Method and apparatus for autonomous services composition

Patent metadata

Field	Value
Publication number	US-11222343-B2
Application number	US-202017038050-A
Country	US
Kind code	B2
Filing date	Sep 30, 2020
Priority date	Feb 13, 2016
Publication date	Jan 11, 2022
Grant date	Jan 11, 2022

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:
employing, by a processing system including a processor, a learning algorithm to perform an analysis of a functional description of a requested network service, the learning algorithm being trained using prior customer service creation requests, the learning algorithm using a plurality of resource models that describe behaviors of virtualized network function resources of a communications network;
providing, by the processing system and for presentation via 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, by the processing system, assistance in defining an arrangement of the icons in the composition environment including interconnections among the icons, the assistance provided according to the learning algorithm; and
overseeing, by the processing system, validation of the arrangement of the icons obtained from the composition environment as representing a feasible service composition for deployment in the communications network, the feasible service composition adapted for deployment in the communications network.

2. The method of claim 1 , further comprising:
obtaining, by the processing system, 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
providing, by the processing system, 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 that describe 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, by the processing system, 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, by the processing system, 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, by the processing system, an order from the user equipment for the requested network service; and
in response to the receiving the order, orchestrating, by the processing system, the requested network service including resource management, metering, and billing management.

9. A device, comprising:
a processing system including a processor;
a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising:
employing a learning algorithm to perform an analysis of a functional description of a requested network service, the learning algorithm being trained using prior customer service creation requests, the learning algorithm using a plurality of resource models that describe behaviors of virtualized network function resources of a communications network;
providing for presentation via 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 assistance provided according to the learning algorithm; and
overseeing validation of the arrangement of the icons obtained from the composition environment as representing a feasible service composition for deployment in the communications network.

10. The device of claim 9 , wherein the operations further comprise:
deploying the feasible service composition in the communications network;
obtaining 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
providing real time reports of the deployed feasible service composition in a dashboard of the composition environment using analytics and visualization tools.

11. The device of claim 9 , wherein the plurality of resource models further includes models that describe 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 device of claim 9 , wherein the resource models are further defined using a Topology and Orchestration Specification for Cloud Applications open cloud standard modeling language.

13. The device 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 device 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 device 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 non-transitory computer-readable storage medium comprising executable instructions that, when executed by a processing system including a processor facilitate performance of operations, the operations comprising:
employing a learning algorithm to perform an analysis of a functional description of a requested network service, the learning algorithm being trained using prior customer service creation requests, the learning algorithm using a plurality of resource models that describe behaviors of virtualized network function resources of a communications network;
providing for presentation via user equipment, a composition environment comprising icons representing a suggested subset of the virtualized network function resources

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

• 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

• G06Q10/10

  Office automation; Time management · CPC title

• G06F3/04847

  Interaction techniques to control parameter settings, e.g. interaction with sliders or dials · CPC title

• G06F8/20

  Software design · CPC title

• G06N20/00

  Machine learning · CPC title