Optimizing data center controls using neural networks
US10643121B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 19, 2017 |
| Grant date | May 5, 2020 |
| Priority date | — |
| Expiry date | Aug 18, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/092
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for improving operational efficiency within a data center by modeling data center performance and predicting power usage efficiency. An example method receives a state input characterizing a current state of a data center. For each data center setting slate, the state input and the data center setting slate are processed through an ensemble of machine learning models. Each machine learning model is configured to receive and process the state input and the data center setting slate to generate an efficiency score that characterizes a predicted resource efficiency of the data center if the data center settings defined by the data center setting slate are adopted t. The method selects, based on the efficiency scores for the data center setting slates, new values for the data center settings.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.