Adapting a pre-trained distributed resource predictive model to a target distributed computing environment
US10691491B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 19, 2016 |
| Grant date | Jun 23, 2020 |
| Priority date | — |
| Expiry date | Oct 19, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems for distributed resource system management. A first computing system operates in a first computing environment. A predictive model is trained in the first computing environment to form a trained resource performance predictive model that comprises a set of trained model parameters to capture at least computing and storage IO parameters that are responsive to execution of one or more workloads that consume computing and storage resources in the first computing environment. When the trained resource performance predictive model is deployed to a second computing environment, various computing system configuration differences, and/or workload differences and/or other differences between the first computing environment and the second computing environment are detected and measured. Responsive to the detected differences and/or measurements, some of the trained resource performance predictive model parameters are modified to adapt the trained resource performance predictive model to any of the detected and/or measured characteristics of the second computing environment.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.