Optimizing key allocation during roaming using machine learning
US11910249B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 2, 2021 |
| Grant date | Feb 20, 2024 |
| Priority date | — |
| Expiry date | Mar 11, 2042 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04W84/12
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Systems and methods are provided for optimizing resource consumption by bringing intelligence to the key allocation process for fast roaming. Specifically, embodiments of the disclosed technology use machine learning to predict which AP a wireless client device will migrate to next. In some embodiments, machine learning may also be used to select a subset of top neighbors from a neighborhood list. Thus, instead of allocating keys for each of the APs on the neighborhood list, key allocation may be limited to the predicted next AP, and the subset of top neighbors. In some embodiments, a reinforcement learning model may be used to dynamically adjust the size of the subset in order to optimize resources while satisfying variable client demand.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.