A modified approach for thermal distribution monitoring of the container data center by thermal image registration

Liu, Huan; Xie, Ting; Ran, Jian; Gao, Shan

doi:10.1109/cisp-bmei.2016.7852718

Cited by 2 publications

(1 citation statement)

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“…A monitoring approach was proposed by Liu et al [38] for monitoring a container data center using a thermal camera. First, the thermal images with their corresponding visual effects are matched based on the texture characteristics, and then the thermal distribution of each server used to extract the feature of the hotspot or server from the standard distribution is standardized.…”

Section: Simulationmentioning

confidence: 99%

Research advances on AI-powered thermal management for data centers

Liu

Aljbri

Song

et al. 2022

Tsinghua Sci. Technol.

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Given the complex nature of data centers' thermal management, which costs too many resources, processing time, and energy consumption, thermal awareness and thermal management powered by artificial intelligence (AI ) are the targeted study. In addition to a few research on AI techniques and models, other strategies have also been introduced in recent years. Data center models, including cooling, thermal, power, and workload models, and their relationship are factors that need to be understood in the optimal thermal management system.Simulation approaches have been proposed to help validate new models or methods used for scheduling and consolidating processes and virtual machines (VMs), hotspot identification, thermal state estimation, and power usage change. AI-powered thermal optimization leads to improved process scheduling and consolidation of VMs and eliminates the hotspot from happening. At present, research on AI-powered thermal control is still in its infancy. This paper concludes with four issues in thermal management, which will be the scope of further research.

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Section: Simulationmentioning

confidence: 99%