WO2025237232A1 - 一种分析处理方法、装置、通信设备和存储介质 - Google Patents

一种分析处理方法、装置、通信设备和存储介质

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Publication number
WO2025237232A1
WO2025237232A1 PCT/CN2025/094228 CN2025094228W WO2025237232A1 WO 2025237232 A1 WO2025237232 A1 WO 2025237232A1 CN 2025094228 W CN2025094228 W CN 2025094228W WO 2025237232 A1 WO2025237232 A1 WO 2025237232A1
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WO
WIPO (PCT)
Prior art keywords
network
information
digital twin
analysis
running
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/CN2025/094228
Other languages
English (en)
French (fr)
Inventor
胡玉双
王丹
李琴
孙滔
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China Mobile Communications Group Co Ltd
Research Institute of China Mobile Communication Co Ltd
Original Assignee
China Mobile Communications Group Co Ltd
Research Institute of China Mobile Communication Co Ltd
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Filing date
Publication date
Application filed by China Mobile Communications Group Co Ltd, Research Institute of China Mobile Communication Co Ltd filed Critical China Mobile Communications Group Co Ltd
Publication of WO2025237232A1 publication Critical patent/WO2025237232A1/zh
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/06—Testing, supervising or monitoring using simulated traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/20—Services signaling; Auxiliary data signalling, i.e. transmitting data via a non-traffic channel

Definitions

  • This disclosure relates to the field of communication technology, specifically to an analysis and processing method, apparatus, communication equipment, and storage medium.
  • a signaling storm occurs when a sudden surge of signaling messages overloads a mobile communication network, causing network processing capacity to fail and impacting network performance and stability.
  • Signaling storms can be caused by a major event resulting in too many users simultaneously requesting services, or by network failures, configuration errors, or malicious attacks. During this period, users repeatedly attempt to establish connections until they are reconnected, leading to a sudden influx of signaling messages and triggering a signaling storm.
  • Current availability monitoring solutions for signaling storm scenarios, as well as for network failures and root cause analysis, are all based on existing network technologies.
  • embodiments of this disclosure provide an analysis and processing method, apparatus, communication device, and storage medium.
  • embodiments of this disclosure provide an analysis and processing method, the method being applied to a first network function, the method comprising:
  • the first network function receives first information sent by the consumer, the first information being used to request analysis of signaling storms, and the first information including at least network object information;
  • Obtain second information related to the network object perform network simulation and/or verification of signaling storm analysis based on the second information, generate analysis results, and send the analysis results to the consumer.
  • the network object information includes one or more of the following: network function information, network slice information, network function configuration information, and network slice configuration information.
  • the second information includes one or more of the following: network performance-related information, network element status-related information, network capability-related information, network slicing-related information, resource-related network slicing information, and user and/or network traffic data.
  • obtaining the second information related to the network object includes: the first network function obtaining the second information related to the network object from one or more second network functions based on the first information.
  • the network simulation and/or verification based on the second information to perform signaling storm analysis and generate analysis results includes:
  • generating a network digital twin/digital twin instance related to the network object based on the second information includes:
  • the first network function creates a digital twin object corresponding to the network object, and generates a network digital twin/digital twin instance based on the second information.
  • the network simulation and/or verification of running the network digital twin/digital twin instance to perform signaling storm analysis includes:
  • the first network function runs the network digital twin/digital twin instance to obtain a first running result, which includes relevant information obtained by running the network digital twin/digital twin instance to simulate a signaling storm; and/or,
  • the first network function runs the network digital twin/digital twin instance based on operation information to obtain a second running result.
  • the operation information represents the simulated action or behavior for the network digital twin/digital twin instance
  • the second running result represents the relevant information obtained during the process of running the network digital twin/digital twin instance according to the operation information to simulate and optimize signaling storms.
  • the first information includes the operation information; or, the method further includes: the first network function obtains the operation information through local policy information.
  • generating analysis results based on the operation results includes: the first network function generating analysis results based on one or more of the first operation results, the second operation results, and the first prediction results; the first prediction results are obtained based on the first operation results, and the first prediction results represent the trend information of whether or not a signaling storm will occur in the first future time.
  • this disclosure also provides an analysis and processing method applied to consumers, the method comprising:
  • the consumer sends a first message to the first network function, the first message being used to request analysis of signaling storms, and the first message including at least network object information;
  • the system receives the analysis results sent by the first network function, which are generated by the network simulation and/or verification of the first network function performing signaling storm analysis.
  • the network object information includes one or more of the following: network function information, network slice information, network function configuration information, and network slice configuration information.
  • the first information also includes operation information, which represents the simulated actions or behaviors of the network digital twin/digital twin instance related to the network object.
  • the analysis results are generated based on one or more of the first running results, the second running results, and the first prediction results;
  • the first operational result includes relevant information obtained by the first network function during the process of simulating a signaling storm by running the network digital twin/digital twin instance;
  • the second running result represents the relevant information obtained during the process of running the network digital twin/digital twin instance according to the operation information to simulate and optimize the signaling storm;
  • the first prediction result is obtained based on the first running result, and the first prediction result represents the trend information of whether a signaling storm will occur or not in the first future time.
  • embodiments of this disclosure also provide an analysis and processing apparatus, the apparatus being applied to a first network function, the apparatus comprising: a first communication unit and a first processing unit; wherein,
  • the first communication unit is configured to receive first information sent by a consumer, the first information being used to request analysis of signaling storms, the first information including at least network object information; and is also configured to obtain second information related to the network object.
  • the first processing unit is configured to perform network simulation and/or verification of signaling storm analysis based on the second information, and generate analysis results;
  • the first communication unit is also used to send the analysis results to the consumer.
  • this disclosure also provides an analysis and processing apparatus applied to a consumer.
  • the apparatus includes: a second communication unit, configured to send first information to a first network function, the first information being used to request analysis of signaling storms, the first information including at least network object information; and further configured to receive analysis results sent by the first network function, the analysis results being generated by network simulation and/or verification of signaling storm analysis performed by the first network function.
  • embodiments of this disclosure also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the methods described in the first or second aspect of embodiments of this disclosure.
  • embodiments of this disclosure also provide a communication device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the methods described in the first or second aspect of embodiments of this disclosure.
  • embodiments of this disclosure also provide a computer program product, comprising computer program instructions that cause a computer to perform the steps of the methods described in the first or second aspect of embodiments of this disclosure.
  • the analysis and processing method, apparatus, communication device, and storage medium provided in this disclosure include: a first network function receiving first information sent by a consumer, the first information being used to request analysis of signaling storms, the first information including at least network object information; acquiring second information related to the network object; performing network simulation and/or verification of signaling storm analysis based on the second information; generating analysis results; and sending the analysis results to the consumer.
  • the first network function based on consumer needs, simulates network scenarios such as signaling storms through network simulation, thereby achieving signaling storm analysis through network simulation, reducing the trial-and-error risks and costs of existing networks, and facilitating research on new network technologies.
  • Figure 1 is a schematic flowchart of the analysis and processing method according to an embodiment of this disclosure
  • Figure 2 is a schematic diagram of the creation and operation process of a digital twin instance in the analysis and processing method of this disclosure embodiment
  • FIG. 3 is a schematic flowchart of the analysis and processing method according to an embodiment of this disclosure.
  • Figure 4 is a schematic diagram of the interaction flow of the analysis and processing method according to an embodiment of this disclosure.
  • Figure 5 is a schematic diagram of the composition structure of the analysis and processing device according to an embodiment of this disclosure.
  • Figure 6 is a schematic diagram of the composition structure of the analysis and processing device according to an embodiment of this disclosure.
  • Figure 7 is a schematic diagram of the hardware composition structure of the communication device according to an embodiment of this disclosure.
  • GSM Global System of Mobile communication
  • LTE Long Term Evolution
  • 5G 5th Generation Mobile Communication Technology
  • NR New Radio
  • the communication system used in this disclosure embodiment may include network devices and terminal devices (also referred to as terminals, communication terminals, etc.); the network device may be a device that communicates with the terminal device.
  • the network device can provide communication coverage within a certain area and can communicate with terminals located within that area.
  • the network device may be a base station in various communication systems, such as an evolved Node B (eNB) in an LTE system, or a base station (gNB) in a 5G or NR system.
  • eNB evolved Node B
  • gNB base station
  • Communication devices may include network devices and terminals with communication functions.
  • Network devices and terminal devices can be the specific devices described above, which will not be repeated here.
  • Communication devices may also include other devices in the communication system, such as network controllers, mobility management entities, and other network entities. This disclosure embodiment does not limit these.
  • Figure 1 is a schematic flowchart of the analysis and processing method according to an embodiment of this disclosure; as shown in Figure 1, the method includes:
  • Step 101 The first network function receives the first information sent by the consumer, the first information being used to request analysis of signaling storms, and the first information including at least network object information;
  • Step 102 Obtain second information related to the network object, perform network simulation and/or verification of signaling storm analysis based on the second information, generate analysis results, and send the analysis results to the consumer.
  • the first network function refers to a function or entity capable of providing a Management Service (MnS).
  • MnS Management Service
  • the entity executing the analysis and processing method may also be referred to as a Management Service (MnS), the first entity, etc.
  • the first network function can perform network simulation and/or verification of signaling storm analysis based on consumer requests.
  • the network simulation and/or verification employs technologies such as digital twins to perform external abstract mapping on the traditional physical network, establish a network digital twin, and achieve closed-loop control through management orchestration.
  • the consumer also referred to as the consumer party, refers to the user or the device or entity to which the user belongs that requests the Network Digital Twin (NDT) service.
  • NDT Network Digital Twin
  • the consumer requests signaling storm analysis by sending first information for requesting signaling storm analysis to the first network function.
  • the first information includes network object information, that is, which network objects(s) are being requested to analyze the signaling storm.
  • the network object information includes one or more of the following: network function information, network slice information, network function configuration information, and network slice configuration information.
  • the network object information includes the network object to be analyzed.
  • This network object can refer to one or more network functions or entities; that is, the network function information can include information such as the identifier of the network function or entity.
  • the network object can refer to one or more network slices, in which case the network slice information can include one or more Single Network Slice Selection Assistance Information (S-NSSAI).
  • the network object information may also include configuration information for the network object, such as configuration information for network functions, configuration information for network slices, etc.
  • the configuration information for the network object includes, but is not limited to, configuration information related to interfaces, configuration information related to channels, configuration information related to protocols, etc. Any configuration information related to network functions and/or slices in the physical network can be included within the configuration information of the network object in this embodiment.
  • the first network function collects second information related to the network object, and the second information is used to perform network simulation and/or verification.
  • the second information is network information related to the network object, which may be information related to the network object at the current moment and/or information collected from historical periods.
  • obtaining the second information related to the network object includes: the first network function obtaining the second information related to the network object from one or more second network functions based on the first information.
  • the one or more second network functions refer to a Management Service (MnS) producer or producer.
  • the second network function may also be referred to as a Management Service Provider, which can provide second information related to network objects.
  • the second network function may be one or more of the following: Network Slice Management Function (NSMF), Network Slice Subnet Management Function (NSSMF), or Network Function Management Function (NFMF).
  • NSMF Network Slice Management Function
  • NSSMF Network Slice Subnet Management Function
  • NFMF Network Function Management Function
  • the second network function may also refer to other network functions or entities capable of obtaining second information; this embodiment does not limit this.
  • the second information includes one or more of the following: network performance-related information, network element status-related information, network capability-related information, network slicing-related information, resource-related network slicing information; user and/or network traffic data (traffic, bandwidth, duration).
  • the second information may include one or more of the following three types of information:
  • the first category of information includes one or more of the following: network performance-related information, network element status-related information, and network capability-related information;
  • the second category of information includes one or more of the following: network slice-related information and resource-related network slice information;
  • the third category of information includes user or network traffic data.
  • the network performance-related information may include, for example, any information related to network performance such as bandwidth, latency, throughput, transmission rate, packet loss rate, retransmission rate, and concurrent connections.
  • the network element status-related information may include, for example, online status, offline status, working status, fault status, sleep status, low power status, etc.; any state that can identify a network object can be considered as the network element status-related information.
  • the network capability-related information may specifically refer to information related to network-supported metrics, such as maximum supported bandwidth, maximum throughput, maximum transmission rate, maximum concurrent connections, etc.
  • the network slice information related to resources refers to the resource requirements of the slice, such as the bandwidth required by the slice.
  • the user and/or network traffic data may include user traffic data and/or network traffic data; the traffic data may be represented in one or more of the following ways: traffic (the amount of data transmitted by the network), bandwidth, transmission duration, number of subscribers, etc.
  • the first network function performs network simulation and/or verification based on the second information related to the network object obtained, thereby generating analysis results.
  • the step of performing network simulation and/or verification of signaling storm analysis based on the second information and generating analysis results includes: generating a network digital twin/digital twin instance related to the network object based on the second information; running the network digital twin/digital twin instance to perform network simulation and/or verification of signaling storm analysis; obtaining the running results of the network digital twin/digital twin instance; and generating analysis results based on the running results.
  • the first network function may include a digital twin module. This module generates a digital twin instance related to the network object and controls its operation.
  • the digital twin instance may be one or more of an end-to-end network digital twin instance, a single-domain digital twin instance, and a private network digital twin instance.
  • the first network function executes the digital twin instance's operational requirements by controlling it, and obtains the operational results of the digital twin instance to obtain analysis results.
  • generating a network digital twin/digital twin instance related to the network object based on the second information includes: the first network function creating a digital twin object corresponding to the network object, and arranging and generating a network digital twin/digital twin instance based on the second information.
  • the digital twin component of the first network function may specifically include: a twin model library, a digital twin model generation function, a digital twin orchestration function, a digital twin instance running function, and a digital twin instance control function, etc.; wherein, the twin model library includes various digital twin models required in the network; the digital twin model generation function can, according to the consumer's needs, retrieve the digital twin model related to the network object from the twin model library based on the second information, thereby creating a digital twin object corresponding to the network object, and sending the digital twin object to the digital twin orchestration function; the digital twin orchestration function intelligently orchestrates relevant resources based on the second information, generates corresponding network digital twins/digital twin instances on demand, and sends the network digital twins/digital twin instances to the digital twin instance running function; the digital twin instance control function controls the digital twin instance running function to run the network digital twins/digital twin instances to perform digital twin instantiation control and execute digital twin running requirements.
  • the twin model library includes various digital twin models required in the network
  • FIG. 2 is a schematic diagram of the creation and operation process of a digital twin instance in the analysis and processing method of this embodiment.
  • the user initiates a request to create a digital twin service (equivalent to the first information in this embodiment) to the access management function of the first network function, and the access management function sends the user's request to the digital twin component;
  • the data interaction function of the digital twin component collects and interacts with the data of the network object through the data bus (equivalent to obtaining the second information in this embodiment).
  • 3-4 the management and orchestration function of the digital twin component creates a digital twin object according to the user's requirements, and intelligently orchestrates related resources to generate a responsive digital twin instance on demand.
  • the digital twin control function of the digital twin component executes digital twin instantiation control and executes the digital twin operation requirements.
  • the digital twin returns the digital twin operation results or analysis results to the mobile network, and the mobile network performs configuration optimization behavior.
  • the network simulation and/or verification of running the network digital twin/digital twin instance to perform signaling storm analysis includes: the first network function running the network digital twin/digital twin instance to obtain a first running result, the first running result including relevant information obtained during the process of running the network digital twin/digital twin instance to simulate a signaling storm; and/or, the first network function running the network digital twin/digital twin instance based on operation information to obtain a second running result, the operation information representing simulated actions or behaviors for the network digital twin/digital twin instance, and the second running result representing relevant information obtained during the process of running the network digital twin/digital twin instance according to the operation information to simulate and optimize the signaling storm.
  • the first network function by running a network digital twin/digital twin instance, can, in a first aspect, perform network simulation, i.e., simulate signaling storm behavior in the network, thereby obtaining a first operational result related to the simulated signaling storm process;
  • the first operational result may include network information such as network metrics during the operation of the network digital twin/digital twin instance.
  • the second operational result may include network information such as network metrics during the operation of the network digital twin/digital twin instance according to the operation information, as well as information such as the continuation of signaling storms or the elimination of signaling storms.
  • the first network function by running the network digital twin/digital twin instance, can also obtain a combined operational result of the first and second aspects.
  • the operational result may include the following: a first operational result (i.e., the operational result of simulating signaling storm behavior), and/or a second operational result (including the operational behavior and the operational result corresponding to that operational behavior).
  • the operation information specifically refers to the operations or actions performed in the signaling storm scenario, such as modifying configuration parameters for network objects (e.g., modifying the maximum traffic rate received by network nodes), configuring disaster recovery elements for fault switching, etc.
  • the first information includes the operation information; or, the method further includes: the first network function obtaining the operation information through local policy information.
  • the operation information may be provided by the consumer to the first network function, or the operation information may be obtained from the local configuration information of the first network function.
  • generating analysis results based on the operation results includes: the first network function generating analysis results based on one or more of the first operation results, the second operation results, and the first prediction results; the first prediction results are obtained based on the first operation results, and the first prediction results represent trend information on whether a signaling storm will occur or not in the first future time.
  • the first network function can also predict the trend information of whether a signaling storm will occur at a future time based on the first running result (i.e., the running result of simulating signaling storm behavior).
  • the trend information may specifically include prediction information of whether a signaling storm will occur at the first time.
  • the trend information may also include running information of digital twin instances in scenarios where a signaling storm occurs or does not occur.
  • the first network function can obtain the trend information using a neural network model based on the first running result combined with the obtained second information (current data and/or historical data). Then, the first network function can generate an analysis result based on one or more of the first running result, the second running result, and the first prediction result.
  • the analysis result may include one or more of the first running result, the second running result, and the first prediction result.
  • the first network function may also send third information to a third network function associated with the network object based on the analysis results, the third information being used to instruct or suggest performing the optimization operation.
  • the first network function can send third information to the third network function related to the network object.
  • the third information may include the operation information to instruct or suggest that the third network function execute the operation information to eliminate signaling storms, thereby performing configuration optimization.
  • Figure 3 is a schematic flowchart of the analysis and processing method according to an embodiment of this disclosure; as shown in Figure 3, the method includes:
  • Step 201 The consumer sends first information to the first network function, the first information being used to request analysis of signaling storms, and the first information including at least network object information;
  • Step 202 Receive the analysis results sent by the first network function, wherein the analysis results are generated by the network simulation and/or verification of the first network function performing signaling storm analysis.
  • the consumer also referred to as the consumer party, refers to the user or the device or entity to which the user belongs that requests the Network Digital Twin (NDT) service.
  • NDT Network Digital Twin
  • the consumer requests signaling storm analysis by sending first information for requesting signaling storm analysis to the first network function.
  • the first information includes network object information, that is, which network objects(s) are being requested to analyze the signaling storm.
  • the network object information includes one or more of the following: network function information, network slice information, network function configuration information, and network slice configuration information.
  • the network object information includes the network object requested for analysis.
  • This network object can refer to one or more network functions or entities; that is, the network function information can include information such as the identifier of the network function or entity.
  • the network object can also refer to one or more network slices, in which case the network slice information can include one or more S-NSSAIs.
  • the network object information may also include configuration information for the network object, such as configuration information for network functions, configuration information for network slices, etc.
  • the configuration information for the network object includes, but is not limited to, configuration information related to interfaces, configuration information related to channels, configuration information related to protocols, etc. All configuration information related to network functions and/or network slices in the physical network can be included within the configuration information of the network object in this embodiment.
  • the first information may further include operation information, which represents simulated actions or behaviors of a network digital twin/digital twin instance associated with the network object.
  • the operation information specifically refers to the operations or actions performed in the signaling storm scenario, such as modifying configuration parameters for network objects (e.g., modifying the maximum traffic rate received by network nodes), configuring disaster recovery elements for fault switching, etc.
  • the analysis results are generated based on one or more of a first running result, a second running result, and a first prediction result; wherein, the first running result includes relevant information obtained by the first network function during the process of running the network digital twin/digital twin instance to simulate a signaling storm; the second running result represents relevant information obtained during the process of running the network digital twin/digital twin instance according to the operation information to simulate and optimize the signaling storm; the first prediction result is obtained based on the first running result, and the first prediction result represents the trend information of whether a signaling storm will occur or not in the first future time.
  • the consumer may send fourth information to a third network function related to the network object based on the analysis results.
  • the fourth information is used to instruct or suggest the execution of the optimization operation.
  • the consumer can send fourth information to the third network function related to the network object.
  • the fourth information may include the operation information to instruct or suggest that the third network function execute the operation information to eliminate signaling storms, thereby performing configuration optimization.
  • the consumer is an NDT consumer
  • the first network function is NDT
  • the second network function is a management service producer (MnS producer).
  • Figure 4 is a schematic diagram of the interactive flow of the analysis and processing method according to an embodiment of this disclosure; as shown in Figure 4, the method includes:
  • Step 301 The NDT consumer sends a signaling storm analysis request to the NDT, which includes network object information.
  • the request may also include operational information.
  • the network object information includes one or more of the following: network function information, slice information, network function configuration information, and slice configuration information.
  • the operation information specifically refers to the operations or actions performed in the signaling storm scenario, such as modifying configuration parameters for network objects (e.g., modifying the maximum traffic rate received by network nodes), configuring disaster recovery elements for fault switching, etc.
  • Step 302 NDT sends a response to the NDT consumer, which indicates the status of the request.
  • the status of the request can include success or failure. If the request status indicates success, subsequent steps are executed; if the request status indicates failure, the process is terminated.
  • Step 303 NDT obtains information related to network objects from the management service producer. This information is network information related to network simulation and/or verification.
  • the information includes one or more of the following: network performance-related information, network element status-related information, network capability-related information, network slicing-related information, resource-related network slicing information, and user and/or network traffic data; by obtaining the above information, the creation and operation of digital twin instances corresponding to network objects are carried out, thereby performing signaling storm behavior analysis.
  • Step 304 NDT performs network simulation and/or verification of signaling storm analysis and generates analysis results.
  • NDT can retrieve the digital twin model related to the network object from the twin model library based on the information obtained, according to the consumer's needs, thereby generating the digital twin object corresponding to the network object. Based on the obtained information, it can intelligently orchestrate the relevant resources, generate the corresponding digital twin instance on demand, control the running of the digital twin instance to simulate the behavior of signaling storm, and obtain the first running result.
  • NDT can also control the operation of the digital twin instance based on the operation information to simulate the execution of the operation information and obtain a second running result after the operation is executed.
  • the second running result may include network information such as network indicators during the operation of the digital twin instance according to the operation information, as well as information such as the continued occurrence of signaling storms or the elimination of signaling storms.
  • NDT can also predict the trend information of whether a signaling storm will occur in the first time in the future based on the first running result (i.e. the running result of simulating the behavior of a signaling storm).
  • the trend information may specifically include prediction information of whether a signaling storm will occur or not in the first time.
  • the trend information may also include the running information of the digital twin instance in the scenario where a signaling storm occurs or not, etc.
  • NDT can generate analysis results based on one or more of the first running results, the second running results, and the first prediction results.
  • the analysis results may include one or more of the first running results, the second running results, and the first prediction results.
  • Step 305 NDT sends the analysis results to NDT consumers.
  • the analysis results may include:
  • Simulation behavior The operational results (i.e., the first operational result) and/or impact obtained by simulating the behavior of a signaling storm.
  • the impact of simulating the behavior of a signaling storm can refer to the trend information regarding whether a signaling storm will occur in the first possible future time (i.e., the aforementioned first prediction result).
  • Verification of optimized operations refers to the operation information, namely the operations performed in the signaling storm scenario to optimize the signaling storm behavior, such as setting the maximum traffic rate received by network nodes and configuring disaster recovery elements for failover;
  • Verification results The results obtained based on the behavior of the optimized operation (i.e., the second result), such as whether a signaling storm will occur, and if so, the recovery time through disaster recovery elements, etc.
  • the technical solution of this disclosure uses a digital twin component in the first network function to partially or completely mirror the physical network; the digital twin component in the first network function can interact with the real physical network, restore the operating state and environment of the real physical network through network simulation, and verify through simulation before performing actual network optimization operations, thereby providing analysis results, which can help improve the reliability of network configuration and deployment.
  • FIG. 5 is a schematic diagram of the composition structure of the analysis and processing device according to an embodiment of this disclosure; as shown in Figure 5, the device includes: a first communication unit 11 and a first processing unit 12; wherein,
  • the first communication unit 11 is configured to receive first information sent by a consumer, the first information being used to request analysis of signaling storms, the first information including at least network object information; and is also configured to obtain second information related to the network object.
  • the first processing unit 12 is used to perform network simulation and/or verification of signaling storm analysis based on the second information, and generate analysis results;
  • the first communication unit 11 is also used to send the analysis results to the consumer.
  • the network object information includes one or more of the following: network function information, network slice information, network function configuration information, and network slice configuration information.
  • the second information includes one or more of the following: network performance-related information, network element status-related information, network capability-related information, network slicing-related information, resource-related network slicing information, and user and/or network traffic data.
  • the first communication unit 11 is configured to obtain second information related to a network object from one or more second network functions based on the first information.
  • the first processing unit 12 is configured to generate a network digital twin/digital twin instance related to the network object based on the second information, run the network digital twin/digital twin instance to perform network simulation and/or verification for signaling storm analysis, obtain the running results of the network digital twin/digital twin instance, and generate analysis results based on the running results.
  • the first processing unit 12 is used to create a digital twin object corresponding to the network object and to generate a network digital twin/digital twin instance based on the second information.
  • the first processing unit 12 is configured to run the digital twin instance and obtain a first running result, the first running result including relevant information obtained by running the network digital twin/digital twin instance to simulate a signaling storm; and/or, run the network digital twin/digital twin instance based on operation information to obtain a second running result, the operation information representing simulated actions or behaviors for the network digital twin/digital twin instance, and the second running result representing relevant information obtained during the process of running the network digital twin/digital twin instance according to the operation information to simulate and optimize the signaling storm.
  • the first information includes the operation information; or,
  • the first processing unit 12 is also configured to obtain the operation information through local policy information.
  • the first processing unit 12 is configured to generate an analysis result based on one or more of the first running result, the second running result, and the first prediction result; the first prediction result is obtained based on the first running result, and the first prediction result represents the trend information of whether a signaling storm will occur or not in the future.
  • the first processing unit 12 in the device can be implemented by a central processing unit (CPU), a digital signal processor (DSP), a microcontroller unit (MCU), or a field-programmable gate array (FPGA) in practical applications;
  • the first communication unit 11 in the device can be implemented by a communication module (including: basic communication kit, operating system, communication module, standardized interface and protocol, etc.) and a transceiver antenna in practical applications.
  • FIG. 6 is a schematic diagram of the composition structure of the analysis and processing apparatus according to an embodiment of this disclosure; as shown in Figure 6, the apparatus includes: a second communication unit 21, configured to send first information to a first network function, the first information being used to request analysis of signaling storms, the first information including at least network object information; and further configured to receive analysis results sent by the first network function, the analysis results being generated by network simulation and/or verification of signaling storm analysis performed by the first network function.
  • the network object information includes one or more of the following: network function information, network slice information, network function configuration information, and network slice configuration information.
  • the first information further includes operation information, which represents simulated actions or behaviors for network digital twin/digital twin instances associated with the network object.
  • the analysis results are generated based on one or more of a first running result, a second running result, and a first prediction result;
  • the first operational result includes relevant information obtained by the first network function during the process of simulating a signaling storm by running a network digital twin/digital twin instance;
  • the second running result represents the relevant information obtained during the process of running the network digital twin/digital twin instance according to the operation information to simulate and optimize the signaling storm;
  • the first prediction result is obtained based on the first running result, and the first prediction result represents the trend information of whether a signaling storm will occur or not in the first future time.
  • the second communication unit 21 in the device can be implemented in practical applications through a communication module (including: basic communication kit, operating system, communication module, standardized interface and protocol, etc.) and a transceiver antenna.
  • a communication module including: basic communication kit, operating system, communication module, standardized interface and protocol, etc.
  • analysis and processing apparatus provided in the above embodiments is only illustrated by the division of the above program modules. In practical applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the apparatus can be divided into different program modules to complete all or part of the processing described above.
  • analysis and processing apparatus and analysis and processing method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.
  • FIG. 7 is a schematic diagram of the hardware composition structure of the communication device according to an embodiment of this disclosure.
  • the communication device includes a memory 32, a processor 31, and a computer program stored in the memory 32 and executable on the processor 31.
  • the processor 31 executes the program, it implements the steps of the analysis and processing method applied to the first network function or consumer according to the embodiment of this disclosure.
  • the communication device may also include at least one network interface 33.
  • the various components in the communication device are coupled together via a bus system 34.
  • the bus system 34 is used to enable communication between these components.
  • the bus system 34 also includes a power bus, a control bus, and a status signal bus.
  • all buses are labeled as bus system 34 in Figure 7.
  • Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); magnetic surface memory can be disk storage or magnetic tape storage.
  • Volatile memory can be random access memory (RAM), which is used as an external cache.
  • RAM Random Access Memory
  • SRAM Static Random Access Memory
  • SSRAM Synchronous Static Random Access Memory
  • DRAM Dynamic Random Access Memory
  • SDRAM Synchronous Dynamic Random Access Memory
  • DDRSDRAM Double Data Rate Synchronous Dynamic Random Access Memory
  • ESDRAM Enhanced Synchronous Dynamic Random Access Memory
  • SLDRAM SyncLink Dynamic Random Access Memory
  • DRRAM Direct Rambus Random Access Memory
  • Processor 31 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 31 or by instructions in software form.
  • the processor 31 may be a general-purpose processor, DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
  • Processor 31 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this disclosure.
  • a general-purpose processor may be a microprocessor or any conventional processor, etc.
  • the steps of the methods disclosed in the embodiments of this disclosure can be directly manifested as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor.
  • the software modules may be located in a storage medium, which is located in memory 32.
  • Processor 31 reads information from memory 32 and completes the steps of the aforementioned method in conjunction with its hardware.
  • the communication device may be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), FPGAs, general-purpose processors, controllers, MCUs, microprocessors, or other electronic components to perform the aforementioned method.
  • ASICs application-specific integrated circuits
  • DSPs digital signal processors
  • PLDs programmable logic devices
  • CPLDs complex programmable logic devices
  • FPGAs general-purpose processors
  • controllers MCUs
  • microprocessors or other electronic components to perform the aforementioned method.
  • this disclosure also provides a computer-readable storage medium, such as a memory 32 including a computer program, which can be executed by a processor 31 of a communication device to perform the steps described in the foregoing method.
  • the computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disc, or CD-ROM; or it may be various devices including one or any combination of the above-mentioned memories.
  • the computer-readable storage medium provided in this disclosure embodiment stores a computer program thereon, which, when executed by a processor, implements the steps of the analysis and processing method of this disclosure embodiment applied to a first network function or consumer.
  • This disclosure also provides a computer program product, including a computer program that can be executed by a computer device (such as the processor 31 of a communication device) to complete the steps of any of the aforementioned analysis and processing methods.
  • a computer device such as the processor 31 of a communication device
  • the disclosed devices and methods can be implemented in other ways.
  • the device embodiments described above are merely illustrative.
  • the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components may be combined, or integrated into another system, or some features may be ignored or not executed.
  • the coupling, direct coupling, or communication connection between the various components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.
  • the units described above as separate components may or may not be physically separate.
  • the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.
  • each functional unit in the various embodiments of this disclosure can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.
  • the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments.
  • the aforementioned storage medium includes various media that can store program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.
  • the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium.
  • This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this disclosure.
  • the aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

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Abstract

本公开实施例公开了一种分析处理方法、装置、通信设备和存储介质。所述方法包括：第一网络功能接收消费者发送的第一信息，所述第一信息用于请求分析信令风暴，所述第一信息至少包括网络对象信息；获取与网络对象相关的第二信息，基于所述第二信息执行信令风暴分析的网络模拟和/或验证，生成分析结果，向所述消费者发送所述分析结果。

Description

一种分析处理方法、装置、通信设备和存储介质
相关申请的交叉引用
本公开主张在2024年05月17日在中国提交的中国专利申请号202410620056.0的优先权，其全部内容通过引用包含于此。
技术领域
本公开涉及通信技术领域，具体涉及一种分析处理方法、装置、通信设备和存储介质。
背景技术
信令风暴是移动通信网络中突然出现大量信令消息涌入的情况，导致网络处理能力超载，从而影响网络性能和稳定性。信令风暴可能是由于发生重大事件导致太多用户同时请求服务，或者由网络故障、配置错误或恶意攻击引起的。在此期间，用户将反复尝试建立连接直到重新连接，从而突然产生大量信令消息涌入，引发信令风暴。目前针对信令风暴场景或者对于网络故障、根因分析等可用性技术监测方案均为基于现网技术。
发明内容
为解决相关技术存在的技术问题，本公开实施例提供一种分析处理方法、装置、通信设备和存储介质。
为达到上述目的，本公开实施例的技术方案是这样实现的：
第一方面，本公开实施例提供了一种分析处理方法，所述方法应用于第一网络功能，所述方法包括：
所述第一网络功能接收消费者发送的第一信息，所述第一信息用于请求分析信令风暴，所述第一信息至少包括网络对象信息；
获取与网络对象相关的第二信息，基于所述第二信息执行信令风暴分析的网络模拟和/或验证，生成分析结果，向所述消费者发送所述分析结果。
上述方案中，所述网络对象信息包括以下一项或多项：网络功能信息、网络切片信息、网络功能的配置信息、网络切片的配置信息。
上述方案中，所述第二信息包括以下一项或多项：网络性能相关信息、网元状态相关信息、网络能力相关信息、网络切片相关信息、与资源相关的网络切片信息、用户和/或网络的流量数据。
上述方案中，所述获取与网络对象相关的第二信息，包括：所述第一网络功能基于所述第一信息，从一个或多个第二网络功能获取与网络对象相关的第二信息。
上述方案中，所述基于所述第二信息执行信令风暴分析的网络模拟和/或验证，生成分析结果，包括：
基于所述第二信息生成与所述网络对象相关的网络数字孪生/数字孪生实例，运行所述网络数字孪生/数字孪生实例以执行信令风暴分析的网络模拟和/或验证；
获得网络数字孪生/数字孪生实例的运行结果，基于所述运行结果生成分析结果。
上述方案中，所述基于所述第二信息生成与所述网络对象相关的网络数字孪生/数字孪生实例，包括：
所述第一网络功能创建所述网络对象对应的数字孪生对象，基于所述第二信息进行编排生成网络数字孪生/数字孪生实例。
上述方案中，所述运行所述网络数字孪生/数字孪生实例以执行信令风暴分析的网络模拟和/或验证，包括：
所述第一网络功能运行所述网络数字孪生/数字孪生实例，获得第一运行结果，所述第一运行结果包括通过运行所述网络数字孪生/数字孪生实例以模拟信令风暴过程中获得的相关信息；和/或，
所述第一网络功能基于操作信息运行所述网络数字孪生/数字孪生实例，获得第二运行结果，所述操作信息表示针对所述网络数字孪生/数字孪生实例的模拟动作或行为，所述第二运行结果表示按照所述操作信息运行所述网络数字孪生/数字孪生实例、以对信令风暴进行模拟优化操作过程中获得的相关信息。
上述方案中，所述第一信息包括所述操作信息；或者，所述方法还包括：所述第一网络功能通过本地策略信息获得所述操作信息。
上述方案中，所述基于所述运行结果生成分析结果，包括：所述第一网络功能基于所述第一运行结果、所述第二运行结果以及第一预测结果中的一项或多项生成分析结果；所述第一预测结果基于所述第一运行结果获得，所述第一预测结果表示在未来的第一时间出现或不出现信令风暴的趋势信息。
第二方面，本公开实施例还提供了一种分析处理方法，所述方法应用于消费者，所述方法包括：
所述消费者向第一网络功能发送第一信息，所述第一信息用于请求分析信令风暴，所述第一信息至少包括网络对象信息；
接收所述第一网络功能发送的分析结果，所述分析结果为所述第一网络功能执行信令风暴分析的网络模拟和/或验证生成的。
上述方案中，所述网络对象信息包括以下一项或多项：网络功能信息、网络切片信息、网络功能的配置信息、网络切片的配置信息。
上述方案中，所述第一信息还包括操作信息，所述操作信息表示针对所述网络对象相关的网络数字孪生/数字孪生实例的模拟动作或行为。
上述方案中，所述分析结果基于第一运行结果、第二运行结果以及第一预测结果中的一项或多项生成；其中，
所述第一运行结果包括所述第一网络功能通过运行所述网络数字孪生/数字孪生实例以模拟信令风暴过程中获得的相关信息；
所述第二运行结果表示按照所述操作信息运行所述网络数字孪生/数字孪生实例、以对信令风暴进行模拟优化操作过程中获得的相关信息；
所述第一预测结果基于所述第一运行结果获得，所述第一预测结果表示在未来的第一时间出现或不出现信令风暴的趋势信息。
第三方面，本公开实施例还提供了一种分析处理装置，所述装置应用于第一网络功能，所述装置包括：第一通信单元和第一处理单元；其中，
所述第一通信单元，用于接收消费者发送的第一信息，所述第一信息用于请求分析信令风暴，所述第一信息至少包括网络对象信息；还用于获取与网络对象相关的第二信息；
所述第一处理单元，用于基于所述第二信息执行信令风暴分析的网络模拟和/或验证，生成分析结果；
所述第一通信单元，还用于向所述消费者发送所述分析结果。
第四方面，本公开实施例还提供了一种分析处理装置，所述装置应用于消费者，所述装置包括：第二通信单元，用于向第一网络功能发送第一信息，所述第一信息用于请求分析信令风暴，所述第一信息至少包括网络对象信息；还用于接收所述第一网络功能发送的分析结果，所述分析结果为所述第一网络功能执行信令风暴分析的网络模拟和/或验证生成的。
第五方面，本公开实施例还提供了一种计算机可读存储介质，其上存储有计算机程序，其该程序被处理器执行时实现本公开实施例上述第一方面或第二方面所述方法的步骤。
第六方面，本公开实施例还提供了一种通信设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述程序时实现本公开实施例上述第一方面或第二方面所述方法的步骤。
第七方面，本公开实施例还提供了一种计算机程序产品，其中，包括计算机程序指令，该计算机程序指令使得计算机执行如本公开实施例上述第一方面或第二方面所述方法的步骤。
本公开实施例提供的分析处理方法、装置、通信设备和存储介质，所述方法包括：第一网络功能接收消费者发送的第一信息，所述第一信息用于请求分析信令风暴，所述第一信息至少包括网络对象信息；获取与网络对象相关的第二信息，基于所述第二信息执行信令风暴分析的网络模拟和/或验证，生成分析结果，向所述消费者发送所述分析结果。采用本公开实施例的技术方案，通过第一网络功能基于消费者的需求，通过网络仿真的方式模拟例如信令风暴等网络场景，从而实现了通过网络仿真的方式对信令风暴的分析，降低现网的试错风险和成本，助力网络新技术研究。
附图说明
图1为本公开实施例的分析处理方法的流程示意图一；
图2为本公开实施例的分析处理方法中的数字孪生实例的创建运行过程示意图；
图3为本公开实施例的分析处理方法的流程示意图二；
图4为本公开实施例的分析处理方法的交互流程示意图；
图5为本公开实施例的分析处理装置的组成结构示意图一；
图6为本公开实施例的分析处理装置的组成结构示意图二；
图7为本公开实施例的通信设备的硬件组成结构示意图。
具体实施方式
下面结合附图及具体实施例对本公开作进一步详细的说明。
本公开实施例的技术方案可以应用于各种通信系统，例如：全球移动通讯(Global System of Mobile communication，GSM)系统、长期演进(Long Term Evolution，LTE)系统或第五代移动通信技术(5th Generation Mobile Communication Technology，5G)系统等。可选地，5G系统或5G网络还可以称为新无线(New Radio，NR)系统或NR网络。
示例性的，本公开实施例应用的通信系统可包括网络设备和终端设备(也可称为终端、通信终端等等)；网络设备可以是与终端设备通信的设备。其中，网络设备可以为一定区域范围内提供通信覆盖，并且可以与位于该区域内的终端进行通信。可选地，网络设备可以是各通信系统中的基站，例如LTE系统中的演进型基站(Evolutional Node B，eNB)，又例如5G系统或NR系统中的基站(gNB)。
应理解，本公开实施例中网络/系统中具有通信功能的设备可称为通信设备。通信设备可包括具有通信功能的网络设备和终端，网络设备和终端设备可以为上文所述的具体设备，此处不再赘述；通信设备还可包括通信系统中的其他设备，例如网络控制器、移动管理实体等其他网络实体，本公开实施例中对此不做限定。
应理解，本文中术语“系统”和“网络”在本文中常被可互换使用。本文中术语“和/或”，仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。另外，本文中字符“/”，一般表示前后关联对象是一种“或”的关系。
本公开的说明书和权利要求书中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的本公开的实施例例如能够以除了在这里图示或描述的那些以外的顺序实施。此外，术语“包括”和“具有”以及他们的任何变形，意图在于覆盖不排他的包含，例如，包含了一系列步骤或单元的过程、方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
本公开实施例提供了一种分析处理方法。图1为本公开实施例的分析处理方法的流程示意图一；如图1所示，所述方法包括：
步骤101：第一网络功能接收消费者发送的第一信息，所述第一信息用于请求分析信令风暴，所述第一信息至少包括网络对象信息；
步骤102：获取与网络对象相关的第二信息，基于所述第二信息执行信令风暴分析的网络模拟和/或验证，生成分析结果，向所述消费者发送所述分析结果。
本实施例中，所述第一网络功能是指能够提供管理服务(Management Service，MnS)的功能或实体。在其他可选实施例中，所述分析处理方法的执行主体也可称为管理服务(MnS)、第一实体等等。
本实施例中，所述第一网络功能能够基于消费者的请求执行信令风暴(signaling storm)分析的网络模拟和/或验证。所述网络模拟和/或验证采用数字孪生等技术，在传统物理网络进行外部抽象映射，建立网络数字孪生体，通过管理编排实现闭环控制。
本实施例中，所述消费者又可称为消费方或consumer，是指请求网络数字孪生(Network Digital Twin，NDT)服务的用户或用户所属设备或实体。在本公开实施例中，消费者请求分析信令风暴，向第一网络功能发送用于请求分析信令风暴的第一信息，所述第一信息包括网络对象信息，也即针对哪个或哪些网络对象请求分析信令风暴。
在一些可选实施例中，所述网络对象信息包括以下一项或多项：网络功能信息、网络切片信息、网络功能的配置信息、网络切片的配置信息。
本实施例中，所述网络对象信息中包括请求分析的网络对象，该网络对象可以是指一个或多个网络功能或实体，也即所述网络功能信息可以包括网络功能或实体的标识等信息。或者，该网络对象也可以是指一个或多个网络切片，则所述网络切片信息可以包括一个或多个单个网络切片选择辅助信息(Single Network Slice Selection Assistance Information，S-NSSAI)。在其他可选实施例中，所述网络对象信息还可包括针对网络对象的配置信息，例如网络功能的配置信息、网络切片的配置信息等等。示例性的，网络对象的配置信息包括但不限于与接口相关的配置信息、与通道相关的配置信息、与协议相关的配置信息等等，凡是实体网络中针对网络功能和/或切片相关的配置信息，均可以包含在本实施例的网络对象的配置信息之内。
本实施例中，所述第一网络功能采集与网络对象相关的第二信息，所述第二信息用于执行网络模拟和/或验证。可以理解，所述第二信息是与网络对象相关的网络信息，该网络信息可以是与网络对象相关的当前时刻的信息和/或历史时期收集到的信息。
在一些可选实施例中，所述获取与网络对象相关的第二信息，包括：所述第一网络功能基于所述第一信息，从一个或多个第二网络功能获取与网络对象相关的第二信息。
本实施例中，所述一个或多个第二网络功能是指管理服务(MnS)生产者或生产方(MnS producer)，在其他可选实施例中，第二网络功能也可称为管理服务提供商，其可提供网络对象相关的第二信息。在一些可选实施例中，第二网络功能可以是以下一个或多个：网络切片管理功能(Network Slice Management Function，NSMF)、网络切片子网管理功能(Network Slice Subnet Management Function，NSSMF)、网络功能管理功能(Network Function Management Function，NFMF)。在其他可选实施例中，所述第二网络功能也可以是指能够获取第二信息的其他网络功能或实体，本实施例对此不做限定。
在一些可选实施例中，所述第二信息包括以下一项或多项：网络性能相关信息、网元状态相关信息、网络能力相关信息、网络切片相关信息、与资源相关的网络切片信息；用户和/或网络的流量数据(流量、带宽、时长)。
本实施例中，所述第二信息可包括以下三类信息中的一类或多类信息：
第一类信息包括以下一项或多项：网络性能相关信息、网元状态相关信息、网络能力相关信息；
第二类信息包括以下一项或多项：网络切片相关信息、与资源相关的网络切片信息；
第三类信息包括用户或网络的流量数据。
其中，所述网络性能相关信息例如可包括带宽、延时、吞吐率、传输速率、丢包率、重传率、并发连接数等与网络性能相关的任何信息。所述网元状态相关信息例如包括在线状态、离线状态、工作状态、故障状态、休眠状态、低功率状态等等，任意能够标识网络对象表现出的形态均可作为所述网元状态相关信息。所述网络能力相关信息具体可以是指网络支持的指标相关信息，例如支持的最大带宽、最大吞吐率、最大传输速率、最大并发连接数等等。
其中，所述与资源相关的网络切片信息，具体是指切片需要的资源要求信息，例如切片需要的带宽大小等等。
其中，所述用户和/或网络的流量数据具体可包括用户使用的流量数据和/或网络使用的流量数据；所述流量数据具体可通过以下一种或多种方式体现：流量(网络传输的数据量)、带宽、传输时长、订阅者数量等等。
本实施例中，第一网络功能基于获取到的与网络对象相关的第二信息执行网络模拟和/或验证，从而生成分析结果。
在本公开的一些可选实施例中，所述基于所述第二信息执行信令风暴分析的网络模拟和/或验证，生成分析结果，包括：基于所述第二信息生成与所述网络对象相关的网络数字孪生/数字孪生实例，运行所述网络数字孪生/数字孪生实例以执行信令风暴分析的网络模拟和/或验证；获得网络数字孪生/数字孪生实例的运行结果，基于所述运行结果生成分析结果。
本实施例中，第一网络功能中可具有数字孪生体模组，通过数字孪生体模组生成与所述网络对象相关的数字孪生实例并控制数字孪生实例运行。在本公开各实施例中，所述数字孪生实例可以是端到端网络数字孪生实例、单域数字孪生实例以及专网数字孪生实例中的一种或多种。所述第一网络功能通过执行数字孪生实例的控制，执行数字孪生实例运行要求，通过获得数字孪生实例的运行结果，从而得到分析结果。
在一些可选实施例中，所述基于所述第二信息生成与所述网络对象相关的网络数字孪生/数字孪生实例，包括：所述第一网络功能创建所述网络对象对应的数字孪生对象，基于所述第二信息进行编排生成网络数字孪生/数字孪生实例。
本实施例中，第一网络功能的数字孪生体组件具体可包括：孪生模型库、数字孪生模型生成功能、数字孪生编排功能、数字孪生实例运行功能以及数字孪生实例控制功能等等；其中，所述孪生模型库中包括网络中所需的各种数字孪生模型；数字孪生模型生成功能可根据消费者的需求，基于所述第二信息从孪生模型库中调用获得与网络对象相关的数字孪生模型，从而创建所述网络对象对应的数字孪生对象，将所述数字孪生对象发送给数字孪生编排功能；数字孪生编排功能基于所述第二信息对相关资源进行智能编排，按需生成相应的网络数字孪生/数字孪生实例，将网络数字孪生/数字孪生实例发送给数字孪生实例运行功能；数字孪生实例控制功能控制数字孪生实例运行功能运行网络数字孪生/数字孪生实例，以执行数字孪生实例化控制，执行数字孪生运行要求。
图2为本公开实施例的分析处理方法中的数字孪生实例的创建运行过程示意图；参照图2所示，①用户发起创建某个数字孪生服务的请求(相当于本实施例中的第一信息)给第一网络功能的接入管理功能，接入管理功能将用户的需求发送给数字孪生体组件；②数字孪生体组件的数据交互功能通过数据总线对网络对象的数据进行采集和交互(相当于本实施例中的获取第二信息)。③-④数字孪生体组件的管理编排功能根据用户需求创建数字孪生对象，并对相关资源进行智能编排，按需生成响应的数字孪生实例。数字孪生体组件的数字孪生控制功能执行数字孪生实例化控制，执行数字孪生运行要求。⑤数字孪生体将数字孪生运行结果或分析结果返回给移动网络，移动网络执行配置优化行为。
在一些可选实施例中，所述运行所述网络数字孪生/数字孪生实例以执行信令风暴分析的网络模拟和/或验证，包括：所述第一网络功能运行所述网络数字孪生/数字孪生实例，获得第一运行结果，所述第一运行结果包括通过运行所述网络数字孪生/数字孪生实例以模拟信令风暴过程中获得的相关信息；和/或，所述第一网络功能基于操作信息运行所述网络数字孪生/数字孪生实例，获得第二运行结果，所述操作信息表示针对所述网络数字孪生/数字孪生实例的模拟动作或行为，所述第二运行结果表示按照所述操作信息运行所述网络数字孪生/数字孪生实例、以对信令风暴进行模拟优化操作过程中获得的相关信息。
本实施例中，所述第一网络功能通过运行网络数字孪生/数字孪生实例，第一方面可执行网络模拟，即模拟网络中的信令风暴行为，从而获得模拟信令风暴过程相关的第一运行结果；其中，示例性的，所述第一运行结果可包括运行所述网络数字孪生/数字孪生实例过程中的网络指标等网络信息。第二方面，可执行网络验证，即在运行网络数字孪生/数字孪生实例过程中模拟执行操作信息，以执行对信令风暴进行模拟优化操作过程，从而获得执行操作信息后第二运行结果；其中，示例性的，所述第二运行结果可包括按照所述操作信息运行所述网络数字孪生/数字孪生实例过程中的网络指标等网络信息以及继续发生信令风暴或信令风暴消除等信息。又一方面，第一网络功能通过运行网络数字孪生/数字孪生实例还可获得上述第一方面和第二方面的组合运行结果。可以理解，所述运行结果可包括以下内容：第一运行结果(即模拟信令风暴的行为的运行结果)，和/或，第二运行结果(包括操作行为以及该操作行为对应的运行结果)。
本实施例中，所述操作信息具体是对信令风暴场景执行的操作或动作，例如针对网络对象修改配置参数(例如修改网络节点接收的最大流量速率等)、配置容灾元素进行故障切换等等。
在一些可选实施例中，所述第一信息包括所述操作信息；或者，所述方法还包括：所述第一网络功能通过本地策略信息获得所述操作信息。
本实施例中，所述操作信息可以是由消费者提供给第一网络功能，或者，所述操作信息也可以是第一网络功能本地配置信息中获得的。
在一些可选实施例中，所述基于所述运行结果生成分析结果，包括：所述第一网络功能基于所述第一运行结果、所述第二运行结果以及第一预测结果中的一项或多项生成分析结果；所述第一预测结果基于所述第一运行结果获得，所述第一预测结果表示在未来的第一时间出现或不出现信令风暴的趋势信息。
本实施例中，所述第一网络功能还可基于所述第一运行结果(即模拟信令风暴的行为的运行结果)，预测在未来的第一时间是否出现信令风暴的趋势信息，所述趋势信息具体可包括在所述第一时间出现或不出现信令风暴的预测信息，可选的，所述趋势信息中还可包括出现或不出现信令风暴的场景下的数字孪生实例的运行信息等等。具体的，所述第一网络功能可基于所述第一运行结果结合获得的第二信息(当前数据和/或历史数据)，利用神经网络模型获得所述趋势信息。则所述第一网络功能可基于所述第一运行结果、所述第二运行结果以及第一预测结果中的一项或多项生成分析结果，所述分析结果可包括所述第一运行结果、所述第二运行结果以及第一预测结果中的一项或多项。
在一些可选实施例中，第一网络功能还可根据所述分析结果向与所述网络对象相关的第三网络功能发送第三信息，所述第三信息用于指示或建议执行所述优化操作。
本实施例中，若所述分析结果中包括所述第二运行结果，且所述第二运行结果表示按照所述操作信息运行所述数字孪生实例能够达到消除信令风暴的运行结果，则所述第一网络功能可向与所述网络对象相关的第三网络功能发送第三信息，所述第三信息中可包括所述操作信息，以指示或建议所述第三网络功能执行所述操作信息以消除信令风暴，从而执行配置优化。
基于上述实施例，本公开实施例还提供了一种分析处理方法。图3为本公开实施例的分析处理方法的流程示意图二；如图3所示，所述方法包括：
步骤201：消费者向第一网络功能发送第一信息，所述第一信息用于请求分析信令风暴，所述第一信息至少包括网络对象信息；
步骤202：接收所述第一网络功能发送的分析结果，所述分析结果为所述第一网络功能执行信令风暴分析的网络模拟和/或验证生成的。
本实施例中，所述消费者又可称为消费方或consumer，是指请求网络数字孪生(Network Digital Twin，NDT)服务的用户或用户所属设备或实体。在本公开实施例中，消费者请求分析信令风暴，向第一网络功能发送用于请求分析信令风暴的第一信息，所述第一信息包括网络对象信息，也即针对哪个或哪些网络对象请求分析信令风暴。
在一些可选实施例中，所述网络对象信息包括以下一项或多项：网络功能信息、网络切片信息、网络功能的配置信息、网络切片的配置信息。
本实施例中，所述网络对象信息中包括请求分析的网络对象，该网络对象可以是指一个或多个网络功能或实体，也即所述网络功能信息可以包括网络功能或实体的标识等信息。或者，该网络对象也可以是指一个或多个网络切片，则所述网络切片信息可以包括一个或多个S-NSSAI。在其他可选实施例中，所述网络对象信息还可包括针对网络对象的配置信息，例如网络功能的配置信息、网络切片的配置信息等等。示例性的，网络对象的配置信息包括但不限于与接口相关的配置信息、与通道相关的配置信息、与协议相关的配置信息等等，凡是实体网络中针对网络功能和/或网络切片相关的配置信息，均可以包含在本实施例的网络对象的配置信息之内。
在一些可选实施例中，所述第一信息还包括操作信息，所述操作信息表示针对所述网络对象相关的网络数字孪生/数字孪生实例的模拟动作或行为。
本实施例中，所述操作信息具体是对信令风暴场景执行的操作或动作，例如针对网络对象修改配置参数(例如修改网络节点接收的最大流量速率等)、配置容灾元素进行故障切换等等。
在一些可选实施例中，所述分析结果基于第一运行结果、第二运行结果以及第一预测结果中的一项或多项生成；其中，所述第一运行结果包括所述第一网络功能通过运行所述网络数字孪生/数字孪生实例以模拟信令风暴过程中获得的相关信息；所述第二运行结果表示按照所述操作信息运行所述网络数字孪生/数字孪生实例、以对信令风暴进行模拟优化操作过程中获得的相关信息；所述第一预测结果基于所述第一运行结果获得，所述第一预测结果表示在未来的第一时间出现或不出现信令风暴的趋势信息。
在一些可选实施例中，所述消费者接收到所述分析结果后，可根据所述分析结果向与所述网络对象相关的第三网络功能发送第四信息，所述第四信息用于指示或建议执行所述优化操作。
本实施例中，若所述分析结果中包括所述第二运行结果，且所述第二运行结果表示按照所述操作信息运行所述数字孪生实例能够达到消除信令风暴的运行结果，则所述消费者可向与所述网络对象相关的第三网络功能发送第四信息，所述第四信息中可包括所述操作信息，以指示或建议所述第三网络功能执行所述操作信息以消除信令风暴，从而执行配置优化。
下面结合一个具体的示例对本公开实施例的分析处理方法进行详细说明。在本示例中，以消费者为NDT消费者(NDT consumer)、第一网络功能为NDT、第二网络功能为管理服务生产者(MnS producer)为例进行说明。
图4为本公开实施例的分析处理方法的交互流程示意图；如图4所示，所述方法包括：
步骤301：NDT消费者向NDT发送信令风暴分析的请求，请求中包括网络对象信息。可选的，请求中还可包括操作信息。
这里，所述网络对象信息包括以下一项或多项：网络功能信息、切片信息、网络功能的配置信息、切片的配置信息。
这里，所述操作信息具体是对信令风暴场景执行的操作或动作，例如针对网络对象修改配置参数(例如修改网络节点接收的最大流量速率等)、配置容灾元素进行故障切换等等。
步骤302：NDT向NDT消费者发送响应，响应用于指示请求的状态。
其中，所述请求的状态可包括成功或失败。在请求的状态表示成功的情况下，执行后续步骤；在请求的状态表示失败的情况下，终止流程。
步骤303：NDT从管理服务生产者获取与网络对象相关的信息。其中，所述信息是与网络模拟和/或验证相关的网络信息。
这里，所述信息(相当于上述实施例中的第二信息)包括以下一项或多项：网络性能相关信息、网元状态相关信息、网络能力相关信息、网络切片相关信息、与资源相关的网络切片信息、用户和/或网络的流量数据；通过获取上述信息用于进行网络对象对应的数字孪生实例的创建以及运行，从而执行信令风暴行为分析。
步骤304：NDT执行信令风暴分析的网络模拟和/或验证，生成分析结果。
这里，NDT可根据消费者的需求，基于获得的信息从孪生模型库中调用获得与网络对象相关的数字孪生模型，从而生成网络对象对应的数字孪生对象，基于获得的信息对相关资源进行智能编排，按需生成相应的数字孪生实例，控制运行数字孪生实例，以模拟信令风暴的行为，获得第一运行结果。
可选的，NDT还可基于操作信息控制运行所述数字孪生实例，以模拟执行操作信息，获得执行操作后的第二运行结果，所述第二运行结果可包括按照所述操作信息运行所述数字孪生实例过程中的网络指标等网络信息以及继续发生信令风暴或信令风暴消除等信息。
可选的，NDT还可基于第一运行结果(即模拟信令风暴的行为的运行结果)，预测在未来的第一时间是否出现信令风暴的趋势信息，所述趋势信息具体可包括在所述第一时间出现或不出现信令风暴的预测信息，可选的，所述趋势信息中还可包括出现或不出现信令风暴的场景下的数字孪生实例的运行信息等等。
则NDT可基于上述第一运行结果、第二运行结果以及第一预测结果中的一项或多项生成分析结果，所述分析结果可包括所述第一运行结果、所述第二运行结果以及第一预测结果中的一项或多项。
步骤305：NDT将分析结果发送给NDT消费者。
其中，所述分析结果可以包括：
仿真行为：通过模拟信令风暴的行为获得的运行结果(即第一运行结果)和/或影响。其中，模拟信令风暴的行为的影响具体可以是指在未来的第一时间是否出现信令风暴的趋势信息(即上述第一预测结果)；
优化操作的验证：表示操作信息，即在信令风暴场景下执行的操作以对信令风暴行为进行优化，例如设置网络节点接收的最大流量速率和配置容灾元素进行故障切换；
验证结果：基于优化操作的行为获得的运行结果(即第二运行结果)，例如信令风暴是否会发生，如果发生，通过灾难恢复元素来解决的恢复时间等等。
采用本公开实施例的技术方案，采用第一网络功能中的数字孪生体组件对物理网络进行部分或全部孪生镜像；第一网络功能中的数字孪生体组件可与真实物理网络进行数据交互，通过网络仿真还原真实物理网络的运行状态和环境，进行实际网络优化操作前可通过仿真进行验证，进而提供分析结果，能够辅助提升网络配置和部署的可靠性。
基于上述实施例，本公开实施例还提供了一种分析处理装置，所述装置应用于第一网络功能。图5为本公开实施例的分析处理装置的组成结构示意图一；如图5所示，所述装置包括：第一通信单元11和第一处理单元12；其中，
所述第一通信单元11，用于接收消费者发送的第一信息，所述第一信息用于请求分析信令风暴，所述第一信息至少包括网络对象信息；还用于获取与网络对象相关的第二信息；
所述第一处理单元12，用于基于所述第二信息执行信令风暴分析的网络模拟和/或验证，生成分析结果；
所述第一通信单元11，还用于向所述消费者发送所述分析结果。
在本公开的一些可选实施例中，所述网络对象信息包括以下一项或多项：网络功能信息、网络切片信息、网络功能的配置信息、网络切片的配置信息。
在本公开的一些可选实施例中，所述第二信息包括以下一项或多项：网络性能相关信息、网元状态相关信息、网络能力相关信息、网络切片相关信息、与资源相关的网络切片信息、用户和/或网络的流量数据。
在本公开的一些可选实施例中，所述第一通信单元11，用于基于所述第一信息，从一个或多个第二网络功能获取与网络对象相关的第二信息。
在本公开的一些可选实施例中，所述第一处理单元12，用于基于所述第二信息生成与所述网络对象相关的网络数字孪生/数字孪生实例，运行所述网络数字孪生/数字孪生实例以执行信令风暴分析的网络模拟和/或验证；获得网络数字孪生/数字孪生实例的运行结果，基于所述运行结果生成分析结果。
在本公开的一些可选实施例中，所述第一处理单元12，用于创建所述网络对象对应的数字孪生对象，基于所述第二信息进行编排生成网络数字孪生/数字孪生实例。
在本公开的一些可选实施例中，所述第一处理单元12，用于运行所述数字孪生实例，获得第一运行结果，所述第一运行结果包括通过运行所述网络数字孪生/数字孪生实例以模拟信令风暴过程中获得的相关信息；和/或，基于操作信息运行所述网络数字孪生/数字孪生实例，获得第二运行结果，所述操作信息表示针对所述网络数字孪生/数字孪生实例的模拟动作或行为，所述第二运行结果表示按照所述操作信息运行所述网络数字孪生/数字孪生实例、以对信令风暴进行模拟优化操作过程中获得的相关信息。
在本公开的一些可选实施例中，所述第一信息包括所述操作信息；或者，
所述第一处理单元12，还用于通过本地策略信息获得所述操作信息。
在本公开的一些可选实施例中，所述第一处理单元12，用于基于所述第一运行结果、所述第二运行结果以及第一预测结果中的一项或多项生成分析结果；所述第一预测结果基于所述第一运行结果获得，所述第一预测结果表示在未来的第一时间出现或不出现信令风暴的趋势信息。
本公开实施例中，所述装置中的第一处理单元12，在实际应用中可由中央处理器(Central Processing Unit，CPU)、数字信号处理器(Digital Signal Processor，DSP)、微控制单元(Microcontroller Unit，MCU)或可编程门阵列(Field－Programmable Gate Array，FPGA)实现；所述装置中的第一通信单元11，在实际应用中可通过通信模组(包含：基础通信套件、操作系统、通信模块、标准化接口和协议等)及收发天线实现。
本公开实施例还提供了一种分析处理装置，所述装置应用于消费者。图6为本公开实施例的分析处理装置的组成结构示意图二；如图6所示，所述装置包括：第二通信单元21，用于向第一网络功能发送第一信息，所述第一信息用于请求分析信令风暴，所述第一信息至少包括网络对象信息；还用于接收所述第一网络功能发送的分析结果，所述分析结果为所述第一网络功能执行信令风暴分析的网络模拟和/或验证生成的。
在本公开的一些可选实施例中，所述网络对象信息包括以下一项或多项：网络功能信息、网络切片信息、网络功能的配置信息、网络切片的配置信息。
在本公开的一些可选实施例中，所述第一信息还包括操作信息，所述操作信息表示针对所述网络对象相关的网络数字孪生/数字孪生实例的模拟动作或行为。
在本公开的一些可选实施例中，所述分析结果基于第一运行结果、第二运行结果以及第一预测结果中的一项或多项生成；其中，
所述第一运行结果包括所述第一网络功能通过运行网络数字孪生/数字孪生实例以模拟信令风暴过程中获得的相关信息；
所述第二运行结果表示按照所述操作信息运行网络数字孪生/数字孪生实例、以对信令风暴进行模拟优化操作过程中获得的相关信息；
所述第一预测结果基于所述第一运行结果获得，所述第一预测结果表示在未来的第一时间出现或不出现信令风暴的趋势信息。
本公开实施例中，所述装置中的第二通信单元21，在实际应用中可通过通信模组(包含：基础通信套件、操作系统、通信模块、标准化接口和协议等)及收发天线实现。
需要说明的是：上述实施例提供的分析处理装置在进行分析处理时，仅以上述各程序模块的划分进行举例说明，实际应用中，可以根据需要而将上述处理分配由不同的程序模块完成，即将装置的内部结构划分成不同的程序模块，以完成以上描述的全部或者部分处理。另外，上述实施例提供的分析处理装置与分析处理方法实施例属于同一构思，其具体实现过程详见方法实施例，这里不再赘述。
本公开实施例还提供了一种通信设备，所述通信设备为第一网络功能或消费者。图7为本公开实施例的通信设备的硬件组成结构示意图，如图7所示，所述通信设备包括存储器32、处理器31及存储在存储器32上并可在处理器31上运行的计算机程序，所述处理器31执行所述程序时实现本公开实施例应用于第一网络功能或消费者的分析处理方法的步骤。
可选地，通信设备还可包括至少一个网络接口33。其中，通信设备中的各个组件通过总线系统34耦合在一起。可理解，总线系统34用于实现这些组件之间的连接通信。总线系统34除包括数据总线之外，还包括电源总线、控制总线和状态信号总线。但是为了清楚说明起见，在图7中将各种总线都标为总线系统34。
可以理解，存储器32可以是易失性存储器或非易失性存储器，也可包括易失性和非易失性存储器两者。其中，非易失性存储器可以是只读存储器(Read Only Memory，ROM)、可编程只读存储器(Programmable Read-Only Memory，PROM)、可擦除可编程只读存储器(Erasable Programmable Read-Only Memory，EPROM)、电可擦除可编程只读存储器(Electrically Erasable Programmable Read-Only Memory，EEPROM)、磁性随机存取存储器(Ferromagnetic Random Access Memory，FRAM)、快闪存储器(Flash Memory)、磁表面存储器、光盘、或只读光盘(Compact Disc Read-Only Memory，CD-ROM)；磁表面存储器可以是磁盘存储器或磁带存储器。易失性存储器可以是随机存取存储器(Random Access Memory，RAM)，其用作外部高速缓存。通过示例性但不是限制性说明，许多形式的RAM可用，例如静态随机存取存储器(Static Random Access Memory，SRAM)、同步静态随机存取存储器(Synchronous Static Random Access Memory，SSRAM)、动态随机存取存储器(Dynamic Random Access Memory，DRAM)、同步动态随机存取存储器(Synchronous Dynamic Random Access Memory，SDRAM)、双倍数据速率同步动态随机存取存储器(Double Data Rate Synchronous Dynamic Random Access Memory，DDRSDRAM)、增强型同步动态随机存取存储器(Enhanced Synchronous Dynamic Random Access Memory，ESDRAM)、同步连接动态随机存取存储器(SyncLink Dynamic Random Access Memory，SLDRAM)、直接内存总线随机存取存储器(Direct Rambus Random Access Memory，DRRAM)。本公开实施例描述的存储器32旨在包括但不限于这些和任意其它适合类型的存储器。
上述本公开实施例揭示的方法可以应用于处理器31中，或者由处理器31实现。处理器31可能是一种集成电路芯片，具有信号的处理能力。在实现过程中，上述方法的各步骤可以通过处理器31中的硬件的集成逻辑电路或者软件形式的指令完成。上述的处理器31可以是通用处理器、DSP，或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。处理器31可以实现或者执行本公开实施例中的公开的各方法、步骤及逻辑框图。通用处理器可以是微处理器或者任何常规的处理器等。结合本公开实施例所公开的方法的步骤，可以直接体现为硬件译码处理器执行完成，或者用译码处理器中的硬件及软件模块组合执行完成。软件模块可以位于存储介质中，该存储介质位于存储器32，处理器31读取存储器32中的信息，结合其硬件完成前述方法的步骤。
在示例性实施例中，通信设备可以被一个或多个应用专用集成电路(Application Specific Integrated Circuit，ASIC)、DSP、可编程逻辑器件(Programmable Logic Device，PLD)、复杂可编程逻辑器件(Complex Programmable Logic Device，CPLD)、FPGA、通用处理器、控制器、MCU、微处理器(Microprocessor)、或其他电子元件实现，用于执行前述方法。
在示例性实施例中，本公开实施例还提供了一种计算机可读存储介质，例如包括计算机程序的存储器32，上述计算机程序可由通信设备的处理器31执行，以完成前述方法所述步骤。计算机可读存储介质可以是FRAM、ROM、PROM、EPROM、EEPROM、Flash Memory、磁表面存储器、光盘、或CD-ROM等存储器；也可以是包括上述存储器之一或任意组合的各种设备。
本公开实施例提供的计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现本公开实施例应用于第一网络功能或消费者中的分析处理方法的步骤。
本公开实施例还提供了一种计算机程序产品，包括计算机程序，所述计算机程序可由计算机设备(如通信设备的处理器31)执行，以完成前述任一分析处理方法的步骤。
本公开所提供的几个方法实施例中所揭露的方法，在不冲突的情况下可以任意组合，得到新的方法实施例。
本公开所提供的几个产品实施例中所揭露的特征，在不冲突的情况下可以任意组合，得到新的产品实施例。
本公开所提供的几个方法或设备实施例中所揭露的特征，在不冲突的情况下可以任意组合，得到新的方法实施例或设备实施例。
在本公开所提供的几个实施例中，应该理解到，所揭露的设备和方法，可以通过其它的方式实现。以上所描述的设备实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，如：多个单元或组件可以结合，或可以集成到另一个系统，或一些特征可以忽略，或不执行。另外，所显示或讨论的各组成部分相互之间的耦合、或直接耦合、或通信连接可以是通过一些接口，设备或单元的间接耦合或通信连接，可以是电性的、机械的或其它形式的。
上述作为分离部件说明的单元可以是、或也可以不是物理上分开的，作为单元显示的部件可以是、或也可以不是物理单元，即可以位于一个地方，也可以分布到多个网络单元上；可以根据实际的需要选择其中的部分或全部单元来实现本实施例方案的目的。
另外，在本公开各实施例中的各功能单元可以全部集成在一个处理单元中，也可以是各单元分别单独作为一个单元，也可以两个或两个以上单元集成在一个单元中；上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成，前述的程序可以存储于一计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质包括：移动存储设备、ROM、RAM、磁碟或者光盘等各种可以存储程序代码的介质。
或者，本公开上述集成的单元如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。基于这样的理解，本公开实施例的技术方案本质上或者说对相关技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机、服务器、或者网络设备等)执行本公开各个实施例所述方法的全部或部分。而前述的存储介质包括：移动存储设备、ROM、RAM、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本公开的具体实施方式，但本公开的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本公开揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本公开的保护范围之内。因此，本公开的保护范围应以所述权利要求的保护范围为准。

Claims (18)

  1. 一种分析处理方法，所述方法应用于第一网络功能，所述方法包括：
    所述第一网络功能接收消费者发送的第一信息，所述第一信息用于请求分析信令风暴，所述第一信息至少包括网络对象信息；
    获取与网络对象相关的第二信息，基于所述第二信息执行信令风暴分析的网络模拟和/或验证，生成分析结果，向所述消费者发送所述分析结果。
  2. 根据权利要求1所述的方法，其中，所述网络对象信息包括以下一项或多项：网络功能信息、网络切片信息、网络功能的配置信息、网络切片的配置信息。
  3. 根据权利要求1所述的方法，其中，所述第二信息包括以下一项或多项：网络性能相关信息、网元状态相关信息、网络能力相关信息、网络切片相关信息、与资源相关的网络切片信息、用户和/或网络的流量数据。
  4. 根据权利要求1所述的方法，其中，所述获取与网络对象相关的第二信息，包括：
    所述第一网络功能基于所述第一信息，从一个或多个第二网络功能获取与网络对象相关的第二信息。
  5. 根据权利要求1所述的方法，其中，所述基于所述第二信息执行信令风暴分析的网络模拟和/或验证，生成分析结果，包括：
    基于所述第二信息生成与所述网络对象相关的网络数字孪生/数字孪生实例，运行所述网络数字孪生/数字孪生实例以执行信令风暴分析的网络模拟和/或验证；
    获得网络数字孪生/数字孪生实例的运行结果，基于所述运行结果生成分析结果。
  6. 根据权利要求5所述的方法，其中，所述基于所述第二信息生成与所述网络对象相关的网络数字孪生/数字孪生实例，包括：
    所述第一网络功能创建所述网络对象对应的数字孪生对象，基于所述第二信息进行编排生成网络数字孪生/数字孪生实例。
  7. 根据权利要求5所述的方法，其中，所述运行所述网络数字孪生/数字孪生实例以执行信令风暴分析的网络模拟和/或验证，包括：
    所述第一网络功能运行所述网络数字孪生/数字孪生实例，获得第一运行结果，所述第一运行结果包括通过运行所述网络数字孪生/数字孪生实例以模拟信令风暴过程中获得的相关信息；和/或，
    所述第一网络功能基于操作信息运行所述网络数字孪生/数字孪生实例，获得第二运行结果，所述操作信息表示针对所述网络数字孪生/数字孪生实例的模拟动作或行为，所述第二运行结果表示按照所述操作信息运行所述网络数字孪生/数字孪生实例、以对信令风暴进行模拟优化操作过程中获得的相关信息。
  8. 根据权利要求7所述的方法，其中，所述第一信息包括所述操作信息；或者，
    所述方法还包括：所述第一网络功能通过本地策略信息获得所述操作信息。
  9. 根据权利要求7所述的方法，其中，所述基于所述运行结果生成分析结果，包括：
    所述第一网络功能基于所述第一运行结果、所述第二运行结果以及第一预测结果中的一项或多项生成分析结果；所述第一预测结果基于所述第一运行结果获得，所述第一预测结果表示在未来的第一时间出现或不出现信令风暴的趋势信息。
  10. 一种分析处理方法，所述方法应用于消费者，所述方法包括：
    所述消费者向第一网络功能发送第一信息，所述第一信息用于请求分析信令风暴，所述第一信息至少包括网络对象信息；
    接收所述第一网络功能发送的分析结果，所述分析结果为所述第一网络功能执行信令风暴分析的网络模拟和/或验证生成的。
  11. 根据权利要求10所述的方法，其中，所述网络对象信息包括以下一项或多项：网络功能信息、网络切片信息、网络功能的配置信息、网络切片的配置信息。
  12. 根据权利要求10所述的方法，其中，所述第一信息还包括操作信息，所述操作信息表示针对所述网络对象相关的网络数字孪生/数字孪生实例的模拟动作或行为。
  13. 根据权利要求10所述的方法，其中，所述分析结果基于第一运行结果、第二运行结果以及第一预测结果中的一项或多项生成；其中，
    所述第一运行结果包括所述第一网络功能通过运行网络数字孪生/数字孪生实例以模拟信令风暴过程中获得的相关信息；
    所述第二运行结果表示按照所述操作信息运行网络数字孪生/数字孪生实例、以对信令风暴进行模拟优化操作过程中获得的相关信息；
    所述第一预测结果基于所述第一运行结果获得，所述第一预测结果表示在未来的第一时间出现或不出现信令风暴的趋势信息。
  14. 一种分析处理装置，所述装置应用于第一网络功能，所述装置包括：第一通信单元和第一处理单元；其中，
    所述第一通信单元，用于接收消费者发送的第一信息，所述第一信息用于请求分析信令风暴，所述第一信息至少包括网络对象信息；还用于获取与网络对象相关的第二信息；
    所述第一处理单元，用于基于所述第二信息执行信令风暴分析的网络模拟和/或验证，生成分析结果；
    所述第一通信单元，还用于向所述消费者发送所述分析结果。
  15. 一种分析处理装置，所述装置应用于消费者，所述装置包括：第二通信单元，用于向第一网络功能发送第一信息，所述第一信息用于请求分析信令风暴，所述第一信息至少包括网络对象信息；还用于接收所述第一网络功能发送的分析结果，所述分析结果为所述第一网络功能执行信令风暴分析的网络模拟和/或验证生成的。
  16. 一种计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现权利要求1至9任一项所述方法的步骤；或者，该程序被处理器执行时实现权利要求10至13任一项所述方法的步骤。
  17. 一种通信设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述程序时实现权利要求1至9任一项所述方法的步骤；或者，所述处理器执行所述程序时实现权利要求10至13任一项所述方法的步骤。
  18. 一种计算机程序产品，包括计算机程序指令，该计算机程序指令使得计算机执行如权利要求1至9任一项所述方法的步骤；或者，该计算机程序指令使得计算机执行如权利要求10至13任一项所述方法的步骤。
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