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- W2899217548 abstract "Changes in operating conditions in a data center lead to heating-up of IT equipment and generation of hot-spots. A required supply of cold air at a specific temperature with an adequate flow rate needs to be maintained to avoid such hot-spots. To do so, appropriately identified Air Control Units (ACUs) that have the best causal effect on the cabinets where the IT equipment runs, need to change the air supply characteristics (i.e., supply-air temperature and flow rate). Hence, it is essential to determine such a relationship between changes in supply from an ACU to its effect on cabinets. In this paper, we study the use of Granger Causality to identify such a relationship between air supply sources and cabinets in a data center. Using an industrial data center simulator (6SigmaRoom), we show that the ACUs exhibiting Granger Causality with cabinets have a time-series inference based unidirectional temporal precedence relationship between them that establishes the relationship between the ACUs and cabinets." @default.
- W2899217548 created "2018-11-09" @default.
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- W2899217548 date "2018-09-01" @default.
- W2899217548 modified "2023-09-27" @default.
- W2899217548 title "Causality-Based Thermal Prediction for Data Center" @default.
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- W2899217548 doi "https://doi.org/10.1109/etfa.2018.8502473" @default.
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