The operation of today’s data centers increasingly relies on environmental data collection and analysis to operate the cooling infrastructure as efficiently as possible and to maintain the reliability of IT equipment. This in turn emphasizes the importance of the quality of the data collected and their relevance to the overall operation of the data center. This study presents an experimentally based analysis and comparison between two different approaches for environmental data collection; one using a discrete sensor network, and another using available data from installed IT equipment through their Intelligent Platform Management Interface (IPMI). The comparison considers the quality and relevance of the data collected and investigates their effect on key performance and operational metrics. The results have shown the large variation of server inlet temperatures provided by the IPMI interface. On the other hand, the discrete sensor measurements showed much more reliable results where the server inlet temperatures had minimal variation inside the cold aisle. These results highlight the potential difficulty in using IPMI inlet temperature data to evaluate the thermal environment inside the contained cold aisle.

The study also focuses on how industry common methods for cooling efficiency management and control can be affected by the data collection approach. Results have shown that using preheated IPMI inlet temperature data can lead to unnecessarily lower cooling set points, which in turn minimizes the potential cooling energy savings. It was shown in one case that using discrete sensor data for control provides 20% more energy savings than using IPMI inlet temperature data.

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