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, Tommaso; Brunelli, Davide; Bartolini, Andrea; Benini, Luca. - 573:(2019), pp. 169-177. (Intervento presentato al convegno APPLEPIES 2018 tenutosi a Pisa nel 26th-27th September 2018) [10.1007/978-3-030-11973-7_20].
A LoRaWAN wireless sensor network for data center temperature monitoring
Brunelli, Davide;Bartolini, Andrea;
2019-01-01
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.File | Dimensione | Formato | |
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