Cooperative management method and system for digital twin and optical transport network management and control system

Abstract

The invention provides a collaborative management method and system for a digital twinning and optical transport network management and control system, and the system comprises a multidirectional interface architecture of a physical layer southbound interface gateway, an application layer northbound interface gateway and a digital twinning east-west interface gateway, and supports data interaction and instruction transmission among a physical layer, an application layer and a digital twinning system. The method covers acquisition and processing of real-time data streams, full life cycle management of digital twin, simulation deduction and decision optimization, asynchronous communication and identity verification and authority management. According to the method, closed-loop control from user intention definition, simulation deduction, configuration issuing, real-time monitoring to optimization adjustment is realized through a multidirectional interface coordination mechanism, the coordination efficiency and control precision between systems are remarkably improved, the requirements of an optical transport network for real-time, dynamic and high-concurrency data processing are met, and the method is suitable for popularization and application. Cooperative operation in a multi-manufacturer and multi-device environment is supported, and an efficient and flexible solution is provided for intelligent management and optimization of the optical transmission network.

Description

Technical Field

[0001] The present invention relates to the technical fields of digital twin and optical transport network, and in particular to a collaborative management method and system for digital twin and optical transport network management and control system based on multi-directional interfaces. Background Art

[0002] In the field of optical transport network, various device physical entities in the optical transport network or optical transmission system continuously generate real-time and continuous data streams. These data streams have high dynamics and timeliness, and can reflect the instantaneous changes of the network operation state and key performance indicators. However, the architectures of most current management and control systems are mainly designed for the persistent storage of static data sets, and the processing capabilities are concentrated on the analysis and modeling of batch data, lacking support for the capture, processing, and analysis of real-time data streams. This limitation makes the existing management and control frameworks difficult to meet the requirements of digital twin optical transport network for real-time, dynamic, and high-concurrency data processing, and thus cannot be directly applied to the actual scenarios of optical transport network or optical transmission system.

[0003] At the same time, the integration of digital twin and management and control system usually relies on single or a few interfaces, making it difficult to meet the information interaction requirements between different levels. The existing technologies lack unified design for physical layer data collection, control, and configuration download (physical layer southbound interface gateway), abstract interaction, operation, and management between the management and control system and the application layer (application layer northbound interface gateway), and information and control interaction between the management and control system and the digital twin, including steps such as establishing models, saving data, model simulation deduction, and decision-making on the optimal configuration according to simulation results (digital twin east-west interface gateway), resulting in inefficient integration of data streams, control signaling, and network management. In addition, the isolation between the device layer and the management and control system is insufficient, restricting the collaborative capabilities in a multi-vendor and multi-device environment. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a collaborative management method and system for digital twin and optical transport network management and control system to eliminate or improve one or more defects existing in the prior art.

[0005] On the one hand, the present invention provides a collaborative management method for digital twin and optical transport network management and control system based on multi-directional interfaces. The method includes the following steps: Collect real-time operation data of each node in the optical transport network through the physical layer southbound interface gateway; store the preprocessed real-time operation data, or perform real-time analysis using a streaming data processing engine; Select the corresponding service based on the type of digital twin model selected by the user in the application layer, and initiate a service request through the application layer northbound interface gateway to apply for creating a new digital twin model; The digital twin east-west interface gateway initiates a creation instruction to create a digital twin business model and instantiate it, generating an executable simulation model instance; Using the real-time operation data obtained by the streaming data processing engine and / or the pre-stored operation data, perform simulation deduction on the instantiated digital twin business model to generate simulation results; among them, the simulation data generated during the simulation process is published to the digital twin east-west interface gateway through the streaming data processing engine; According to the user's intention, business requirements and the simulation results, generate an optimal configuration plan based on a preset decision algorithm; send the optimal configuration plan to the physical network through the physical layer southbound interface gateway; The physical network feeds back the configuration result. After confirming that the configuration takes effect, it returns the business request result to the application layer northbound interface gateway to complete the closed-loop control.

[0006] In some embodiments of the present invention, the physical layer southbound interface gateway continuously collects the real-time operation data of each node in the optical transport network through a passive or active reception mechanism, including: The passive reception mechanism adjusts the collection parameters according to the data type for collection; the collection parameters include collection frequency, collection point location, and collection time; The active reception mechanism adopts a subscription-based data access mechanism. The physical layer southbound interface gateway realizes interface adaptation with the physical network, and the physical layer southbound interface gateway actively obtains real-time operation data in batches from the nodes in the optical transport network.

[0007] In some embodiments of the present invention, storing the preprocessed real-time operation data includes: Perform protocol conversion on the collected real-time operation data to convert it into an encoding format suitable for the digital twin system; After the protocol conversion is completed, perform data preprocessing on the real-time operation data. The processing process includes operations such as standardization, denoising, verification, cleaning, compression, and feature extraction; After the preprocessing is completed, perform structured persistent storage on the real-time operation data.

[0008] In some embodiments of the present invention, after selecting the corresponding service based on the type of digital twin model selected by the user at the application layer and initiating a business request through the application layer northbound interface gateway, it further includes: Verify the identity information of the user. If the verification passes, verify the user's permission level to ensure that the user has the permission to initiate the business request; if the verification of the user's identity information or permission level fails, trigger an exception alarm and record it.

[0009] In some embodiments of the present invention, the method further includes an alarm mechanism, including: The management and control system monitors the event information on the physical network in real time, identifies the content related to the physical network and system failures, and tracks and generates alarm records; the event information on the physical network includes device failures, link interruptions, and performance degradation; The digital twin system monitors the event information of the digital twin application service instructions in real time, identifies abnormal events, and pushes the abnormal events to the management and control system, which generates alarm records; the event information of the digital twin application service instructions includes digital twin model creation, modification, deletion, simulation deduction, and data stream input; The alarm records are sent to the management personnel in a preset form to issue an alarm alert.

[0010] In some embodiments of the present invention, the simulation data generated during the simulation process is published to the digital twin east-west interface gateway through the streaming data processing engine, including: The simulation data is asynchronously sent to the digital twin east-west interface gateway through the distributed message queue system in the streaming data processing engine.

[0011] In some embodiments of the present invention, after the physical network feeds back the configuration result and confirms that the configuration takes effect, it returns the service request result to the application layer northbound interface gateway, and further includes: After the configuration takes effect, the management and control system generates a service status report, which is pushed to the application layer through the application layer northbound interface gateway to be fed back to the user; the service status report includes configuration change records and performance improvement indicators.

[0012] On the other hand, the present invention also provides a collaborative management system for digital twin and optical transport network management and control system based on multi-directional interfaces. When the system is executed, it realizes the steps of any one of the above-mentioned collaborative management methods for digital twin and optical transport network management and control system based on multi-directional interfaces. The system includes: A physical network, an application layer, a management and control system proxy module, a digital twin basic service module, and a multi-directional interface gateway; the multi-directional interface gateway includes a physical layer southbound interface gateway, an application layer northbound interface gateway, and a digital twin east-west interface gateway; Among them, the physical network is connected to the management and control system proxy module through the physical layer southbound interface gateway; the application layer is connected to the management and control system proxy module through the application layer northbound interface gateway; the digital twin basic service module is connected to the management and control system proxy module through the digital twin east-west interface gateway.

[0013] In some embodiments of the present invention, the system further includes a streaming data processing engine and a simulation and deduction decision-making center, and the digital twin basic service module further includes a distributed data storage unit, a real-time monitoring and warning unit, a distributed log collection unit, and a service support unit; Among them, the streaming data processing engine is used to analyze in real time the real-time operation data of each node in the physical network obtained by collection, and provide real-time operation data for the simulation and deduction of the digital twin business model; the simulation and deduction decision-making center is used to perform simulation and deduction on the digital twin business model.

[0014] On the other hand, the present invention also provides a computer-readable storage medium, on which a computer program / instructions are stored, and when the computer program / instructions are executed by a processor, the steps of any one of the methods mentioned above are implemented.

[0015] The present invention provides a method and system for collaborative management of digital twin and optical transport network management and control systems, including a multi-directional interface architecture of a physical layer southbound interface gateway, an application layer northbound interface gateway, and a digital twin east-west interface gateway, which supports efficient data interaction and instruction transmission between the physical layer, the application layer, and the digital twin system. The technical solutions cover the collection and processing of real-time data streams, the full life cycle management of digital twins, simulation and deduction and decision optimization, asynchronous communication of a distributed message queue system, identity authentication and permission management, and an intelligent warning mechanism. Through the multi-directional interface collaboration mechanism, the method realizes a complete closed-loop management and control from user intention definition, simulation and deduction, configuration distribution, real-time monitoring to optimization and adjustment. The method can significantly improve the collaboration efficiency and control accuracy between systems, meet the requirements of the optical transport network for real-time performance, dynamics, and high-concurrency data processing, support collaborative operations in a multi-vendor and multi-device environment, and provide an efficient and flexible solution for the intelligent management and optimization of the optical transport network.

[0016] The additional advantages, objects, and features of the present invention will be partially described below, and will become partially obvious to those of ordinary skill in the art after studying the following text, or can be learned from the practice of the present invention. The objects and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in the specification and the drawings.

[0017] Those skilled in the art will understand that the objects and advantages that can be achieved by the present invention are not limited to the above specifically described, and the above and other objects that the present invention can achieve will be more clearly understood according to the following detailed description. Description of the Drawings

[0018] The drawings described herein are used to provide a further understanding of the present invention, constitute a part of this application, and do not limit the present invention. In the drawings: Figure 1 Schematic diagram of steps of the collaborative management method of digital twin and optical transport network management and control system based on multi-directional interfaces in an embodiment of the present invention.

[0019] Figure 2 Schematic diagram of the structure of the collaborative management system of digital twin and optical transport network management and control system based on multi-directional interfaces in an embodiment of the present invention.

[0020] Figure 3 Flowchart of data collection by the southbound interface gateway of the physical layer in an embodiment of the present invention.

[0021] Figure 4 Sequence diagram of digital twin service model simulation and deduction in an embodiment of the present invention. Specific implementation manners

[0022] To make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in combination with the implementation manners and the drawings. Herein, the illustrative implementation manners and descriptions of the present invention are used to explain the present invention, but do not limit the present invention.

[0023] Herein, it also needs to be noted that in order to avoid obscuring the present invention due to unnecessary details, only the structures and / or processing steps closely related to the solution of the present invention are shown in the drawings, while other details less related to the present invention are omitted.

[0024] It should be emphasized that the term "including / comprising" when used herein refers to the presence of features, elements, steps or components, but does not exclude the presence or addition of one or more other features, elements, steps or components.

[0025] Herein, it also needs to be noted that if not specifically stated, the term "connection" in this article can not only refer to a direct connection, but also represent an indirect connection with an intermediate.

[0026] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the drawings, the same reference numerals represent the same or similar components, or the same or similar steps.

[0027] It should be emphasized here that the step labels mentioned hereinafter do not limit the sequence of each step. Instead, it should be understood that the steps can be executed in the sequence mentioned in the embodiments, or different from the sequence in the embodiments, or several steps can be executed simultaneously.

[0028] To address the problems existing in the existing control systems, such as insufficient support for capturing, processing, and analyzing real-time data streams, making it difficult to meet the requirements of digital twin optical transport networks for real-time performance, dynamicity, and high-concurrency data processing, and with a single interface design, resulting in low integration efficiency of data streams, control signaling, and network management, and being unable to effectively support collaborative operations in a multi-vendor and multi-device environment, the present invention provides a collaborative management method for a digital twin and an optical transport network control system based on multi-directional interfaces, as Figure 1 shown. The method includes the following steps S101 to S106: Step S101: Collect the real-time operation data of each node in the optical transport network through the physical layer southbound interface gateway; store the preprocessed real-time operation data, or perform real-time analysis using a streaming data processing engine.

[0029] Step S102: Select the corresponding service based on the type of digital twin model selected by the user at the application layer, and initiate a service request through the application layer northbound interface gateway to apply for creating a new digital twin model.

[0030] Step S103: The digital twin east-west interface gateway issues a creation instruction to create and instantiate a digital twin service model, generating an executable simulation model instance.

[0031] Step S104: Use the real-time operation data obtained by the streaming data processing engine and / or the pre-stored operation data to perform simulation deduction on the instantiated digital twin service model, generating a simulation result. Among them, the simulation data generated during the simulation process is published to the digital twin east-west interface gateway through the streaming data processing engine.

[0032] Step S105: Generate an optimal configuration plan based on the user's intention, service requirements, and simulation result according to a preset decision algorithm; issue the optimal configuration plan to the physical network through the physical layer southbound interface gateway.

[0033] Step S106: The physical network feeds back the configuration result. After confirming that the configuration takes effect, it returns the service request result to the application layer northbound interface gateway to complete the closed-loop control.

[0034] As Figure 2 shown, correspondingly to the above-mentioned collaborative management method for a digital twin and an optical transport network control system based on multi-directional interfaces, the present invention also provides a collaborative management system for a digital twin and an optical transport network control system based on multi-directional interfaces. The system includes a physical network, an application layer, a control system proxy module, a digital twin basic service module, and a multi-directional interface gateway. The multi-directional interface gateway includes a physical layer southbound interface gateway, an application layer northbound interface gateway, and a digital twin east-west interface gateway.

[0035] The physical network is connected to the management and control system proxy module through the southbound interface gateway of the physical layer; the application layer is connected to the management and control system proxy module through the northbound interface gateway of the application layer; the digital twin basic service module is connected to the management and control system proxy module through the digital twin east-west interface gateway.

[0036] To implement the above method, the system is also provided with a streaming data processing engine and a simulation and deduction decision-making center. The streaming data processing engine is used to analyze in real time the real-time operation data of each node in the physical network obtained by collection, and to provide real-time operation data for the simulation and deduction of the digital twin business model; the simulation and deduction decision-making center is used to perform simulation and deduction on the digital twin business model.

[0037] The following further explains in combination with the method and the system.

[0038] In step S101, the real-time operation data of each node in the optical transport network is collected through the southbound interface gateway of the physical layer; the preprocessed real-time operation data is stored, or is analyzed in real time by using the streaming data processing engine.

[0039] As Figure 3 shown, it is a flowchart of the southbound interface gateway of the physical layer collecting data.

[0040] The intelligent optical transport network and the digital twin system require richer, higher-frequency, and more accurate parameter sampling capabilities. The southbound interface gateway of the physical layer is deployed at each node of the optical transport network (i.e., the physical network) (including optical amplifiers, etc.). By deploying the gateway as the core collection module, it can realize seamless connection and efficient interaction with different types of devices and systems based on a variety of standardized data communication protocols, thereby significantly improving the flexibility and compatibility of data acquisition.

[0041] In some embodiments, in terms of software architecture design, the southbound interface gateway of the physical layer continuously collects the real-time operation data of each node in the optical transport network through a passive or active reception mechanism.

[0042] Among them, for different data types, the passive reception mechanism uses different collection methods. For example, for the setting of the collection frequency, the selection of the collection point, the selection of the collection time, etc., different collection methods need to be determined according to different application requirements. Specifically, for physical data with a lower change frequency, a low-frequency collection method is adopted, and for physical data with a higher change frequency, a high-frequency collection method is adopted. The real-time operation data can also be obtained by polling the gateway application programming interface (API).

[0043] In some embodiments, a lightweight and structured data format, such as JSON, etc., is adopted to improve the data transmission speed.

[0044] The active reception mechanism adopts a subscription-based data access mechanism. For example, by using Telemetry, it adapts the southbound interface gateway of the physical layer to the physical network. The southbound interface gateway of the physical layer actively obtains real-time operation data in batches from nodes in the physical network to ensure efficient processing of the massive data transmission requirements.

[0045] Furthermore, through the hierarchical processing mechanism of network element devices and the management and control system, unnecessary data transmission between the two is effectively reduced, optimizing the utilization rate of system resources. In addition, the platform can actively query the resource data, configuration data, performance data, and alarm data of devices from various manufacturers to ensure the timeliness and integrity of the data. By docking with diverse data interfaces of the gateway and devices, the consistency and effectiveness of the data acquisition platform and device real-time data are further ensured.

[0046] In some embodiments, protocol conversion and preprocessing operations are performed on the acquired real-time operation data, including: Convert the encoding format of the real-time operation data acquired from the physical network into the encoding format used in the digital twin system, usually converting a low-level communication protocol to a high-level communication protocol. Convert it to a unified format for subsequent processing. Specifically, after the southbound interface gateway of the physical layer acquires the real-time operation data, it identifies the packet header identifier to determine the source protocol type. Exemplarily, when identifying the Telemetry binary stream, it uses GPB (Google Protocol Buffers) for deserialization and parsing, and performs encoding format standardization conversion, uniformly converting the protocol data into the JSON structured format, and performing unit normalization processing on the optical parameters. At the same time, data tags can be added according to the actual situation, attaching a triple of timestamp, device ID, and address location to each data packet for convenient data classification.

[0047] After the protocol conversion is completed, data preprocessing is performed on the real-time operation data, including integration, standardization, denoising, removing abnormal data, verification, cleaning, compression, feature extraction, etc. Specifically, abnormal data is filtered, and data integrity verification is performed on the data. The batch reporting data packets are verified, and the data segments that fail the verification are discarded. For data packets missing key fields, a compensation acquisition mechanism is triggered. Based on the device topology relationship, the associated device status information is supplemented for isolated alarm events.

[0048] After the real-time operation data processing is completed, data registration and reporting are performed in the distributed message queue system through the management and control system proxy module, and unified scheduling is performed by the digital twin east-west interface gateway based on, for example, business priorities. This real-time operation data can be analyzed in real time through a streaming data processing engine or persistently stored by the distributed data storage unit in the digital twin basic service module.

[0049] In step S102, corresponding services are selected based on the type of digital twin model selected by the user at the application layer, and a service request is initiated through the northbound interface gateway of the application layer to apply for creating a new digital twin model.

[0050] In some embodiments, the types of digital twin models include device models, network element models, topology models, service models, performance prediction models, and performance optimization models. Among them, the device model is a virtual entity that constitutes various units of the optical transmission system and has various effects on transmission performance. It is the basis for the application of upper-layer models and includes various devices such as optical signals and devices in terms of physical attributes, material attributes, and resource attributes. The network element model is an abstract description of each network element in the optical transport network (such as switching nodes, routers, transmission devices, etc.), covering aspects such as the hardware, software, functions, and communication protocols of the network element. The topology model describes the physical or logical connection relationships between each network element in the optical transport network. It shows the connection structure between each network element and how data flows through links (optical fibers, transmission channels, etc.). The service model defines the types of services provided by the optical transport network, such as health assessment models, performance prediction models, transmission optimization models, fault simulation models, and dynamic configuration models. The performance prediction model is used to evaluate the main indicators of the optical transmission system performance, such as wave power, signal-to-noise ratio, Q value, and bit error rate BER, etc. The performance optimization model controls the model to generate device control configurations and configuration processes according to the optimized parameters and sends them to the device through the management and control platform.

[0051] In some embodiments, after selecting the corresponding service based on the type of digital twin model selected by the user at the application layer and initiating a service request through the northbound interface gateway of the application layer, the identity information of the user is verified. If the verification is passed, the user's permission level is verified to ensure that the user has the permission to initiate the service request.

[0052] At the same time, the management and control system proxy module can perform identity authorization and permission grading for different users, restrict the access and operation permissions of users to system data by adding, deleting users, and querying and modifying user attributes. The management and control system proxy module has a logging function for recording user login information, system operation logs, and alarm record logs. When the verification of the user's identity information or permission level fails, an exception alarm is triggered and recorded in the alarm record log.

[0053] After initiating the service request, the management and control system requests the digital twin east-west interface gateway to create a new service model and provides all necessary parameters. Specifically, the parameters required for creating a digital twin model vary according to the model category and model application scenario. For example, the parameters required for a device model may be configuration information such as optical fiber channels, optical transceivers, optical amplifiers, and ROADM.

[0054] Such as Figure 4As shown, it is a sequence diagram for the simulation and deduction of a digital twin business model, which includes steps S103 to S106.

[0055] In step S103, the digital twin east-west interface gateway initiates a creation instruction to create and instantiate a digital twin business model, generating an executable simulation model instance.

[0056] Based on the user's business request, the digital twin east-west interface gateway distributes the corresponding parameters of the digital twin business model to the digital twin basic service module, and the digital twin basic service module creates a digital twin business model for simulation and deduction.

[0057] Before simulation and deduction, model instantiation needs to be performed in the simulation and deduction decision center to generate an executable simulation model instance.

[0058] In some embodiments, the control system is notified to complete instantiation through an asynchronous callback mechanism.

[0059] In step S104, the real-time operation data obtained by the streaming data processing engine and / or the pre-stored operation data are used to perform simulation and deduction on the instantiated digital twin business model, generating a simulation result.

[0060] According to the algorithm, the digital twin model can be further divided into a machine learning digital twin model and a non-machine learning digital twin model. According to the user's intention and the algorithm type of the digital twin business model, the digital twin business model simulation instance can perform operations such as machine learning digital twin body training, machine learning digital twin body prediction and inference, and non-machine learning digital twin body prediction and inference in the simulation and deduction decision center. Specifically, for an untrained machine learning digital twin model, a machine learning digital twin model training operation can be performed, that is, training the machine learning model. For a trained machine learning digital twin model, a machine learning digital twin model prediction and inference operation can be performed, that is, performing a prediction and inference operation according to the trained machine learning model and applying its model corresponding function. For a non-machine learning digital twin model, a non-machine learning digital twin body prediction and inference operation can be performed, such as a calculation function.

[0061] During the simulation process, the data required for simulation can be defined as the following three types of data: real-time operation data, historical operation data, and hybrid data. Among them, real-time operation data refers to the real-time data stream obtained by the streaming data processing engine. By establishing a long connection channel between the real-time operation data and the distributed message queue system in the streaming data processing engine, real-time metric data streams such as optical power and bit error rate can be subscribed. Historical operation data refers to the structured data collected by the physical layer southbound interface gateway in step S101 and stored in the digital twin basic service module. The digital twin basic service module can be accessed through, for example, RESTful API, and the time range can be set to query and retrieve the historical performance data within that time range. Hybrid data refers to the simultaneous use of real-time operation data and historical operation data.

[0062] By default, the priority of real-time operation data is higher than that of historical operation data. When it is detected that the real-time operation data has a too high delay or abnormal data volume, or when historical operation data is selected according to the user's intention, the system automatically switches to the historical cache data.

[0063] When using dual-modal data (i.e., hybrid data) for simulation, the real-time data provides the network state at the current moment, while the historical data provides a more macroscopic background and trend information for the simulation. The combination of the two can help the simulation model make decisions within the short-term real-time and long-term historical ranges.

[0064] In some embodiments, the simulation data (such as training metrics, etc.) generated during the simulation is asynchronously sent to the digital twin east-west interface gateway through the distributed message queue system in the streaming data processing engine, and then fed back to the management and control system. Since the data is transmitted asynchronously, the management and control system can continue to perform other operations, such as configuration adjustment, alarm handling, etc., without causing system stagnation due to waiting for the simulation progress.

[0065] When the digital twin business model completes the simulation, the simulation model will return the final key performance indicators, which are obtained through the simulation and used to evaluate the effectiveness of network configurations or operation strategies. For example, the simulation model may return multiple indicators such as bandwidth utilization, network latency, device load, link failure rate, network reliability, etc.

[0066] In some embodiments, the user can download the data during the simulation process, including simulation data, simulation results, and the digital twin business model, through a preset instruction at the application layer.

[0067] In step S105, based on the user's intention, business requirements, and simulation results, an optimal configuration plan is generated based on a preset decision algorithm, completing multiple functions such as prediction, evaluation, and simulation of business requirements, and the optimal configuration plan is sent to the physical network through the physical layer southbound interface gateway by the management and control system proxy module.

[0068] Specifically, the current network performance status is extracted and analyzed from the simulation results to identify bottlenecks, inefficient resource usage, potential failure points, etc. in the network. According to the user's intention and business requirements, it may be required to optimize the bandwidth in certain areas, improve the network reliability, reduce latency, or support new network services. The simulation and deduction decision center recommends the optimal network configuration plan through decision algorithms. For example, the simulation results show that the bandwidth utilization of some links is close to full load, while there is idle bandwidth on other links. The decision algorithm can propose suggestions for bandwidth reallocation based on this information to optimize the resource allocation of the entire network. Based on the simulation results and decision algorithms, the simulation and deduction decision center will generate one or more possible network configuration plans. Each plan optimizes different objectives (such as bandwidth, latency, reliability, etc.) according to business requirements and simulation results. The simulation and deduction decision center will recommend the network configuration plan that best meets the user's needs according to the optimized objectives and constraints. For example, if the user's goal is to minimize latency, the optimal configuration plan may be to reduce the traffic passing through high-latency links by adjusting the traffic routing.

[0069] Among them, the decision algorithm is the key technology to realize the optimization from user requirements to the physical network. This decision algorithm automatically generates the optimal network configuration plan based on the user's business requirements and network performance goals, and verifies the effectiveness of the plan through simulation and deduction, ultimately realizing the closed-loop management from the prediction, evaluation, simulation of user requirements to the reconfiguration of the physical network. The core function of the decision algorithm is to generate a configuration plan that can optimize the physical network performance according to the business requirements and network goals (such as bandwidth requirements, latency optimization, improvement of network reliability, etc.) input by the user, combined with the deduction results of the simulation model.

[0070] In step S106, after the physical network feeds back the configuration result and confirms that the configuration takes effect, it returns the service request result to the northbound interface gateway of the application layer to complete the closed-loop control.

[0071] Specifically, in step S105, the optimal configuration plan is obtained based on the simulation results and decision algorithms, such as adjusting bandwidth allocation, optimizing traffic paths, adjusting network topology, etc. This plan has been optimized through decision-making and can meet the user's business requirements.

[0072] The management and control system proxy module receives the optimal configuration plan recommended by the digital twin east-west interface gateway and distributes the optimal configuration plan to the physical network through the physical layer southbound interface gateway. Exemplarily, the management and control system proxy module sends the optimal configuration plan to the physical layer southbound interface gateway in a standardized format (such as a protocol packet). The physical layer southbound interface gateway parses the received optimal configuration plan according to the protocol and gradually transmits it to each device in the physical network (such as optical transmission devices, switches, routers, etc.). During the configuration distribution process, the physical layer southbound interface gateway will ensure the data integrity of the configuration to ensure that each device receives the correct configuration.

[0073] Devices in the physical network (such as switches, fiber routers, terminal devices, etc.) will perform corresponding operations according to the configuration plan distributed by the physical layer southbound interface gateway. For example, adjust the routing path, optimize the traffic flow direction, and reduce network latency. When the physical layer southbound interface gateway receives feedback information from the physical network, it will summarize the results and confirm with the management and control system proxy module whether the configuration takes effect. If a device fails to successfully apply the configuration during the configuration process, the interface gateway will provide failure information, including the device that was not successfully configured, the reason for the failure, etc., so that the management and control system can take corresponding remedial measures.

[0074] After the management and control system proxy module confirms that the configuration takes effect, it returns the service provisioning request result to the application layer northbound interface gateway. The application layer northbound interface gateway pushes a service status report containing configuration change records and performance improvement metrics to the application layer where the user is located, completing the closed-loop management and control from digital twin deduction to physical network optimization.

[0075] Specifically, after the configuration takes effect, the management and control system proxy module will update the service status report and record the detailed information of the configuration change. These reports will be passed to the application layer northbound interface gateway and finally feedback to the user. The content of the report includes: Key performance indicators: such as bandwidth utilization rate, latency, network reliability, fault recovery time, etc.

[0076] Optimization effect comparison: Show the performance comparison before and after optimization to help users understand the actual effect of the optimization.

[0077] Implementation details: Provide the specific implementation steps and impact analysis of the configuration change to ensure that users can clearly understand how the optimization plan is implemented.

[0078] After receiving the service status report, users can put forward new requirements for further optimization of the network, or continue to make adjustments according to the performance metrics in the report to form a new optimization cycle. For example, if the report shows that some links still have high load, users may further adjust the bandwidth or routing strategy.

[0079] In some embodiments, the management and control system agent module can actively or passively monitor event information on the physical network in real time, identify content related to physical network and system failures, and track and generate alarm records. Among them, the fault event information on the physical network includes device failures, link interruptions, performance degradation, etc. And send network alarm alerts to management personnel in the form of alarm windows, text messages, or emails.

[0080] The digital twin system can actively or passively monitor event information of digital twin application service instructions in real time, such as digital twin model creation, modification, deletion, simulation deduction, data stream input, etc., identify abnormal events, and push the abnormal events to the management and control system agent module, which generates alarm records. Among them, abnormal events usually include model life cycle anomalies, such as model creation failure, model update anomalies, etc.; simulation deduction anomalies, such as real-time data stream interruption, numerical overflow, iteration non-convergence, etc.; data stream input and output anomalies, such as packet detection failure, data stream time sequence chaos, data violating business rules, etc.; system resource anomalies, such as insufficient memory resources, etc.; security anomalies, such as illegal identities, etc.; cross-system multi-directional interface collaboration anomalies, such as the physical layer southbound interface gateway control command being rejected by physical devices, the state difference between the digital twin and physical devices, etc.

[0081] Corresponding to the above method, the present invention also provides an electronic device, which includes a computer device. The computer device includes a processor and a memory. Computer instructions are stored in the memory, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the electronic device implements the steps of the method described above.

[0082] The embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the foregoing edge computing server deployment method. The computer-readable storage medium can be a tangible storage medium, such as a random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, register, floppy disk, hard disk, removable storage disk, CD-ROM, or any other form of storage medium well-known in the technical field.

[0083] Those of ordinary skill in the art should understand that the various exemplary components, systems, and methods described in connection with the embodiments disclosed herein can be implemented in hardware, software, or a combination of both. Specifically, whether to implement it in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention. When implemented in hardware, it can be, for example, an electronic circuit, an application-specific integrated circuit (ASIC), appropriate firmware, a plug-in, a functional card, and so on. When implemented in software, the elements of the present invention are programs or code segments used to perform the required tasks. The program or code segment can be stored in a machine-readable medium or transmitted through a data signal carried in a carrier wave over a transmission medium or a communication link.

[0084] It should be clear that the present invention is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and illustrated as examples. However, the method process of the present invention is not limited to the specific steps described and illustrated. Those skilled in the art can make various changes, modifications, and additions, or change the order between steps after understanding the spirit of the present invention.

[0085] In the present invention, the features described and / or exemplified for one embodiment can be used in the same or a similar manner in one or more other embodiments, and / or combined with the features of other embodiments or replace the features of other embodiments.

[0086] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, various changes and modifications can be made to the embodiments of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A collaborative management method of digital twin and optical transport network control system based on multi-directional interface, characterized in that: The method comprises the following steps: Collect the real-time operation data of each node in the optical transmission network through the physical layer southbound interface gateway; store the pre-processed real-time operation data, or use the streaming data processing engine for real-time analysis; Select the corresponding service based on the type of digital twin model selected by the user at the application layer, initiate a service request through the northbound interface gateway of the application layer, and apply to create a new digital twin model; The digital twin east-west interface gateway initiates a creation instruction to create and instantiate a digital twin business model to generate an executable simulation model instance; The real-time operation data and / or pre-stored operation data acquired by the streaming data processing engine are used to simulate and deduce the instantiated digital twin business model to generate simulation results; wherein the simulation data generated during the simulation process is published to the digital twin east-west interface gateway through the streaming data processing engine; According to the user intention, business requirements and the simulation results, an optimal configuration scheme is generated based on a preset decision algorithm; the optimal configuration scheme is sent to the physical network through the physical layer southbound interface gateway; The physical network feeds back the configuration result, and after confirming that the configuration is effective, returns the service request result to the application layer northbound interface gateway to complete the closed-loop control.

2. According to claim 1, the collaborative management method of digital twin and optical transport network control system based on multi-directional interface is characterized in that: The physical layer southbound interface gateway continuously collects real-time operation data of each node in the optical transmission network through a passive or active receiving mechanism, including: The passive receiving mechanism adjusts the acquisition parameters according to the data type for acquisition; the acquisition parameters include acquisition frequency, acquisition point location, and acquisition time; The active receiving mechanism adopts a subscription data access mechanism, and the interface adaptation is realized between the physical layer southbound interface gateway and the physical network. The physical layer southbound interface gateway actively obtains real-time operation data in batches from the nodes in the optical transmission network.

3. The collaborative management method of digital twin and optical transport network control system based on multi-directional interface according to claim 1 is characterized in that: The pre-processed real-time operation data is stored, including: Perform protocol conversion on the collected real-time operation data to convert it into a coding format suitable for the digital twin system; After the protocol conversion is completed, the real-time operation data is preprocessed, and the processing process includes standardization, denoising, verification, cleaning, compression and feature extraction operations; After the preprocessing is completed, the real-time operation data is stored in a structured and persistent manner.

4. The collaborative management method of digital twin and optical transport network control system based on multi-directional interface according to claim 1 is characterized in that: Based on the type of digital twin model selected by the user at the application layer, the corresponding service is selected. After the service request is initiated through the application layer northbound interface gateway, it also includes: The user's identity information is verified. If the verification passes, the user's authority level is verified to ensure that the user has the authority to initiate the service request; if the user's identity information or authority level verification fails, an abnormal alarm is triggered and recorded.

5. The collaborative management method of digital twin and optical transport network control system based on multi-directional interface according to claim 1 is characterized in that: The method is also provided with an alarm mechanism, including: The management and control system monitors event information on the physical network in real time, identifies content related to the physical network and system failures, and tracks and generates alarm records; The digital twin system monitors the event information of the digital twin application service instructions in real time, identifies abnormal events, and pushes the abnormal events to the management and control system, which generates alarm records; the event information of the digital twin application service instructions includes digital twin model creation, modification, deletion, simulation deduction, and data stream input; The alarm record is sent to the management personnel in a preset form to issue an alarm.

6. The collaborative management method of digital twin and optical transport network control system based on multi-directional interface according to claim 1 is characterized in that: The simulation data generated during the simulation process is published to the digital twin east-west interface gateway through the streaming data processing engine, including: The simulation data is asynchronously sent to the digital twin east-west interface gateway through a distributed message queue system in the streaming data processing engine.

7. The collaborative management method of digital twin and optical transport network control system based on multi-directional interface according to claim 1 is characterized in that: The physical network feeds back the configuration result, and after confirming that the configuration is effective, returns the service request result to the application layer northbound interface gateway, further comprising: After the configuration takes effect, the management and control system generates a business status report, which is pushed to the application layer via the application layer northbound interface gateway for feedback to the user; the business status report includes configuration change records and performance improvement indicators.

8. A collaborative management system of digital twin and optical transport network control system based on multi-directional interface, characterized in that: When the system is executed, the steps of the collaborative management method of the digital twin and the optical transport network control system based on the multi-directional interface according to any one of claims 1 to 7 are implemented, and the system includes: Physical network, application layer, management and control system proxy module, digital twin basic service module and multi-directional interface gateway; the multi-directional interface gateway includes a physical layer southbound interface gateway, an application layer northbound interface gateway and a digital twin east-west interface gateway; Among them, the physical network is connected to the management and control system agent module through the physical layer southbound interface gateway; the application layer is connected to the management and control system agent module through the application layer northbound interface gateway; the digital twin basic service module is connected to the management and control system agent module through the digital twin east-west interface gateway.

9. The collaborative management system of digital twin and optical transport network control system based on multi-directional interface according to claim 8, characterized in that: The system also includes a streaming data processing engine and a simulation deduction decision center, and the digital twin basic service module also includes a distributed data storage unit, a real-time monitoring alarm unit, a distributed log collection unit, and a service support unit; Among them, the streaming data processing engine is used to analyze the real-time operation data of each node in the physical network collected in real time, and provide real-time operation data for the simulation and deduction of the digital twin business model; the simulation and deduction decision center is used to simulate and deduce the digital twin business model.

10. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method as claimed in any one of claims 1 to 7 are implemented.

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