Causal attention-based multi-stream RNN for computer system metric prediction and influential events identification based on metric and event logs
US11782812B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 1, 2021 |
| Grant date | Oct 10, 2023 |
| Priority date | — |
| Expiry date | Dec 3, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for system metric prediction and influential events identification by concurrently employing metric logs and event logs is presented. The method includes concurrently modeling multivariate metric series and individual events in event series by a multi-stream recurrent neural network (RNN) to improve prediction of future metrics, where the multi-stream RNN includes a series of RNNs, one RNN for each metric and one RNN for each event sequence and modeling causality relations between the multivariate metric series and the individual events in the event series by employing an attention mechanism to identify target events most responsible for fluctuations of one or more target metrics.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.