Method and system of scheduling and linking virtual network functions

Abstract

The present invention discloses a method and system of scheduling and linking virtual network functions. The method comprises the following steps of constructing a Markov initial model according to the network environment information and the network request information; carrying out the deep reinforcement learning training on the Markov initial model to obtain a Markov training model by the randomgeneration action and in a back-propagation neural network manner; real-timely obtaining the network environment information and the network request information, and obtaining the virtual network function placement nodes and the service chains of the network requests according to the obtained network environment information, the network request information and the Markov training model. Accordingto the present invention, by carrying out the deep reinforcement learning training on the Markov initial model to obtain the Markov training model via the random generation action and in the back-propagation neural network manner, the optimal deployment of the network functions and the service chains can be realized furthest, and the purposes of reducing the total delay of the network requests and improving the network resource utilization rate are achieved.

Description

technical field [0001] The invention belongs to the field of network function virtualization research, and more specifically relates to a method and system for scheduling and linking virtual network functions. Background technique [0002] Network Function Virtualization (Network Function Virtualization, NFV) is a technology that uses virtualization technology to divide the functions of dedicated network equipment into several functional blocks, which are respectively realized by software virtualization, so that they can run on general-purpose computing platforms. Through network function virtualization, operators are no longer bound by dedicated network equipment, operating costs are greatly reduced, and the flexibility and scalability of network architecture, applications, and service deployment are greatly improved. [0003] The network function virtualization platform is mainly divided into four parts: network function virtualization infrastructure layer, including under...

AI Technical Summary

Problems solved by technology

[0007] Aiming at the above defects or improvement needs of the prior art, the present invention provides a method and system for scheduling and linking virtual network functions. Technical problems with low configuration efficiency

Images