Network management control method, network management control system, network system, and storage medium

Abstract

The present invention provides a network management control method, a system therefor, a network system, and a storage medium, the method including the steps of: acquiring DT model data corresponding to physical objects in a physical network (S110); generating DT cases having different hierarchies based on the DT model data, where the hierarchies of the DT cases correspond to the hierarchies of the physical objects and there is a functional cooperative relationship between the DT cases having different hierarchies (S120); obtaining a target analysis result based on the cooperative relationship and all the DT cases (S130); and generating network configuration information based on the target analysis result, distributing the network configuration information to the physical network, and allowing the physical network to perform network management control based on the network configuration information (S140).

Description

[Technical field]

[0001] This application is filed based on a Chinese patent application bearing application number 202110326389.9 and filing date March 26, 2021, and claims priority to the Chinese patent application, the entire contents of which are hereby incorporated by reference into this application.

[0002] The present application relates to the field of network communications, but is not limited thereto, and in particular to a network management control method, a system thereof, a network system, and a storage medium. [Background technology]

[0003] With the development of communication technology, transmission networks are faced with the current situation of diversifying resources, widening coverage, and complex deployment environment. At the same time, with the advent of the digital transformation era, transmission services are also rapidly developing toward agile operations and virtualization of network functions. Under the background of increasingly complex and diverse hardware equipment and digital technologies in transmission networks, in order to realize highly efficient intelligent management of self-optimization, self-repair, and autonomy of networks, it is necessary to rely on systematic and accurate real-time digital analysis technology, carry out digital model abstraction for complex network systems, build a multi-dimensional network digital simulation system that can integrate the actual network system, working mechanism, management control, and maintenance method, and use artificial intelligence (AI) technology to carry out real-time dynamic feedback, evaluation optimization, simulation and prediction of the working status of the actual physical network, thereby laying the digital analysis foundation for highly efficient intelligent management of networks.

[0004] Digital Twin (DT) technology can create high-fidelity digital virtual models of physical objects, simulate the behavior of physical objects, depict the working state of physical objects, and realize the fusion of digital information and physical objects. When DT technology is applied to network communications, it can extract necessary network data from the transmission network and combine AI technology with requirements to build a Digital Twin case (DT case) model, thereby realizing functions such as analysis, optimization, and simulation prediction of the transmission network.

[0005] In practical application, it is necessary to construct DT cases of corresponding hierarchies for different analysis objects, and perform intelligent management control for the transmission network based on the analysis results of the DT cases. However, in a transmission network, objects corresponding to DT cases of different hierarchies may be associated with each other, for example, the failure of a certain functional module is the fundamental failure that causes an alarm or interruption of the transmission network. Therefore, how to consider the coordination relationship between DT cases of different hierarchies is the key to improving the dynamic detection ability and digital analysis ability of the network system. Summary of the Invention [Problem to be solved by the invention]

[0006] The following provides a summary of the subject matter described in detail herein, which is not intended to limit the scope of protection of the claims.

[0007] SUMMARY OF THE DISCLOSURE The embodiments of the present application provide a network management control method, a network system, and a storage medium, which can improve the dynamic detection capability and digital analysis capability of a network system. [Means for solving the problem]

[0008] In a first aspect, the present embodiment comprises: A network management control method applied to a network management control system, comprising: obtaining digital twin DT model data corresponding to physical objects in a physical network; A step of generating a digital twin case DT case having different hierarchies based on the DT model data, where the hierarchy of the DT case corresponds to the hierarchy of a physical object, and there is a functional coordination relationship between the DT cases having different hierarchies; obtaining a target analysis result based on the collaboration relationship and all the DT cases; generating network configuration information based on the target analysis result, distributing the network configuration information to the physical network, and allowing the physical network to perform network management control based on the network configuration information.

[0009] In a second aspect, the present embodiment comprises: A network management control method applied to a data acquisition device communicatively connected to a network management control system, comprising: generating DT model data corresponding to physical objects in a physical network; The method includes a step of transmitting the DT model data to the network management control system, the network management control system generating network configuration information based on the DT model data, and distributing the network configuration information to a physical network, so that the physical network performs network management control based on the network configuration information, wherein the network configuration information is generated by the network management control system based on a purpose analysis result, the purpose analysis result is obtained by the network management control system based on all DT cases having a cooperative relationship and different hierarchies, the DT cases having different hierarchies are generated by the network management control system based on the DT model data, the hierarchy of the DT case corresponds to the hierarchy of a physical object, and there is a functional cooperative relationship between the DT cases having different hierarchies.

[0010] In a third aspect, an embodiment of the present application provides a network management control system including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor realizing the network management control method described in the first aspect when it executes the computer program.

[0011] No. 4 In an aspect, the present embodiments include A network system is provided that includes a network management control system for executing the network management control method described in the first aspect, and a data acquisition device for executing the network management control method described in the first aspect, wherein the network management control system and the data acquisition device are communicatively connected.

[0012] Other features and advantages of the present application will be set forth in the following specification, and in part will be obvious from the specification, or may be learned by the practice of the present application. The objectives and other advantages of the present application may be attained by the structure particularly pointed out in the specification, claims, and drawings. The drawings are used to provide a further understanding of the technical solution of the present application, constitute a part of the specification, and are used to explain the technical solution of the present application together with the embodiments of the present application, and are not intended to limit the technical solution of the present application. [Brief description of the drawings]

[0013] [Figure 1] 2 is a flowchart of a network management control method applied to a network management control system according to an embodiment of the present application. [Diagram 2] 11 is a flow chart for obtaining DT model data according to another embodiment of the present application; [Diagram 3] 11 is a flowchart for generating a DT case according to another embodiment of the present application; [Figure 4] 4 is a flowchart for obtaining a target analysis result according to another embodiment of the present application; [Diagram 5] 11 is a flowchart of a process based on an AI algorithm according to another embodiment of the present application. [Figure 6] 11 is a flowchart for determining a management control scenario according to another embodiment of the present application. [Figure 7] 11 is a flowchart for implementing synchronous updating of DT model data according to another embodiment of the present application; [Figure 8] 4 is a flowchart illustrating how to obtain and display network status information according to another embodiment of the present application. [Figure 9] 4 is a flowchart of a network management control method applied to a data acquisition device according to another embodiment of the present application. [Figure 10] 11 is a flowchart for generating DT model data according to another embodiment of the present application. [Figure 11] 13 is a flowchart for updating DT model data according to another embodiment of the present application; [Figure 12] 1 is a structure of an OTN system to which a network management control method according to another embodiment of the present application is applied. [Figure 13] 1 is a flow chart of Example 1 according to another embodiment of the present application. [Figure 14] 1 is a flow chart of Example 2 according to another embodiment of the present application. [Figure 15] FIG. 2 is an apparatus diagram of a network management control system according to another embodiment of the present application. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be described in more detail below with reference to the drawings and examples. Note that the specific examples described in this specification are only used to interpret the present application, and are not used to limit the present application.

[0015] It should be noted that although a functional module division is shown in the schematic diagram of the device and a logical order is shown in the flowchart, the steps shown or described may, in some cases, be performed out of the order shown in the modular division of the device or in the flowchart. The terms "first," "second," etc. in the specification, claims, or the foregoing drawings are not used to describe a particular order or priority, but are used to distinguish between similar objects.

[0016] The present application provides a network management control method, its system, network system, and storage medium. The network management control method includes the steps of: obtaining DT model data corresponding to a physical object in a physical network; generating digital twin cases DT cases having different hierarchies based on the DT model data, where the hierarchies of the DT cases correspond to the hierarchies of the physical objects, and there is a functional collaboration relationship between the DT cases having different hierarchies; obtaining a target analysis result based on the collaboration relationship and all the DT cases; generating network configuration information based on the target analysis result, and distributing the network configuration information to a physical network, so that the physical network performs network management control based on the network configuration information. The scheme according to the embodiment of the present application can realize network management control based on the DT cases and the collaboration relationship, and can improve the dynamic detection ability and digital analysis ability of the network system.

[0017] It should be noted that the network management control method according to the embodiments of the present application can be applied to any network system, such as an Optical Transport Network (OTN), a Packet Transport Network (PTN), a Packet Optical Transport Network (POTN), etc. For ease of explanation, the embodiments of the present application take the application to an OTN system as an example to explain the technical solution, and those skilled in the art are capable of applying the technical solution of the embodiments of the present application to other network systems, and this does not limit the patent scope of the present application.

[0018] In addition, the network management control system may be a device with multiple functional modules. For example, in order to realize the management control function, the network management control system may be provided with functional modules such as a database, a processor, and an actuator according to actual needs, and the specific type of device may be determined according to the specific network system. For example, for a hierarchical digital twin OTN (HDTON), the network management control system may be an HDTON intelligent management control system for managing and controlling the HDTON. In addition, in order to realize the generation of the DT case, the HDTON intelligent management control system may be provided with an HDTON case scheduler as a controller and a Software Defined Optical Network (SDON) system as an actuator. In addition, an AI algorithm engine library that stores multiple pre-set AI algorithms is provided to accommodate various management control scenarios. Of course, the above SDON system, HDTON case scheduler, and AI algorithm engine library may be devices that operate independently in the actual network configuration, and may be installed in various physical devices or physical equipment, as long as they can be functionally assembled into a network management control system. In addition, the above device is an example for explaining the network management control system, and those skilled in the art are motivated to add or remove functional modules corresponding to the network management control system according to actual needs, and this embodiment is not limited to this.

[0019] Hereinafter, the embodiments of the present application will be further described with reference to the drawings.

[0020] As shown in Figure 1, Figure 1 is a network management control method according to an embodiment of the present application applied to a network management control system, the network management control method includes but is not limited to the following steps:

[0021] Step S110: Obtain DT model data corresponding to a physical object in a physical network.

[0022] The physical network may be any network system, and it is sufficient that there is a subordinate relationship between physical objects in multiple layers in the physical network, and a functional cooperative relationship. For example, in an OTN system, the ODU business of the entire network is composed of multiple optical data units (ODUs), and the traffic throughput prediction result of the ODU node has a certain effect on the optimization simulation of the entire network ODU business, so when performing the optimization simulation of the entire network ODU business, it is necessary to integrate the traffic throughput prediction for each ODU node, and in this embodiment, the physical network to which the network management control method is applied is not particularly limited.

[0023] A physical object may be a specific physical device or a system of multiple physical devices. For example, in an OTN system, a physical object may be the entire OTN, an optical module in the OTN, or each ODU node in the OTN, and the physical object may be determined according to specific needs.

[0024] It should be noted that the specific content of the DT model data can be determined according to the physical object actually required. For example, when it is necessary to perform fault analysis on an OTN network optical module, the acquired DT model data can include the OTN network topology, the whole network optical channel (OCH) optical layer service distribution in the OTN network topology, and the optical module data in each reconfigurable optical add-drop multiplexer (ROADM) node in the OTN network topology, and the embodiment does not particularly limit the specific type of the DT model data. The DT model data can be obtained from the physical network according to the specific data requirements of the network management and control system. According to digital twin technology, corresponding parameters and attributes can be extracted from the physical network to construct a high-fidelity digital virtual model to form the DT model data, so that the DT model data can reflect the actual operating conditions of the physical network in real time, and the accuracy of the evaluation and prediction of the network system can be improved.

[0025] Step S120: Based on the DT model data, a digital twin case DT case with different hierarchies is generated, the hierarchy of the DT case corresponds to the hierarchy of the physical object, and there is a functional coordination relationship between the DT cases with different hierarchies.

[0026] In addition, the layer can represent the scale or scope of influence of the physical object in the physical network corresponding to the DT case. For example, in the case of an OTN system, the physical object with the highest layer may be the entire OTN network, and the physical object with the lowest layer may be an optical module in the OTN network. The correspondence between the size of a specific physical object and the height of the layer can be adjusted according to actual needs, and is not particularly limited.

[0027] The hierarchy of the generated DT case corresponds to the hierarchy of the physical object. For example, if the physical object is an OTN network and its hierarchy is at the network level, the hierarchy of the DT case corresponding to the OTN network generated based on the DT model data is also at the network level.

[0028] In addition, in a physical network, there is usually a dependency relationship between physical objects of different scales, that is, a physical object corresponding to a DT case of a higher hierarchy is usually assembled by or composed of physical objects corresponding to a DT case of a lower hierarchy. For example, a physical object corresponding to a DT case of a higher hierarchy is a ROADM node, and a physical object corresponding to a DT case of a lower hierarchy is an optical module, and a ROADM node is usually composed of an optical module. Therefore, physical objects having a dependency relationship are also functionally in a cooperative relationship. For example, when predictively analyzing a DT case corresponding to a ROADM node, it is necessary to integrate the results of failure prediction of the optical module belonging to the ROADM node. Due to the cooperative relationship, when predictively analyzing a DT case of a higher hierarchy, the analysis results of the DT case of a lower hierarchy can be integrated, and the accuracy of the final target analysis result can be improved.

[0029] Note that the DT case may be generated after acquiring the DT model data in order to confirm that a corresponding DT case exists when performing collaboration analysis, and this will not be described in detail later.

[0030] Step S130: Obtain a target analysis result based on the collaboration relationship and all DT cases.

[0031] In addition, since DT cases can maintain their working state even after they are generated, predictive analysis can be performed once for each DT case, and then nested analysis can be performed based on the cooperative relationship to obtain the target analysis result, or a DT case at a higher level can perform integrated analysis after receiving the analysis result reported by a DT case at a lower level, and the analysis result obtained from the DT case at the highest level can be used as the target analysis result, that is, cooperative analysis is realized by a trigger mechanism.The specific method can be selected according to actual needs, as long as it can realize cooperative analysis between DT cases.

[0032] In actual applications, there is usually a coordination relationship between DT cases corresponding to dependent physical objects. For example, the failure of an optical module in an existing network is often the root cause of an OTN network fault alarm or business interruption due to the optical module failure. Such coordination and propagation relationships between local and global networks in actual existing networks are also reflected in Digital Twin OTN (DTON), so a coordination relationship exists between the network-level fault analysis DT case and the optical module-level fault prediction DT case.

[0033] Step S140: Generate network configuration information based on the target analysis result, and distribute the network configuration information to the physical network so that the physical network performs network management control based on the network configuration information.

[0034] In addition, a physical network is generally a collection of physical devices, and needs to be managed and controlled through a general intelligent management and control system, for example, a physical network is controlled through a general SDON system. In this embodiment, the specific intelligent management and control system is not particularly limited.

[0035] The network configuration information may be any type of information that allows the physical network to realize network management control by adjusting the operating parameters. For example, in the case of an OTN system, if the target analysis result is the analysis result of the disconnection and re-routing optimization of the ODU business of the whole network, the SDON system can generate corresponding network configuration information according to the processing requirements such as re-routing optimization of related business and node capacity expansion for the current OTN network.

[0036] Also, as shown in FIG. 2, in one embodiment, step S110 in the embodiment shown in FIG. 1 includes, but is not limited to, the following steps S210 and S220.

[0037] Step S210: A management control scenario is determined, and a data request is determined according to the management control scenario.

[0038] Step S220: In response to the data request, obtain DT model data corresponding to the physical object in the physical network.

[0039] In addition, the management control scenario may be a scenario that needs to reflect the management control needs of a network, such as a network service scenario that reflects the business needs of a user, or a network analysis scenario that reflects the detection and analysis needs of a physical network, but this is not particularly limited in this embodiment.

[0040] Through the management control scenario, the physical objects that need to collect data can be determined, so that the specific data requirements can be determined and the efficiency of data processing can be improved. For example, if it is determined that the management control scenario is an OTN network traffic analysis scenario, the DT model data of the OTN network business needs to be obtained from the physical network, which may include the OTN network topology, the whole network ODU business distribution in the network topology, the traffic throughput of each node, etc. Once the data requirements are determined, the hierarchy of the DT cases that need to be constructed is also determined. For example, in the above OTN network traffic analysis scenario, it is necessary to construct a network-level DT case to correspond to the ODU business of the whole network, and a node-level DT case to correspond to each ODU node, and the above network level and node level are one example of the hierarchy and do not limit the specific selection of the hierarchy.

[0041] To further embody the hierarchy to which the physical objects correspond, when constructing the DT model data, a hierarchical digital twin (HDT) model data format can be adopted, in which the data level is predetermined according to the height of the hierarchy. For example, in the above OTN network traffic analysis scenario, the OTN network topology and the entire network ODU service distribution in the network topology are taken as network-level data, and the traffic throughput of each node is taken as node-level data, so that the DT case container levels of various data can be quickly identified from the HDT model data.

[0042] Also, as shown in FIG. 3, in one embodiment, step S120 in the embodiment shown in FIG. 1 includes, but is not limited to, the following step S310.

[0043] Step S310: generate DT cases in target DT case containers with different container levels according to the DT model data and the hierarchy of the physical objects, the target DT case container is determined from the pre-defined DT case containers according to the management control scenario and the hierarchy of the physical objects, the DT case container generates and manages the DT cases, and the corresponding DT cases generated by the DT case containers with different container levels are Container Level are different from each other.

[0044] In addition, in order to facilitate the management of the DT case container, an HDTON case scheduler may be provided in the intelligent management control system. At least two DT case containers may be pre-provided in the HDTON case scheduler. After determining the management control scenario, the HDTON case scheduler determines the data requirements and obtains the DT model data, and then determines at least two target DT case containers from the pre-defined DT case containers, and generates DT cases in the target DT case containers.

[0045] In addition, the specific container level may be determined according to actual needs. For example, a high-level DT case container, a middle-level DT case container, and a low-level DT case container may be provided according to the network level, device level, and element level of the hierarchy, and each container level may correspond to one hierarchy, so that the DT case hierarchies generated by the DT case containers of different hierarchies correspond to different hierarchies, and this embodiment is not particularly limited thereto.

[0046] It should be noted that, referring to the description of the embodiment shown in Fig. 2, the data request may be determined by the determined target DT case container. For example, referring to the above DT case container level, if it is determined that analysis from the network level and the element level is required according to the management control scenario, it is necessary to generate corresponding DT cases by a high-level DT case container and a low-level DT case container. In this case, a data request can be generated according to the data required by each target DT case container. After the DT model data is obtained, each target DT case container obtains the data of the corresponding level from the DT model data and generates a DT case according to the obtained DT model data, thereby ensuring the availability and accuracy of the obtained data.

[0047] In addition, the DT case container may be used to generate DT cases, or may be used to manage DT cases. For example, it is possible to perform analysis processing of DT cases using AI algorithms, or to obtain intermediate analysis results reported from DT case containers having lower container levels to perform collaborative analysis, and it is also possible to increase or decrease the functions that can be realized for a DT case according to actual needs. In this embodiment, there is no particular limitation on this.

[0048] The target DT case container to be used is not necessarily different for different management control scenarios. For example, in one scenario, it is necessary to use all the pre-configured DT case containers, while in another scenario, it is necessary to use only the DT case containers of some container levels, and it is determined according to the actual needs of the management control scenario. In this embodiment, there is no specific limit to the number.

[0049] Also, as shown in FIG. 4, in one embodiment, step S130 in the embodiment shown in FIG. 1 includes, but is not limited to, the following steps S410 and S420.

[0050] Step S410: Based on the collaboration relationship and the container level corresponding to the target DT case container, apply processing based on an AI algorithm to the DT case generated by the target DT case container having a lower container level to obtain an interim analysis result, report the interim analysis result to the target DT case container having a higher container level, and apply processing based on an AI algorithm to the DT case generated by the target DT case container having a higher container level based on the interim analysis result to obtain a collaboration analysis result.

[0051] Step S420: The collaboration analysis result obtained in the target DT case container having the highest container level is determined as the target analysis result.

[0052] There is a functional cooperative relationship between physical objects corresponding to DT cases of different hierarchies, and the hierarchies of DT cases generated by DT cases and containers of different container levels are different from each other, so that the container levels may correspond to hierarchies. In addition, the cooperative processing usually uses the analysis results obtained by the DT cases of lower hierarchical levels to obtain the analysis results in cooperation with the DT cases of higher hierarchical levels, so that the intermediate analysis results can be reported sequentially in ascending order of container levels. After the target DT case container with a higher container level receives the intermediate analysis results, it integrates the analysis results and performs processing based on the AI ​​algorithm on the DT cases generated by the DT case container. The resulting cooperative analysis results include both the analysis results of the hierarchy corresponding to the target DT case container and the analysis results of the DT cases of lower hierarchies with cooperative relationships, and finally the cooperative relationships between the DT cases of all related hierarchies are integrated into the target analysis results, thereby improving the dynamic detection and digital analysis capabilities of the network system.

[0053] Note that "having a higher container level" and "having a lower container level" described in step S420 are determined based on a cooperative relationship, not on a container level. For example, in some management control scenarios, when only a low-level DT case container and a high-level DT case container are involved, in step S420, the target DT case container having a higher container level is a high-level DT case container, and the target DT case container having a higher container level is a low-level DT case container. In addition, in some management control scenarios, when a low-level DT case container, a medium-level DT case container, and a high-level DT case container are involved at the same time, the target DT case container that first performs processing based on an AI algorithm on a DT case is a low-level DT case container, that is, a target DT case container having a lower container level in the first operation, and the corresponding target DT case container having a higher container level is a medium-level DT case container. Similarly, when a medium-level DT case container performs processing based on an AI algorithm on a DT case, the medium-level DT case container is a target DT case container having a lower container level, and the high-level DT case container is a target DT case container having a higher container level. After the highest-level target DT case container performs processing based on the AI ​​algorithm on the DT case, the collaborative analysis result obtained in this highest-level target DT case container is determined as the target analysis result, thereby coordinating the collaborative analysis results by hierarchy and improving the referability of the data.

[0054] The collaborative analysis results can include the results of the corresponding DT case processed based on the AI ​​algorithm, as well as all lower-level intermediate analysis results, making the collaborative analysis results richer in data.

[0055] In addition, the target analysis result can be a collaborative result obtained by the highest-level target DT case container performing processing based on an AI algorithm on the DT case. After the target analysis result is obtained, the highest-level DT case container reports the target analysis result to the SDON system for generating network configuration information, thereby ensuring that the generated network configuration information can take into account DT cases at all hierarchies in a collaborative manner.

[0056] In some embodiments, one DT case container may have multiple DT case containers with lower container levels, in which case one DT case container may receive multiple interim analysis results at the same time. In order to avoid contention, a time threshold may be set to put the DT case container with a higher container level into a receiving state within a certain period of time, stop receiving the interim analysis results after that period, and perform processing based on an AI algorithm on the DT case, and coordinate to receive all interim analysis results within that period. Alternatively, other methods may be used, for example, all interim analysis results may be re-coordinated each time one interim analysis result is received when processing based on an AI algorithm is performed on the DT case. This embodiment is not limited to this, and a specific judgment method may be selected according to actual needs.

[0057] Also, as shown in FIG. 5, in one embodiment, step S420 in the embodiment shown in FIG. 4 includes, but is not limited to, the following steps S510 and S520.

[0058] Step S510: Determine a target AI algorithm from a preset AI algorithm library according to a supervisory control scenario.

[0059] Step S520: Analyze and process the DT case according to the target AI algorithm.

[0060] In addition, the AI ​​algorithm library can be in the form of a database, and the corresponding target AI algorithm can be matched through the management control scenario. The number of AI algorithms in the AI ​​algorithm library can be arbitrary and can be increased or decreased according to actual needs.

[0061] The AI ​​algorithm library may include any type of AI algorithm, such as a Reinforcement Learning (RL) algorithm, a Convolution Neural Network (CNN), a Deep Neural Network (DNN), a Graph Convolution Network (GCN), or a Recurrent Neural Network (RNN). Those skilled in the art are motivated to increase or decrease the types of AI algorithms according to actual needs. In addition, the above AI algorithms are preset, and the embodiments of the present application do not include a specific algorithm training process, which will not be described in detail here.

[0062] Different management control scenarios require different operations. Therefore, by setting multiple AI algorithms in the AI ​​algorithm library and determining a specific target AI algorithm through the management control scenario, it is possible to ensure that the optimal AI algorithm processes the corresponding DT case. In addition, the correspondence between the management control scenario and the target AI algorithm can be set in advance. For example, in response to the demand for an end-to-end OTN high-end leased line service optimized based on the intended delay required by the user, the OTN topology scale is determined according to the management control scenario, and the algorithm with the best calculation effect is the Reinforcement Learning (RL) algorithm as a result of matching analysis.

[0063] The target AI algorithm can be determined once when each DT case container processes a DT case based on an AI algorithm so that each DT case container can process the DT case using the optimal AI algorithm. Of course, one target AI algorithm can be determined under the same cooperative relationship, and the same target AI algorithm can be adopted each time the DT case container processes a DT case based on an AI algorithm under that cooperative relationship. The specific method can be selected according to actual needs.

[0064] Also, as shown in FIG. 6, in one embodiment, step S210 in the embodiment shown in FIG. 2 includes, but is not limited to, the following steps S610 and S620.

[0065] Step S610: obtain the current working state of the physical network, and determine a management control scenario according to the working state and the preset management information; or

[0066] Step S620: Obtain an administration control request, and determine an administration control scenario based on the administration control request.

[0067] It should be noted that the management control scenario may include a network analysis scenario and a network service scenario, where the network analysis scenario is determined according to a network analysis demand, and the network analysis demand is a demand for a user to perform fault prediction, operation state analysis or inquiry on a current physical network, which may be generated by a user sending demand information to the network management control system through a client, or the network management control system may generate it by itself based on the management goal of self-inspection, self-optimization and self-repair of the physical network, which is not particularly limited in this embodiment.

[0068] A network service scenario can be generated based on a service demand of a user. For example, an OTN intelligent network management control application (APP) communicatively connected to the network management control system is configured, and the service demand of the user for the OTN network is obtained through the OTN intelligent network management control APP. The service demand may be Bandwidth On Demand (BOD), Multi-Layer Optimization (MLO), Service-Level Agreement (SLA), Optical Virtual Private Network (OVPN), Intent-Based Optical Network (IBON), etc. The specific type of the service demand may be determined based on the actual network resources, and will not be described in detail here.

[0069] Moreover, as shown in FIG. 7, in one embodiment, before performing step S140 in the embodiment shown in FIG. 1, the following step S710 is further included, but is not limited thereto.

[0070] Step S710: upon obtaining new DT model data reported by the physical network after performing network management control based on the network configuration information, regenerate the network configuration information based on the new DT model data.

[0071] When the network management control according to the network configuration information is completed, the relevant parameters of the physical objects of the physical network will change, that is, the relevant parameters in the DT model data will also change, and in order to ensure the correspondence between the DT model data and the parameters of the physical objects of the physical network, the DT model data is updated according to the new physical network data after the network management control of the physical network is completed, so that the next DT case generation can be based on the latest DT model data. Furthermore, by updating the DT model data to trigger the generation of further DT cases, the entire network management control can be made into a closed loop, and the DT cases can be constantly updated within the life cycle of the DT model data, and the target analysis results can be determined, which effectively improves the dynamic detection ability.

[0072] As shown in FIG. 8, in one embodiment, after executing step S140 in the embodiment shown in FIG. 1, the following step S810 is included, but is not limited thereto.

[0073] Step S810: Obtain and display network status information of the physical network after the network management control is completed.

[0074] In addition, the acquired network status information may be displayed through the OTN intelligent network management control APP described in the embodiment of Figure 6, or may be displayed through other devices communicably connected to the network management control system, as long as the user can intuitively grasp the current working status of the physical network. In addition, the network status information may be content related to the physical network, for example, for an OTN system, the network status information may include real-time OTN network topology, OTN network service working status, network performance status, network resource availability status, etc., and the specific display content may be selected according to actual needs.

[0075] The network status information may be acquired and displayed in real time, and may be displayed in the OTN intelligent network management and control APP according to the needs of users, which is not particularly limited in this embodiment.

[0076] As shown in FIG. 9, FIG. 9 illustrates a network management control method applied to a data acquisition device communicatively connected to a network management control system according to one embodiment of the present application, which includes, but is not limited to, the following steps S910 and S920.

[0077] Step S910: Generate DT model data corresponding to a physical object in a physical network.

[0078] In addition, for the network management control system, SDON can realize the functions of management control of the physical network, such as dynamic management control of end-to-end OTN business in the OTN system, network topology management, OTN business fault protection, etc., but SDON cannot directly obtain DT model data from the physical network, so the data acquisition device in the embodiment of the present application may be a device for obtaining data from the physical network and generating DT model data. The specific entity of the device may be any entity, and this embodiment is not limited to this, as long as it can realize the corresponding function.

[0079] In addition, the data acquisition device may acquire DT model data from the physical OTN network according to the needs of the HDTON case scheduler, report the acquired DT model data to the HDTON case scheduler, and each DT case container may generate a DT case based on the DT model data.

[0080] Step S920: Send the DT model data to a network management control system, so that the network management control system generates network configuration information based on the DT model data, and distributes the network configuration information to the physical network, so that the physical network performs network management control based on the network configuration information. The network configuration information is generated by the network management control system based on the objective analysis result. The objective analysis result is obtained by the network management control system based on the collaboration relationship and all DT cases with different hierarchies. All DT cases with different hierarchies are generated by the network management control system based on the DT model data. The hierarchy of the DT case corresponds to the hierarchy of the physical object, and there is a functional collaboration relationship between the DT cases with different hierarchies.

[0081] It should be noted that the method and principle of the network management control system generating the DT case and the network configuration information may refer to the description of the embodiment shown in Fig. 1. Similarly, the specific description of the hierarchy and collaboration relationship may also refer to the description of the embodiment shown in Fig. 1, and for the sake of simplicity, a detailed description will not be given here.

[0082] Also, as shown in FIG. 10, in one embodiment, step S910 in the embodiment shown in FIG. 9 includes, but is not limited to, the following steps S1010 and S1020.

[0083] Step S1010: Obtain a data request delivered by a network management control system; the data request is received by the network management control system; Pipe It is determined according to the management control scenario.

[0084] Step S1020: In response to the data request, generate DT model data corresponding to the physical objects in the physical network.

[0085] The specific method and principle of generating the data request may be referred to the description of the embodiment shown in FIG. 2, and for the sake of simplicity, they will not be described in detail here.

[0086] In addition, the data request may be delivered to the data acquisition device by the HDTON case scheduler of the network management control system. Based on the specific data request, the data acquisition device uses digital twin technology to determine a physical model of a physical object in a physical network, obtains required parameters and attributes from the physical model, and extracts DT model data from the obtained parameters and attributes, thereby ensuring that the DT model data is consistent with the parameters of the physical object in the actual physical network.

[0087] Moreover, as shown in FIG. 11, in one embodiment, after performing step S1020 in the embodiment shown in FIG. 10, the following steps S1110 and S1120 are included, but are not limited thereto.

[0088] Step S1110: If a change in the physical parameters and / or physical attributes of a physical object is detected in the life cycle of the DT model data, the DT model data is updated based on the changed physical object.

[0089] Step S1120: Synchronize the updated DT model data with the network management control system, so that the network management control system obtains network configuration information based on the updated DT model data.

[0090] In addition, the life cycle of the DT model data is from determining the management control scenario to the physical network completing the network management control, or the set operating period. The specific form is selected according to actual needs, as long as it can maintain the consistency of the corresponding physical model of the DT model data within the life cycle.

[0091] By maintaining real-time synchronization of the DT model data within the life cycle of the DT model data, it is possible to ensure that the acquired DT model data can reflect the real-time parameters of the physical objects of the current physical network, so that the obtained target analysis results can reflect the actual network situation and ensure the dynamic detection capability of the network.

[0092] The change in the physical parameter and / or physical attribute may be a numerical change, a change in data collected within one collection period, or an attribute may be newly added or removed, etc. In this embodiment, specific changes are not particularly described.

[0093] In the following, with reference to the configuration of the OTN system shown in FIG. 12, the technical solution of the embodiment of the present application will be further illustrated by way of two specific management control scenarios.

[0094] In addition, the OTN system shown in FIG. 12 includes an OTN transmission plane and an HDTON intelligent management control system, and a communication connection between the OTN intelligent network management control APP and the HDTON intelligent management control system is provided. The HDTON intelligent management control system is provided with an SDON system, an HDTON case scheduler, and an AI algorithm engine library. The HDTON case scheduler is pre-provided with a high-level DT case container, a mid-level DT case container, and a low-level DT case container. The AI ​​algorithm engine library includes an application scenario analysis adapter and some pre-trained AI algorithms. The OTN transmission plane includes a physical network including a plurality of physical devices, and a DT model in which a digital model corresponding to the physical devices is constructed. In addition, the above components may be physical devices or functional modules having corresponding functions, and the specific implementation form is not particularly limited in this embodiment. In addition, the above devices are examples selected for convenience of explanation, and do not limit the technical proposal of the present application.

[0095] Example 1: As shown in FIG. 13, in an OTN network traffic analysis application scenario, the network management control method includes, but is not limited to, the following steps S1310 to S1370.

[0096] Step S1310: The HDTON case scheduler obtains OTN network traffic DT model data from the OTN transmission plane based on the OTN network traffic analysis requirements, where the OTN network traffic DT model data includes: an OTN network topology, a whole network ODU service distribution in the OTN network topology, and a traffic throughput of each ODU node.

[0097] Step S1320: After obtaining the OTN network traffic DT model data, the HDTON case scheduler DTs the ODU operations in the entire network OTN topology in the high-level DT case container, generates a network-level ODU operation DT case, and DTs the traffic throughput of each ODU node in the mid-level DT case container, and individually creates and generates a traffic throughput DT case for each ODU node.

[0098] Step S1330: The mid-level DT case container obtains an AI algorithm from the AI ​​algorithm engine library through the scenario analysis adapter according to an OTN network traffic analysis application scenario, and builds and trains an ODU node traffic throughput prediction model for each ODU node traffic throughput DT case, where the ODU node traffic throughput DT case obtains a traffic throughput prediction result within a specified prediction period of the ODU node based on its own ODU node traffic throughput prediction model, and obtains a capacity expansion analysis result for the DT case in which the traffic throughput increases and approaches the exchange capacity of this ODU node.

[0099] Step S1340: The mid-level DT case container reports the traffic throughput prediction result of each ODU node traffic throughput DT case to the corresponding network-level ODU service DT case in the high-level DT case container, and the network-level ODU service DT case performs a disconnection and re-routing optimization simulation for the ODU service carried by the ODU node requiring capacity expansion processing based on the prediction result of the traffic throughput of the ODU node according to the DT case of the switching capacity of each ODU node and the capacity expansion analysis result, where the disconnection and re-routing optimization simulation includes the following steps: The high-level DT case container obtains an AI algorithm from the AI ​​algorithm engine library through the scenario analysis adapter based on the OTN network traffic analysis application scenario, and for the ODU service that is the target of disconnection and re-routing optimization in the network-level ODU service DT case, performs the optimization calculation of a single ODU service according to the optimization strategy of each ODU service, or performs the simultaneous optimization calculation of multiple ODU services, and obtains the whole network ODU service distribution simulation effect after optimization, and records it in the network-level ODU service DT case.

[0100] Step S1350: The high-level DT case container notifies the SDON system via the HDTON case scheduler of all recorded ODU node information that requires capacity expansion analysis as a result of the disconnection and rerouting optimization analysis of the entire network ODU service performed by the network-level ODU service DT case in step S1340.

[0101] Step S1360: Based on the disconnection / rerouting optimization analysis results obtained in step S1350 and all recorded ODU node information requiring capacity expansion analysis, the SDON system performs rerouting optimization and node capacity expansion processing for related business for the current OTN physical network of the OTN transmission plane.

[0102] Step S1370: After the management control of the OTN physical network is completed, update the OTN network traffic DT model data, and execute step S1310 again. In addition, the traffic throughput may include the up / down traffic and through traffic of the ODU node, and may be selected according to actual needs.

[0103] The traffic throughput prediction result may be a traffic throughput value for any period, such as the average value and peak value of the traffic throughput for the next 15 days, or the average value and peak value of the traffic throughput for the next month, etc. In this embodiment, there is no particular limitation thereon.

[0104] In addition, the disconnection and re-routing optimization analysis result obtained in step S1340 may be an optimal time window for re-routing optimization in which business re-optimization arrangement is performed with minimal impact on the operation of the existing network OTN physical network of the OTN transmission plane.

[0105] Example 2: In the OTN network optical module failure prediction application scenario, the network management control method includes, but is not limited to, the following steps S1410 to S1470.

[0106] Step S1410: The HDTON case scheduler obtains OTN network optical module failure analysis DT model data from the OTN transmission plane in response to an OTN network optical module failure analysis request, where the OTN network optical module failure analysis DT model data includes: an OTN network topology, a whole network OCH optical layer service distribution in the OTN network topology, and optical module data at each ROADM node in the OTN network topology.

[0107] Step S1420: After obtaining the OTN network optical module failure analysis DT model data, the HDTON case scheduler DTs the OCH optical layer service in the whole network OTN topology in the high-level DT case container to generate a network-level OCH optical layer service DT case, and DTs the optical module data in each ROADM node in the low-level DT case container to individually create and generate a failure prediction DT case for each optical module in each ROADM node.

[0108] Step S1430: The low-level DT case container obtains an AI algorithm from the AI ​​algorithm engine library through the scenario analysis adapter according to an application scenario of an OTN network optical module failure prediction, and builds and trains an optical module failure prediction model for each optical module failure prediction DT case in each ROADM node, where each optical module failure prediction DT case predicts the time window of this module failure occurrence based on its own optical module failure prediction model, and obtains a replacement analysis result for the optical module predicted to fail.

[0109] Step S1440: The low-level DT case container reports the replacement analysis result of the optical module predicted to fail to the corresponding network-level OCH optical layer service DT case in the high-level DT case container. Based on the conclusion of each optical module failure prediction analysis, the network-level OCH optical layer service DT case performs a disconnection and rerouting optimization simulation for the OCH optical layer service carried by the optical module in the ROADM node that needs to be replaced due to the failure. Here, the disconnection and rerouting optimization simulation specifically includes the following steps: The high-level DT case container obtains an AI algorithm from the AI ​​algorithm engine library through the scenario analysis adapter according to the OTN network optical module failure prediction application scenario, and performs a single OCH optical layer service optimization calculation or a simultaneous optimization calculation of multiple OCH optical layer services for the OCH optical layer service that is the target of disconnection and rerouting optimization caused by the optical module failure prediction in the network-level OCH optical layer service DT case according to the optimization strategy of each OCH optical layer service, and obtains the whole network OCH optical layer service distribution simulation effect after optimization, and records it in this network-level OCH optical layer service DT case.

[0110] Step S1450: The high-level DT case container notifies the SDON system via the HDTON case scheduler of all recorded ROADM node optical module information that requires failure prediction replacement as a result of the disconnection and rerouting optimization analysis of the entire network OCH optical layer service performed by the network-level OCH optical layer service DT case in step S1440.

[0111] Step S1460: Based on the analysis results of the optimization of disconnection and rerouting of the OCH optical layer services of the entire network obtained in step S1450 and the recorded information of all ROADM node optical modules requiring failure prediction replacement, the SDON system performs related OCH optical layer service rerouting optimization and optical module failure prediction replacement processing for the current OTN physical network of the OTN transmission plane.

[0112] Step S1470: After the management and control of the OTN physical network is completed, update the OTN network optical module failure analysis DT model data, and execute step S1410 again.

[0113] The optical module data in each ROADM node may be modeled data for failure prediction, such as optical module input / output power, laser bias current, optical module temperature, etc. Here, there is no particular limitation.

[0114] The traffic throughput forecast result is the optimal time window for re-routing optimization, where business re-optimization placement of the OTN transmission plane with minimal impact on the operation of the existing network OTN physical network is performed.

[0115] Also, as shown in FIG. 15, an embodiment of the present application further provides a network management control system 1500 including a memory 1510, a processor 1520, and a computer program stored on the memory 1510 and executable on the processor 1520.

[0116] The processor 1520 and the memory 1510 may be connected via a bus or other means.

[0117] Non-transitory software programs and instructions necessary to realize the network management control method of the above embodiment are stored in memory 1510, and when executed by processor 1520, the network management control method applied to network management control system 1500 of the above embodiment is performed, for example, method steps S110 to S140 of Figure 1, method steps S210 to S220 of Figure 2, method step S310 of Figure 3, method steps S410 to S420 of Figure 4, method steps S510 to S520 of Figure 5, method steps S610 to S620 of Figure 6, method step S710 of Figure 7, and method step S810 of Figure 8 are performed.

[0118] The embodiment of the present application includes the steps of: obtaining DT model data corresponding to physical objects in a physical network; generating digital twin cases DT cases having different hierarchies based on the DT model data, where the hierarchies of the DT cases correspond to the hierarchies of the physical objects, and there is a functional collaboration relationship between the DT cases having different hierarchies; obtaining a target analysis result based on the collaboration relationship and all the DT cases; generating network configuration information based on the target analysis result, distributing the network configuration information to the physical network, and allowing the physical network to perform network management control based on the network configuration information. According to the scheme of the embodiment of the present application, network management control can be realized based on the DT cases having different hierarchies and the collaboration relationship, and the dynamic detection ability and digitalization analysis ability of the network system can be improved.

[0119] The above described device embodiment is merely schematic, and the units described as separate components may or may not be physically separated, i.e., located in one place or distributed in multiple network units. Some or all of these modules may be selected to achieve the purpose of the scheme of the embodiment according to actual needs.

[0120] Moreover, an embodiment of the present application further provides a computer-readable storage medium, in which computer-executable instructions are stored, and the computer-executable instructions are executed by a processor or controller. For example, when the computer-executable instructions are executed by one processor of the above embodiments, the processor is caused to execute a network management control method applied to the network management control system of the above embodiments, such as method steps S110-S140 of FIG. 1, method steps S210-S220 of FIG. 2, method step S310 of FIG. 3, method steps S410-S420 of FIG. 4, method steps S510-S520 of FIG. 5, method steps S610-S620 of FIG. 6, method step S710 of FIG. 7, and method step S810 of FIG. 8, as described above; or, when executed by one processor of the above embodiments, the processor is caused to execute a network management control method applied to the data acquisition device of the above embodiments, such as method steps S910-S920 of FIG. 9, method steps S1010-S1020 of FIG. 10, and method steps S1110-S1120 of FIG. 11, as described above.

[0121] Those skilled in the art will appreciate that all or part of the steps in the methods, systems disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer readable medium, which may include computer storage media (or non-transitory media) and communication media (or transitory media). As known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (e.g., computer readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cartridge, magnetic tape, magnetic disk storage or other magnetic storage, or any other medium that can be used to store the desired information and that can be accessed by a computer. Additionally, as known to those skilled in the art, communication media typically includes computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transmission mechanism and may include any information delivery media.

[0122] Although the above describes preferred embodiments of the present application in detail, the present application is not limited to the above embodiments, and those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present application, and all of these equivalent modifications or substitutions are included in the scope defined by the claims of the present application.

Claims

1. A network management control method applied to a network management control system, comprising: determining a management control scenario and determining a data request in response to the management control scenario; In response to the data request, obtaining digital twin DT model data corresponding to a physical object in a physical network; A step of generating a digital twin case DT case having different hierarchies based on the DT model data, where the hierarchy of the DT case corresponds to the hierarchy of a physical object, and the DT cases having different hierarchies have a functional cooperative relationship with each other; obtaining a target analysis result based on the collaboration relationship and all the DT cases; generating network configuration information based on the target analysis result, distributing the network configuration information to the physical network, and causing the physical network to perform network management control based on the network configuration information.

2. The step of generating DT cases having different hierarchies based on the DT model data includes:

2. The method of claim 1, further comprising: generating a DT case in a target DT case container having a different container level based on the DT model data and a hierarchy of physical objects, the target DT case container being determined from among predefined DT case containers based on the management control scenario and the hierarchy of physical objects, the DT case container generating and managing the DT case, and the corresponding container levels of the DT cases generated by the DT case containers having different container levels are different from each other.

3. The step of obtaining a target analysis result based on the collaboration relationship and all the DT cases includes: Based on the collaboration relationship and the container level corresponding to the target DT case container, a DT generated by the target DT case container having a lower container level is A step of performing a process based on an artificial intelligence (AI) algorithm on the DT case to obtain an intermediate analysis result, reporting the intermediate analysis result to a target DT case container having a higher container level, and performing a process based on the AI ​​algorithm on the DT case generated by the target DT case container having the higher container level based on the intermediate analysis result to obtain a collaborative analysis result; and determining a collaboration analysis result obtained at a target DT case container having a highest container level as a target analysis result.

4. The process based on the AI ​​algorithm is: Determining a target AI algorithm from a preset AI algorithm library according to the management control scenario; and analyzing and processing the DT case by the target AI algorithm.

5. The step of determining a management control scenario comprises: obtaining a current operating state of the physical network, and determining the management control scenario based on the operating state and preset management information; or The method of claim 1 , comprising obtaining an administrative control request and determining the administrative control scenario based on the administrative control request.

6. prior to the step of distributing the network configuration information to the physical network and causing the physical network to perform network management control based on the network configuration information; The method of claim 1 , further comprising the step of regenerating the network configuration information based on new DT model data when new DT model data reported by the physical network after performing network management control based on the network configuration information is obtained.

7. After the step of distributing the network configuration information to the physical network and causing the physical network to perform network management control based on the network configuration information, The method of claim 1 , further comprising obtaining and displaying network status information of the physical network after network management control is completed.

8. A network management control method applied to a data acquisition device communicatively connected to a network management control system, comprising: obtaining a data request delivered by the network management control system, the data request being determined by the network management control system according to a management control scenario; generating DT model data corresponding to physical objects in a physical network in response to the data request; a step of transmitting the DT model data to the network management control system, the network management control system generating network configuration information based on the DT model data, and distributing the network configuration information to a physical network, so that the physical network performs network management control based on the network configuration information, wherein the network configuration information is generated by the network management control system based on a purpose analysis result, the purpose analysis result is obtained by the network management control system based on all DT cases having a cooperative relationship and different hierarchies, the DT cases having different hierarchies are generated by the network management control system based on the DT model data, a hierarchy of the DT case corresponds to a hierarchy of a physical object, and there is a functional cooperative relationship between the DT cases having different hierarchies.

9. After the step of generating DT model data corresponding to physical objects in a physical network, updating the DT model data based on the changed physical object when a change in a physical parameter and / or a physical attribute of the physical object is detected during the life cycle of the DT model data; 9. The method of claim 8, further comprising: synchronizing the updated DT model data with the network management control system, so that the network management control system obtains the network configuration information based on the updated DT model data.

10. A network management control system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the network management control method according to any one of claims 1 to 7 when it executes the computer program.

11. A network system comprising: a network management control system for executing the network management control method described in any one of claims 1 to 7; and a data acquisition device for executing the network management control method described in any one of claims 8 to 9, wherein the network management control system and the data acquisition device are communicatively connected.

12. A computer-readable storage medium storing computer-executable instructions for executing the network management control method according to any one of claims 1 to 7, or computer-executable instructions for executing the network management control method according to any one of claims 8 to 9.

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