Methods, systems and appratuses for optimizing the bin selection of a network scheduling and configuration tool (NST) by bin allocation, demand prediction and machine learning
US11552857B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 28, 2019 |
| Grant date | Jan 10, 2023 |
| Priority date | — |
| Expiry date | Oct 28, 2041 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L49/25
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems and apparatuses to enable an optimum bin selection by implementing a neural network with a network scheduling and configuration tool (NST), the method includes: configuring an agent with a critic function from neural networks wherein the agent neural network represents each bin of the collection of bins in the network that performs an action, and a critic function evaluates a criteria of success for performing the action; processing, by a scheduling algorithm, the VLs by the NST; determining one or more reward functions using global quality measurements based on criteria comprising: a lack of available bins, a lack of available VLs, and successfully scheduling operations of a VL into a bin; and training the network based on a normalized state model of the scheduled network by using input data sets to arrive at an optimum bin selection.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.