System and methods for intelligent service function placement and autoscale based on machine learning
US10419530B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 2, 2015 |
| Grant date | Sep 17, 2019 |
| Priority date | — |
| Expiry date | Dec 6, 2036 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L67/63
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
A method implemented by a computing device to optimize resource usage of service function chains (SFCs) in a network using machine learning. The method includes obtaining, from an autoscale machine learning (ML) system associated with a virtual network function (vNF), a suggested adjustment to an amount of resources provisioned for the vNF. The autoscale ML system is trained online using machine learning to predict an amount of resources to be utilized by the vNF. The autoscale ML system is configured to receive as input an amount of resources currently utilized by the vNF and an amount of resources currently available to the vNF, determine using machine learning the suggested adjustment to the amount of resources provisioned for the vNF based on the input, and output the suggested adjustment. The method further includes providing the suggested adjustment to a resource re-allocator component.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.