Dynamic resource distribution using periodicity-aware predictive modeling
US10484301B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 30, 2016 |
| Grant date | Nov 19, 2019 |
| Priority date | — |
| Expiry date | Jan 17, 2037 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L41/16
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Resource allocation techniques for distributed data storage. A set of distributed storage system historical resource usage measurements are collected and stored using distributed storage system measurement techniques. The resource usage metrics are associated with and/or derived from processing entities in the distributed storage computing system. An analysis module determines a training window time period corresponding to a portion of the collected distributed storage system historical resource usage measurements. The training window time period is determined so as to provide an earlier time boundary and a later time boundary that defines a periodically recurring portion of the distributed storage system historical resource usage measurements. A latest cycle of those periodically recurring measurements are then used to train a predictive model, which in turn is used to produce distributed storage system predicted resource usage characteristics. Resource allocation decisions are made based at least in part on predictions from the trained predictive model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.