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Cooling control restraining effects due to ICT equipment utilization of disturbance based on model predictive control for modular data center

机译:基于模块化数据中心模型预测控制的ICT设备扰动对制冷控制的抑制作用

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This paper proposes a cooling control method that reduces spikes in CPU temperature that occur due to fluctuation in the utilization of information communication technology (ICT) equipment based on model predictive control (MPC) for a modular datacenter. To cope with the fluctuations, the proposed method not only considers the server power consumption using a prediction model, but also switches between an MPC controller and a necessary-air-volume controller based on the rate at which server power consumption rises. The MPC controller controls the CPU temperature in order to do three things simultaneously: avoid throttling the operation of the CPU, reduce as much as possible the power consumed by data center cooling fans, and adjust for the effects of fluctuations. The necessary-air-volume controller calculates the command value of the revolution speed of the cooling fans to supply the air volume required during maximum CPU utilization. The results of our control simulation show that the proposed control method can drastically reduce spikes in CPU temperature. The proposed method provided energy savings of more than 37.6% compared to the conventional control method under conditions where the CPU utilization is 80% and the fresh air temperature is 20°C.
机译:本文提出了一种冷却控制方法,该方法可减少基于模块化数据中心的模型预测控制(MPC)的信息通信技术(ICT)设备利用率波动引起的CPU温度峰值。为了应对波动,所提出的方法不仅使用预测模型考虑服务器功耗,而且根据服务器功耗上升的速率在MPC控制器和必要的风量控制器之间进行切换。 MPC控制器控制CPU温度以便同时执行三件事:避免限制CPU的运行,尽可能减少数据中心冷却风扇所消耗的功率,并针对波动的影响进行调整。必需风量控制器计算冷却风扇转速的指令值,以提供最大CPU使用率时所需的风量。我们的控制仿真结果表明,所提出的控制方法可以大大降低CPU温度的峰值。与传统的控制方法相比,在CPU利用率为80%,新鲜空气温度为20°C的情况下,与传统的控制方法相比,该方法可节省超过37.6%的能源。

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