2025-05-23
DOI
https://doi.org/10.1109/ccai65422.2025.11189418
Citations
17
Primary Topic
Software-Defined Networks and 5G
Type
article
Field-Weighted Citation Impact
25.28
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article

Decarbonisation of Data Centre Networks through Computing Power Migration

Heng Hu, Goran Štrbac, Spyros Giannelos, Zhigang Du et al.
17 citations
Software-Defined Networks and 5G
25.28
article

Decarbonisation of Data Centre Networks through Computing Power Migration

Heng Hu, Goran Štrbac, Spyros Giannelos, Zhigang Du, Hairong Yin, T. Liu, Xi Zhang, Meng Hou
article en
17 citations

Abstract

With the rapid development of Internet technologies and the widespread application of large-scale models, the computational load demand of data centers (DCs) continues to increase, exacerbating issues such as high energy consumption and operational costs. To address these challenges, DCs can improve their power and computing resource adjustment capabilities by migrating computational loads or incorporating energy storage systems to reduce operational costs. This paper aims to explore the economic impact of these two approaches on DCs. First, a computing power scheduling model for DCs is constructed. Then, we consider three different cases and use Yalmip and Cplex to solve the data migration strategy. Finally, the results demonstrate that the combination of energy storage and computing power migration not only facilitates the integration of renewable energy, but also yields better economic benefits.

North China Electric Power University (CN), Inner Mongolia Electric Power (China) (CN), China Power Engineering Consulting Group (China) (CN), China Electric Power Research Institute, Imperial College London (GB)
Openalex Percentile: Top 0%
Software-Defined Networks and 5G
25.28
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Decarbonisation of Data Centre Networks through Computing Power Migration — Heng Hu, Goran Štrbac, et al. · (2025) | TGRS Research Map | TGRS