WO2025200420A1 - 基于数字孪生的意图处理方法、设备及存储介质 - Google Patents

基于数字孪生的意图处理方法、设备及存储介质

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Publication number
WO2025200420A1
WO2025200420A1 PCT/CN2024/127726 CN2024127726W WO2025200420A1 WO 2025200420 A1 WO2025200420 A1 WO 2025200420A1 CN 2024127726 W CN2024127726 W CN 2024127726W WO 2025200420 A1 WO2025200420 A1 WO 2025200420A1
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WO
WIPO (PCT)
Prior art keywords
intent
twin
intention
executor
request
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/CN2024/127726
Other languages
English (en)
French (fr)
Inventor
谢宝国
杨建军
谢鹏翔
阮帮秋
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.)
ZTE Corp
Original Assignee
ZTE Corp
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Filing date
Publication date
Application filed by ZTE Corp filed Critical ZTE Corp
Publication of WO2025200420A1 publication Critical patent/WO2025200420A1/zh
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/50Business processes related to the communications industry
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computing arrangements using knowledge-based models
    • G06N5/02Knowledge representation; Symbolic representation
    • G06N5/022Knowledge engineering; Knowledge acquisition
    • G06N5/025Extracting rules from data
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computing arrangements using knowledge-based models
    • G06N5/04Inference or reasoning models
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computing arrangements using knowledge-based models
    • G06N5/04Inference or reasoning models
    • G06N5/041Abduction

Definitions

  • the present application relates to the field of communication technology, for example, to an intent processing method, device and storage medium based on digital twins.
  • Intent management of communication networks refers to the process of managing and controlling expectations and goals for communication networks or communication services.
  • Communication service providers use intents to describe their expectations and goals for network performance and specific communication services.
  • intents are realized, ensuring that network performance and communication services meet user needs while maximizing service benefits. This helps improve service efficiency and reliability, and enhances user satisfaction and service quality.
  • Intent management is used to ensure that network performance and communication services meet business needs.
  • problems such as the expected network performance and communication service requirements in the intent description cannot meet the intent expectations and goals, network failures caused by potential conflicts when multiple intents are running simultaneously, the inability to optimize the description of network expectations and goals when intents are formulated, and the inability to achieve the expected goals of high-priority intents.
  • the embodiments of the present application disclose an intent processing method, device and storage medium based on digital twins, which simulates and executes network management tasks corresponding to intents through digital twin technology to improve the accuracy and reliability of intent processing.
  • An embodiment of the present application discloses a computer device, including a memory, a processor, and a computer program stored in the memory and runnable on the processor, wherein when the processor executes the program, the digital twin-based intention processing method as described in the embodiment of the present application is implemented.
  • An embodiment of the present application discloses a computer-readable storage medium having a computer program stored thereon.
  • the program is executed by a processor, the digital twin-based intention processing method as described in the embodiment of the present application is implemented.
  • FIG4 is a diagram of a simulation process for satisfying desired target requirements throughout the entire life cycle of an intention based on digital twin technology, provided in an embodiment of the present application;
  • FIG6 is a process diagram of multiple intention conflict detection based on digital twin technology provided in an embodiment of the present application.
  • FIG9 is a flowchart of a method for processing intentions based on digital twins provided in an embodiment of the present application.
  • FIG10 is a flowchart of a method for processing intentions based on digital twins provided in an embodiment of the present application.
  • FIG11 is a flowchart of a method for processing intentions based on digital twins provided in an embodiment of the present application.
  • FIG12 is a schematic structural diagram of an intention processing device based on digital twins provided in an embodiment of the present application.
  • FIG13 is a schematic structural diagram of an intention processing device based on digital twins provided in an embodiment of the present application.
  • FIG14 is a schematic structural diagram of an intention processing device based on digital twins provided in an embodiment of the present application.
  • FIG15 is a schematic structural diagram of a computer device provided in an embodiment of the present application.
  • the management service consumer is the intent owner, and the management service producer is the intent processor.
  • the management service producer includes the intent manager and the intent executor.
  • the intent manager is used for intent parsing and translation, intent optimization, intent execution result monitoring, etc.
  • the intent executor is used for intent object instance life cycle management, intent object instance execution operation management, etc.
  • the intent producer has the following capabilities: (1) verify the intent; (2) convert the received intent into executable operations, including executing business or network management tasks, identifying, Develop and activate service or network management policies, etc.; (3) Evaluate results/information about intent realization (e.g., whether the intent was initially satisfied) and intent assurance (e.g., whether the intent continues to be satisfied).
  • the intent formulated by the intent consumer can include the consumer's communication service or network resource requirements (Requirement), the network performance goals described in the intent's desired objectives, and the intent's contextual constraints.
  • Intent translation refers to the process of determining the intent's strategy.
  • the business requirement information described in the intent might include "In region A and the data center (region B), support for up to 200 users is required, with end-to-end latency less than 5ms and downlink latency less than 3ms.”
  • Intent management is used to ensure that network performance and communication services meet business needs.
  • problems such as the expected network performance and communication service requirements in the intent description cannot meet the intended goals, network failures caused by potential conflicts when multiple intents are running simultaneously, the inability to optimize the description of network expectations and goals when intent is formulated, and the inability to achieve the intended goals of high-priority intents.
  • FIG1 is a schematic diagram of the structure of a digital twin-based intent processing system provided in an embodiment of the present application.
  • the system includes: a management service consumer 110, a management service producer 120, a managed network 130, and a digital twin manager 140.
  • the management service producer 120 includes an intent manager 121 and an intent executor 122.
  • the management service consumer 110 includes one or more for sending intents to the intent manager 121 in the management service producer 120.
  • the intent manager 121 is used to send a twin creation request to the digital twin manager 140 when one or more intents carry simulation prediction requirements or receive information that the expected target is not met returned by the intent executor.
  • the intent executor 122 is used to execute the intent sent by the intent manager.
  • the digital twin manager 140 is used to create an intent executor twin and a managed network twin according to the twin creation request to simulate one or more intents.
  • the managed network can be a network slice, a base station, a network element, a radio access network (RAN) or a core network (CN), etc.
  • RAN radio access network
  • CN core network
  • the intent manager 121 determines that the intent has simulation prediction requirements.
  • the intent manager 121 determines the managed network based on the managed network described by a single intent or by merging the managed networks described by multiple intents. And determines the intent executor 122 required to execute the intent, which includes the intent lifecycle management function, the intent execution function, etc.
  • the intent manager 121 requests the digital twin manager 140 to model the intent executor and the managed network, and create the intent executor twin and the managed network twin.
  • the intent manager 121 can interact with the intent executor twin and send down the intent to simulate the intent. Through digital twin simulation, evaluation and verification technology, the intent is predicted. Intent failures may occur and find out the causes and solutions, and solve various potential problems in the operation of intent object instances.
  • the intent executor 122 requests the intent executor twin to simulate the intent to determine the cause and solution.
  • the intent executor 122 can also interact directly with the intent executor twin. If the intent's expected goals are not met during the execution of the intent, the intent executor 122 directly requests the intent executor twin to simulate and verify the intent's object twin instance to identify the cause and verify possible solutions. Based on the solution provided by the intent executor twin, the intent executor 122 updates the intent's object instance and network management task, ensuring that the intent's expected goals are consistently met during the execution of the intent.
  • the intent manager in the management service producer receives one or more intents carrying simulation prediction requirements sent by the management service consumer and/or the intent execution result report containing the failure to meet the expected goals sent by the intent executor.
  • Simulation prediction requirements include at least one of the following: optimizing the desired intent, ensuring that the intent meets the desired intent throughout its lifecycle, predicting that the intent meets the desired intent, and detecting conflicts between multiple intents. Failure to meet the desired intent includes failure to meet the desired intent for a high-priority intent and failure to meet the desired intent at any point during the intent's lifecycle.
  • the intent manager in the intent producer receives an intent from a management service consumer. If the intent carries information such as the intent expected target optimization requirement, the intent full life cycle satisfaction of the expected target requirement, the intent satisfaction of the expected target prediction requirement, and multiple intent conflict detection requirements, the intent manager decides to initiate a digital twin simulation operation for the intent.
  • the intent executor in the process of executing the network management task related to the intent, will feedback the result of the intent execution based on the real-time network performance data of the network.
  • the intent manager in the intent producer receives the intent execution process result report from the intent executor, analyzes that the network performance parameters of the intent during execution do not meet the expected target of the intent, and the intent manager decides Use digital twin simulation technology to find causes and possible solutions.
  • Data includes functional data, entity data, and operational data.
  • Operational data includes historical and current operational data.
  • the digital twin manager collects data in real time from physical intent actuators and managed networks to model these intent actuators and managed networks.
  • the digital twin manager creates the intent actuator twin model and the managed network twin model, and inputs the operational data to create the intent actuator twin and the managed network twin.
  • the digital twin manager notifies the intent manager that the intent actuator twin and the managed network twin have been created, along with the twin information.
  • the simulation prediction demand is the intention expected target optimization demand
  • the intention manager sends the intention to the intention executor twin, please Request to create an intent object twin instance
  • the intent executor twin creates the intent object twin instance of the intent and sends information on the successful creation of the intent object twin instance to the intent manager
  • the intent manager sends a simulation request to the digital twin manager or the intent executor twin; wherein, the simulation request carries the intent expected target optimization requirement;
  • the intent executor twin configures the managed network twin according to the network parameters in the intent object twin instance, and executes the network management task corresponding to the intent expected target optimization requirement; in the process of executing the network management task, the managed network twin executes different combinations of network performance parameters to determine at least one optimal network performance parameter;
  • the intent executor twin sends at least one optimal network performance parameter to the intent manager, and the intent manager sends at least one optimal network performance parameter to the management service consumer for selection by the management service consumer.
  • FIG3 is a process diagram for optimizing the intended desired target based on the digital twin technology in this embodiment. As shown in FIG3 , the process includes:
  • the management service consumer sends the intent and the intent expected target optimization requirement to the intent manager.
  • the intent manager sends an intent to the intent executor twin, requesting the creation of an intent object twin instance.
  • the intent executor twin sends information to the intent manager indicating that the intent object twin instance has been successfully created.
  • the intent manager sends a simulation request to the digital twin manager or the intent executor twin.
  • the intent manager sends the simulation request to the digital twin manager, which forwards the simulation request to the intent executor twin.
  • the intent manager sends the simulation request directly to the intent executor twin.
  • the intention executor twin configures the managed network twin according to the network parameters in the intention object twin instance, and executes the network management task corresponding to the intention expected target optimization requirement.
  • the managed network twin attempts to execute different parameter configurations of the network performance parameters described in the desired target. Combine these parameters and find the closest performance parameters achieved. For example, combination 1: 2,000 users in a specific area, 100 Mbps bandwidth, and 10 ms service latency. Combination 2: 5,000 users in a specific area, 50 Mbps bandwidth, and 15 ms service latency. Find the optimal parameter configuration for these combinations.
  • the intent executor twin sends at least one optimal network performance parameter to the intent manager.
  • the intent manager generates an intent report according to at least one optimal network performance parameter, and sends the intent report to the management service consumer for selection by the management service consumer.
  • the intent when a management service consumer issues an intent to an intent consumer for execution, the intent is authorized to the intent producer for update or modification.
  • the intent producer is required to ensure that the intent consistently meets its intended goals throughout its lifecycle.
  • simulation verification is required to identify the cause and verify the solution when problems arise.
  • the intent manager decides to create a digital twin, using digital twin technology to ensure that network or service performance meets the intended goals during intent execution. If the intended goals are not met during execution, the intent executor promptly requests verification of the network optimization strategy or solution from the intent executor twin, directly identifying a solution that meets the intended goals.
  • the intent manager determines one or more managed networks and intent executors corresponding to the intent, it also includes: the intent manager creates an intent object instance of the intent, so that the intent executor executes the intent according to the intent object instance.
  • the intent executor twin after creating the intent executor twin and the managed network twin, it also includes: the intent executor twin creates an intent object twin instance of the intent; during the process of the intent executor executing the intent, if it detects that the expected target is not met, the intent executor sends a simulation request and a network update strategy to the intent executor twin; the intent executor twin verifies and optimizes the network update strategy until the expected target is not met during the intent simulation, obtains the final network optimization strategy, and sends the network optimization strategy to the intent executor; the intent manager executor updates the intent object instance and its network management task according to the network optimization strategy, and sends the updated intent object instance information to the intent manager; the intent manager updates the intent according to the updated intent object instance information, generates an intent report, and sends the intent report to the management service consumer.
  • FIG4 is a simulation process diagram of a digital twin technology based on the entire life cycle of an intention to meet the desired target requirements. As shown in FIG4 , the process includes:
  • the management service consumer sends the intent, the intent's entire life cycle to meet the expected target requirements and authorization information to the intent manager.
  • a management service consumer When a management service consumer sends an intent to an intent generator, it authorizes the intent generator to update or modify the intent and requests the intent producer to ensure that the intent is always in a state that meets the expected goals during the execution of the lifecycle.
  • S402 The intent manager collaborates with the intent executor to create an instance of the intent object and execute the intent in the managed network.
  • the intent manager requests the digital twin manager to create the intent executor twin, the managed network twin and the intent twin object instance.
  • the intent executor requests the intent executor twin to simulate the intent object twin instance, and can input multiple network optimization strategies or solutions.
  • the intent executor twin can also formulate multiple network optimization strategies and solutions for verification.
  • the intent executor twin sends the network optimization strategy to the intent executor.
  • the intent executor updates the intent object instance and its network management task according to the network optimization strategy.
  • the intent executor sends the updated intent object instance information to the intent manager.
  • the intent manager updates the intent according to the updated intent object instance information, generates an intent report, and sends the intent report to the management service consumer.
  • the way to update an intent can be to change the intended goal or intent context constraints of the intent.
  • a management service consumer When a management service consumer defines an intent's expected goal, it needs to predict whether the intent can be achieved when executed. This is to determine whether the intent's expected goal and the intent's contextual constraints are reasonable.
  • the management service consumer sends the intent to the management service producer, requesting in the message that the intent producer perform a full lifecycle prediction for the intent and provide a solution if the intent's expected goal is not met.
  • the intent executor twin sends information to the intent manager indicating that the intent object twin instance has been successfully created.
  • the intent manager sends the simulation request to the digital twin manager, which forwards the simulation request to the intent executor twin.
  • the intent manager sends the simulation request directly to the intent executor twin.
  • the intention executor twin configures the managed network twin according to the network parameters in the intention object twin instance, and executes the network management task corresponding to the intention to meet the expected target prediction requirements; in the process of executing the network management task, when the intention does not meet the expected target, the intention executor twin determines the cause and solution.
  • the intent executor twin sends the prediction result, the reasons when the intent does not meet the expectations, and the solution to the intent manager.
  • the intent executor twin sends the intent prediction results of the intent object twin instance, the reasons for not meeting the expected goals of the intent, and the solutions to the intent manager in the form of a prediction report.
  • S509 Generate an intention report and send it to the management service consumer.
  • the intent manager receives multiple intents from different management service consumers. To prevent conflicts caused by the simultaneous execution of multiple intents on the same managed network, the intent manager decides to create a digital twin. It uses digital twin technology to perform intent simulation operations, determine whether multiple intents will conflict, analyze the conflict prediction results, and feed back the intent conflict prediction analysis and possible solutions to each intent consumer, so that the intent consumer can decide whether to update the intent to avoid potential intent conflicts in actual network operation.
  • the simulation prediction requirement is multiple intention conflict detection requirements
  • the intention manager sends multiple intentions to the intention executor twin, requesting the creation of an intention object twin instance
  • the intention executor twin creates multiple intention object twin instances, and sends information on the successful creation of the intention object twin instance to the intention manager
  • the intention manager sends multiple intention conflict detection simulation requests to the digital twin manager or the intention executor twin
  • the intention executor twin configures the managed network twin according to the network parameters in the multiple intention object twin instances, and simultaneously executes the network management of multiple intention object twin instances.
  • adjusting the network management tasks includes adjusting at least one of the network configuration, network constraints and the expected target value of the intent; the intent executor twin sends the intent execution result, conflict cause and solution to the intent manager, and the intent manager creates intent conflict prediction reports corresponding to multiple intents according to the intent execution result, conflict cause and solution, and sends the intent conflict prediction report to each management service consumer.
  • FIG6 is a process diagram of performing multiple intention conflict detection based on digital twin technology in this embodiment. As shown in FIG6 , the process includes:
  • S601 Multiple management service consumers send intents to an intent manager.
  • Different management service consumers have business requirements and network performance requirements for commonly related managed networks, such as RAN, CN, network slices, base stations, etc.
  • Multiple management service consumers send multiple intents to the intent manager to request that the network requirements of the intent be met.
  • the intent manager decides on multi-intent conflict detection and requests the digital twin manager to create the intent executor twin and the managed network twin.
  • the intent manager receives multiple intents from multiple managed service consumers.
  • the intent manager decides to create a digital twin and uses this technology to simulate the intents to determine whether there are conflicts.
  • the intent manager sends multiple intents to the intent executor twin, requesting the creation of intent object twin instances of multiple intents.
  • the intent executor twin sends information on the successful creation of multiple intent object twin instances to the intent manager.
  • the intent manager needs to promptly respond, eliminate potential causes, and find solutions to ensure the high-priority intent's expected goal is achieved when executed on the network.
  • the intent manager decides to create a digital twin. Using digital twin technology, it analyzes the causes, identifies and verifies feasible solutions for high-priority intent failures, and promptly updates the network management tasks associated with the intent object instance to ensure that high-priority intents meet their expected goals throughout the entire time cycle.
  • the intention manager sends a high-priority intention to the intention executor twin, requesting the creation of an intention object twin instance; the intention executor twin creates an intention object twin instance of the high-priority intention, and sends a message to the intention manager that the intention object twin instance has been successfully created; the intention manager sends a simulation request to the digital twin manager or the intention executor twin; wherein the simulation request carries the requirement that the high-priority intention meets the expected goal; the intention executor twin configures the managed network twin according to the network parameters in the intention object twin instance, and executes the high-priority intention to meet the requirement.
  • the network management task corresponding to the demand of the expected goal; in the process of executing the network management task, when the high-priority intention does not meet the expected goal, the intention executor twin determines the cause and at least one solution; the intention executor twin sends the cause and at least one solution to the intention manager, the intention manager analyzes the cause and at least one solution, and updates the high-priority intention object or downgrades other low-priority intentions based on the analysis results; the intention manager requests the intention executor to update the intention object instance and the corresponding network management task; the intention executor and the managed network execute the updated network management task, and interactively verify whether the high-priority intention meets the expected goal, and feedback the intention execution result report to the intention manager.
  • FIG7 is a process diagram of ensuring that a high-priority intent satisfies an intended goal in an embodiment of the present application. As shown in FIG7 , the method includes:
  • the intent manager receives an intent execution result report from the intent executor indicating that a high-priority intent does not meet an expected goal.
  • the intent executor monitors the network performance status and generates an intent execution result report to feed back to the intent manager.
  • the intent execution result report carries information that the intent does not meet the expected target.
  • the intent manager requests the digital twin manager to create the intent executor twin and the managed network twin.
  • the intent manager analyzes the state that does not meet the expected target of the intent during the execution of the network management task of the high-priority intent object instance.
  • the network performance or business performance of a period of time cannot meet the expected target of the intent. It is necessary to promptly discover the potential cause and find a solution to ensure that the high-priority intent is executed on the network side.
  • the intent manager identifies the managed network described in the high-priority intent and the intent executor required for the intent, and interacts with the digital twin manager to request the creation of a twin.
  • the specific process of creating the intent executor twin and the managed network twin is described in S210-S240 and will not be repeated here.
  • the intent manager sends a high-priority intent to the intent executor twin, requesting the creation of an intent object twin instance corresponding to the high-priority intent.
  • the intent executor twin sends information to the intent manager indicating that the intent object twin instance has been successfully created.
  • the intent manager sends a simulation request to the digital twin manager or the intent executor twin.
  • the intent manager sends the simulation request to the digital twin manager, which forwards the simulation request to the intent executor twin.
  • the intent manager sends the simulation request directly to the intent executor twin.
  • the intention executor twin configures the managed network twin according to the network parameters in the intention object twin instance, and executes the network management task corresponding to the high-priority intention to meet the expected target prediction requirements; in the process of executing the network management task, when the high-priority intention does not meet the expected target, the intention executor twin determines the cause and feasible solutions.
  • the intent executor twin sends the cause and at least one solution to the intent manager.
  • the intent executor twin After the solution to the intent not meeting the expected goal is verified, the intent executor twin sends the reasons and possible solutions for the intent not meeting the expected goal of the high-priority intent object twin instance to the intent manager.
  • the intent manager analyzes the cause and at least one solution, and updates the high-priority intent or downgrades other low-priority intents based on the analysis results.
  • the intent manager executes solutions to the failure of the high-priority intent to meet the expected goal, such as updating the high-priority intent and adjusting the expected goal parameters or constraints of the intent; updating the network management tasks of the low-priority intent and adjusting the expected goal parameters or constraints of the low-priority intent, or downgrading or suspending the low-priority intent, so as to ensure that the expected goal of the high-priority intent is met.
  • the intent manager requests the intent executor to update the intent object instance and the corresponding network management Task.
  • the Intent Manager requests the Intent Executor to update a high-priority Intent object instance, update a low-priority object instance, or downgrade or suspend a low-priority Intent.
  • the Intent Executor updates the network management task for a high-priority Intent or a low-priority Intent. For example, the Intent Executor downgrades the desired target of a low-priority Intent or suspends the task of a low-priority Intent to avoid affecting the high-priority Intent.
  • the intent executor and the managed network execute the updated network management task and interactively verify whether the high-priority intent meets the expected goal.
  • the intent manager reports the intent's execution results and detects that network or service performance indicators do not meet the intent's expected targets within a certain period of time.
  • the intent manager needs to provide feedback to the intent consumer regarding the non-compliance and possible solutions.
  • the intent consumer decides whether to continue executing, update, suspend, or delete the intent.
  • the intent manager decides to create a digital twin, and uses digital twin technology to find and verify possible solutions when the intent does not meet the expected goals, and then feeds back to the intent consumer.
  • the intention manager sends the intention to the intention executor twin, requesting the creation of the intention object twin instance; the intention executor twin creates the intention object twin instance of the intention, and sends information on the successful creation of the intention object twin instance to the intention manager; the intention manager sends a simulation request for the solution to the intention not meeting the expected goal to the digital twin manager or the intention executor twin; the intention executor twin configures the managed network twin according to the network parameters in the intention object twin instance, and executes the network management task of the intention; in the process of executing the network management task, when the intention does not meet the expected goal, the intention executor twin discovers the cause and determines and verifies possible solutions; the intention executor twin sends the intention execution result, the cause when the expected goal is not met, and the solution to the intention manager, and the intention manager sends the intention execution result, the cause when the expected goal is not met, and
  • FIG8 is a process diagram of a method for resolving a problem in which a period of the entire life cycle of an intention does not meet the intended goal. As shown in FIG8 , the method includes:
  • the intent manager receives an intent sent by the intent executor and the intent does not meet the expected target of the intent within a time period.
  • the management service consumer sends the intent to the management service producer for execution.
  • the network management task of the graph object instance is performed, and the intent execution report is sent to the intent manager periodically during the execution process or according to the result change.
  • the intent manager requests the digital twin manager to create the intent executor twin and the managed network twin.
  • the intent manager determines that the intended objectives for a time period are not met, it decides to create a digital twin. Using digital twin technology, it executes the intent simulation to analyze the reasons for the non-compliance and possible solutions.
  • the intent manager identifies the managed network described in the intent and the intent executor required for the intent, and interacts with the digital twin manager to request twin creation. The detailed process for creating the intent executor twin and the managed network twin is described in S210-S240 and is not detailed here.
  • the intent manager sends an intent to the intent executor twin, requesting the creation of an intent object twin instance.
  • FIG10 is a flowchart of a digital twin-based intention processing method disclosed in this application. The method is executed by a digital twin manager and includes:
  • the creation request creates an intent executor twin and a managed network twin in the digital twin platform to simulate one or more intents; wherein the twin creation request carries the intent executor information and the managed network information.
  • Simulation prediction requirements include: optimization requirements for intention expected goals, satisfaction of intention expected goals throughout the entire life cycle, prediction requirements for intention satisfaction of expected goals, and at least one of multiple intention conflict detection requirements; failure to meet expected goals includes: high-priority intentions failing to meet expected goals, and failure to meet intention expected goals in a period of the entire life cycle of the intention.
  • the system further includes a first simulation request sending module, which is used to:
  • Execute one or more intentions send an intent to the intent executor twin to request the creation of an intent object twin instance; when it is detected that the intent does not meet the expected goal, send a simulation request and a network update strategy to the intent executor twin, so that the intent executor twin verifies and optimizes the network update strategy to obtain the final network optimization strategy; receive the final network optimization strategy sent by the intent executor twin, and update one or more intentions according to the network optimization strategy.
  • the method further includes: a third simulation request sending module, which is used to:
  • the method further includes: a fourth simulation request sending module, which is configured to:
  • the twin body performs network management tasks for multiple intent conflict detection requirements to determine the cause and solution of the conflict; receives the conflict cause and solution sent by the intent executor twin body, and generates conflict prediction reports corresponding to multiple intents based on the conflict cause and solution; sends the conflict prediction report to each management service consumer.
  • the method further includes: a sixth simulation request sending module, which is used to:
  • FIG13 is a schematic diagram of the structure of a digital twin-based intention processing device provided by an embodiment of the present disclosure.
  • the device is provided in a digital twin manager and includes:
  • the twin creation request receiving module 1301 is used to receive the twin creation request sent by the management service producer; wherein the twin creation request carries the intention executor information and the managed network information; the twin creation module 1302 is used to create the intention executor twin and the managed network twin in the digital twin platform based on the twin creation request to simulate one or more intentions.
  • FIG14 is a schematic diagram of the structure of an intention processing device based on digital twins provided in an embodiment of the present application.
  • the device is provided in the intention executor twin and the managed network twin pre-created and deployed on the digital twin platform, including:
  • the intention object twin instance creation request receiving module 1401 is used to receive one or more intentions and intention object twin instance creation requests sent by the management service producer; the intention object twin instance creation module 1402 is used to create one or more intention object twin instances based on one or more intentions and intention object twin instance creation requests; the intention simulation module 1403 is used to receive the simulation request sent by the management service producer, and simulate one or more intentions according to the simulation request; wherein the simulation request includes at least one of the following: intention expected target value optimization request, intention realization full life cycle guarantee request, intention satisfaction request
  • the expected target prediction request is met, multiple intent conflict detection requests are met, high priority intent does not meet the expected target request, and the intent does not meet the expected target in a period of time during the entire life cycle of the intent.
  • the intention simulation module 1403 is further configured to:
  • the intention simulation module 1403 is further used to:
  • the intention simulation module 1403 is further configured to:
  • the intention simulation module 1403 is further configured to:
  • the intent simulation module 1403 is further configured to:
  • FIG15 is a schematic diagram of the structure of a computer device provided by an embodiment of the present application.
  • the device provided by the present application includes: a processor 510 and a memory 520.
  • the number of processors 510 in the device may be one or more, with one processor 510 being used as an example in FIG15 .
  • the number of memories 520 in the device may be one or more, with one memory 520 being used as an example in FIG15 .
  • the processor 510 and memory 520 of the device may be connected via a bus or other means, with a bus connection being used as an example in FIG15 .
  • the device is a computer device.
  • the memory 520 can be configured to store software programs, computer executable programs, and modules, such as program instructions/modules corresponding to the device of any embodiment of the present application (for example, the encoding module and the first sending module in the data transmission device).
  • the memory 520 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the device, etc.
  • the memory 520 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device.
  • the device provided above can be configured to execute the digital twin-based intention processing method provided in any of the above embodiments, and have corresponding functions and effects.
  • An embodiment of the present application also provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to execute a digital twin-based intention processing method, the method comprising: the current node receives pilot information and/or scheduling information of an interfering node; and performs digital twin-based intention processing according to the pilot information and/or scheduling information.
  • user equipment encompasses any suitable type of wireless user equipment, such as a mobile phone, a portable data processing device, a portable web browser or a car-mounted mobile station.
  • various embodiments of the present application may be implemented in hardware or dedicated circuits, software, logic, or any combination thereof.
  • some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software that can be executed by a controller, microprocessor, or other computing device, although the present application is not limited thereto.
  • Machine program instructions may be assembly instructions, Instruction Set Architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages.
  • ISA Instruction Set Architecture
  • the data processor may be of any type suitable for the local technical environment, such as but not limited to a general-purpose computer, a special-purpose computer, a microprocessor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), and a processor based on a multi-core processor architecture.
  • a general-purpose computer such as but not limited to a general-purpose computer, a special-purpose computer, a microprocessor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), and a processor based on a multi-core processor architecture.
  • DSP digital signal processor
  • ASIC application-specific integrated circuit
  • FPGA field-programmable gate array
  • Embodiments of the present application may be implemented by executing computer program instructions by a data processor of a mobile device, for example, in a processor entity, or by hardware, or by a combination of software and hardware.
  • the computer program instructions may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages.
  • ISA instruction set architecture

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Abstract

本申请公开了基于数字孪生的意图处理方法、设备及存储介质。接收管理服务消费者发送的携带有仿真预测需求的一个或多个意图,或获取包含不满足期望目标的意图执行结果报告;根据所述仿真预测需求和/或所述意图执行结果报告确定对意图进行数字孪生仿真验证操作。根据意图描述信息确定一个或多个所述意图对应的被管网络及意图执行器,并请求数字孪生管理器创建意图执行器孪生体及被管网络孪生体,以对所述一个或多个意图进行仿真。

Description

基于数字孪生的意图处理方法、设备及存储介质 技术领域
本申请涉及通信技术领域,例如涉及基于数字孪生的意图处理方法、设备及存储介质。
背景技术
通信网络的意图管理是指对通信网络或通信业务的期望及目标进行管理和控制的过程。通信服务提供商通过意图的方式描述对网络性能及特定通信业务的期望及目标。通过意图消费者及意图生产者之间的协作来实现意图,从而网络性能及通信业务能够满足用户需求,同时实现业务效益的最大化,有助于提高业务的效率和可靠性,提升用户满意度和服务质量。
通过意图管理来确保网络性能及通信业务满足业务需求,在实际运行中存在意图描述中期望的网络性能与通信业务需求无法满足意图期望及目标、多个意图同时运行潜在冲突引起的网络故障、意图制定时无法最优化描述网络期望及目标、高优先级意图的期望目标无法实现等种种问题。
发明内容
本申请实施例公开了基于数字孪生的意图处理方法、设备及存储介质,通过数字孪生技术对意图对应的网络管理任务进行仿真执行,以提高意图处理的准确性及可靠性。
本申请实施例提供了一种基于数字孪生的意图处理方法,所述方法由管理服务生产者执行,包括:
接收管理服务消费者发送的携带有仿真预测需求的一个或多个意图,或获取包含不满足期望目标的意图执行结果报告;根据所述仿真预测需求和/或所述意图执行结果报告确定对意图进行数字孪生仿真验证操作;根据意图描述信息确定一个或多个所述意图对应的被管网络及意图执行器,并请求数字孪生管理器创建意图执行器孪生体及被管网络孪生体,以对所述一个或多个意图进行仿真。
为了实现上述目的,本申请实施例公开了一种基于数字孪生的意图处理方法,所述方法由数字孪生管理器执行,包括:
接收管理服务生产者发送的孪生体创建请求;其中,所述孪生体创建请求 携带有意图执行器信息及被管网络信息;基于所述孪生体创建请求在数字孪生平台中创建意图执行器孪生体及被管网络孪生体,以对一个或多个意图进行仿真。
本申请实施例公开了一种基于数字孪生的意图处理方法,所述方法由预先创建并部署在数字孪生平台的意图执行器孪生体及被管网络孪生体执行,包括:
接收管理服务生产者发送的一个或多个意图及意图对象孪生实例创建请求;基于所述一个或多个意图及意图对象孪生实例创建请求创建一个或多个意图对象孪生实例;接收管理服务生产者发送的仿真请求,并根据所述仿真请求对所述一个或多个意图进行仿真;其中,所述仿真请求包括如下至少一项:意图期望目标值寻优请求、意图实现全生命周期保障请求、意图满足期望目标预测请求、多个意图冲突检测请求、高优先级意图不满足期望目标请求及意图全生命周期过程中一个时段不满足意图期望目标。
本申请实施例公开了一种计算机设备,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,其中,所述处理器执行所述程序时实现如本申请实施例所述的基于数字孪生的意图处理方法。
本申请实施例公开了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如本申请实施例所述的基于数字孪生的意图处理方法。
本申请实施例公开了一种基于数字孪生的意图处理系统、方法、设备及存储介质。接收管理服务消费者发送的携带有仿真预测需求的一个或多个意图,或获取包含不满足期望目标的意图执行结果报告;根据仿真预测需求和/或意图执行结果报告确定对意图进行数字孪生仿真验证操作。根据意图描述信息确定一个或多个意图对应的被管网络及意图执行器,并请求数字孪生管理器创建意图执行器孪生体及被管网络孪生体,以对一个或多个意图进行仿真。本公开实施例提供的基于数字孪生的意图处理系统,基于通过数字孪生技术对意图对应的网络管理任务进行仿真执行,以提高意图处理的准确性及可靠性。
附图说明
图1是本申请实施例提供的一种基于数字孪生的意图处理系统的结构示意图;
图2是本申请实施例提供的一种创建数字孪生体的流程图;
图3是本申请实施例提供的一种基于数字孪生技术进行意图期望目标寻优的过程图;
图4是本申请实施例提供的一种基于数字孪生技术进行意图全生命周期满足期望目标需求的仿真过程图;
图5是本申请实施例提供的一种基于数字孪生技术进行意图满足期望目标预测的过程图;
图6是本申请实施例提供的一种基于数字孪生技术进行多个意图冲突检测的过程图;
图7是本申请实施例提供的一种保障高优先意图满足意图期望目标的过程图;
图8是本申请实施例提供的一种解决意图全生命周期过程中一个时段不满足意图期望目标的过程图;
图9是本申请实施例提供的一种基于数字孪生的意图处理方法的流程图;
图10是本申请实施例提供的一种基于数字孪生的意图处理方法的流程图;
图11是本申请实施例提供的一种基于数字孪生的意图处理方法的流程图;
图12是本申请实施例提供的一种基于数字孪生的意图处理装置的结构示意图;
图13是本申请实施例提供的一种基于数字孪生的意图处理装置的结构示意图;
图14是本申请实施例提供的一种基于数字孪生的意图处理装置的结构示意图;
图15是本申请实施例提供的一种计算机设备的结构示意图。
具体实施方式
下文中将结合附图对本申请的实施例进行详细说明。在不冲突的情况下,本申请中的实施例及实施例中的特征可以相互任意组合。
在后续的描述中,使用用于表示元件的诸如“模块”、“部件”或“单元”的后缀仅为了有利于本申请的说明,其本身没有特有的意义。因此,“模块”、“部件”或“单元”可以混合地使用。
管理服务消费者为意图所有者,管理服务生产者为意图处理者,管理服务生产者包括意图管理器和意图执行器,意图管理器用于意图解析与翻译、意图寻优、意图执行结果监控等操作,意图执行器用于意图对象实例生命周期管理,意图对象实例的执行操作管理等。意图生产者具有以下能力:(1)验证意图;(2)将收到的意图转换为可执行的操作,包括执行业务或网络管理任务,识别、 制定和激活服务或网络管理策略等;(3)评估有关意图实现(例如意图最初是否得到满足)和意图保证(例如意图持续得到满足)的结果/信息。
意图消费者制定的意图可以包括消费者的通信业务或网络资源需求(Requirement)、意图期望目标中描述网络性能目标及意图上下文约束条件等。意图的翻译则是指确定意图策略的过程,举例来说,意图描述的业务需求信息可以包括“在区域A和数据中心(区域B),要求支持最多200用户,端到端时延小于5ms,下行时延小于3ms”。
通过意图管理来确保网络性能及通信业务满足业务需求,在实际运行中存在意图描述中期望的网络性能与通信业务需求无法满足意图期望目标、多个意图同时运行潜在冲突引起的网络故障、意图制定时无法最优化描述网络期望及目标、高优先级意图的意图期望目标无法实现等种种问题。
为解决描述及执行过程中遇到的意图执行结果不满足期望、不同意图同时执行时的潜在冲突、意图性能参数寻优、意图故障预测、意图满足期望保障等问题及需求,需要为意图对象实例创建高保真的数字孪生仿真环境,通过数字孪生技术进行意图对象实例的仿真验证、测试及评估,找出最佳的网络性能参数设置及意图执行时潜在问题的解决方案。
图1是本申请实施例提供的一种基于数字孪生的意图处理系统的结构示意图,如图1所示,该系统包括:管理服务消费者110、管理服务生产者120、被管网络130及数字孪生管理器140。其中,管理服务生产者120包括意图管理器121及意图执行器122。
管理服务消费者110包括一个或多个,用于向管理服务生产者120中的意图管理器121发送意图。意图管理器121用于当一个或多个意图携带有仿真预测需求或者接收到意图执行器返回的不满足期望目标信息时,向数字孪生管理器140发送孪生体创建请求。意图执行器122用于执行意图管理器发送的意图。数字孪生管理器140用于根据孪生体创建请求创建意图执行器孪生体和被管网络孪生体,以对一个或多个意图进行仿真。其中,被管网络可以是一个网络切片、一个基站、一个网元、无线接入网(RAN)或者核心网(CN)等。
当管理服务消费者110将意图下发给意图管理器121时,意图管理器121判断该意图有仿真预测需求,意图管理器121根据单个意图描述的被管网络或将多个意图描述的被管网络合并,确定被管网络。并确定执行该意图所需的意图执行器122,其中包括意图生命周期管理功能、意图执行功能等。意图管理器121请求数字孪生管理器140对意图执行器及被管网络进行建模,创建意图执行器孪生体及被管网络孪生体。意图管理器121可与意图执行器孪生体进行交互,下发意图以对该意图进行仿真。通过数字孪生仿真及评估、验证技术,预测该 意图会出现的故障并找出原因及解决方法,解决意图对象实例在操作过程中各种潜在问题。
可选的,在意图执行器122执行意图对应的网络管理任务的过程中,若不满足意图期满目标,则意图执行器122请求意图执行器孪生体对意图进行仿真,以确定原因及解决方案。
本实施例中,意图执行器122也可以与意图执行器孪生体直接进行交互,当意图执行器122在执行意图的过程中不满足意图期望目标时,意图执行器122直接请求意图执行器孪生体进行该意图对象孪生实例的仿真验证,找出原因及验证可能的解决方案。意图执行器122根据意图执行器孪生体给出的解决方案,更新该意图的意图对象实例及网络管理任务,确保该意图执行过程中意图期望目标一直被满足。
本实施例中,意图管理器121接收到来自管理服务消费者110的携带仿真预测需求的意图,需要对该意图进行数字孪生仿真预测操作;或来自意图执行器122的意图执行结果报告,意图管理器121分析该意图执行结果报告,发现意图相关需求没有在网络中被满足,需要通过数字孪生仿真技术查找原因,验证解决方案。意图管理器121决策创建数字孪生体,通过数字孪生技术来执行意图仿真操作,找出该意图执行时可能存在的问题并验证解决方案,从而使该意图在实施时能意图消费者的需求
具体的,图2是本申请实施例提供的一种创建数字孪生体的的信令图,如图2所示,该包括S201-S206。
S201,管理服务生产者中的意图管理器接收管理服务消费者发送的携带有仿真预测需求的一个或多个意图和/或意图执行器发送的包含不满足期望目标的意图执行结果报告。
仿真预测需求包括:意图期望目标寻优需求、意图全生命周期满足期望目标需求、意图满足期望目标预测需求及多个意图冲突检测需求中的至少一种。不满足期望目标包括:高优先级意图不满足期望目标、意图全生命周期过程中一个时段不满足意图期望目标。
本实施例中,意图生产者中的意图管理器接收到来自管理服务消费者的意图,若该意图中携带有意图期望目标寻优需求、意图全生命周期满足期望目标需求、意图满足期望目标预测需求及多个意图冲突检测需求等信息,则意图管理器决策发起该意图的数字孪生仿真操作。或者,意图执行器在执行该意图相关的网络管理任务过程中,会根据网络实时网络性能数据反馈意图执行的结果。意图生产者中的意图管理器接收到来自意图执行器的意图执行过程结果报告,分析该意图在执行过程中网络性能参数不满足意图期望目标,意图管理器决策 采用数字孪生仿真技术寻求原因及可能的解决方案。
S202,意图管理器确定一个或多个意图对应的被管网络及意图执行器.
S203,并向数字孪生管理器发送孪生体创建请求。
孪生体创建请求携带有意图执行器信息及被管网络信息。意图执行器信息可以是意图执行器的唯一标识,被管网络信息可以是被管网络的唯一标识。
意图管理器分析该意图所需的意图执行器,以及该意图中描述的被管网络。对于多个意图,则需要分析多个意图所共同需要的意图执行器,以及多个意图中描述的被管网络,并合并这些被管网络。意图管理器向数字孪生管理器请求创建意图对应的意图执行器孪生体及被管网络孪生体,携带所需建模的意图执行器信息及被管网络信息。
S204,数字孪生管理器从意图执行器信息对应的意图执行器及被管网络信息对应的被管网络读取数据。
数据包括功能数据、实体数据及运行数据。运行数据包括历史运行数据及当前运行数据。具体的,数字孪生管理器从物理的意图执行器及被管网络实时采集数据,以进行意图执行器及被管网络建模。
S205,数字孪生管理器根据功能数据及实体数据创建意图执行器孪生模型及被管网络孪生模型,将运行数据输入意图执行器孪生模型及被管网络孪生模型,创建意图执行器孪生体及被管网络孪生体,使得意图执行器孪生体和被管网络孪生体对一个或多个意图进行仿真。
数字孪生管理器创建意图执行器孪生模型及被管网络孪生模型,并输入运行数据创建意图执行器孪生体及被管网络孪生体。数字孪生管理器通知意图管理器,通知意图执行器孪生体及被管网络孪生体已创建完成,同时携带孪生体信息。
S206,向意图管理器发送孪生体信息。
在一种应用场景下,管理服务消费者在制定意图期望目标时,无法判断被管网络在意图描述的特定时间段及特定地域进行网络任务操作时,被管网络所能达到的最优性能。意图消费者希望意图生产者与被管网络进行判断,并反馈网络最佳性能参数。意图消费者对相关意图期望目标进行缺省或给出一个区间,请求意图生产者给出最优参数。为找出该意图期望目标的最优参数值,意图管理器决策创建数字孪生体,通过数字孪生技术来执行意图期望目标的寻优操作,生成意图期望目标规定的网络性能参数优选组合,并反馈给意图消费者。
若仿真预测需求为意图期望目标寻优需求,则在创建意图执行器孪生体及被管网络孪生体之后,还包括:意图管理器向意图执行器孪生体发送意图,请 求创建意图对象孪生实例;意图执行器孪生体创建意图的意图对象孪生实例,并向意图管理器发送意图对象孪生实例创建成功的信息;意图管理器向数字孪生管理器或者意图执行器孪生体发送仿真请求;其中,仿真请求携带有意图期望目标寻优需求;意图执行器孪生体根据意图对象孪生实例中的网络参数配置被管网络孪生体,执行意图期望目标寻优需求对应的网络管理任务;在执行网络管理任务的过程中,被管网络孪生体执行不同组合的网络性能参数,以确定出至少一个最优网络性能参数;意图执行器孪生体将至少一个最优网络性能参数发送给意图管理器,意图管理器将至少一个最优网络性能参数发送至管理服务消费者,以供管理服务消费者选择。
本实施例中,图3是本实施例中为基于数字孪生技术进行意图期望目标寻优的过程图,如图3所示,该过程包括:
S301,管理服务消费者向意图管理器发送意图及意图期望目标寻优需求。
管理服务消费者在制定意图期望目标时,无法确定意图期望中各个期望目标的网络性能参数,不能制定出合理的期望目标。意图消费者将该意图下发给意图管理者,并在消息中请求意图生产者进行意图期望目标的寻优。
S302,意图管理器请求数字孪生管理器创建意图执行器孪生体及被管网络孪生体。
创建意图执行器孪生体及被管网络孪生体的具体过程参见S210-S240,此处不再赘述。
S303,意图管理器向意图执行器孪生体发送意图,请求创建意图对象孪生实例。
S304,意图执行器孪生体创建意图的意图对象孪生实例。
S305,意图执行器孪生体向意图管理器发送意图对象孪生实例创建成功的信息。
S306,意图管理器向数字孪生管理器或者意图执行器孪生体发送仿真请求。
本实施例中,意图管理器将仿真请求发送至数字孪生管理器,由数字孪生管理器将仿真请求转发至意图执行器孪生体。或者,意图管理器直接向意图执行器孪生体发送仿真请求。
S307,意图执行器孪生体根据意图对象孪生实例中的网络参数配置被管网络孪生体,并执行意图期望目标寻优需求对应的网络管理任务。
本实施例中,在执行的意图期望目标寻优需求对应的网络管理任务过程中,被管网络孪生体尝试执行意图期望目标中描述的网络性能参数的不同参数配置 组合,并寻找出所达到的最近性能参数。如组合一:特定区域用户接入数2000人,带宽100M,业务时延10ms。组合二:特定区域用户接入数5000人,带宽50M,业务时延15ms;等等组合,寻求最佳参数配置。
S308,意图执行器孪生体将至少一个最优网络性能参数发送给意图管理器。
S309,意图管理器根据至少一个最优网络性能参数生成意图报告,并将意图报告发送至管理服务消费者,供管理服务消费者选择。
在一种应用场景下,管理服务消费者下发意图给意图消费者进行执行时,该意图授权给意图生产者可进行更新或修改,需要意图生产者保障该意图在全生命周期执行过程中一直处于满足意图期望目标的状态。为保障该意图执行达到意图预期目标,需要在遇到问题时继续通过仿真验证的方式寻找故障原因及验证解决方案。意图管理器决策创建数字孪生体,通过数字孪生技术来保障该意图在执行时网络性能或业务性能能达到意图期望目标。当运行意图期望目标出现不达标的情况,意图执行器需要及时请求意图执行器孪生体验证网络优化策略或解决方案,直接找到意图期望目标达标的解决方案。意图孪生体将验证后的解决方案或网络优化策略提供给意图执行器,意图执行器更新该意图相关的网络管理任务,如意图上下文中的网络约束或意图期望目标中的网络性能参数,保障该意图运行时网络性能达到意图期望目标,意图处于满足意图期望目标的状态。
若仿真预测需求为意图全生命周期满足期望目标需求,意图中还携带有授权更新或修改的信息;则在意图管理器确定一个或多个意图对应的被管网络及意图执行器之后,还包括:意图管理器创建意图的意图对象实例,使得意图执行器根据意图对象实例执行意图。相应的,在创建意图执行器孪生体及被管网络孪生体之后,还包括:意图执行器孪生体创建意图的意图对象孪生实例;在意图执行器执行意图的过程中,若检测到不满足期望目标,则意图执行器向意图执行器孪生体发送仿真请求及网络更新策略;意图执行器孪生体对网络更新策略进行验证及优化,直到意图仿真时未出现不满足期望目标,获得最终的网络优化策略,并将网络优化策略发送至意图执行器;意图管执行器根据网络优化策略更新意图对象实例及其网络管理任务,并将更新后的意图对象实例信息发送至意图管理器;意图管理器根据更新后的意图对象实例信息更新意图,并生成意图报告,将意图报告发送至管理服务消费者。
本实施例中,图4是本实施例中的一种基于数字孪生技术进行意图全生命周期满足期望目标需求的仿真过程图,如图4所示,该过程包括:
S401,管理服务消费者向意图管理器发送意图、意图全生命周期满足期望目标需求及授权信息。
管理服务消费者向意图生成者发送意图时,授权意图生成者可进行更新或修改意图,并请求意图生产者保障该意图在生命周期执行过程中一直处于满足意图期望目标的状态。
S402,意图管理器与意图执行器进行协作,创建该意图对象实例,并在被管网络中执行该意图。
S403,意图管理器请求数字孪生管理器创建意图执行器孪生体、被管网络孪生体及意图孪生对象实例。
S404,意图执行器在意图执行过程中,监测不满足意图期望目标时,查询意图孪生对象实例信息及对应的意图执行器孪生体信息。
S405,意图执行器向意图执行器孪生体发送仿真请求及网络更新策略。
本实施例中,意图执行器向意图执行器孪生体请求对该意图对象孪生实例进行仿真操作,可输入多种网络优化策略或解决方案。意图执行器孪生体也可以制定多种网络优化策略及方案进行验证。
S406,意图执行器孪生体对网络更新策略进行验证及优化,直到意图仿真时未出现不满足期望目标,获得最终的网络优化策略。
S407,意图执行器孪生体将网络优化策略发送至意图执行器。
S408,意图执行器根据网络优化策略更新意图对象实例及其网络管理任务。
S409,意图执行器将更新后的意图对象实例信息发送至意图管理器。
S410,意图管理器根据更新后的意图对象实例信息更新意图,并生成意图报告,并将意图报告发送至管理服务消费者。
更新意图的方式可以是新该意图的期望目标或意图上下文约束。
在一种应用场景下,管理服务消费者向管理服务生成者下发意图时,意图中携带意图满足期望目标预测需求,需要意图生产者能进行该意图的整个生命周期的意图期望目标是否满足意图期望目标的预测,以及在不满足意图期望目标的原因及解决方案。
意图管理器为实现对意图的全生命周期过程的意图期望目标是否达成的预测,意图管理器决策创建数字孪生体,通过意图执行器孪生体来执行意图对象孪生实例,并给出意图预测报告,其中描述意图在全生命周期时段的满足意图期望目标的状态,及不满足意图期望目标时的解决方案。
若仿真预测需求为意图满足期望目标预测需求,则在创建意图执行器孪生体及被管网络孪生体之后,还包括:意图管理器向意图执行器孪生体发送意图,请求创建意图对象孪生实例;意图执行器孪生体创建意图的意图对象孪生实例, 并向意图管理器发送意图对象孪生实例创建成功的信息;意图管理器向数字孪生管理器或者意图执行器孪生体发送仿真请求;其中,仿真请求携带有意图满足期望目标预测需求;意图执行器孪生体根据意图对象孪生实例中的网络参数配置被管网络孪生体,执行意图满足期望目标预测需求对应的网络管理任务;在执行网络管理任务的过程中,当意图不满期望目标时,意图执行器孪生体确定原因及解决方案;意图执行器孪生体将预测结果及意图不满足期望时的原因及解决方案发送至意图管理器,意图管理器将预测结果及意图不满足期望时的原因及解决方案发送至管理服务消费者。
本实施例中,图5是本实施例中为一种基于数字孪生技术进行意图满足期望目标预测的过程图,如图5所示,该过程包括:
S501,管理服务消费者向意图管理器发送意图及意图满足期望目标预测需求。
管理服务消费者在制定意图期望目标时,需要预测运行该意图时是否能达到预期,以判断意图期望目标、意图上下文约束条件是否合理。管理服务消费者将该意图下发给管理服务生产者,并在消息中请求意图生产者进行该意图的全生命周期预测,以及在不满足意图期望目标时的解决方案。
S502,意图管理器请求数字孪生管理器创建意图执行器孪生体及被管网络孪生体。
创建意图执行器孪生体及被管网络孪生体的具体过程参见S210-S240,此处不再赘述。
S503,意图管理器向意图执行器孪生体发送意图,请求创建意图对象孪生实例。
S504,意图执行器孪生体创建意图的意图对象孪生实例。
S505,意图执行器孪生体向意图管理器发送意图对象孪生实例创建成功的信息。
S506,意图管理器向数字孪生管理器或者意图执行器孪生体发送仿真请求。
本实施例中,意图管理器将仿真请求发送至数字孪生管理器,由数字孪生管理器将仿真请求转发至意图执行器孪生体。或者,意图管理器直接向意图执行器孪生体发送仿真请求。
S507,意图执行器孪生体根据意图对象孪生实例中的网络参数配置被管网络孪生体,并执行意图满足期望目标预测需求对应的网络管理任务;在执行所述网络管理任务的过程中,当意图不满期望目标时,意图执行器孪生体确定原因及解决方案。
S508,意图执行器孪生体将预测结果、意图不满足期望时的所述原因及解决方案发送至意图管理器。
意图执行器孪生体将该意图对象孪生实例的意图预测结果、不满足意图期望目标的原因及解决方案,通过预测报告的方式发送给意图管理器。
S509,生成意图报告,并发送至管理服务消费者。
在一种应用场景下,意图管理器接收到来自不同管理服务消费者的多个意图,为防止在同一被管网上多个意图同时执行会发生冲突,意图管理器决策创建数字孪生体,通过数字孪生技术来执行意图仿真操作,判断多个意图是否会有冲突,并对冲突预测结果进行分析,反馈给各个意图消费者的意图冲突预测分析及可能的解决方案,供意图消费者决策是否更新意图,以避免实际网络运行中潜在的意图冲突。
若仿真预测需求为多个意图冲突检测需求,则在创建意图执行器孪生体及被管网络孪生体之后,还包括:意图管理器向意图执行器孪生体发送多个意图,请求创建意图对象孪生实例;意图执行器孪生体创建多个意图的意图对象孪生实例,并向意图管理器发送意图对象孪生实例创建成功的信息;意图管理器向数字孪生管理器或者意图执行器孪生体发送多个意图冲突检测的仿真请求;意图执行器孪生体根据多个意图对象孪生实例中的网络参数配置被管网络孪生体,同时执行多个意图对象孪生实例的网络管理任务;在同时执行网络管理任务的过程中,若多个意图对象孪生实例间发生冲突,则调整多个意图对象孪生实例的网络管理任务,直到多个意图对象孪生实例间不再发生冲突,获得解决方案;其中,调整网络管理任务包括调整网络配置、网络约束及意图期望目标值中的至少一项;意图执行器孪生体将意图执行结果、冲突原因及解决方案发送至意图管理器,意图管理器根据意图执行结果、冲突原因及解决方案创建多个意图分别对应的意图冲突预测报告,并将意图冲突预测报告发送至各管理服务消费者。
本实施例中,图6是本实施例中为一种基于数字孪生技术进行多个意图冲突检测的过程图,如图6所示,该过程包括:
S601,多个管理服务消费者向意图管理器发送意图。
不同管理服务消费者针对共同相关的被管网络,如RAN、CN、网络切片、基站等有业务需求及网络性能需求,多个管理服务消费者将多个意图发送给意图管理器请求满足该意图对网络的需求。
S602,意图管理器决策多意图冲突检测,请求数字孪生管理器创建意图执行器孪生体及被管网络孪生体。
意图管理器接收到来自多个管理服务消费者的多个意图,为防止在同一被管网络上多个意图同时执行会发生冲突,如多个意图同时作用在一个RAN基站上,RAN基站资源有限,可能无法满足多个意图需要的终端接入数、带宽、上下行速率、业务时延等网络性能及业务性能需求。意图管理器决策创建数字孪生体,通过数字孪生技术来执行意图仿真操作,判断多个意图是否会有冲突。
意图管理器识别多个意图中的共同被管网络(多个意图被管网络叠加成一个大的被管网络)及所需的意图执行器(多个意图所需的意图执行器总和),并与数字孪生管理器进行交互,请求创建孪生体。
S603,意图管理器向意图执行器孪生体发送多个意图,请求创建多个意图的意图对象孪生实例。
S604,意图执行器孪生体创建多个意图对象孪生实例。
S605,意图执行器孪生体向意图管理器发送多个意图对象孪生实例创建成功的信息。
S606,意图管理器向数字孪生管理器或者意图执行器孪生体发送仿真请求。
本实施例中,意图管理器将仿真请求发送至数字孪生管理器,由数字孪生管理器将仿真请求转发至意图执行器孪生体。或者,意图管理器直接向意图执行器孪生体发送仿真请求。
S607,意图执行器孪生体根据多个意图对象孪生实例中的网络参数配置被管网络孪生体,同时执行多个意图对象孪生实例的网络管理任务;在同时执行网络管理任务的过程中,若多个意图对象孪生实例间发生冲突,则调整多个意图对象孪生实例的网络管理任务,直到多个意图对象孪生实例间不再发生冲突,获得解决方案。
S608,意图执行器孪生体将意图执行结果、冲突原因及解决方案发送至意图管理器。
S609,意图管理器根据意图执行结果、冲突原因及解决方案创建多个意图分别对应的意图冲突预测报告,并将意图冲突预测报告发送至各管理服务消费者。
意图管理器根据意图对象孪生实例运行冲突预测报告及可行的冲突解决方案,分析意图之间潜在的冲突,如网络配置冲突、约束条件冲突、网络期望目标冲突等,对于每个意图都创建意图冲突预测报告。对于有冲突的,给出意图优化可行性策略,如调整网络配置参数,可以避免冲突。意图管理器将意图冲突预测报告及可选的意图优化可行性策略,发送给意图消费者,由意图消费者决策该意图是否继续实施、撤回、挂起、修改、删除等操作。
在一种应用场景下,意图在执行过程中,针对高优先级意图的意图期望目标不满足的情况,意图管理器需要及时应对,消除潜在原因,找到解决方案,确保高优先级意图在网络侧执行时意图期望目标的实现。为寻找高优先级意图不满足意图期望目标的潜在原因及可能的解决方案,意图管理器决策创建数字孪生体,通过数字孪生技术来分析原因,寻找并验证高优先级意图不满足意图期望目标时可行的解决方案,并及时更新意图对象实例关联的网络管理任务,保障高优先级意图能够全时间周期满足意图期望目标。
若不满足期望目标为高优先级意图不满足期望目标,则在创建意图执行器孪生体及被管网络孪生体之后,还包括:意图管理器向意图执行器孪生体发送高优先级意图,请求创建意图对象孪生实例;意图执行器孪生体创建高优先级意图的意图对象孪生实例,并向意图管理器发送意图对象孪生实例创建成功的信息;意图管理器向数字孪生管理器或者意图执行器孪生体发送仿真请求;其中,仿真请求携带有高优先级意图满足期望目标的需求;意图执行器孪生体根据意图对象孪生实例中的网络参数配置被管网络孪生体,执行高优先级意图满足期望目标的需求对应的网络管理任务;在执行网络管理任务的过程中,当高优先级意图不满足期望目标时,意图执行器孪生体确定原因及至少一种解决方案;意图执行器孪生体将原因及至少一种解决方案发送至意图管理器,意图管理器分析原因及至少一种解决方案,并根据分析结果更新高优先级意图对象或者降级其他低优先级意图;意管理器向意图执行器请求更新意图对象实例及对应的网络管理任务;意图执行器与被管网络执行更新后的网络管理任务,并交互验证高优先级意图是否满足期望目标,并将意图执行结果报告反馈至意图管理器。
本实施例中,图7是本申请实施例中一种保障高优先意图满足意图期望目标的过程图,如图7所示,该方法包括:
S701,意图管理器接收意图执行器发送的高优先级意图不满足期望目标的意图执行结果报告。
在高优先级意图对象实例的网络管理任务执行过程中,意图执行器会监控网络性能状态,并生成意图执行结果报告反馈给意图管理器,该意图执行结果报告中携带意图不满足意图期望目标的信息。
S702,意图管理器请求数字孪生管理器创建意图执行器孪生体及被管网络孪生体。
意图管理器分析高优先级意图对象实例的网络管理任务执行过程中出现了不满足意图期望目标的状态,一个时段网络性能或业务性能不能满足意图期望目标,需要及时发现潜在原因,找到解决方案,确保高优先级意图在网络侧执 行时意图期望目标的实现。意图管理器识别该高优先级意图中描述的被管网络及该意图所需的意图执行器,并与数字孪生管理器进行交互,请求创建孪生体。其中,创建意图执行器孪生体及被管网络孪生体的具体过程参见S210-S240,此处不再赘述。
S703,意图管理器向意图执行器孪生体发送高优先级意图,请求创建高优先级意图对应的意图对象孪生实例。
S704,意图执行器孪生体创建高优先级意图的意图对象孪生实例。
S705,意图执行器孪生体向意图管理器发送意图对象孪生实例创建成功的信息。
S706,意图管理器向数字孪生管理器或者意图执行器孪生体发送仿真请求。
本实施例中,意图管理器将仿真请求发送至数字孪生管理器,由数字孪生管理器将仿真请求转发至意图执行器孪生体。或者,意图管理器直接向意图执行器孪生体发送仿真请求。
S707,意图执行器孪生体根据意图对象孪生实例中的网络参数配置被管网络孪生体,并执行高优先级意图满足期望目标预测需求对应的网络管理任务;在执行网络管理任务的过程中,当高优先级意图不满期望目标时,意图执行器孪生体确定原因及可行的解决方案。
潜在原因及解决方案包括:高优先级意图的意图期望目标或意图上下文的约束条件不合理,需要进行调整;高优先级意图与低优先级意图存在冲突,需要更新低优先级意图,或对低优先级意图进行降级或挂起等。
S708,意图执行器孪生体将原因及至少一种解决方案发送至意图管理器。
意图不满足意图期望目标的解决方案验证通过后,意图执行器孪生体将该高优先级意图对象孪生实例的意图期望目标不满足预期的原因及可能的解决方案,发送给意图管理器
S709,意图管理器分析原因及至少一种解决方案,并根据分析结果更新高优先级意图或者降级其他低优先级意图。
意图管理器基于高优先级意图对象孪生实例的意图期望目标不满足预期的原因及可行的解决方案,执行高优先级意图不满足意图期望目标的解决方案,如更新高优先级意图,调整该意图期望目标参数或约束条件;更新低优先级意图的网络管理任务,调整该低优先级意图期望目标参数或约束条件,或对低优先级意图进行降级或挂起,从而保障高优先级意图的期望目标满足。
S710,意图管理器向意图执行器请求更新意图对象实例及对应的网络管理 任务。
意图管理器请求意图执行器更新高优先级意图对象实例,或更新低优先级对象实例,或降级、挂起低优先级意图。意图执行器更新高优先级意图的网络管理任务,或低优先级意图的网络管理任务。如:意图执行器降级原有低优先级的意图期望目标或对低优先级意图的任务进行挂起,避免对高优先级意图产生影响。
S711,意图执行器与被管网络执行更新后的网络管理任务,并交互验证高优先级意图是否满足期望目标。
S712,将意图执行结果报告反馈至意图管理器。
在一种应用场景下,意图管理器根据意图执行结果报告,监测到在一个时间段,网络或业务性能指标不满足意图期望目标。意图管理器需要反馈不满足意图期望目标的信息及可能的解决方案给意图消费者,由意图消费者决定是否继续执行、更新、挂起、删除该意图。
为寻找意图不满足意图期望目标可能的解决方案,意图管理器决策创建数字孪生体,通过数字孪生技术来执行寻找并验证意图不满足意图期望目标可能的解决方案,并反馈给意图消费者。
若不满足期望目标为意图全生命周期过程中一个时段不满足意图期望目标,则在创建意图执行器孪生体及被管网络孪生体之后,还包括:意图管理器向意图执行器孪生体发送意图,请求创建意图对象孪生实例;意图执行器孪生体创建意图的意图对象孪生实例,并向意图管理器发送意图对象孪生实例创建成功的信息;意图管理器向数字孪生管理器或者意图执行器孪生体发送意图不满足期望目标解决方案的仿真请求;意图执行器孪生体根据意图对象孪生实例中的网络参数配置被管网络孪生体,执行意图的网络管理任务;在执行网络管理任务的过程中,当意图不满足期望目标时,意图执行器孪生体发现原因及确定并验证可能的解决方案;意图执行器孪生体将意图执行结果、不满足期望目标时的原因及解决方案发送至意图管理器,意图管理器将意图执行结果、不满足期望目标时的原因及解决方案发送至管理服务消费者,使得消费者决策是否更新意图。
本实施例中,图8是申请实施例中的一种解决意图全生命周期过程中一个时段不满足意图期望目标的过程图,如图8所示,该方法包括:
S801,意图管理器接收意图执行器发送的意图在一个时段不满足意图期望目标。
管理服务消费者下发意图给管理服务生产者执行。意图执行器在执行该意 图对象实例的网络管理任务,并在执行过程中定期或根据结果变更发送意图执行报告给意图管理器。
S802,意图管理器请求数字孪生管理器创建意图执行器孪生体及被管网络孪生体。
意图管理器判断一个时段意图期望目标不满足,意图管理器决策创建数字孪生体,通过数字孪生技术来执行意图仿真操作,分析对意图期望目标不达标的原因及可能的解决方案。意图管理器识别意图中描述的被管网络及该意图所需的意图执行器,并与数字孪生管理器进行交互,请求创建孪生体。其中,创建意图执行器孪生体及被管网络孪生体的具体过程参见S210-S240,此处不再赘述。
S803,意图管理器向意图执行器孪生体发送意图,请求创建意图对象孪生实例。
S804,意图执行器孪生体创建意图的意图对象孪生实例。
S805,意图执行器孪生体向意图管理器发送意图对象孪生实例创建成功的信息。
S806,意图管理器向数字孪生管理器或者意图执行器孪生体发送仿真请求。
本实施例中,意图管理器将仿真请求发送至数字孪生管理器,由数字孪生管理器将仿真请求转发至意图执行器孪生体。或者,意图管理器直接向意图执行器孪生体发送仿真请求。
S807,意图执行器孪生体根据意图对象孪生实例中的网络参数配置被管网络孪生体,并执行意图对应的网络管理任务;在执行网络管理任务的过程中,当意图不满期望目标时,意图执行器孪生体确定原因及解决方案。
S808,意图执行器孪生体将意图执行结果、不满足期望目标时的原因及解决方案发送至意图管理器。
S809,意图管理器根据意图执行结果、不满足期望目标时的原因及解决方案生成意图报告,并将意图报告发送至管理服务消费者,使得消费者决策是否更新意图。
图9是本申请实施例中的一种基于数字孪生的意图处理方法的流程图,该方法由管理服务生产者执行,该方法包括:
S910,接收管理服务消费者发送的携带有仿真预测需求的一个或多个意图,或获取包含不满足期望目标的意图执行结果报告。
S920,根据仿真预测需求和/或意图执行结果报告确定对意图进行数字孪生 仿真验证操作。
S930,根据意图描述信息确定一个或多个意图对应的被管网络及意图执行器,并请求数字孪生管理器创建意图执行器孪生体及被管网络孪生体,以对一个或多个意图进行仿真。
S910-S920的具体实现过程参见上述实施例,此处不再赘述,
请求数字孪生管理器创建意图执行器孪生体及被管网络孪生体,以对一个或多个意图进行仿真的方式可以是:
向数字孪生管理器发送孪生体创建请求,使得数字孪生管理器基于孪生体创建请求在数字孪生平台中创建意图执行器孪生体及被管网络孪生体,以对一个或多个意图进行仿真;其中,孪生体创建请求携带有意图执行器信息及被管网络信息。
仿真预测需求包括:意图期望目标寻优需求、意图全生命周期满足期望目标、意图满足期望目标预测需求及多个意图冲突检测需求中的至少一种;不满足期望目标包括:高优先级意图不满足期望目标、意图全生命周期过程中一个时段不满足意图期望目标。
若仿真预测需求为意图期望目标寻优需求,则在向数字孪生管理器发送孪生体创建请求之后,还包括:
向意图执行器孪生体发送意图,以请求创建意图对象孪生实例;向数字孪生管理器或者意图执行器孪生体发送仿真请求,使得意图执行器孪生体执行意图期望目标寻优需求对应的网络管理任务,以确定出至少一个最优网络性能参数;其中,仿真请求携带有意图期望目标寻优需求;接收意图执行器孪生体发送的至少一个最优网络性能参数,并将至少一个最优网络性能参数发送至管理服务消费者,以供管理服务消费者选择。
若仿真预测需求为意图全生命周期满足期望目标需求,则一个或多个意图中还携带有授权更新或修改的信息;在确定一个或多个意图对应的被管网络及意图执行器之后,还包括:
执行一个或多个意图;相应的,在向数字孪生管理器发送孪生体创建请求之后,还包括:
向意图执行器孪生体发送意图,以请求创建意图对象孪生实例;当检测到意图不满足期望目标时,向意图执行器孪生体发送仿真请求及网络更新策略,使得意图执行器孪生体对网络更新策略进行验证及优化,获得最终的网络优化策略;接收意图执行器孪生体发送的最终的网络优化策略,根据网络优化策略更新一个或多个意图。
若仿真预测需求为意图满足期望目标预测需求,则在向数字孪生管理器发送孪生体创建请求之后,还包括:
向意图执行器孪生体发送意图,以请求创建意图对象孪生实例;向数字孪生管理器或者意图执行器孪生体发送仿真请求,使得意图执行器孪生体执行意图满足期望目标预测需求对应的网络管理任务,并确定不满足期望目标的原因及解决方案;接收意图执行器孪生体发送的不满足期望目标的原因及解决方案,并将不满足期望目标的原因及解决方案发送至管理服务消费者。
若仿真预测需求为多个意图冲突检测需求,则在向数字孪生管理器发送孪生体创建请求之后,还包括:
向意图执行器孪生体发送多个意图,以请求创建多个意图对象孪生实例;向数字孪生管理器或者意图执行器孪生体发送仿真请求,使得意图执行器孪生体执行多个意图冲突检测需求的网络管理任务,以确定冲突原因及解决方案;接收意图执行器孪生体发送的冲突原因及解决方案,并基于冲突原因及解决方案生成多个意图分别对应的冲突预测报告;将冲突预测报告发送至各管理服务消费者。
若不满足期望目标为高优先级意图不满足期望目标,则在向数字孪生管理器发送孪生体创建请求之后,还包括:
向意图执行器孪生体发送高优先级意图,请求创建意图对象孪生实例;向数字孪生管理器或者意图执行器孪生体发送仿真请求,使得意图执行器孪生体执行意图对象孪生实例对应的网络管理任务,以确定高优先级意图不满足期望目标的原因及解决方案;接收意图执行器孪生体发送的高优先级意图不满足期望目标的原因及解决方案,并对高优先级意图不满足期望目标的解决方案进行验证。
若不满足期望目标为意图全生命周期过程中一个时段不满足意图期望目标,则在向数字孪生管理器发送孪生体创建请求之后,还包括:
向意图执行器孪生体发送意图,以请求创建意图对象孪生实例;向数字孪生管理器或者意图执行器孪生体发送仿真请求,使得意图执行器孪生体执行意图对象孪生实例对应的网络管理任务,以确定不满足期望目标的原因及解决方案;接收意图执行器孪生体发送的不满足期望目标的原因及解决方案,并将不满足期望目标的原因及解决方案发送至管理服务消费者。
本实施例的技术方案,接收管理服务消费者发送的携带有仿真预测需求的一个或多个意图,或获取包含不满足期望目标的意图执行结果报告;根据仿真预测需求和/或意图执行结果报告确定对意图进行数字孪生仿真验证操作。根据意图描述信息确定一个或多个意图对应的被管网络及意图执行器,并请求数字 孪生管理器创建意图执行器孪生体及被管网络孪生体,以对一个或多个意图进行仿真。基于通过数字孪生技术对意图对应的网络管理任务进行仿真执行,以提高意图处理的准确性及可靠性。
图10是本申请公开的一种基于数字孪生的意图处理方法的流程图,该方法由数字孪生管理器执行,包括:
S1001,接收管理服务生产者发送的孪生体创建请求;其中,孪生体创建请求携带有意图执行器信息及被管网络信息。
S1002,基于孪生体创建请求在数字孪生平台中创建意图执行器孪生体及被管网络孪生体,以对一个或多个意图进行仿真。
本实施例中,S1001-S1002的具体过程可以参见上述实施例,此处不再赘述。
图11是本申请公开的一种基于数字孪生的意图处理方法的流程图,方法由预先创建并部署在数字孪生平台的意图执行器孪生体及被管网络孪生体执行,包括:
S1101,接收管理服务生产者发送的一个或多个意图及意图对象孪生实例创建请求。
S1102,基于一个或多个意图及意图对象孪生实例创建请求创建一个或多个意图对象孪生实例。
S1103,接收管理服务生产者发送的仿真请求,并根据仿真请求对一个或多个意图进行仿真。
仿真请求包括如下至少一项:意图期望目标值寻优请求、意图实现全生命周期保障请求、意图满足期望目标预测请求、多个意图冲突检测请求、高优先级意图不满足期望目标请求及意图全生命周期过程中一个时段不满足意图期望目标。
若仿真请求为意图期望目标值寻优请求,则根据仿真请求对一个或多个意图进行仿真,包括:
根据意图对象孪生实例中的网络参数配置被管网络孪生体;执行期望目标寻优请求对应的网络管理任务,以确定出至少一个最优网络性能参数;将至少一个最优网络性能参数发送至管理服务生产者。
若仿真请求为意图实现全生命周期保障请求,则根据仿真请求对一个或多个意图进行仿真,包括:
接收管理服务生产者发送的网络更新策略;对网络更新策略进行验证及优化,获得最终的网络优化策略;将最终的网络优化策略发送至管理服务生产者, 使得管理服务生产者根据最终的网络优化策略更新意图。
若仿真请求为意图满足期望目标预测请求,则根据仿真请求对一个或多个意图进行仿真,包括:
根据意图对象孪生实例中的网络参数配置被管网络孪生体;执行意图满足期望目标预测请求对应的网络管理任务,并确定不满足期望目标的原因及解决方案;将不满足期望目标的原因及解决方案发送至管理服务生产者。
若仿真请求为多个意图冲突检测请求,则根据仿真请求对多个意图进行仿真,包括:
根据多个意图对象孪生实例中的网络参数配置被管网络孪生体;执行多个意图对象孪生实例的网络管理任务,以确定冲突原因及解决方案;将冲突原因及解决方案发送至管理服务生产者。
若仿真请求为高优先级意图不满足期望目标请求,则根据仿真请求对一个或多个意图进行仿真,包括:
根据意图对象孪生实例中的网络参数配置被管网络孪生体;执行高优先级意图对应的网络管理任务;在执行网络管理任务的过程中,当高优先级意图不满足期望目标时,以确定高优先级意图不满足期望目标的原因及解决方案;将高优先级意图不满足期望目标的原因及解决方案发送至管理服务生产者。
若仿真请求为意图全生命周期过程中一个时段不满足意图期望目标请求,则根据仿真请求对一个或多个意图进行仿真,包括:
根据意图对象孪生实例中的网络参数配置被管网络孪生体;执行意图的网络管理任务,以确定不满足期望目标的原因及解决方案;将不满足期望目标的原因及解决方案发送至管理服务生产者。
图12是本申请实施例提供的一种基于数字孪生的意图处理装置的结构示意图,该装置设置于管理服务生产者中,包括:
获取模块1201,用于接收管理服务消费者发送的携带有仿真预测需求的一个或多个意图,或获取包含不满足期望目标的意图执行结果报告;仿真验证操作确定模块1202,用于根据仿真预测需求和/或意图执行结果报告确定对意图进行数字孪生仿真验证操作;孪生体创建请求模块1203,用于根据意图描述信息确定一个或多个意图对应的被管网络及意图执行器,并请求数字孪生管理器创建意图执行器孪生体及被管网络孪生体,以对一个或多个意图进行仿真。
孪生体创建请求模块1203,还用于:
向数字孪生管理器发送孪生体创建请求,使得数字孪生管理器基于孪生体 创建请求在数字孪生平台中创建意图执行器孪生体及被管网络孪生体,以对一个或多个意图进行仿真;其中,孪生体创建请求携带有意图执行器信息及被管网络信息。
仿真预测需求包括:意图期望目标寻优需求、意图全生命周期满足期望目标、意图满足期望目标预测需求及多个意图冲突检测需求中的至少一种;不满足期望目标包括:高优先级意图不满足期望目标、意图全生命周期过程中一个时段不满足意图期望目标。
若仿真预测需求为意图期望目标寻优需求,还包括第一仿真请求发送模块,用于:
向意图执行器孪生体发送意图,以请求创建意图对象孪生实例;向数字孪生管理器或者意图执行器孪生体发送仿真请求,使得意图执行器孪生体执行意图期望目标寻优需求对应的网络管理任务,以确定出至少一个最优网络性能参数;其中,仿真请求携带有意图期望目标寻优需求;接收意图执行器孪生体发送的至少一个最优网络性能参数,并将至少一个最优网络性能参数发送至管理服务消费者,以供管理服务消费者选择。
若仿真预测需求为意图全生命周期满足期望目标需求,则一个或多个意图中还携带有授权更新或修改的信息;还包括:第二仿真请求发送模块,用于:
执行一个或多个意图;向意图执行器孪生体发送意图,以请求创建意图对象孪生实例;当检测到意图不满足期望目标时,向意图执行器孪生体发送仿真请求及网络更新策略,使得意图执行器孪生体对网络更新策略进行验证及优化,获得最终的网络优化策略;接收意图执行器孪生体发送的最终的网络优化策略,根据网络优化策略更新一个或多个意图。
若仿真预测需求为意图满足期望目标预测需求,还包括:第三仿真请求发送模块,用于:
向意图执行器孪生体发送意图,以请求创建意图对象孪生实例;向数字孪生管理器或者意图执行器孪生体发送仿真请求,使得意图执行器孪生体执行意图满足期望目标预测需求对应的网络管理任务,并确定不满足期望目标的原因及解决方案;接收意图执行器孪生体发送的不满足期望目标的原因及解决方案,并将不满足期望目标的原因及解决方案发送至管理服务消费者。
若仿真预测需求为多个意图冲突检测需求,还包括:第四仿真请求发送模块,用于:
向意图执行器孪生体发送多个意图,以请求创建多个意图对象孪生实例;向数字孪生管理器或者意图执行器孪生体发送仿真请求,使得意图执行器孪生 体执行多个意图冲突检测需求的网络管理任务,以确定冲突原因及解决方案;接收意图执行器孪生体发送的冲突原因及解决方案,并基于冲突原因及解决方案生成多个意图分别对应的冲突预测报告;将冲突预测报告发送至各管理服务消费者。
若不满足期望目标为高优先级意图不满足期望目标,还包括:第五仿真请求发送模块,用于:
向意图执行器孪生体发送高优先级意图,请求创建意图对象孪生实例;向数字孪生管理器或者意图执行器孪生体发送仿真请求,使得意图执行器孪生体执行意图对象孪生实例对应的网络管理任务,以确定高优先级意图不满足期望目标的原因及解决方案;接收意图执行器孪生体发送的高优先级意图不满足期望目标的原因及解决方案,并对高优先级意图不满足期望目标的解决方案进行验证。
若不满足期望目标为意图全生命周期过程中一个时段不满足意图期望目标,,还包括:第六仿真请求发送模块,用于:
向意图执行器孪生体发送意图,以请求创建意图对象孪生实例;向数字孪生管理器或者意图执行器孪生体发送仿真请求,使得意图执行器孪生体执行意图对象孪生实例对应的网络管理任务,以确定不满足期望目标的原因及解决方案;接收意图执行器孪生体发送的不满足期望目标的原因及解决方案,并将不满足期望目标的原因及解决方案发送至管理服务消费者。
图13是本公开实施例提供的一种基于数字孪生的意图处理装置的结构示意图,该装置设置于数字孪生管理器中,包括:
孪生体创建请求接收模块1301,用于接收管理服务生产者发送的孪生体创建请求;其中,孪生体创建请求携带有意图执行器信息及被管网络信息;孪生体创建模块1302,用于基于孪生体创建请求在数字孪生平台中创建意图执行器孪生体及被管网络孪生体,以对一个或多个意图进行仿真。
图14是本申请实施例提供的一种基于数字孪生的意图处理装置的结构示意图,该装置设置于预先创建并部署在数字孪生平台的意图执行器孪生体及被管网络孪生体中,包括:
意图对象孪生实例创建请求接收模块1401,用于接收管理服务生产者发送的一个或多个意图及意图对象孪生实例创建请求;意图对象孪生实例创建模块1402,用于基于一个或多个意图及意图对象孪生实例创建请求创建一个或多个意图对象孪生实例;意图仿真模块1403,用于接收管理服务生产者发送的仿真请求,并根据仿真请求对一个或多个意图进行仿真;其中,仿真请求包括如下至少一项:意图期望目标值寻优请求、意图实现全生命周期保障请求、意图满 足期望目标预测请求、多个意图冲突检测请求、高优先级意图不满足期望目标请求及意图全生命周期过程中一个时段不满足意图期望目标。
若仿真请求为意图期望目标值寻优请求,意图仿真模块1403,还用于:
根据意图对象孪生实例中的网络参数配置被管网络孪生体;执行期望目标寻优请求对应的网络管理任务,以确定出至少一个最优网络性能参数;将至少一个最优网络性能参数发送至管理服务生产者。
若仿真请求为意图实现全生命周期保障请求,意图仿真模块1403,还用于,还用于:
接收管理服务生产者发送的网络更新策略;对网络更新策略进行验证及优化,获得最终的网络优化策略;将最终的网络优化策略发送至管理服务生产者,使得管理服务生产者根据最终的网络优化策略更新意图。
若仿真请求为意图满足期望目标预测请求,意图仿真模块1403,还用于:
根据意图对象孪生实例中的网络参数配置被管网络孪生体;执行意图满足期望目标预测请求对应的网络管理任务,并确定不满足期望目标的原因及解决方案;将不满足期望目标的原因及解决方案发送至管理服务生产者。
若仿真请求为多个意图冲突检测请求,意图仿真模块1403,还用于:
根据多个意图对象孪生实例中的网络参数配置被管网络孪生体;执行多个意图对象孪生实例的网络管理任务,以确定冲突原因及解决方案;将冲突原因及解决方案发送至管理服务生产者。
若仿真请求为高优先级意图不满足期望目标请求,意图仿真模块1403,还用于:
根据意图对象孪生实例中的网络参数配置被管网络孪生体;执行高优先级意图对应的网络管理任务;在执行网络管理任务的过程中,当高优先级意图不满足期望目标时,以确定高优先级意图不满足期望目标的原因及解决方案;将高优先级意图不满足期望目标的原因及解决方案发送至管理服务生产者。
若仿真请求为意图全生命周期过程中一个时段不满足意图期望目标请求,意图仿真模块1403,还用于:
根据意图对象孪生实例中的网络参数配置被管网络孪生体;执行意图的网络管理任务,以确定不满足期望目标的原因及解决方案;将不满足期望目标的原因及解决方案发送至管理服务生产者。
在一个实施例中,图15是本申请实施例提供的一种计算机设备的结构示意图。如图15所示,本申请提供的设备,包括:处理器510以及存储器520。该 设备中处理器510的数量可以是一个或者多个,图15中以一个处理器510为例。该设备中存储器520的数量可以是一个或者多个,图15中以一个存储器520为例。该设备的处理器510以及存储器520可以通过总线或者其他方式连接,图15中以通过总线连接为例。实施例中,该设备为计算机设备。
存储器520作为一种计算机可读存储介质,可设置为存储软件程序、计算机可执行程序以及模块,如本申请任意实施例的设备对应的程序指令/模块(例如,数据传输装置中的编码模块和第一发送模块)。存储器520可包括存储程序区和存储数据区,其中,存储程序区可存储操作系统、至少一个功能所需的应用程序;存储数据区可存储根据设备的使用所创建的数据等。此外,存储器520可以包括高速随机存取存储器,还可以包括非易失性存储器,例如至少一个磁盘存储器件、闪存器件、或其他非易失性固态存储器件。在一些实例中,存储器520可进一步包括相对于处理器510远程设置的存储器,这些远程存储器可以通过网络连接至设备。上述网络的实例包括但不限于互联网、企业内部网、局域网、移动通信网及其组合。
上述提供的设备可设置为执行上述任意实施例提供的基于数字孪生的意图处理方法,具备相应的功能和效果。
对应存储器520中存储的程序可以是本申请实施例所提供应用于基于数字孪生的意图处理方法对应的程序指令/模块,处理器510通过运行存储在存储器520中的软件程序、指令以及模块,从而执行计算机设备的一种或多种功能应用以及数据处理,即实现上述方法实施例中应用于数据的关联查询方法。可以理解的是,上述设备为接收端时,可执行本申请任意实施例所提供的基于数字孪生的意图处理方法,且具备相应的功能和效果。
本申请实施例还提供一种包含计算机可执行指令的存储介质,计算机可执行指令在由计算机处理器执行时用于执行基于数字孪生的意图处理方法,该方法包括:本节点接收干扰节点的导频信息和/或调度信息;根据所述导频信息和/或调度信息进行基于数字孪生的意图处理。
本领域内的技术人员应明白,术语用户设备涵盖任何适合类型的无线用户设备,例如移动电话、便携数据处理装置、便携网络浏览器或车载移动台。
一般来说,本申请的多种实施例可以在硬件或专用电路、软件、逻辑或其任何组合中实现。例如,一些方面可以被实现在硬件中,而其它方面可以被实现在可以被控制器、微处理器或其它计算装置执行的固件或软件中,尽管本申请不限于此。
本申请的实施例可以通过移动装置的数据处理器执行计算机程序指令来实现,例如在处理器实体中,或者通过硬件,或者通过软件和硬件的组合。计算 机程序指令可以是汇编指令、指令集架构(Instruction Set Architecture,ISA)指令、机器指令、机器相关指令、微代码、固件指令、状态设置数据、或者以一种或多种编程语言的任意组合编写的源代码或目标代码。
本申请附图中的任何逻辑流程的框图可以表示程序操作,或者可以表示相互连接的逻辑电路、模块和功能,或者可以表示程序操作与逻辑电路、模块和功能的组合。计算机程序可以存储在存储器上。存储器可以具有任何适合于本地技术环境的类型并且可以使用任何适合的数据存储技术实现,例如但不限于只读存储器(Read-Only Memory,ROM)、随机访问存储器(Random Access Memory,RAM)、光存储器装置和系统(数码多功能光碟(Digital Video Disc,DVD)或光盘(Compact Disk,CD))等。计算机可读介质可以包括非瞬时性存储介质。数据处理器可以是任何适合于本地技术环境的类型,例如但不限于通用计算机、专用计算机、微处理器、数字信号处理器(Digital Signal Processing,DSP)、专用集成电路(Application Specific Integrated Circuit,ASIC)、可编程逻辑器件(Field-Programmable Gate Array,FPGA)以及基于多核处理器架构的处理器。
以上所述,仅为本申请的示例性实施例而已,并非用于限定本申请的保护范围。
本申请的实施例可以通过移动装置的数据处理器执行计算机程序指令来实现,例如在处理器实体中,或者通过硬件,或者通过软件和硬件的组合。计算机程序指令可以是汇编指令、指令集架构(ISA)指令、机器指令、机器相关指令、微代码、固件指令、状态设置数据、或者以一种或多种编程语言的任意组合编写的源代码或目的代码。

Claims (19)

  1. 一种基于数字孪生的意图处理方法,由管理服务生产者执行,包括:
    接收管理服务消费者发送的携带有仿真预测需求的至少一个意图,或获取包含不满足期望目标的意图执行结果报告;
    根据所述仿真预测需求和所述意图执行结果报告中的至少之一确定对意图进行数字孪生仿真验证操作;
    根据意图描述信息确定至少一个意图对应的被管网络及意图执行器,并请求数字孪生管理器创建意图执行器孪生体及被管网络孪生体,以对所述至少一个意图进行仿真。
  2. 根据权利要求1所述的方法,其中,所述请求数字孪生管理器创建意图执行器孪生体及被管网络孪生体,以对所述至少一个意图进行仿真,包括:
    向所述数字孪生管理器发送孪生体创建请求,使得所述数字孪生管理器基于所述孪生体创建请求在数字孪生平台中创建所述意图执行器孪生体及所述被管网络孪生体,以对所述至少一个意图进行仿真;其中,所述孪生体创建请求携带有意图执行器信息及被管网络信息。
  3. 根据权利要求2所述的方法,其中,所述仿真预测需求包括:意图期望目标寻优需求、意图全生命周期满足期望目标需求、意图满足期望目标预测需求及多个意图冲突检测需求中的至少一种;所述不满足期望目标包括:高优先级意图不满足期望目标、意图全生命周期过程中一个时段不满足意图期望目标。
  4. 根据权利要求3所述的方法,其中,响应于所述仿真预测需求为所述意图期望目标寻优需求,在所述向所述数字孪生管理器发送孪生体创建请求之后,还包括:
    向所述意图执行器孪生体发送所述意图,以请求创建意图对象孪生实例;
    向所述数字孪生管理器或者所述意图执行器孪生体发送仿真请求,使得所述意图执行器孪生体执行所述意图期望目标寻优需求对应的网络管理任务,以确定出至少一个最优网络性能参数;其中,所述仿真请求携带有所述意图期望目标寻优需求;
    接收所述意图执行器孪生体发送的所述至少一个最优网络性能参数,并将所述至少一个最优网络性能参数发送至所述管理服务消费者,以供所述管理服务消费者选择。
  5. 根据权利要求3所述的方法,其中,响应于所述仿真预测需求为所述意图全生命周期满足期望目标需求,所述至少一个意图中还携带有授权更新或修改的信息;在所述确定至少一个意图对应的被管网络及意图执行器之后,还包括:
    执行所述至少一个意图;
    在所述向所述数字孪生管理器发送孪生体创建请求之后,还包括:
    向所述意图执行器孪生体发送所述意图,以请求创建意图对象孪生实例;
    响应于检测到所述意图不满足期望目标,向所述意图执行器孪生体发送仿真请求及网络更新策略,使得所述意图执行器孪生体对所述网络更新策略进行验证及优化,获得最终的网络优化策略;
    接收所述意图执行器孪生体发送的最终的网络优化策略,根据所述网络优化策略更新所述至少一个意图。
  6. 根据权利要求3所述的方法,其中,响应于所述仿真预测需求为所述意图满足期望目标预测需求,在所述向所述数字孪生管理器发送孪生体创建请求之后,还包括:
    向所述意图执行器孪生体发送所述意图,以请求创建意图对象孪生实例;
    向所述向数字孪生管理器或者所述意图执行器孪生体发送仿真请求,使得所述意图执行器孪生体执行所述意图满足期望目标预测需求对应的网络管理任务,并确定不满足期望目标的原因及解决方案;
    接收所述意图执行器孪生体发送的所述不满足期望目标的原因及解决方案,并将所述不满足期望目标的原因及解决方案发送至所述管理服务消费者。
  7. 根据权利要求3所述的方法,其中,响应于所述仿真预测需求为所述多个意图冲突检测需求,在所述向数字孪生管理器发送孪生体创建请求之后,还包括:
    向所述意图执行器孪生体发送所述多个意图,以请求创建多个意图对象孪生实例;
    向所述数字孪生管理器或者所述意图执行器孪生体发送仿真请求,使得所述意图执行器孪生体执行所述多个意图冲突检测需求的网络管理任务,以确定冲突原因及解决方案;
    接收所述意图执行器孪生体发送的冲突原因及解决方案,并基于所述冲突原因及解决方案生成所述多个意图分别对应的冲突预测报告;
    将所述冲突预测报告发送至所述管理服务消费者。
  8. 根据权利要求3所述的方法,其中,响应于所述不满足期望目标为所述高优先级意图不满足期望目标,在所述向数字孪生管理器发送孪生体创建请求之后,还包括:
    向所述意图执行器孪生体发送所述高优先级意图,请求创建意图对象孪生 实例;
    向所述向数字孪生管理器或者所述意图执行器孪生体发送仿真请求,使得所述意图执行器孪生体执行所述意图对象孪生实例对应的网络管理任务,以确定所述高优先级意图不满足期望目标的原因及解决方案;
    接收所述意图执行器孪生体发送的所述高优先级意图不满足期望目标的原因及解决方案,并对所述高优先级意图不满足期望目标的原因及解决方案进行验证。
  9. 根据权利要求3所述的方法,其中,响应于所述不满足期望目标为所述意图全生命周期过程中一个时段不满足意图期望目标,在所述向数字孪生管理器发送孪生体创建请求之后,还包括:
    向所述意图执行器孪生体发送所述意图,以请求创建意图对象孪生实例;
    向所述向数字孪生管理器或者所述意图执行器孪生体发送仿真请求,使得所述意图执行器孪生体执行所述意图对象孪生实例对应的网络管理任务,以确定所述不满足期望目标的原因及解决方案;
    接收所述意图执行器孪生体发送的所述不满足期望目标的原因及解决方案,并将所述不满足期望目标的原因及解决方案发送至所述管理服务消费者。
  10. 一种基于数字孪生的意图处理方法,由数字孪生管理器执行,包括:
    接收管理服务生产者发送的孪生体创建请求;其中,所述孪生体创建请求携带有意图执行器信息及被管网络信息;
    基于所述孪生体创建请求在数字孪生平台中创建意图执行器孪生体及被管网络孪生体,以对至少一个意图进行仿真。
  11. 一种基于数字孪生的意图处理方法,由预先创建并部署在数字孪生平台的意图执行器孪生体及被管网络孪生体执行,包括:
    接收管理服务生产者发送的至少一个意图及意图对象孪生实例创建请求;
    基于所述至少一个意图及所述意图对象孪生实例创建请求创建至少一个意图对象孪生实例;
    接收所述管理服务生产者发送的仿真请求,并根据所述仿真请求对所述至少一个意图进行仿真;其中,所述仿真请求包括如下至少一项:意图期望目标值寻优请求、意图实现全生命周期保障请求、意图满足期望目标预测请求、多个意图冲突检测请求、高优先级意图不满足期望目标请求及意图全生命周期过程中一个时段不满足意图期望目标。
  12. 根据权利要求11所述的方法,其中,响应于所述仿真请求为所述意图 期望目标值寻优请求,所述根据所述仿真请求对所述至少一个意图进行仿真,包括:
    根据所述意图对象孪生实例中的网络参数配置所述被管网络孪生体;
    执行所述意图期望目标寻优请求对应的网络管理任务,以确定出至少一个最优网络性能参数;
    将所述至少一个最优网络性能参数发送至所述管理服务生产者。
  13. 根据权利要求11所述的方法,其中,响应于所述仿真请求为所述意图实现全生命周期保障请求,所述根据所述仿真请求对所述至少一个意图进行仿真,包括:
    接收所述管理服务生产者发送的网络更新策略;
    对所述网络更新策略进行验证及优化,获得最终的网络优化策略;
    将所述最终的网络优化策略发送至所述管理服务生产者,使得所述管理服务生产者根据所述最终的网络优化策略更新意图。
  14. 根据权利要求11所述的方法,其中,响应于所述仿真请求为所述意图满足期望目标预测请求,所述根据所述仿真请求对所述至少一个意图进行仿真,包括:
    根据所述意图对象孪生实例中的网络参数配置所述被管网络孪生体;
    执行所述意图满足期望目标预测请求对应的网络管理任务,并确定不满足期望目标的原因及解决方案;
    将所述不满足期望目标的原因及解决方案发送至所述管理服务生产者。
  15. 根据权利要求11所述的方法,其中,响应于所述仿真请求为所述多个意图冲突检测请求,所述根据所述仿真请求对所述至少一个意图进行仿真,包括:
    根据所述至少一个意图对象孪生实例中的网络参数配置所述被管网络孪生体;
    执行所述至少一个意图对象孪生实例的网络管理任务,以确定冲突原因及解决方案;
    将所述冲突原因及解决方案发送至所述管理服务生产者。
  16. 根据权利要求11所述的方法,其中,响应于所述仿真请求为所述高优先级意图不满足期望目标请求,所述根据所述仿真请求对所述至少一个意图进行仿真,包括:
    根据所述意图对象孪生实例中的网络参数配置所述被管网络孪生体;
    执行所述高优先级意图对应的网络管理任务;在执行所述网络管理任务的过程中,响应于所述高优先级意图不满足期望目标,以确定所述高优先级意图不满足期望目标的原因及解决方案;
    将所述高优先级意图不满足期望目标的原因及解决方案发送至所述管理服务生产者。
  17. 根据权利要求11所述的方法,其中,响应于所述仿真请求为所述意图全生命周期过程中一个时段不满足意图期望目标请求,所述根据所述仿真请求对所述至少一个意图进行仿真,包括:
    根据所述意图对象孪生实例中的网络参数配置所述被管网络孪生体;
    执行所述意图的网络管理任务,以确定不满足期望目标的原因及解决方案;
    将所述不满足期望目标的原因及解决方案发送至所述管理服务生产者。
  18. 一种计算机设备,包括存储器、处理器及存储在所述存储器上并可在所述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如权利要求1-17任一项所述的基于数字孪生的意图处理方法。
  19. 一种计算机可读存储介质,存储有计算机程序,所述程序被处理器执行时实现如权利要求1-17任一项所述的基于数字孪生的意图处理方法。
PCT/CN2024/127726 2024-03-29 2024-10-28 基于数字孪生的意图处理方法、设备及存储介质 Pending WO2025200420A1 (zh)

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WO2023109905A1 (zh) * 2021-12-15 2023-06-22 中国移动通信有限公司研究院 一种数字孪生网络构建方法及网元
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CN117640376A (zh) * 2022-08-18 2024-03-01 中兴通讯股份有限公司 意图处理方法、电子设备和存储介质
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