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

Abstract

The invention provides a network cutover verification method and device, electronic equipment, a medium and a program product, which are applied to the technical field of communication, and the method comprises the following steps: obtaining 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 the network cutover 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, the target data including 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. According to the method, the cutover scheme is simulated through the digital twin network, and the cutover effect is quantified through data change, so that whether the scheme is correct or not and needs to be optimized or not is judged, direct implementation of high-risk operation in a real network is avoided, and the stability of the real network is guaranteed.

Description

Technical Field

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

[0002] Network cutover refers to operations such as adjusting, replacing, or upgrading network devices, lines, configurations, etc. in a communication network to achieve purposes such as network optimization, expansion, transformation, or fault repair.

[0003] When carrying out network adjustment work in the existing network, it is mainly based on past cutover experience. For a network cutover plan that has never been implemented, it is necessary to gradually implement and verify it in the network by formulating a detailed pre-plan in advance. Once the pre-plan is not fully considered, it is very likely to cause network failures. When a failure occurs, a rollback operation needs to be performed. Multiple rollbacks will not only seriously affect the network stability but also have a great negative impact on the customer experience. It can be seen that the network cutover verification method in the related technology has a risk of affecting network stability. Summary of the Invention

[0004] Embodiments of this application provide a method, apparatus, electronic device, medium, and program product for network cutover verification to solve the problem of affecting network stability in the existing network cutover verification method.

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

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

[0007] Obtain network data of the core network;

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

[0009] Adjust the digital twin network based on the network cutover plan 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, where the target data includes at least one of network performance data, network alarm data, and flow control parameter data;

[0010] Verify the network cutover plan 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 constructing a digital twin network of the core network based on the network data includes:

[0013] Construct a network architecture model based on the network topology data;

[0014] Construct a user data model based on the network element performance data;

[0015] Construct a basic network element model based on the network configuration data;

[0016] Embed the basic network element model into the network architecture model, and use the network usage characteristics of each user in the user data model to construct the digital twin network of the core network.

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

[0018] The constructing a network architecture model based on the network topology data includes:

[0019] Determine the types and functions of the multiple network nodes according to the feature data of the multiple network nodes;

[0020] Construct a network topology structure according to the types and functions of the multiple network nodes and the connection relationship data between each network node;

[0021] Map the attribute data of the network links into the network topology structure to obtain the network architecture model.

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

[0023] Based on the user identification data of the core network, integrate the network element performance data associated with the same user identification in the network element performance data in chronological order to obtain a behavior feature sequence associated with each user identification;

[0024] Extract features from the behavior feature sequence of each user to obtain the network usage characteristics of each user;

[0025] Construct a user data model 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 further includes network operation status data;

[0027] The constructing a basic network element model based on the network configuration data includes:

[0028] Construct the hardware framework of the basic network element model based on the hardware specification data;

[0029] Configure the software functions of the basic network element model based on the software version data;

[0030] Determine the real-time status of the basic network element model based on the network operation status data.

[0031] Optionally, the method further includes:

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

[0033] Synchronously update and adjust the digital twin network of the core network based on the network data of the updated core network.

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

[0035] Based on the mapping relationship established in advance between the target data and the actual network data of the core network, map the change information of the target data to the change information of the actual network data of the core network;

[0036] Verify the network cutover plan based on the change information of the actual network data of the core network.

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

[0038] Perform a data rollback operation on the adjusted digital twin network to restore the digital twin network to the state before adjustment.

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

[0040] Form a network cutover report based on the network cutover verification result;

[0041] Output network adjustment suggestions for the core network based on the network cutover report.

[0042] In a second aspect, an embodiment of the present application further provides a network cutover verification device, and the network cutover verification device includes:

[0043] A data acquisition module, configured to acquire network data of the core network;

[0044] A network construction module, configured 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 plan of the core network and monitor the changes in the 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 plan based on the changes in the target data.

[0047] In a third aspect, an embodiment of the present application further provides an electronic device, including a processor, a memory, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, the steps of the above network cutover verification method are implemented.

[0048] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above network cutover verification method are implemented.

[0049] In a fifth aspect, a computer program product is provided, including computer instructions, which implement the steps of the above network cutover verification method when executed by a processor.

[0050] The network cutover verification method of the embodiment of the present application includes obtaining 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 plan of the core network, and obtaining 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; verifying the network cutover plan based on the change information of the target data. By simulating the cutover plan through the digital twin network and quantifying the cutover effect with data changes, the embodiment of the present application can determine whether the plan is correct and whether optimization is needed, avoiding directly implementing high-risk operations in the real network and being beneficial to ensuring the stability of the real network. Description of the Drawings

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments of the present application. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0052] Figure 1 It is a flowchart of the network cutover verification method provided by the embodiment of the present application;

[0053] Figure 2 It is a structural diagram of a network cutover verification device provided by an embodiment of the present application;

[0054] Figure 3 It is a structural diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0055] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0056] An embodiment of the present application provides a network cutover verification method, which is applied to a network cutover verification device. Figure 1 It is a flowchart of the network cutover verification method provided by an embodiment of the present application, as Figure 1 shown, including the following steps:

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

[0058] In this step, the data acquisition module of the network cutover verification device can obtain the network data of the core network from each data reporting system. The network data of the core network includes network topology data, network element performance data, network configuration data, network operation status data, core network workbench data, wireless statistics data, etc.

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

[0060] Step 102: Build 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 build a digital twin network of the core network based on the network data. It should be noted that before using the network construction module to build a digital twin network of the core network based on the network data, the data processing module of the network cutover verification device can be used to process and clean the network data, so that the network data is converted into a data format adapted to the digital twin network.

[0062] Constructing the digital twin network of the core network based on the network data can be understood as creating a highly similar digital model of the real core network in the virtual space based on various network data generated during the actual operation of the core network. Through data collection, processing, and analysis, this digital twin network can real-time map the operating status of the core network, including the working conditions of devices, the traffic distribution of the network, the signal transmission path, etc.

[0063] Step 103: Adjust the digital twin network based on the network cutover plan 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 network cutover plan of the core network can be understood as a plan for the transformation, upgrade, or adjustment of the core network, as well as operations such as equipment replacement and line adjustment. The digital twin network can be understood as a virtual mirror network of the core network, which can simulate and reflect the operating status of the real network and can perform various "destructive tests" without damaging the real network.

[0065] Network performance data can include data such as bandwidth, latency, and throughput; network alarm data can include alarm data for abnormal states such as equipment failures, link terminals, and overloads; flow control parameter data can include configuration parameters related to traffic control (such as QoS priorities, bandwidth limits, and traffic policies).

[0066] The cutover module of the network cutover verification device can be used to simulate the implementation of the network cutover plan of the core network in the digital twin network. Exemplarily, if the network cutover plan of the core network is "plan to upgrade the core network equipment in a certain area to increase the bandwidth", then the cutover operation can be "pre-played" 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 implementation of the cutover plan (such as the current bandwidth of 1 Gbps, latency of 50 ms, and no alarms). After simulating the implementation of the cutover plan, collect the same data again (such as the bandwidth is increased to 2 Gbps, the latency is reduced to 30 ms, but new link alarms appear), and pay attention to the differences in the data before and after the adjustment (such as whether the performance is improved, whether new alarms are introduced, and whether the flow control parameters take effect as expected).

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

[0069] In this step, the target data is the network performance data, network alarm data, flow control parameter data, etc. mentioned above. The change information refers to the comparison result of these data before and after the adjustment of the digital twin network (i.e., the simulation implementation of the network cutover plan). The core of verifying the network cutover plan is to judge whether the cutover plan has achieved the expected goal and whether there are potential problems by observing the data changes. For example, whether the network performance has improved after the cutover, whether the alarms have decreased, and whether the flow control parameters meet the design expectations. This step can be executed by using the cutover verification module of the network cutover device.

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

[0071] In this implementation, the cutover plan is simulated through the digital twin network, and the cutover effect is quantified by data changes, so as to judge whether the plan is correct and whether it needs to be optimized, avoiding directly implementing high-risk operations in the real network, which is beneficial to ensuring 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 constructing the digital twin network of the core network based on the network data includes:

[0074] Constructing a network architecture model based on the network topology data;

[0075] Constructing a user data model based on the network element performance data;

[0076] Constructing a basic network element model based on the network configuration data;

[0077] Embedding the basic network element model into the network architecture model, and using the network usage characteristics of each user in the user data model to construct the digital twin network of the core network.

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

[0079] Constructing a network architecture model based on network topology data can be understood as building a "network skeleton" model with network topology data to describe the overall structure of the network. The network architecture model is used to define the "spatial layout" of the digital twin network. For example, which devices the core network consists of, how the devices are connected, and what the data transmission path is.

[0080] Constructing a user data model based on network element performance data can be understood as collecting the network element performance data corresponding to each user (such as the load and latency of a certain server when user A uses it), and constructing a model that reflects "how users use the network". The user data model focuses on the "user perspective". For example, the bandwidth requirements of different users and the impact of service types on network performance reflect the personalized characteristics of network usage.

[0081] Constructing a basic network element model based on network configuration data can be understood as constructing a "digital model" of a single network element according to the configuration parameters of each network element (such as the initial settings and functional parameters of the device). The basic network element model details the "individual characteristics" of each device. For example, the bandwidth limit of a certain router and the security policy of a certain server ensure that the virtual network element behaves the same as the real device.

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

[0083] In this implementation, through hierarchical modeling and data integration, the digital twin network not only includes the hardware architecture and configuration of the network, but also can reflect the dynamic performance driven by user behavior, and finally realizes the full simulation of the real core network.

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

[0085] Constructing the network architecture model based on the network topology data includes:

[0086] According to the characteristic data of the multiple network nodes, determine the types and functions of the multiple network nodes;

[0087] According to the types and functions of the multiple network nodes, and the connection relationship data between each network node, construct a network topology structure;

[0088] Map the attribute data of the network links to the network topology structure to obtain the network architecture model.

[0089] In one implementation, the characteristic data of network nodes may include the identification and type of network nodes, etc. The connection relationship data between network nodes is used to determine which network nodes are interconnected with each other. The attribute data of network links may include the bandwidth and latency of network links, etc.

[0090] Based on the characteristic data of network nodes, determine the type (such as server, router, etc.) and function (such as data storage, data forwarding, etc.) of each node. Combining the type and function of network nodes, as well as the connection relationship data between them, depict the layout and connection method of each node in the network to form a network topology structure. Add the attribute data of network links to the network topology structure, so that the model includes the detailed information of nodes and links, thereby obtaining a complete network architecture model.

[0091] When conducting network planning or expansion, the network architecture model can be used as a reference to help determine the location, connection method of new nodes, and the required link resources, improving the efficiency and accuracy of network planning.

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

[0093] Based on the user identification data of the core network, integrate the network element performance data associated with the same user identification in the network element performance data in chronological order to obtain a behavior feature sequence associated with each user identification;

[0094] Extract features from the behavior feature sequence of each user to obtain the network usage features of each user;

[0095] Construct a user data model based on the network usage features of each user.

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

[0097] Using the user identification data in the core network as a "link", data associated with the same user identification is filtered out from the massive network element performance data and arranged in chronological order to form the behavior feature sequence of the user in the network. Exemplarily, user A downloads a file using the 5G network at 10:00 (corresponding to the traffic data of base station A), and switches to Wi-Fi to browse the web at 11:00 (corresponding to the connection data of router B). After these data are associated through the user ID, they are integrated into the behavior sequence of the user in chronological order.

[0098] Analyze the behavior feature sequence of each user, and extract key features (i.e., network usage features) that can reflect the user's network usage habits through technologies such as data mining and machine learning. Network usage features may include high-frequency usage periods, service preferences, frequently occurring network lag periods, connection interruption frequencies, etc.

[0099] Map the extracted user network usage features to the digital twin network to form the digital twin body of each user (i.e., the user data model). This model is a virtual mirror of the real user's behavior in the network, containing the user's historical behavior patterns, real-time status, and potential needs.

[0100] In this implementation manner, the digital twin network needs to completely map the interaction relationship of "human-network-service" in the real network, and the user data model integrates multi-dimensional network element performance data such as the core network, access network, and terminal (such as the base station accessed by the user, the frequency band used, and the traffic generated), and transforms each connection, service access, and status change of the user in the physical network into "digital footprints" in the virtual space, so that the behavior of the virtual user is kept in real-time synchronization with that of the real user.

[0101] Optionally, the network configuration data includes the hardware specification data and software version data of the network element device, and the network data further includes the network operation status data;

[0102] Constructing the basic network element model based on the network configuration data includes:

[0103] Construct the hardware framework of the basic network element model based on the hardware specification data;

[0104] Configure the software functions of the basic network element model based on the software version data;

[0105] Determine the real-time status of the basic network element model based on the network operation status data.

[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, physical form. The hardware parameters include, for example, CPU model / core number, memory capacity, interface type / quantity, power supply specification, etc. The physical form includes, for example, rack size, heat dissipation design, etc. The software version data of the network element device is used to describe the software information of the device operation, such as operating system version, service software version, firmware version. The network operation status data may include real-time device operation data, such as CPU utilization rate, memory occupancy rate, port traffic, etc.

[0107] When constructing the basic network element model, first construct the hardware framework based on the hardware specification data. Then configure the software functions based on the software version, and on the basis of the hardware framework, load the software logic of the device operation to realize the function simulation of the virtual network element. Finally, inject the real-time collected operation status data into the model to synchronize the status 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 the basic network element model is beneficial to the credibility of the overall simulation.

[0109] Optionally, the method further includes:

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

[0111] Perform synchronous update and adjustment on the digital twin network of the core network based on the network data of the updated core network.

[0112] In one implementation, new data will be continuously generated during the operation of the core network, and the digital twin network is a mapping of the core network in the virtual space, which simulates various characteristics and behaviors of the core network. When the network data updated by the core network is obtained, it is necessary to perform corresponding updates and adjustments on the digital twin network of the core network according to these new data. For example, if a new server is added to the core network, a corresponding virtual server needs to be added in the digital twin network, and relevant parameters and connection relationships are set; if the operation status of a network element device in the core network changes, the status of the corresponding virtual network element device in the digital twin network should also be synchronously updated to reflect this change.

[0113] In this implementation, by performing real-time updates on the digital twin network, it is beneficial to enable the digital twin network to always accurately reflect the actual status of the core network, thereby improving the accuracy of subsequent simulation cutover.

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

[0115] Based on the mapping relationship established in advance between the target data and the actual network data of the core network, map the change information of the target data to the change information of the actual network data of the core network;

[0116] Verify the network cutover plan based on the change information of 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, throughput, etc.; network alarm data may include alarm data for abnormal states such as device failures, link terminals, overloads, etc.; flow control parameter data may include configuration parameters related to traffic control (such as QoS priorities, bandwidth limits, and traffic policies, etc.). A corresponding relationship (i.e., mapping relationship) between the target data and the actual network data of the core network has been established in advance. When the target data changes (such as the desired network bandwidth needs to be increased, or a new network alarm trigger condition is set, etc., which are change information), according to the established mapping relationship, convert this change information of the target data into the corresponding change information of the actual network data of the core network. For example, if the bandwidth of a certain link in the target data needs to be increased from 100 Mbps to 200 Mbps, through the mapping relationship, the change information of the actual network data such as how to configure the relevant devices in the actual network can be obtained.

[0118] Based on the obtained change information of the actual network data of the core network, determine whether the network cutover plan is feasible, whether it will bring the expected results, and whether it will trigger some potential problems

[0119] In this implementation, before actually performing the network cutover, through simulation and verification, various problems that may be caused by the cutover plan can be discovered in advance, such as performance degradation, unreasonable alarm rules, traffic control imbalance, etc. This avoids discovering problems only when directly implementing the cutover in the real network environment, thereby reducing the risk of network failures and the impact on services.

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

[0121] Perform a data rollback operation on the adjusted digital twin network to restore the digital twin network to the state before adjustment.

[0122] In one implementation, a data rollback operation is performed on the already adjusted digital twin network. The data rollback operation is to restore the relevant data in the digital twin network to the state before the adjustment. For example, if the bandwidth parameter of a certain router in the digital twin network was previously adjusted from 100 Mbps to 200 Mbps, after performing the data rollback operation, the bandwidth parameter of the router will change back to 100 Mbps, making the state of the entire digital twin network exactly the same as before the adjustment. This is beneficial for the digital twin network to execute the next network cutover plan.

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

[0124] Forming a network cutover report based on the network cutover verification result;

[0125] Outputting network adjustment suggestions for the core network based on the network cutover report.

[0126] In one implementation, after implementing the cutover plan in the digital twin network and observing the changes in the actual network data of the core network, various performance indicators, equipment operation status, etc., all the obtained verification results are sorted, analyzed, and summarized to form a network cutover report. This report may include the specific content of the cutover plan, problems found during the verification process, such as equipment compatibility problems, performance degradation problems, etc., the comparison data of various performance indicators before and after, and the evaluation conclusion on the feasibility of the cutover plan.

[0127] Based on the already formed network cutover report, the content therein is deeply analyzed and interpreted. Based on the advantages and disadvantages of the cutover plan presented in the report, the problems exposed during the verification process, and the impact on the overall network operation, etc., specific network adjustment suggestions for the core network are proposed. These suggestions may include modifying and improving the cutover plan, upgrading or replacing certain equipment, adjusting network management strategies, etc., so that the core network can operate better and meet business requirements.

[0128] In this implementation, the network cutover report details the process and results of the cutover verification, providing comprehensive and accurate information for network managers and decision-makers. Based on this information, they can more scientifically judge the feasibility and potential risks of the network cutover plan, and thus make more reasonable decisions to avoid losses and risks caused by blind decisions.

[0129] See Figure 2 , Figure 2 which is the structural diagram of the network cutover verification device provided by an embodiment of the present application. As Figure 2 shown, the network cutover verification device 200 includes:

[0130] A data acquisition module 201, configured to acquire network data of a core network;

[0131] A network construction module 202, configured to construct a digital twin network of the core network based on the network data;

[0132] A cutover simulation module 203, configured to adjust the digital twin network based on a network cutover plan of the core network, and monitor changes in target data during the adjustment of the digital twin network, where the target data includes at least one of network performance data, network alarm data, and flow control parameter data;

[0133] A cutover verification module 204, configured to verify the network cutover plan based on 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 construction unit, configured to construct a network architecture model based on the network topology data;

[0137] A user data model construction unit, configured to construct a user data model based on the network element performance data;

[0138] A basic network element model construction unit, configured to construct a basic network element model based on the network configuration data;

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

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

[0141] The network architecture model construction unit includes:

[0142] A first determination subunit, configured to determine types and functions of the multiple network nodes according to the feature data of the multiple network nodes;

[0143] A first construction subunit, configured to construct a network topology structure according to the types and functions of the multiple network nodes and the connection relationship data between the network nodes;

[0144] A first mapping subunit, configured to map the attribute data of the network links into the network topology structure to obtain the network architecture model.

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

[0146] A first integration subunit, configured to integrate, according to a time sequence, the network element performance data associated with the same user identifier in the network element performance data based on the user identifier data of the core network, so as to obtain a behavior feature sequence associated with each user identifier;

[0147] A first extraction subunit, configured to perform feature extraction on the behavior feature sequence of each user to obtain the network usage features of each user;

[0148] A second construction subunit, configured to construct a user data model based on the network usage features of each user.

[0149] Optionally, the network configuration data includes the hardware specification data and software version data of network elements, and the network data further includes network operation status data;

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

[0151] A third construction subunit, configured to construct a hardware framework of the basic network element model based on the hardware specification data;

[0152] A first configuration subunit, configured to configure the software functions of the basic network element model based on the software version data;

[0153] A second determination subunit, configured to determine the real-time state of the basic network element model based on the network operation status data.

[0154] Optionally, the apparatus further includes:

[0155] A data acquisition module, configured to acquire the network data updated by the core network;

[0156] A network adjustment module, configured to perform synchronous update and adjustment on the digital twin network of the core network based on the network data of the updated core network.

[0157] Optionally, the network verification module includes:

[0158] A data mapping unit, configured 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 mapping relationship established in advance between the target data and the actual network data of the core network;

[0159] A solution verification unit, configured to verify the network cutover solution based on the change information of the actual network data of the core network.

[0160] Optionally, the device further includes:

[0161] A network recovery module, configured to perform a data rollback operation on the adjusted digital twin network to restore the digital twin network to the state before adjustment.

[0162] Optionally, the device further includes:

[0163] A report generation module, configured to form a network cutover report based on the network cutover verification result;

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

[0165] An embodiment of the present application further provides an electronic device. Since the principle of the electronic device to solve problems is similar to the network cutover verification method in the embodiment of the present application, the implementation of the electronic device can refer to the implementation of the method, and the repeated parts will not be described again. As Figure 3 shown, the electronic device in the embodiment of the present application includes: a processor 300, configured to read a program in a memory 320 and execute the following processes:

[0166] Obtain network data of the core network;

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

[0168] Adjust the digital twin network based on the network cutover plan 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, where the target data includes at least one of network performance data, network alarm data, and flow control parameter data;

[0169] Verify the network cutover plan based on the change information of the target data.

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

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

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

[0173] Construct a network architecture model based on the network topology data;

[0174] Construct a user data model based on the network element performance data;

[0175] Construct a basic network element model based on the network configuration data;

[0176] Embed the basic network element model into the network architecture model, and utilize the network usage characteristics of each user in the user data model to construct the digital twin network of the core network.

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

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

[0179] Determine the types and functions of the multiple network nodes according to the feature data of the multiple network nodes;

[0180] Construct a network topology structure according to the types and functions of the multiple network nodes and the connection relationship data between each network node;

[0181] Map the attribute data of the network links into the network topology structure to obtain the network architecture model.

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

[0183] Based on the user identification data of the core network, integrate the network element performance data associated with the same user identification in the network element performance data in chronological order to obtain the behavior feature sequence associated with each user identification;

[0184] Extract features from the behavior feature sequence of each user to obtain the network usage characteristics of each user;

[0185] Construct a user data model based on the network usage characteristics of each user.

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

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

[0188] Construct the hardware framework of the basic network element model based on the hardware specification data;

[0189] Configure the software functions of the basic network element model based on the software version data;

[0190] Determine the real-time status of the basic network element model based on the network operation status data.

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

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

[0193] Synchronously update and adjust the digital twin network of the core network based on the network data of the updated core network.

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

[0195] Based on the mapping relationship established in advance between the target data and the actual network data of the core network, map the change information of the target data to the change information of the actual network data of the core network;

[0196] Verify the network cutover plan based on the change information of the actual network data of the core network.

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

[0198] Perform a data rollback operation on the adjusted digital twin network to restore the digital twin network to the state before adjustment.

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

[0200] Generate a network cutover report based on the network cutover verification result;

[0201] Output network adjustment suggestions for the core network based on the network cutover report.

[0202] The embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements each process of the above-mentioned embodiment of the network cutover verification method and can achieve the same technical effects. To avoid repetition, details are not described herein again. The computer-readable storage medium includes, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc, etc.

[0203] The embodiments of the present application also provide a computer program product, including computer instructions, which implement each process of the above-mentioned Figure 1 method embodiment when executed by a processor and can achieve the same technical effects. To avoid repetition, details are not described herein again.

[0204] It should be noted that in this document, the term "including", "comprising", or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or device including a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article, or device including such element.

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

[0206] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present application, those of ordinary skill in the art can also make many forms without departing from the purpose of the present application and the scope protected by the claims, and all of them belong to the protection scope of the present application.

Claims

1. A network cutover verification method, characterized in that: The method comprises: Obtain network data of the core network; Building a digital twin network of the core network based on the network data; Adjusting the digital twin network based on the network cutover solution of the core network, and obtaining 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; Based on the change information of the target data, the network cutover solution is verified.

2. The network cutover verification method according to claim 1, characterized in that: The network data includes network topology data, network element performance data and network configuration data; The constructing the digital twin network of the core network based on the network data includes: Building a network architecture model based on the network topology data; Building a user data model based on the network element performance data; Building a basic network element model based on the 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 build a digital twin network of the core network.

3. The network cutover verification method according to claim 2, 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 constructing of a network architecture model based on the network topology data includes: Determining types and functions of the plurality of network nodes according to the characteristic data of the plurality of network nodes; Constructing a network topology structure according to the types and functions of the plurality of network nodes and the connection relationship data between the network nodes; The attribute data of the network link is mapped to the network topology structure to obtain the network architecture model.

4. The network cutover verification method according to claim 2, characterized in that: The constructing a user data model based on the network element performance data includes: Based on the user identification data of the core network, integrating the network element performance data associated with the same user identification in the network element performance data in chronological order to obtain a behavior feature sequence associated with each user identification; Extracting features from the behavioral feature sequence of each user to obtain network usage features of each user; A user data model is constructed based on the network usage characteristics of each user.

5. The network cutover verification method according to claim 2, characterized in that: The network configuration data includes hardware specification data and software version data of network element devices, and the network data also includes network operation status data; The constructing a basic network element model based on the network configuration data includes: Based on the hardware specification data, construct a hardware framework of the basic network element model; Based on the software version data, configuring the software function of the basic network element model; Based on the network operation status data, a real-time status of the basic network element model is determined.

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

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

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

9. The network cutover verification method according to claim 1, characterized in that: After verifying the network cutover solution 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, a network adjustment suggestion for the core network is output.

10. A network cutover verification device, characterized in that: The device comprises: A data acquisition module, used to acquire network data of the core network; A network construction module, used to construct a digital twin network of the core network based on the network data; A cutover simulation module, used to adjust the digital twin network based on the network cutover solution of the core network, and monitor the changes of target data of the digital twin network during the adjustment process, wherein 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 solution based on the change of the target data.

11. An electronic device, characterized in that: The invention comprises a processor, a memory and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the steps of the network cutover verification method according to any one of claims 1 to 9 are implemented.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the network cutover verification method according to any one of claims 1 to 9 are implemented.

13. A computer program product, characterized in that The method comprises computer instructions, which, when executed by a processor, implement the steps of the network cutover verification method according to any one of claims 1 to 9.

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