Seasonal trending, forecasting, anomaly detection, and endpoint prediction of java heap usage
US10205640B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 17, 2013 |
| Grant date | Feb 12, 2019 |
| Priority date | — |
| Expiry date | Jul 21, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2201/88
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Data can be categorized into facts, information, hypothesis, and directives. Activities that generate certain categories of data based on other categories of data through the application of knowledge which can be categorized into classifications, assessments, resolutions, and enactments. Activities can be driven by a Classification-Assessment-Resolution-Enactment (CARE) control engine. The CARE control and these categorizations can be used to enhance a multitude of systems, for example diagnostic system, such as through historical record keeping, machine learning, and automation. Such a diagnostic system can include a system that forecasts computing system failures based on the application of knowledge to system vital signs such as thread or stack segment intensity and memory heap usage. These vital signs are facts that can be classified to produce information such as memory leaks, convoy effects, or other problems. Classification can involve the automatic generation of classes, states, observations, predictions, norms, objectives, and the processing of sample intervals having irregular durations.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.