Optimally configuring an information landscape

• US 9,043,255 B2
• Filed: 05/09/2012
• Issued: 05/26/2015
• Est. Priority Date: 05/09/2012
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Byrne, Brian P., Pandit, Sushain
• Primary Examiner(s): Gaffin, Jeffrey A
• Assistant Examiner(s): Bharadwaj, Kalpana
• Application Number:
  US13/467,315
• Publication Number:
  US 20130304682A1
• Time in Patent Office: 1,112 Days
• Field of Search: 706/19
• US Class Current: 706/19
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06N 3/084 Backpropagation, e.g. using gradient descent

Abstract

According to an embodiment of the present invention, a system optimizes an information processing environment, and comprises at least one processor. The system collects information pertaining to operational behavior of the information processing environment and including a plurality of parameters. A neural network structure is established to associate the parameters to a desired operational performance characteristic for the information processing environment. The neural network structure is trained with the collected information from the information processing environment to produce a model for the information processing environment. The model is optimized to determine values for the parameters and the information processing environment is adjusted based on the determined parameter values to attain the desired operational performance of the information processing environment. Embodiments of the present invention further include a method and computer program product for optimizing an information processing environment in substantially the same manner described above.

Claims

1. A system for optimizing an information processing environment comprising:

at least one processor configured to;

collect information pertaining to operational behavior of the information processing environment, wherein the collected information includes a plurality of parameters for the information processing environment;

establish a neural network structure to associate the parameters to a desired operational performance characteristic for the information processing environment, wherein the neural network structure includes a series of neural networks each modeling a corresponding one of the parameters and an output node combining results of the neural networks to map the parameters to the desired operational performance characteristic of the information processing environment;

train the neural network structure with the collected information from the information processing environment to produce a model for the information processing environment; and

optimize the model to determine values for the parameters and adjust the information processing environment based on the determined parameter values to attain the desired operational performance of the information processing environment.

2. The system of claim 1, wherein the at least one processor is further configured to:

collect additional information pertaining to operational behavior of the adjusted information processing environment;

train the neural network structure with the additional information to update the model for the information processing environment; and

optimize the updated model to determine updated values for the parameters and adjust the information processing environment based on the determined updated parameter values.

3. The system of claim 1, wherein the neural network structure includes plural sets of weights for application to information transferred between nodes of the neural network structure, and training the neural network structure includes:

determining values for the plural sets of weights that enable the neural network structure to associate parameter values with the desired operational performance characteristic, wherein the model includes the parameter values, determined sets of weights, and the desired operational performance characteristic.

4. The system of claim 3, wherein optimizing the model includes:

determining values for the parameters that optimize the desired operational performance characteristic based on the determined sets of weights.

5. The system of claim 1, wherein training the neural network structure includes:

producing training data for the neural network structure from the collected information from the information processing environment, wherein the training data includes values for the parameters and the desired operational performance characteristic.

6. The system of claim 1, wherein the information processing environment includes an information landscape employing a plurality of information processing systems each contributing to the desired operational performance characteristic of the information landscape.

7. A computer program product for optimizing an information processing environment comprising:

a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising computer readable program code configured to;

collect information pertaining to operational behavior of the information processing environment, wherein the collected information includes a plurality of parameters for the information processing environment;

establish a neural network structure to associate the parameters to a desired operational performance characteristic for the information processing environment, wherein the neural network structure includes a series of neural networks each modeling a corresponding one of the parameters and an output node combining results of the neural networks to map the parameter to the desired operational performance characteristic of the information processing environment;

train the neural network structure with the collected information from the information processing environment to produce a model for the information processing environment; and

optimize the model to determine values for the parameters and adjust the information processing environment based on the determined parameter values to attain the desired operational performance of the information processing environment.

8. The computer program product of claim 7, wherein the computer readable program code further comprises computer readable program code configured to:

collect additional information pertaining to operational behavior of the adjusted information processing environment;

train the neural network structure with the additional information to update the model for the information processing environment; and

optimize the updated model to determine updated values for the parameters and adjust the information processing environment based on the determined updated parameter values.

9. The computer program product of claim 7, wherein the neural network structure includes plural sets of weights for application to information transferred between nodes of the neural network structure, and training the neural network structure includes:

determining values for the plural sets of weights that enable the neural network structure to associate parameter values with the desired operational performance characteristic, wherein the model includes the parameter values, determined sets of weights, and the desired operational performance characteristic.

10. The computer program product of claim 9, wherein optimizing the model includes:

determining values for the parameters that optimize the desired operational performance characteristic based on the determined sets of weights.

11. The computer program product of claim 7, wherein training the neural network structure includes:

producing training data for the neural network structure from the collected information from the information processing environment, wherein the training data includes values for the parameters and the desired operational performance characteristic.

12. The computer program product of claim 7, wherein the information processing environment includes an information landscape employing a plurality of information processing systems each contributing to the desired operational performance characteristic of the information landscape.