High-performance computing installations, which are at the basis of web and cloud servers as well as supercomputers, are constrained by two main conflicting requirements: IT power consumption generated by the computing nodes and the heat that must be removed to avoid thermal hazards. In the worst cases, up to 60% of the energy consumed in a data center is used for cooling, often related to an over-designed cooling system. We propose a low-cost and battery-supplied wireless sensor network (WSN) for fine-grained, flexible and long-term data center temperature monitoring. The WSN has been operational collecting more than six million data points, with no losses, for six months without battery recharges. Our work reaches a 300× better energy efficiency than the previously reported WSNs for similar scenarios and on a 7× wider area. The data collected by the network can be used to optimize cooling effort while avoiding dangerous hot spots.

A LoRaWAN wireless sensor network for data center temperature monitoring

Polonelli T.;Bartolini A.;Benini L.
2019

Abstract

High-performance computing installations, which are at the basis of web and cloud servers as well as supercomputers, are constrained by two main conflicting requirements: IT power consumption generated by the computing nodes and the heat that must be removed to avoid thermal hazards. In the worst cases, up to 60% of the energy consumed in a data center is used for cooling, often related to an over-designed cooling system. We propose a low-cost and battery-supplied wireless sensor network (WSN) for fine-grained, flexible and long-term data center temperature monitoring. The WSN has been operational collecting more than six million data points, with no losses, for six months without battery recharges. Our work reaches a 300× better energy efficiency than the previously reported WSNs for similar scenarios and on a 7× wider area. The data collected by the network can be used to optimize cooling effort while avoiding dangerous hot spots.
2019
Lecture Notes in Electrical Engineering
169
177
Polonelli T.; Brunelli D.; Bartolini A.; Benini L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/788619
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