Solution based on the DCIM model to assist in the energy efficiency process of small and medium data centers

Autores

  • Alexandre Barbosa de Souza
  • Flávio Barcelos Braz da Silva
  • Gustavo Maia de Almeida
  • Filipe Leôncio Braga

Palavras-chave:

DCIM, Energy Efficiency, Data Center, PUE, Artificial Intelligence

Resumo

In the current scenario of large data centers, the increase in demand for the provision of digital services
coupled with the increase in the volume of traffic generated by these services has driven the excessive and
increasing consumption of energy needed to supply and maintain the availability and quality of the services
provided. In order to improve and increase Energy Efficiency in Data Centers, several solutions are available
(policies, methods, metrics, tools, etc.) that assist in the process of implementing and maintaining modern and
efficient Energy Management. However, small and medium data centers also have characteristics similar to large
data centers. Only with consumption on a smaller scale but with the same challenges of increasing energy
efficiency. However, small data centers do not have the input and / or infrastructure available to large ones to
implement solutions related to Energy Efficiency, thus becoming a challenge in the area. This work proposes the
implementation of a solution based on the existing model on the DCIM platform (Data Center Infrastructure
Management), performing real-time monitoring of some of the infrastructure characteristics of the Data Center
environment that will assist in Energy Management aiming to achieve the maximum Energy Efficiency without
impacting the quality of its services. For this purpose, a physical layer will be implemented using SBC (Single
Board Computers) equipment that will function as a centralizer of the information collected through sensors
responsible for monitoring the Data Center environment, and an application layer that, in possession of the
information collected, it will carry out the treatment and analysis, resulting in analytical data, alerts and reports
that will serve as a basis to assist in the Energy Management process.

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Publicado

2024-06-22

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