Data storage system with self tuning based on cluster analysis of workload features
US12124714B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 20, 2022 |
| Grant date | Oct 22, 2024 |
| Priority date | — |
| Expiry date | Jul 20, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F3/0685
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A data storage system includes a tuner that obtains data samples for data storage operations of workloads and calculates feature measures for a set of features of the data storage operations over aggregation intervals of an operating period. It further (1) applies a cluster analysis to the feature measures to define a set of clusters, and assigns the feature measures to the clusters, and (2) applies a classification analysis to the feature measures labelled by their clusters to identify dominating features of each cluster, and generates workload profiles for the clusters based on the dominating features, and then automatically adjusts configurable processing mechanisms (e.g., caching or tiering) based on the workload profiles and performance or efficiency goals.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.