In this paper, we consider a server cooling system in a data center with fans and a super-multipoint temperature sensing technology using optimal time-domain reflectometry of optical fiber. The sensing system was developed to visualize the temperature distribution of the room in real time, and it can also be a key technology to control the distribution in order to reduce total power consumption in data centers. In this paper, we first present a concept of the fan control system. The objective of the system is to uniformize the rack air inlet temperature distribution in the presence of heat from each server. Since the control scheme requires a dynamical model of the temperature variations in the room, this paper mainly addresses the modeling. The challenge of the modeling stems from a large volume of data provided by the sensing system. It is computationally hard to directly apply standard identification techniques to the data. We thus present a two-stage reduction scheme of the output dimension using the concept of so-called mutual information. The effectiveness of the proposed scheme is finally demonstrated using real data.
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