Cross-trace scalable issue detection and clustering
US8538897B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 3, 2010 |
| Grant date | Sep 17, 2013 |
| Priority date | — |
| Expiry date | Aug 14, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F11/3409
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques and systems for cross-trace scalable issue detection and clustering that scale-up trace analysis for issue detection and root-cause clustering using a machine learning based approach are described herein. These techniques enable a scalable performance analysis framework for computing devices addressing issue detection, which is designed as a multiple scale feature for learning based on issue detection, and root cause clustering. In various embodiments the techniques employ a cross-trace similarity model, which is defined to hierarchically cluster problems detected in the learning based issue detection via butterflies of trigram stacks. The performance analysis framework is scalable to manage millions of traces, which include high problem complexity.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.