Machine-learning based optimization of data center designs and risks
AssigneeHewlett Packard Enterprise Development LP
InventorsMehmet Kivanc Ozonat, Tahir Cader, Matthew Richard Slaby
Life of this patent
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Abstract
In exemplary aspects of optimizing data centers, historical data corresponding to a data center is collected. The data center includes a plurality of systems. A data center representation is generated. The data center representation can be one or more of a schematic and a collection of data from among the historical data. The data center representation is encoded into a neural network model. The neural network model is trained using at least a portion of the historical data. The trained model is deployed using a first set of inputs, causing the model to generate one or more output values for managing or optimizing the data center with respect to design and risk aspects.
Claims22
An apparatus comprising,
- one or more processors, and
- at least one memory communicatively coupled to the one or more processors, the at least one memory storing machine readable instructions that, when executed by the one or more processors, cause the one or more processors to:
- receive historical data corresponding to a data center, the data center including a plurality of systems, a portion of the plurality of systems being housed in one or more facilities of the data center;
- generate a representation of the data center, the data center representation being one or more of a schematic and a collection of data from among the historical data;
- encode the data center representation into a neural network model;
- train the neural network model using at least a portion of the historical data;
- and
- deploy the trained model using a first set of inputs, causing the model to generate one or more output values for managing or optimizing the data center.
A computer implemented method, comprising:
- receiving historical data corresponding to a data center, the data center including a plurality of systems, a portion of the plurality of systems being housed in one or more facilities of the data center;
- generating a data center representation of the data center, the data center representation being one or more of a schematic and a collection of data from among the historical data;
- encoding the data center representation into a neural network model;
- training the neural network model using at least a portion of the historical data;
- and
- deploying the trained model using a first set of inputs, causing the model to generate one or more output values for managing or optimizing the data center.
Dependencies are inferred from the claim text.