IP Library › Granted Patent US 12,439,278
Granted Patent B2
US 12,439,278 · App. 17/541,842 · Granted Oct 7, 2025

Network system level division method and apparatus

Inventor: Ruiyue Xu (Shanghai, CN)
Assignee: Huawei Technologies Co., Ltd.
H04W24/02H04L41/0654H04L41/0886H04L41/5009H04W24/04
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Quick Facts
Patent No.
US 12,439,278
App. No.
17/541,842
Granted
Oct 7, 2025
Kind
B2
Abstract

A network system level division method and an apparatus. The method may include: obtaining an operation and maintenance parameter of a network system in an operation and maintenance scenario, where the operation and maintenance parameter is used to represent operation and maintenance performance of the network system in the operation and maintenance scenario; and determining an automation level of the network system in the operation and maintenance scenario based on the operation and maintenance parameter of the network system in the operation and maintenance scenario, where the automation level of the network system in the operation and maintenance scenario is used to represent an automatic operation and maintenance degree of the network system in the operation and maintenance scenario. In this way, level division of automation degrees of the network system in a specific operation and maintenance scenario is implemented.

Claims (43)

1. A network system level division method comprising:

obtaining an operation and maintenance parameter of a network system in a first operation and maintenance scenario, wherein the operation and maintenance parameter is used to represent operation and maintenance performance of the network system in the first operation and maintenance scenario;

determining a first automation level of the network system in the first operation and maintenance scenario based on the operation and maintenance parameter of the network system in the first operation and maintenance scenario, wherein the first automation level of the network system in the first operation and maintenance scenario is used to represent an automatic operation and maintenance degree of the network system in the first operation and maintenance scenario,

calculating, based on a weight corresponding to each of a plurality of operation and maintenance scenarios supported by the network system, a weighted average value of automation levels of the network system in the plurality of operation and maintenance scenarios supported by the network system, wherein the plurality of operation and maintenance scenarios comprises the first operation and maintenance scenario; and

obtaining an automation level of the network by performing one of:

rounding up on the weighted average value when automation degrees respectively represented by automation levels increase in an ascending order of the automation levels; or

rounding down on the weighted average value when automation degrees respectively represented by automation levels decrease in a descending order of the automation levels.

2. The network system level division method according to claim 1 , wherein the plurality of operation and maintenance scenarios comprises at least two of a site deployment scenario, a network deployment scenario, a network optimization scenario, a network maintenance scenario, a network planning scenario, or a service operation scenario.

3. The network system level division method according to claim 2 , wherein, when the operation and maintenance scenario comprises the site deployment scenario, the operation and maintenance parameter comprises at least one of the following parameters:

a site planning parameter, a full configuration data generation parameter, a site provisioning parameter, or a site acceptance parameter.

4. An apparatus, comprising a processor, wherein the processor is configured to invoke instructions stored in a memory, to:

obtain an operation and maintenance parameter of a network system in a first operation and maintenance scenario, wherein the operation and maintenance parameter is used to represent operation and maintenance performance of the network system in the first operation and maintenance scenario;

determine a first automation level of the network system in the first operation and maintenance scenario based on the operation and maintenance parameter of the network system in the first operation and maintenance scenario, wherein the first automation level of the network system in the first operation and maintenance scenario is used to represent an automatic operation and maintenance degree of the network system in the first operation and maintenance scenario;

calculate, based on a weight corresponding to each of a plurality of operation and maintenance scenarios supported by the network system, a weighted average value of automation levels of the network system in the plurality of operation and maintenance scenarios supported by the network system, wherein the plurality of operation and maintenance scenarios comprises the first operation and maintenance scenario; and

obtain an automation level of the network by performing one of:

rounding up on the weighted average value when automation degrees respectively represented by automation levels increase in an ascending order of the automation levels; or

rounding down on the weighted average value when automation degrees respectively represented by automation levels decrease in a descending order of the automation levels.

5. The apparatus according to claim 4 , wherein the processor is further configured to invoke the instructions to:

determine, based on the operation and maintenance parameter of the network system in the operation and maintenance scenario and evaluation information of a plurality of reference automation levels in the operation and maintenance scenario, one of the plurality of reference automation levels as the determined automation level of the network system in the operation and maintenance scenario.

6. The apparatus according to claim 5 , wherein the evaluation information of the automation level of the network system comprises level information corresponding to the automation level.

7. The apparatus according to claim 5 , wherein the processor is further configured to invoke the instructions to:

select a reference automation level of the highest level from the plurality of reference automation levels as the selected automation level of the network system in the operation and maintenance scenario, wherein the operation and maintenance parameter of the network system in the operation and maintenance scenario meets evaluation information of the selected reference automation level of the highest level.

8. The apparatus according to claim 5 , wherein the processor is further configured to invoke the instructions to:

in response to finding that the operation and maintenance parameter of the network system in the operation and maintenance scenario meets evaluation information of a first reference automation level, and the operation and maintenance parameter of the network system in the operation and maintenance scenario does not meet evaluation information of a second reference automation level, determine that the automation level of the network system in the operation and maintenance scenario is the first reference automation level, wherein the second reference automation level and the first reference automation level are adjacent levels, and an automation degree represented by the second reference automation level is higher than an automation degree represented by the first reference automation level.

9. The apparatus according to claim 5 , wherein the processor is further configured to invoke the instructions to:

in response to finding that the operation and maintenance parameter of the network system in the operation and maintenance scenario meets evaluation information of a third reference automation level, determine that the automation level of the network system in the operation and maintenance scenario is the third reference automation level, wherein an automation degree represented by the third reference automation level is higher than automation degrees represented by all reference automation levels except the third reference automation level.

10. The apparatus according to claim 4 , wherein the operation and maintenance scenario comprises at least one of a site deployment scenario, a network deployment scenario, a network optimization scenario, a network maintenance scenario, a network planning scenario, or a service operation scenario.

11. The apparatus according to claim 10 , wherein when the operation and maintenance scenario comprises the site deployment scenario, the operation and maintenance parameter comprises at least one of the following parameters:

a site planning parameter, a full configuration data generation parameter, a site provisioning parameter, or a site acceptance parameter.

12. The apparatus according to claim 4 , wherein the processor is further configured to invoke the instructions to:

determine a plurality of operation and maintenance scenarios supported by the network system; and

determine the automation level of the network system based on automation levels of the network system in the plurality of supported operation and maintenance scenarios.

13. A non-transitory computer-readable storage medium, comprising program instructions, wherein when the program instructions are run on a computer, the computer is enabled to perform a network system level division method, the non-transitory computer-readable storage medium comprising:

instructions for obtaining an operation and maintenance parameter of a network system in a first operation and maintenance scenario, wherein the operation and maintenance parameter is used to represent operation and maintenance performance of the network system in the first operation and maintenance scenario;

instructions for determining a first automation level of the network system in the first operation and maintenance scenario based on the operation and maintenance parameter of the network system in the first operation and maintenance scenario, wherein the first automation level of the network system in the first operation and maintenance scenario is used to represent an automatic operation and maintenance degree of the network system in the first operation and maintenance scenario;

instructions for calculating, based on a weight corresponding to each of a plurality of operation and maintenance scenarios supported by the network system, a weighted average value of automation levels of the network system in the plurality of operation and maintenance scenarios supported by the network system, wherein the plurality of operation and maintenance scenarios comprises the first operation and maintenance scenario; and

instructions for obtaining an automation level of the network by performing one of:

rounding up on the weighted average value when automation degrees respectively represented by automation levels increase in an ascending order of the automation levels; or

rounding down on the weighted average value when automation degrees respectively represented by automation levels decrease in a descending order of the automation levels.

14. The apparatus of claim 4 , wherein, when the operation and maintenance scenario comprises the site deployment scenario, the operation and maintenance parameter comprises at least one of the following parameters:

a site planning parameter, a full configuration data generation parameter, a site provisioning parameter, or a site acceptance parameter.

15. The non-transitory computer-readable storage medium of claim 13 , wherein, when the operation and maintenance scenario comprises the site deployment scenario, the operation and maintenance parameter comprises at least one of the following parameters:

a site planning parameter, a full configuration data generation parameter, a site provisioning parameter, or a site acceptance parameter.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 10, 2025
From: XU, RUIYUE
To: HUAWEI TECHNOLOGIES CO., LTD.
Reel/Frame 071662/0017 →
Priority Claims (1)
CN 201910492320.6 · Jun 6, 2019 · national
Continuity (2)
Continuation PCTCN2020094747 · Jun 5, 2020
Related Publication 20220095133A1 · Mar 24, 2022
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