Intelligent mapping method for cloud tenant virtual network based on reinforcement learning model
US11973662B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 31, 2023 |
| Grant date | Apr 30, 2024 |
| Priority date | — |
| Expiry date | Aug 31, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L43/20
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
The present disclosure discloses an intelligent mapping method for a cloud tenant virtual network based on a reinforcement learning model, where a mapping algorithm is used to combine a resource abstraction model, Blocking Island, with a deep reinforcement learning algorithm, Actor-Critic, reasonably abstract underlying network resources by means of the Blocking Island model, and efficiently represent resource connectivity information of the entire network with an amount of available resources between nodes as a lower bound. The method specifically includes: (1): completing modeling of virtual network embedding; (2): modeling computing resources and bandwidth resources in a physical network; (3): constructing a neural network; and the like. Compared with the prior art, the present disclosure has better performance in average mapping cost, benefit-cost ratio, total benefit value and mapping success rate, further improves mapping accuracy, reduces the average mapping cost, and has a wide application prospect.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.