Energy Efficiency of Data Centers: A data-driven model-based approach

Hadid, Baya; Lecœuche, S.; Gille, D.; Labarre, C.

doi:10.1109/energycon.2016.7514136

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2020

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“…The state-of-the-art methods in mathematical modeling of data center cooling system are physical modeling, Computational Fluid Dynamics (CFD) modeling [11,20], and recently also data-driven modeling including neural networks [1,6,8]. CFD models target the air flow and heat transfer in data centers, but usually only for the air interactions in the server room.…”

Section: Introductionmentioning

confidence: 99%

Physical and Data-Driven Models for Edge Data Center Cooling System

Siltala

Brännvall

Gústafsson

et al. 2020

2020 Swedish Workshop on Data Science (SweDS)

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Edge data centers are expected to become prevalent providing low latency computing power for 5G mobile and IoT applications. This article develops two models for the complete cooling system of an edge data center: one model based on the laws of thermodynamics and one data-driven model based on LSTM neural networks. The models are validated against an actual edge data center experimental set-up showing root mean squared errors (RMSE) for most individual components below 1°C over a simulation period of approximately 10 hours; which compares favourably to state-of-the-art models.

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Section: Introductionmentioning

confidence: 99%