Robust training technique to facilitate prognostic pattern recognition for enterprise computer systems
US10796242B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 25, 2016 |
| Grant date | Oct 6, 2020 |
| Priority date | — |
| Expiry date | Aug 8, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F11/3058
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The disclosed embodiments relate to a technique for training a prognostic pattern-recognition system to detect incipient anomalies that arise during execution of a computer system. During operation, the system gathers and stores telemetry data obtained from n sensors in the computer system during operation of the computer system. Next, the system uses the telemetry data gathered from the n sensors to train a baseline model for the prognostic pattern-recognition system. The prognostic pattern-recognition system then uses the baseline model in a surveillance mode to detect incipient anomalies that arise during execution of the computer system. The system also uses the stored telemetry data to train a set of additional models, wherein each additional model is trained to operate with one or more missing sensors. Finally, the system stores the additional models to be used in place of the baseline model when one or more sensors fail in the computer system.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.