Method and apparatus for autonomous services composition

Patent metadata

Field	Value
Publication number	US-10846706-B2
Application number	US-202016736982-A
Country	US
Kind code	B2
Filing date	Jan 8, 2020
Priority date	Feb 13, 2016
Publication date	Nov 24, 2020
Grant date	Nov 24, 2020

Abstract

A cloud services composition system allows customers to interactively create service constructs from network function virtualization resources. The network function virtualization primitives are modeled using a standard modeling language. An expert system suggests network function virtualization resources for use in the service construct, based on an expert system learning algorithm. The customer uses a graphical user interface to interconnect the resources and create the service construct. The process may involve collaboration with the network provider. The resulting construct is validated for use in a communications network.

First claim

What is claimed is:

1. A method, comprising:
by an intelligent agent, receiving from a user equipment a functional description of a requested network service in a communications network, the communications network comprising a plurality of virtualized network function resources;
by the intelligent agent, employing a learning algorithm to perform an analysis of the functional description of the requested network service, the learning algorithm being trained using prior customer service creation requests, the learning algorithm using a plurality of resource models describing behaviors of the virtualized network function resources;
by the intelligent agent, presenting via the user equipment a composition environment comprising icons representing a suggested subset of the virtualized network function resources for use in composing the requested network service, the suggested subset being based on the analysis of the functional description of the requested network service;
by the intelligent agent, providing assistance in defining an arrangement of the icons in the composition environment including interconnections among the icons, the providing assistance using the learning algorithm;
by the intelligent agent, receiving the arrangement of the icons from the composition environment;
by the intelligent agent, overseeing validation of the arrangement of the icons as representing a feasible service composition for deployment in the communications network; and
deploying the feasible service composition in the communications network.

2. The method of claim 1 , further comprising:
receiving real-time asset information regarding the feasible service composition from a virtual network function management framework, the virtual network function management framework including a data collection, analytics and event engine and an active and available inventory subsystem; and
presenting real time reports of the deployed feasible service composition in a dashboard of the composition environment using analytics and visualization tools.

3. The method of claim 1 , wherein the plurality of resource models includes models describing network requirements of the virtualized network function resources, exposed properties of the virtualized network function resources and interconnection relationships of the virtualized network function resources with other virtualized network function resources.

4. The method of claim 1 , wherein the resource models are defined using a Topology and Orchestration Specification for Cloud Applications open cloud standard modeling language.

5. The method of claim 1 , wherein the validation of the arrangement of the icons as representing a feasible service composition for deployment in the communications network further comprises simulating the requested network service using the resource models.

6. The method of claim 1 , wherein the validation of the arrangement of the icons as representing a feasible service composition for deployment in the communications network further comprises determining whether the communications network contains Layer I resources where required by the requested network service.

7. The method of claim 1 , wherein the suggested subset of the virtualized network function resources for use in composing the requested network service is further based on a domain of the user equipment.

8. The method of claim 1 , wherein deploying the feasible service composition further comprises:
receiving an order from the user equipment for the requested network service; and
in response to the receiving the order, orchestrating the requested network service including resource management, metering and billing management.

9. An intelligent agent, comprising:
one or more processors;
a memory storing computer readable instructions that, when executed by the processor, cause the processor to perform operations comprising:
receiving from a user equipment a functional description of a requested network service in a communications network, the communications network comprising a plurality of virtualized network function resources;
employing a learning algorithm to perform an analysis of the functional description of the requested network service, the learning algorithm being trained using prior customer service creation requests, the learning algorithm using a plurality of resource models describing behaviors of the virtualized network function resources;
presenting via the user equipment a composition environment comprising icons representing a suggested subset of the virtualized network function resources for use in composing the requested network service, the suggested subset being based on the analysis of the functional description of the requested network service;
providing assistance in defining an arrangement of the icons in the composition environment including interconnections among the icons, the providing assistance using the learning algorithm;
receiving the arrangement of the icons from the composition environment; and
overseeing validation of the arrangement of the icons as representing a feasible service composition for deployment in the communication network.

10. The intelligent agent of claim 9 , wherein the operations further comprise:
deploying the feasible service composition in the communications network;
receiving real-time asset information regarding the feasible service composition from a virtual network function management framework, the virtual network function management framework including a data collection, analytics and event engine and an active and available inventory subsystem; and
presenting real time reports of the deployed feasible service composition in a dashboard of the composition environment using analytics and visualization tools.

11. The intelligent agent of claim 9 , wherein the plurality of resource models includes models describing network requirements of the virtualized network function resources, exposed properties of the virtualized network function resources and interconnection relationships of the virtualized network function resources with other virtualized network function resources.

12. The intelligent agent of claim 9 , wherein the resource models are defined using a Topology and Orchestration Specification for Cloud Applications open cloud standard modeling language.

13. The intelligent agent of claim 9 , wherein the validation of the arrangement of the icons as representing a feasible service composition for deployment in the communications network further comprises simulating the requested network service using the resource models.

14. The intelligent agent of claim 9 , wherein the validation of the arrangement of the icons as representing a feasible service composition for deployment in the communications network further comprises determining whether the communications network contains Layer I resources where required by the requested network service.

15. The intelligent agent of claim 9 , wherein the suggested subset of the virtualized network function resources for use in composing the requested network service is further based on a domain of the user equipment.

16. A computer-readable storage device having stored thereon computer readable instructions, wherein execution of the computer readable instructions by a processor causes the processor to perform operations comprising:
receiving from a user equipment a functional description of a requested network service in a communications network, the communications network comprising a plurality of virtualized network function resources;
employing a learning algorithm to

Assignees

• At & T Ip I Lp

Inventors

• Jana Rittwik
• Kirk Thomas
• Aftab Syed Anwar
• Murray John F
• Gilbert Mazin E
• Shi Shu
• Jora Serban
• Zahavi Avi

Classifications

• G06Q30/016 Primary

  After-sales · CPC title

• G06N20/00

  Machine learning · CPC title

• G06Q10/10

  Office automation; Time management · CPC title

• G06F9/5077

  Logical partitioning of resources; Management or configuration of virtualized resources (specific details on emulation or internal functioning of virtual machines G06F9/455) · CPC title

• G06F3/04817

  using icons (graphical or visual programming using iconic symbols G06F8/34) · CPC title