Granted Patent B2

US 12,585,486 · App. 18/067,300 · Granted Mar 24, 2026

Inventors: Abhishek Kumar (Irving, TX); Hans Raj Nahata (New Providence, NJ); Neeraj Bhatt (Vienna, VA)

Assignee: Verizon Patent and Licensing Inc.

G06F9/45558G06F9/4881G06F2009/4557G06F2009/45595

Abstract

Claims (79)

1 . A method performed by an orchestration system, the method comprising:

receiving information regarding a containerized network function (CNF) to be deployed;

obtaining deployment information regarding requirements for deploying the CNF,

wherein the requirements include one or more of a computing requirement, a memory requirement, or a network connectivity requirement;

providing a request to obtain one or more recommendations regarding one or more schedulers configured to deploy CNFs associated with the requirements;

obtaining the one or more recommendations regarding the one or more schedulers based on providing the request; and

providing the one or more recommendations regarding the one or more schedulers to a container management system,

wherein the one or more recommendations are provided to cause the container management system to use the one or more schedulers to deploy the CNF on one or more computing nodes that comply with the requirements,

wherein the one or more recommendations indicate that the one or more schedulers include a default scheduler or a custom scheduler, and

wherein the custom scheduler is configured to deploy the CNF based on capabilities of the one or more computing nodes.

2 . The method of claim 1 , further comprising:

obtaining cluster information identifying a cluster of CNFs associated with the requirements for deploying the CNF; and

determining the one or more recommendations based on the cluster information.

3 . The method of claim 2 , wherein obtaining the cluster information comprises:

providing the deployment information as an input to a machine learning model trained to identify clusters of CNFs; and

obtaining the cluster information as an output of the machine learning model.

4 . The method of claim 1 , further comprising:

obtaining topology information identifying schedulers configured to deploy CNFs associated with the requirements for deploying the CNF; and

determining the one or more recommendations based on the topology information.

5 . The method of claim 1 , wherein the request to obtain the one or more recommendations is a first request, and

wherein providing the first request to obtain the one or more recommendations comprises:

receiving a second request for the one or more recommendations from a scheduler manager component of the container management system; and

providing the first request to obtain the one or more recommendations based on receiving the second request.

6 . The method of claim 1 , further comprising:

determining a constraint associated with deploying the CNF; and

determining the one or more recommendations based on the constraint.

7 . The method of claim 6 , wherein the one or more recommendations indicate that the custom scheduler is to be used to deploy the CNF based on the constraint being a first constraint, and

wherein the one or more recommendations indicate that the custom scheduler or the default scheduler is to be used to deploy the CNF based on the constraint being a second constraint.

8 . An orchestration system, comprising:

one or more processors configured to:

receive information regarding a containerized network function (CNF) to be deployed;

obtain deployment information regarding requirements for deploying the CNF,

wherein the requirements include one or more of a computing requirement, a memory requirement, or a network connectivity requirement;

obtain cluster information identifying a cluster of CNFs with deployment requirements that are similar to the requirements for deploying the CNF,

wherein the cluster information indicates schedulers that were used to deploy the cluster of CNFs and indicate capabilities of computing nodes that support the cluster of CNFs;

determine that the schedulers, that were used to deploy the cluster of CNFs, are available;

generate a recommendation regarding one or more schedulers, of the schedulers, based on the cluster information; and

provide the recommendation regarding the one or more schedulers to a container management system,

wherein the recommendation is provided to cause the container management system to use the one or more schedulers to deploy the CNF on one or more computing nodes that comply with the requirements.

9 . The orchestration system of claim 8 , wherein the one or more processors, to obtain the cluster information, are configured to:

provide the deployment information as an input to a machine learning model trained to identify clusters of CNFs; and

obtain the cluster information as an output of the machine learning model.

10 . The orchestration system of claim 8 , wherein the one or more processors, to determine that the schedulers are available, are further configured to:

obtain topology information identifying the schedulers; and

determine that the schedulers are available based on the topology information.

11 . The orchestration system of claim 8 , wherein the one or more processors, to generate the recommendation regarding the one or more schedulers, are configured to:

receive a request for the recommendation from a scheduler manager component of the container management system; and

generate the recommendation based on receiving the request.

12 . The orchestration system of claim 8 , wherein the one or more processors are further configured to:

determine a constraint associated with deploying the CNF; and

determine the recommendation based on the constraint.

13 . The orchestration system of claim 12 , wherein the recommendation indicates that a custom scheduler is to be used to deploy the CNF based on the constraint being a first constraint, and

wherein the recommendation indicates that a custom scheduler or a default scheduler is to be used to deploy the CNF based on the constraint being a second constraint.

14 . The orchestration system of claim 8 , wherein the one or more schedulers include one or more of a first scheduler configured to deploy CNFs that require computing resources exceeding a computing resource threshold, a second scheduler configured to deploy CNFs that require memory resources exceeding a memory resource threshold, or a third scheduler configured to deploy CNFs that require network connectivity resources exceeding a network resource threshold.

15 . A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:

one or more instructions that, when executed by one or more processors of an orchestration system, cause the orchestration system to:

receive information regarding a containerized network function (CNF) to be deployed;

obtain deployment information regarding requirements for deploying the CNF,

wherein the requirements include one or more of a computing requirement, a memory requirement, or a network connectivity requirement;

obtain cluster information identifying a cluster of CNFs associated with the requirements for deploying the CNF;

determine that schedulers, configured to deploy CNFs associated with the requirements, are available;

generate a recommendation regarding one or more schedulers, of the schedulers, based on the cluster information; and

provide the recommendation regarding the one or more schedulers to a container management system,

wherein the recommendation is provided to cause the container management system to use the one or more schedulers to deploy the CNF on one or more computing nodes that comply with the requirements,

wherein the recommendation indicates that the one or more schedulers include a default scheduler or a custom scheduler, and

wherein the custom scheduler is configured to deploy the CNF based on capabilities of the one or more computing nodes.

16 . The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, that cause the orchestration system to obtain the cluster information, cause the orchestration system to:

provide the deployment information as an input to a machine learning model trained to identify clusters of CNFs; and

obtain the cluster information as an output of the machine learning model.

17 . The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, that cause the orchestration system to determine that the schedulers are available, cause the orchestration system to:

obtain topology information identifying the schedulers; and

determine that the schedulers are available based on the topology information.

18 . The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, that cause the orchestration system to generate the recommendation regarding the one or more schedulers, cause the orchestration system to:

receive a request for the recommendation from a scheduler manager component of the container management system; and

generate the recommendation based on receiving the request.

19 . The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions further cause the orchestration system to:

determine a constraint associated with deploying the CNF; and

determine the recommendation based on the constraint.

20 . The non-transitory computer-readable medium of claim 15 , wherein the one or more schedulers include one or more of a first scheduler configured to deploy CNFs that require computing resources exceeding a computing resource threshold, a second scheduler configured to deploy CNFs that require memory resources exceeding a memory resource threshold, or a third scheduler configured to deploy CNFs that require network connectivity resources exceeding a network resource threshold.

Assignments (1)

Continuity (1)

References Cited (31)