NETWORK RESOURCE MODELS AND TECHNOLOGIES FOR ACTIONS EXECUTED ACCORDING TO MACHINE LEARNING INFERENCE REPORTS
This disclosure describes systems, methods, and devices related to optimized resource technologies. A device may create a Managed Object Instance (MOI) representing actions executed based on artificial intelligence or machine learning (AI/ML) inference function. The device may notify a management and network service (MnS) consumer about the creation of the MOI. The device may execute actions by a network or management function acting as the consumer of the inference output. The device may manage performance of the AI/ML inference function.
1 . An apparatus, the apparatus comprising processing circuitry coupled to storage, the processing circuitry configured to:
create a Managed Object Instance (MOI) representing actions executed based on artificial intelligence or machine learning (AI/ML) inference function;
notify a management and network service (MnS) consumer about the creation of the MOI;
execute actions by a network or management function acting as the consumer of the inference output; and
manage performance of the AI/ML inference function.
2 . The apparatus of claim 1 , wherein the AI/ML inference function includes an Analytics Logical Function (AnLF), management data analytics function (MDAF), AI/ML enabled Energy Saving function, AI/ML enabled MRO function, or AI/ML enabled MLB function.
3 . The apparatus of claim 2 , wherein the AI/ML inference function is represented by an MOI.
4 . The apparatus of claim 3 , wherein the MOI representing the AnLF contains attributes indicating supported analytics ID(s).
5 . The apparatus of claim 1 , wherein the MOI representing the actions executed based on the AI/ML inference output contains at least one of the following attributes: identifier of the inference output, actions executed, or timestamp of action completion.
6 . The apparatus of claim 1 , wherein the MnS consumer is configured to take actions based on the executed actions and resulting performance.
7 . The apparatus of claim 6 , wherein the actions taken by the MnS consumer include deactivating the AI/ML inference function.
8 . The apparatus of claim 6 , wherein the MnS consumer requests re-training of the ML model for the AI/ML inference function.
9 . The apparatus of claim 6 , wherein the MnS consumer uses a different ML model to support the AI/ML inference function.
10 . The apparatus of claim 1 , wherein an MnS producer and the MnS consumer are configured for performance management of the AI/ML inference function.
11 . A non-transitory computer-readable medium storing computer-executable instructions which when executed by one or more processors result in performing operations comprising:
creating a Managed Object Instance (MOI) representing actions executed based on artificial intelligence or machine learning (AI/ML) inference function;
notifying a management and network service (MnS) consumer about the creation of the MOI;
executing actions by a network or management function acting as the consumer of the inference output; and
managing performance of the AI/ML inference function.
12 . The non-transitory computer-readable medium of claim 11 , wherein the AI/ML inference function includes an Analytics Logical Function (AnLF), management data analytics function (MDAF), AI/ML enabled Energy Saving function, AI/ML enabled MRO function, or AI/ML enabled MLB function.
13 . The non-transitory computer-readable medium of claim 12 , wherein the AI/ML inference function is represented by an MOI.
14 . The non-transitory computer-readable medium of claim 13 , wherein the MOI representing the AnLF contains attributes indicating supported analytics ID(s).
15 . The non-transitory computer-readable medium of claim 11 , wherein the MOI representing the actions executed based on the AI/ML inference output contains at least one of the following attributes: identifier of the inference output, actions executed, or timestamp of action completion.
16 . The non-transitory computer-readable medium of claim 11 , wherein the MnS consumer is configured to take actions based on the executed actions and resulting performance.
17 . The non-transitory computer-readable medium of claim 16 , wherein the actions taken by the MnS consumer include deactivating the AI/ML inference function.
18 . The non-transitory computer-readable medium of claim 16 , wherein the MnS consumer requests re-training of the ML model for the AI/ML inference function.
19 . The non-transitory computer-readable medium of claim 16 , wherein the MnS consumer uses a different ML model to support the AI/ML inference function.
20 . A method comprising:
creating a Managed Object Instance (MOI) representing actions executed based on artificial intelligence or machine learning (AI/ML) inference function;
notifying a management and network service (MnS) consumer about the creation of the MOI;
executing actions by a network or management function acting as the consumer of the inference output; and
managing performance of the AI/ML inference function.