Network cut verification method and device, electronic equipment, medium and program product

Abstract

The application provides a network slicing verification method and device, electronic equipment, medium and program product, which are applied to the technical field of communication. The method comprises the following steps: acquiring network data of a core network; constructing a digital twin network of the core network based on the network data; adjusting the digital twin network based on a network slicing scheme of the core network, and acquiring change information of target data of the digital twin network before and after the adjustment of the digital twin network, wherein the target data comprises at least one of network performance data, network alarm data and flow control parameter data; and verifying the network slicing scheme based on the change information of the target data. The method simulates the slicing scheme through the digital twin network, quantifies the slicing effect by using the data change, thereby determining whether the scheme is correct and whether it needs to be optimized, avoiding directly implementing high-risk operations in the real network, and being beneficial to guaranteeing the stability of the real network.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a network cutover verification method, apparatus, electronic device, medium, and program product. Background Technology

[0002] Network cutover refers to the adjustment, replacement, or upgrade of network equipment, lines, configurations, etc. in a communication network to achieve network optimization, expansion, transformation, or fault repair.

[0003] Network adjustments in a live network are primarily based on past cutover experience. However, for network cutover solutions that have never been implemented before, detailed contingency plans must be developed in advance and implemented step-by-step for verification. If these contingency plans are inadequate, network failures are highly likely. When a failure occurs, a rollback operation is required, and multiple rollbacks not only severely impact network stability but also negatively affect customer experience. Therefore, the network cutover verification methods in related technologies carry the risk of affecting network stability. Summary of the Invention

[0004] This application provides a network cutover verification method, apparatus, electronic device, medium, and program product to solve the problem of network stability in existing network cutover verification methods.

[0005] To solve the above-mentioned technical problems, this application is implemented as follows:

[0006] In a first aspect, embodiments of this application provide a network cutover verification method, the method comprising:

[0007] Obtain network data from the core network;

[0008] Construct a digital twin network of the core network based on the network data;

[0009] The digital twin network is adjusted based on the network cutover scheme of the core network, and the change information of the target data of the digital twin network before and after the adjustment of the digital twin network is obtained. The target data includes at least one of network performance data, network alarm data and flow control parameter data.

[0010] The network cutover scheme is verified based on the change information of the target data.

[0011] Optionally, the network data includes network topology data, network element performance data, and network configuration data;

[0012] The construction of the digital twin network of the core network based on the network data includes:

[0013] A network architecture model is constructed based on the network topology data;

[0014] A user data model is constructed based on the network element performance data;

[0015] A basic network element model is constructed based on the aforementioned network configuration data;

[0016] The basic network element model is embedded into the network architecture model, and the network usage characteristics of each user in the user data model are used to construct the digital twin network of the core network.

[0017] Optionally, the network topology data includes characteristic data of multiple network nodes, connection relationship data between network nodes, and attribute data of network links;

[0018] The construction of the network architecture model based on the network topology data includes:

[0019] Based on the characteristic data of the multiple network nodes, determine the type and function of the multiple network nodes;

[0020] Based on the types and functions of the multiple network nodes, and the connection relationship data between the network nodes, a network topology is constructed;

[0021] The attribute data of the network links are mapped to the network topology to obtain the network architecture model.

[0022] Optionally, constructing a user data model based on the network element performance data includes:

[0023] Based on the user identification data of the core network, the network element performance data associated with the same user identification in the network element performance data are integrated in chronological order to obtain the behavioral feature sequence associated with each user identification.

[0024] Feature extraction is performed on the behavioral feature sequence of each user to obtain the network usage features of each user;

[0025] A user data model is constructed based on the network usage characteristics of each user.

[0026] Optionally, the network configuration data includes hardware specification data and software version data of network element devices, and the network data also includes network operating status data;

[0027] The construction of the basic network element model based on the network configuration data includes:

[0028] Based on the hardware specification data, construct the hardware framework of the basic network element model;

[0029] Based on the software version data, configure the software functions of the basic network element model;

[0030] Based on the network operation status data, the real-time status of the basic network element model is determined.

[0031] Optionally, the method further includes:

[0032] Obtain the updated network data from the core network;

[0033] The digital twin network of the core network is synchronously updated and adjusted based on the updated core network data.

[0034] Optionally, verifying the network cutover scheme based on the change information of the target data includes:

[0035] Based on the pre-established mapping relationship between target data and the actual network data of the core network, the change information of the target data is mapped to the change information of the actual network data of the core network;

[0036] The network cutover scheme is verified based on the changes in the actual network data of the core network.

[0037] Optionally, after verifying the network cutover scheme based on the change information of the target data, the method further includes:

[0038] A data rollback operation is performed on the adjusted digital twin network to restore it to its state before the adjustment.

[0039] Optionally, after verifying the network cutover scheme based on the change information of the target data, the method further includes:

[0040] Based on the network cutover verification results, a network cutover report is generated;

[0041] Based on the network cutover report, network adjustment recommendations for the core network are output.

[0042] Secondly, embodiments of this application also provide a network cutover verification device, which includes:

[0043] The data acquisition module is used to acquire network data from the core network.

[0044] The network construction module is used to construct a digital twin network of the core network based on the network data;

[0045] The cutover simulation module is used to adjust the digital twin network based on the network cutover scheme of the core network, and to monitor the changes in target data of the digital twin network during the adjustment process. The target data includes at least one of network performance data, network alarm data, and flow control parameter data.

[0046] The cutover verification module is used to verify the network cutover scheme based on changes in the target data.

[0047] Thirdly, embodiments of this application also provide an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the network cutover verification method described above.

[0048] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the network cutover verification method described above.

[0049] Fifthly, a computer program product is provided, including computer instructions that, when executed by a processor, implement the steps of the network cutover verification method described above.

[0050] The network cutover verification method of this application includes acquiring network data of the core network; constructing a digital twin network of the core network based on the network data; adjusting the digital twin network based on the network cutover scheme of the core network, and acquiring the change information of target data of the digital twin network before and after the adjustment of the digital twin network, wherein the target data includes at least one of network performance data, network alarm data, and flow control parameter data; and verifying the network cutover scheme based on the change information of the target data. This application embodiment simulates the cutover scheme through a digital twin network, quantifies the cutover effect using data changes, and thereby determines whether the scheme is correct and whether optimization is needed, avoiding the direct implementation of high-risk operations in the real network, which is beneficial to ensuring the stability of the real network. Attached Figure Description

[0051] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a flowchart of the network cutover verification method provided in the embodiments of this application;

[0053] Figure 2 This is a structural diagram of a network cutover verification device provided in an embodiment of this application;

[0054] Figure 3 This is a structural diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0055] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0056] This application provides a network cutover verification method, which is applied to a network cutover verification device. Figure 1 This is a flowchart of the network cutover verification method provided in the embodiments of this application, such as... Figure 1 As shown, it includes the following steps:

[0057] Step 101: Obtain network data from the core network;

[0058] In this step, the data acquisition module of the network cutover verification device can obtain core network data from various data reporting systems. Core network data includes network topology data, network element performance data, network configuration data, network operating status data, core network workbench data, and wireless statistics data.

[0059] The data acquisition module includes a data aggregation unit and a data detection unit. The data aggregation unit is used to collect network data from the core network in real time. The data detection unit is specifically used to detect the connectivity status of the data aggregation unit and each data reporting system, as well as the accuracy of the data, to ensure that the data from the data reporting system can be aggregated in real time and accurately.

[0060] Step 102: Construct a digital twin network of the core network based on the network data;

[0061] In this step, the network construction module of the network cutover verification device can be used to construct a digital twin network of the core network based on network data. It should be noted that before using the network construction module to construct the digital twin network of the core network based on network data, the data processing module of the network cutover verification device can be used to process and clean the network data to convert it into a data format suitable for the digital twin network.

[0062] The construction of a digital twin network for the core network based on the aforementioned network data can be understood as creating a digital model in virtual space that is highly similar to the real core network, based on various types of network data generated during the actual operation of the core network, through data collection, processing, and analysis. This digital twin network can map the operating status of the core network in real time, including the working status of equipment, network traffic distribution, signal transmission paths, etc.

[0063] Step 103: Adjust the digital twin network based on the network cutover scheme of the core network, and obtain the change information of the target data of the digital twin network before and after the adjustment of the digital twin network. The target data includes at least one of network performance data, network alarm data and flow control parameter data.

[0064] In this step, the core network cutover scheme can be understood as a plan to modify, upgrade, or adjust the core network, as well as operations such as equipment replacement and line adjustment. A digital twin network can be understood as a virtual mirror network of the core network, capable of simulating and reflecting the operating state of the real network, allowing for various "destructive tests" without damaging the real network.

[0065] Network performance data can include bandwidth, latency, throughput, and other data; network alarm data can include alarm data for abnormal states such as device failure, link termination, and overload; flow control parameter data can include configuration parameters related to flow control (such as QoS priority, bandwidth limit, and flow policy).

[0066] The cutover module of the network cutover verification device can be used to simulate the implementation of the core network cutover scheme in the digital twin network. For example, if the core network cutover scheme is "to upgrade the core network equipment in a certain area and increase the bandwidth", then the cutover operation can be "rehearsed" in the digital twin network, such as modifying the configuration of virtual devices and simulating device replacement.

[0067] Record the original state of the digital twin network before the cutover scheme is implemented (e.g., current bandwidth 1Gbps, latency 50ms, no alarms). After the cutover scheme is implemented and simulated, collect the same data again (e.g., bandwidth is increased to 2Gbps, latency is reduced to 30ms, but new link alarms appear). Pay attention to the differences in data before and after the adjustment (e.g., whether performance is improved, whether new alarms are introduced, whether flow control parameters take effect as expected).

[0068] Step 104: Verify the network cutover scheme based on the change information of the target data.

[0069] In this step, the target data refers to the network performance data, network alarm data, and flow control parameter data mentioned earlier. Change information refers to the comparison results of these data before and after the digital twin network adjustment (i.e., simulating the implementation of the network cutover scheme). The core of verifying the network cutover scheme is to determine whether the scheme has achieved its expected goals and whether there are any potential problems by observing data changes. For example, whether network performance has improved after the cutover, whether alarms have decreased, and whether flow control parameters meet design expectations. This step can be performed using the cutover verification module of the network cutover device.

[0070] In one implementation, network data of the core network is acquired; a digital twin network of the core network is constructed based on the network data; the digital twin network is adjusted based on the network cutover scheme of the core network, and the change information of target data of the digital twin network before and after the adjustment of the digital twin network is acquired, wherein the target data includes at least one of network performance data, network alarm data, and flow control parameter data; the network cutover scheme is verified based on the change information of the target data.

[0071] In this implementation, a cutover scheme is simulated using a digital twin network, and the cutover effect is quantified by data changes. This allows for the determination of whether the scheme is correct and whether it needs optimization, avoiding the direct implementation of high-risk operations in the real network and helping to ensure the stability of the real network.

[0072] Optionally, the network data includes network topology data, network element performance data, and network configuration data;

[0073] The construction of the digital twin network of the core network based on the network data includes:

[0074] A network architecture model is constructed based on the network topology data;

[0075] A user data model is constructed based on the network element performance data;

[0076] A basic network element model is constructed based on the aforementioned network configuration data;

[0077] The basic network element model is embedded into the network architecture model, and the network usage characteristics of each user in the user data model are used to construct the digital twin network of the core network.

[0078] In one implementation, network topology data may include the physical or logical connections of the network, such as device locations, link connections, and routing paths; network element performance data may include the operating data of network elements (such as servers, switches, and routers) (such as CPU utilization, memory usage, and processing latency); and network configuration data may include the parameter configurations of network elements (such as IP addresses, bandwidth limits, and security policies).

[0079] Building a network architecture model based on network topology data can be understood as using network topology data to construct a "network skeleton" model, describing the overall structure of the network. The network architecture model is used to define the "spatial layout" of the digital twin network, such as which devices make up the core network, how these devices are connected, and what the data transmission paths are.

[0080] Building a user data model based on network element performance data can be understood as collecting network element performance data for each user (such as the load and latency of a server when user A is using the network) to construct a model that reflects "how users use the network." The user data model focuses on the "user perspective," such as the impact of different users' bandwidth requirements and service types on network performance, reflecting the personalized characteristics of network usage.

[0081] Building a basic network element model based on network configuration data can be understood as constructing a "digital model" of a single network element based on its configuration parameters (such as the initial settings and functional parameters of the device). The basic network element model is refined to the "individual characteristics" of each device, such as the bandwidth limit of a router or the security policy of a server, to ensure that the behavior of virtual network elements is consistent with that of real devices.

[0082] First, the "individual model" (basic network element model) of each network element is put into the "overall skeleton" (network architecture model) of the network to form the "hardware framework of the virtual network". Then, the "user usage characteristics" (user data model) drive this framework to simulate the impact of real user behavior on the network, thus obtaining the digital twin network of the core network.

[0083] In this implementation, through layered modeling and data integration, the digital twin network includes both the network's hardware architecture and configuration, and reflects the dynamic performance driven by user behavior, ultimately achieving a true simulation of the real core network.

[0084] Optionally, the network topology data includes characteristic data of multiple network nodes, connection relationship data between network nodes, and attribute data of network links;

[0085] The construction of the network architecture model based on the network topology data includes:

[0086] Based on the characteristic data of the multiple network nodes, determine the type and function of the multiple network nodes;

[0087] Based on the types and functions of the multiple network nodes, and the connection relationship data between the network nodes, a network topology is constructed;

[0088] The attribute data of the network links are mapped to the network topology to obtain the network architecture model.

[0089] In one implementation, the characteristic data of a network node may include the identifier and type of the network node, the connection relationship data between network nodes is used to determine which network nodes are connected to each other, and the attribute data of a network link may include the bandwidth and latency of the network link.

[0090] Based on the characteristic data of network nodes, determine the type (e.g., server, router) and function (e.g., data storage, data forwarding) of each node. Combining the types and functions of network nodes with their interconnection data, depict the layout and connection methods of each node in the network, forming the network topology. Add the attribute data of network links to the network topology, making the model include detailed information about nodes and links, thus obtaining a complete network architecture model.

[0091] When planning or expanding a network, a network architecture model can serve as a reference to help determine the location of new nodes, connection methods, and required link resources, thereby improving the efficiency and accuracy of network planning.

[0092] Optionally, constructing a user data model based on the network element performance data includes:

[0093] Based on the user identification data of the core network, the network element performance data associated with the same user identification in the network element performance data are integrated in chronological order to obtain the behavioral feature sequence associated with each user identification.

[0094] Feature extraction is performed on the behavioral feature sequence of each user to obtain the network usage features of each user;

[0095] A user data model is constructed based on the network usage characteristics of each user.

[0096] In one implementation, user identification data can be a unique identifier such as a user ID, International Mobile Subscriber Identity (IMSI), or Mobile Station International Subscriber Directory Number (MSISDN). Network element performance data can include metrics such as traffic, latency, connection status, and throughput of devices such as base stations, routers, and servers.

[0097] Using user identification data in the core network as a "link," data associated with the same user identifier is filtered from massive network element performance data and arranged in chronological order to form a sequence of the user's behavioral characteristics in the network. For example, user A downloads a file using the 5G network at 10:00 (corresponding to traffic data of base station A) and switches to Wi-Fi to browse the web at 11:00 (corresponding to connection data of router B). These data, after being associated with the user ID, are integrated into the user's behavioral sequence in chronological order.

[0098] The behavioral characteristic sequences of each user are analyzed, and key features reflecting the user's network usage habits (i.e., network usage characteristics) are extracted through data mining, machine learning, and other techniques. Network usage characteristics may include high-frequency usage periods, service preferences, periods of frequent network lag, and connection interruption frequency.

[0099] The extracted user network features are mapped onto a digital twin network to form a digital twin (i.e., a user data model) for each user. This model is a virtual mirror image of the real user's behavior in the network, including the user's historical behavioral patterns, real-time status, and potential needs.

[0100] In this implementation, the digital twin network needs to fully map the interaction relationship between "people-network-services" in the real network. The user data model integrates multi-dimensional network element performance data (such as the base station accessed by the user, the frequency band used, and the traffic generated) from the core network, access network, and terminal, and transforms every connection, service access, and state change of the user in the physical network into a "digital footprint" in the virtual space, so that the behavior of virtual users and real users is kept synchronized in real time.

[0101] Optionally, the network configuration data includes hardware specification data and software version data of network element devices, and the network data also includes network operating status data;

[0102] The construction of the basic network element model based on the network configuration data includes:

[0103] Based on the hardware specification data, construct the hardware framework of the basic network element model;

[0104] Based on the software version data, configure the software functions of the basic network element model;

[0105] Based on the network operation status data, the real-time status of the basic network element model is determined.

[0106] In one implementation, the hardware specification data of the network element device is used to describe the physical attributes of the network element device, such as device model, hardware parameters, and physical form. Hardware parameters include, for example, CPU model / core count, memory capacity, interface type / quantity, and power supply specifications. Physical form includes, for example, rack size and heat dissipation design. The software version data of the network element device is used to describe the software information running on the device, such as operating system version, service software version, and firmware version. Network operation status data may include real-time device operation data, such as CPU utilization, memory usage, and port traffic.

[0107] When constructing the basic network element model, the hardware framework is first built based on the hardware specifications. Then, software functions are configured based on the software version. On top of the hardware framework, the software logic for device operation is loaded to simulate the functions of the virtual network element. Finally, real-time collected operational status data is injected into the model to synchronize the state of the virtual network element with that of the physical device.

[0108] In this implementation, the digital twin network needs to simulate the end-to-end process of user services flowing through multiple network elements, and accurately constructing basic network element models is beneficial to the credibility of the overall simulation.

[0109] Optionally, the method further includes:

[0110] Obtain the updated network data from the core network;

[0111] The digital twin network of the core network is synchronously updated and adjusted based on the updated core network data.

[0112] In one implementation, the core network continuously generates new data during operation, and the digital twin network is a virtual mapping of the core network, simulating its various characteristics and behaviors. Once updated network data from the core network is acquired, the digital twin network needs to be updated and adjusted accordingly. For example, if a new server is added to the core network, a corresponding virtual server needs to be added to the digital twin network, with relevant parameters and connection relationships configured. Similarly, if the operating status of a network element in the core network changes, the status of the corresponding virtual network element in the digital twin network should be updated synchronously to reflect this change.

[0113] In this implementation, real-time updates to the digital twin network enable it to accurately reflect the actual state of the core network, thereby improving the accuracy of subsequent simulation cutovers.

[0114] Optionally, verifying the network cutover scheme based on the change information of the target data includes:

[0115] Based on the pre-established mapping relationship between target data and the actual network data of the core network, the change information of the target data is mapped to the change information of the actual network data of the core network;

[0116] The network cutover scheme is verified based on the changes in the actual network data of the core network.

[0117] In one implementation, the target data includes at least one of network performance data, network alarm data, and flow control parameter data. Network performance data may include data such as bandwidth, latency, and throughput; network alarm data may include alarm data for abnormal states such as device failure, link termination, and overload; flow control parameter data may include configuration parameters related to flow control (such as QoS priority, bandwidth limits, and flow policies). A pre-established correspondence (i.e., mapping relationship) between the target data and the actual network data in the core network is established. When the target data changes (e.g., the desired network bandwidth needs to be increased, or a new network alarm trigger condition is set), based on the established mapping relationship, this change information in the target data is converted into corresponding change information in the actual network data of the core network. For example, if the target data indicates an increase in the bandwidth of a link from 100Mbps to 200Mbps, the mapping relationship will determine the actual network data change information, such as what configuration modifications need to be made to the relevant devices in the actual network.

[0118] Based on the changes in the actual core network data obtained, we can determine whether the network cutover scheme is feasible, whether it will bring the expected results, and whether it will cause any potential problems.

[0119] In this implementation, simulations and verifications can identify potential problems with the cutover plan before actual network cutover, such as performance degradation, unreasonable alarm rules, and unbalanced traffic control. This avoids discovering problems only during actual cutover in a real network environment, thereby reducing the risk of network failures and the impact on services.

[0120] Optionally, after verifying the network cutover scheme based on the change information of the target data, the method further includes:

[0121] A data rollback operation is performed on the adjusted digital twin network to restore it to its state before the adjustment.

[0122] In one implementation, a data rollback operation is performed on the adjusted digital twin network. The data rollback operation restores the relevant data in the digital twin network to its state before the adjustment. For example, if the bandwidth parameter of a router in the digital twin network was previously adjusted from 100Mbps to 200Mbps, after performing the data rollback operation, the router's bandwidth parameter will revert back to 100Mbps, making the entire digital twin network identical to its state before the adjustment. This facilitates the implementation of the next network cutover plan in the digital twin network.

[0123] Optionally, after verifying the network cutover scheme based on the change information of the target data, the method further includes:

[0124] Based on the network cutover verification results, a network cutover report is generated;

[0125] Based on the network cutover report, network adjustment recommendations for the core network are output.

[0126] In one implementation, a cutover scheme is carried out in a digital twin network. After observing changes in actual network data, performance indicators, and equipment operating status in the core network, all verification results are compiled, analyzed, and summarized to form a network cutover report. This report may include the specific details of the cutover scheme, problems discovered during the verification process (such as equipment compatibility issues and performance degradation), before-and-after comparisons of various performance indicators, and an assessment of the feasibility of the cutover scheme.

[0127] Based on the completed network cutover report, its contents are analyzed and interpreted in depth. Based on the advantages and disadvantages of the cutover scheme presented in the report, the problems exposed during the verification process, and the impact on the overall network operation, specific network adjustment recommendations are proposed for the core network. These recommendations may include modifying and improving the cutover scheme, upgrading or replacing certain equipment, and adjusting network management policies to ensure better operation of the core network and meet business needs.

[0128] In this implementation, the network cutover report records the process and results of the cutover verification in detail, providing network administrators and decision-makers with comprehensive and accurate information. Based on this information, they can more scientifically assess the feasibility and potential risks of the network cutover plan, thereby making more rational decisions and avoiding losses and risks caused by blind decision-making.

[0129] See Figure 2 , Figure 2 This is a structural diagram of a network cutover verification device provided in an embodiment of this application. Figure 2 As shown, the network cutover verification device 200 includes:

[0130] Data acquisition module 201 is used to acquire network data from the core network;

[0131] Network construction module 202 is used to construct a digital twin network of the core network based on the network data;

[0132] The cutover simulation module 203 is used to adjust the digital twin network based on the network cutover scheme of the core network, and to monitor the changes in target data of the digital twin network during the adjustment process. The target data includes at least one of network performance data, network alarm data, and flow control parameter data.

[0133] The cutover verification module 204 is used to verify the network cutover scheme based on the changes in the target data.

[0134] Optionally, the network data includes network topology data, network element performance data, and network configuration data;

[0135] The network construction module includes:

[0136] A network architecture model building unit is used to build a network architecture model based on the network topology data.

[0137] The user data model construction unit is used to construct a user data model based on the network element performance data.

[0138] A basic network element model construction unit is used to construct a basic network element model based on the network configuration data.

[0139] An integration unit is used to embed the basic network element model into the network architecture model and to construct a digital twin network of the core network by utilizing the network usage characteristics of each user in the user data model.

[0140] Optionally, the network topology data includes characteristic data of multiple network nodes, connection relationship data between network nodes, and attribute data of network links;

[0141] The network architecture model building unit includes:

[0142] The first determining subunit is used to determine the type and function of the plurality of network nodes based on the feature data of the plurality of network nodes;

[0143] The first construction subunit is used to construct a network topology based on the types and functions of the plurality of network nodes and the connection relationship data between the network nodes;

[0144] The first mapping subunit is used to map the attribute data of the network links to the network topology to obtain the network architecture model.

[0145] Optionally, the user data model construction unit includes:

[0146] The first integration subunit is used to integrate the network element performance data associated with the same user identifier in the network element performance data according to the time sequence based on the user identifier data of the core network, so as to obtain the behavioral feature sequence associated with each user identifier.

[0147] The first extraction subunit is used to extract features from the behavioral feature sequence of each user to obtain the network usage features of each user.

[0148] The second construction subunit is used to construct a user data model based on the network usage characteristics of each user.

[0149] Optionally, the network configuration data includes hardware specification data and software version data of network element devices, and the network data also includes network operating status data;

[0150] The basic network element model construction model includes:

[0151] The third construction subunit is used to construct the hardware framework of the basic network element model based on the hardware specification data;

[0152] The first configuration subunit is used to configure the software functions of the basic network element model based on the software version data;

[0153] The second determining subunit is used to determine the real-time status of the basic network element model based on the network operation status data.

[0154] Optionally, the device further includes:

[0155] The data acquisition module is used to acquire the network data updated by the core network;

[0156] The network adjustment module is used to synchronously update and adjust the digital twin network of the core network based on the updated core network data.

[0157] Optionally, the network verification module includes:

[0158] The data mapping unit is used to map the change information of the target data to the change information of the actual network data of the core network based on the pre-established mapping relationship between the target data and the actual network data of the core network.

[0159] The scheme verification unit is used to verify the network cutover scheme based on the actual network data change information of the core network.

[0160] Optionally, the device further includes:

[0161] The network recovery module is used to perform a data rollback operation on the adjusted digital twin network to restore the digital twin network to its state before the adjustment.

[0162] Optionally, the device further includes:

[0163] The report generation module is used to generate network cutover reports based on the network cutover verification results.

[0164] A suggestion generation module is used to output network adjustment suggestions for the core network based on the network cutover report.

[0165] This application also provides an electronic device. Since the principle by which the electronic device solves the problem is similar to the network cutover verification method in this application, the implementation of this electronic device can be found in the implementation of the method, and repeated details will not be described again. Figure 3 As shown, the electronic device in this embodiment includes a processor 300, configured to read a program from a memory 320 and execute the following processes:

[0166] Obtain network data from the core network;

[0167] Construct a digital twin network of the core network based on the network data;

[0168] The digital twin network is adjusted based on the network cutover scheme of the core network, and the change information of the target data of the digital twin network before and after the adjustment of the digital twin network is obtained. The target data includes at least one of network performance data, network alarm data and flow control parameter data.

[0169] The network cutover scheme is verified based on the change information of the target data.

[0170] Among them, Figure 3 In this context, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits together, represented by one or more processors (processor 300) and memory (memory 320). The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. A bus interface provides the interface. Processor 300 is responsible for managing the bus architecture and general processing, and memory 320 can store data used by processor 300 during operation.

[0171] Optionally, the network data includes network topology data, network element performance data, and network configuration data;

[0172] The processor 300 is used to read the program in the memory 320 and execute the following processes:

[0173] A network architecture model is constructed based on the network topology data;

[0174] A user data model is constructed based on the network element performance data;

[0175] A basic network element model is constructed based on the aforementioned network configuration data;

[0176] The basic network element model is embedded into the network architecture model, and the network usage characteristics of each user in the user data model are used to construct the digital twin network of the core network.

[0177] Optionally, the network topology data includes characteristic data of multiple network nodes, connection relationship data between network nodes, and attribute data of network links;

[0178] The processor 300 is used to read the program in the memory 320 and execute the following processes:

[0179] Based on the characteristic data of the multiple network nodes, determine the type and function of the multiple network nodes;

[0180] Based on the types and functions of the multiple network nodes, and the connection relationship data between the network nodes, a network topology is constructed;

[0181] The attribute data of the network links are mapped to the network topology to obtain the network architecture model.

[0182] Optionally, the processor 300 is configured to read the program from the memory 320 and execute the following processes:

[0183] Based on the user identification data of the core network, the network element performance data associated with the same user identification in the network element performance data are integrated in chronological order to obtain the behavioral feature sequence associated with each user identification.

[0184] Feature extraction is performed on the behavioral feature sequence of each user to obtain the network usage features of each user;

[0185] A user data model is constructed based on the network usage characteristics of each user.

[0186] Optionally, the network configuration data includes hardware specification data and software version data of network element devices, and the network data also includes network operating status data;

[0187] The processor 300 is used to read the program in the memory 320 and execute the following processes:

[0188] Based on the hardware specification data, construct the hardware framework of the basic network element model;

[0189] Based on the software version data, configure the software functions of the basic network element model;

[0190] Based on the network operation status data, the real-time status of the basic network element model is determined.

[0191] Optionally, the processor 300 is configured to read the program from the memory 320 and execute the following processes:

[0192] Obtain the updated network data from the core network;

[0193] The digital twin network of the core network is synchronously updated and adjusted based on the updated core network data.

[0194] Optionally, the processor 300 is configured to read the program from the memory 320 and execute the following processes:

[0195] Based on the pre-established mapping relationship between target data and the actual network data of the core network, the change information of the target data is mapped to the change information of the actual network data of the core network;

[0196] The network cutover scheme is verified based on the changes in the actual network data of the core network.

[0197] Optionally, the processor 300 is configured to read the program from the memory 320 and execute the following processes:

[0198] A data rollback operation is performed on the adjusted digital twin network to restore it to its state before the adjustment.

[0199] Optionally, the processor 300 is configured to read the program from the memory 320 and execute the following processes:

[0200] Based on the network cutover verification results, a network cutover report is generated;

[0201] Based on the network cutover report, network adjustment recommendations for the core network are output.

[0202] This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, this computer program implements the various processes of the network cutover verification method embodiments described above and achieves the same technical effects. To avoid repetition, it will not be described again here. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0203] This application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the above-described... Figure 1 The various processes of the method embodiments shown can achieve the same technical effect, and will not be described again here to avoid repetition.

[0204] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0205] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0206] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A network cutover verification method, characterized in that, The method includes: Obtain network data from the core network; Construct a digital twin network of the core network based on the network data; The digital twin network is adjusted based on the network cutover scheme of the core network, and the change information of the target data of the digital twin network before and after the adjustment is obtained. The target data includes at least one of network performance data, network alarm data, and flow control parameter data. The network cutover scheme is verified based on the change information of the target data; The network data includes network topology data, network element performance data, and network configuration data. The construction of the digital twin network of the core network based on the network data includes: A network architecture model is constructed based on the network topology data; A user data model is constructed based on the network element performance data; A basic network element model is constructed based on the aforementioned network configuration data; The basic network element model is embedded into the network architecture model, and the network usage characteristics of each user in the user data model are used to construct the digital twin network of the core network.

2. The network cutover verification method according to claim 1, characterized in that, The network topology data includes characteristic data of multiple network nodes, connection relationship data between network nodes, and attribute data of network links; The construction of the network architecture model based on the network topology data includes: Based on the characteristic data of the multiple network nodes, determine the type and function of the multiple network nodes; Based on the types and functions of the multiple network nodes, and the connection relationship data between the network nodes, a network topology is constructed; The attribute data of the network links are mapped to the network topology to obtain the network architecture model.

3. The network cutover verification method according to claim 1, characterized in that, The construction of the user data model based on the network element performance data includes: Based on the user identification data of the core network, the network element performance data associated with the same user identification in the network element performance data are integrated in chronological order to obtain the behavioral feature sequence associated with each user identification. Feature extraction is performed on the behavioral feature sequence of each user to obtain the network usage features of each user; A user data model is constructed based on the network usage characteristics of each user.

4. The network cutover verification method according to claim 1, characterized in that, The network configuration data includes hardware specifications and software version data of network element devices, and the network data also includes network operating status data; The construction of the basic network element model based on the network configuration data includes: Based on the hardware specification data, construct the hardware framework of the basic network element model; Based on the software version data, configure the software functions of the basic network element model; Based on the network operation status data, the real-time status of the basic network element model is determined.

5. The network cutover verification method according to any one of claims 1 to 4, characterized in that, The method further includes: Obtain the updated network data from the core network; The digital twin network of the core network is synchronously updated and adjusted based on the updated core network data.

6. The network cutover verification method according to claim 1, characterized in that, The verification of the network cutover scheme based on the change information of the target data includes: Based on the pre-established mapping relationship between target data and the actual network data of the core network, the change information of the target data is mapped to the change information of the actual network data of the core network; The network cutover scheme is verified based on the changes in the actual network data of the core network.

7. The network cutover verification method according to claim 1 or 6, characterized in that, After verifying the network cutover scheme based on the change information of the target data, the method further includes: A data rollback operation is performed on the adjusted digital twin network to restore it to its state before the adjustment.

8. The network cutover verification method according to claim 1, characterized in that, After verifying the network cutover scheme based on the change information of the target data, the method further includes: Based on the network cutover verification results, a network cutover report is generated; Based on the network cutover report, network adjustment recommendations for the core network are output.

9. A network cutover verification device, characterized in that, The device includes: The data acquisition module is used to acquire network data from the core network. The network construction module is used to construct a digital twin network of the core network based on the network data; The cutover simulation module is used to adjust the digital twin network based on the network cutover scheme of the core network, and to monitor the changes in target data of the digital twin network during the adjustment process. The target data includes at least one of network performance data, network alarm data, and flow control parameter data. The cutover verification module is used to verify the network cutover scheme based on changes in the target data; The network data includes network topology data, network element performance data, and network configuration data. The construction of the digital twin network of the core network based on the network data includes: A network architecture model is constructed based on the network topology data; A user data model is constructed based on the network element performance data; A basic network element model is constructed based on the aforementioned network configuration data; The basic network element model is embedded into the network architecture model, and the network usage characteristics of each user in the user data model are used to construct the digital twin network of the core network.

10. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the network cutover verification method as described in any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the network cutover verification method as described in any one of claims 1 to 8.

12. A computer program product, characterized in that, It includes computer instructions that, when executed by a processor, implement the steps of the network cutover verification method as described in any one of claims 1 to 8.

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