Systems and methods of forecasting temperatures of storage objects using machine learning
US12067280B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 23, 2022 |
| Grant date | Aug 20, 2024 |
| Priority date | — |
| Expiry date | Nov 3, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques for forecasting temperatures of storage objects in a storage system using machine learning (ML). The techniques can include forecasting at least one temperature of a storage object using at least one ML model, modifying storage of the storage object based on the at least one temperature of the storage object, and, having modified storage of the storage object, obtaining at least one performance metric associated with the storage object. The techniques can further include, based on the performance metric(s), varying a frequency of forecasting the at least one temperature of the storage object, retraining the at least one ML model used in forecasting the at least one temperature, and/or adjusting at least one operational parameter of the system. The techniques provide increased accuracy over known statistical approaches to forecasting temperatures of storage objects, leading to increased performance gains in terms of IO latency, IO operations per second, and bandwidth.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.