Network element data processing method, program product, electronic device, and storage medium

Abstract

This invention discloses a method for processing network element data, a program product, an electronic device, and a storage medium. The method includes: obtaining network element data of multiple network element types from a source database based on multiple defined network element data models; performing field mapping on defined fields in the network element data of the multiple network element types, whereby the field mapping maps the defined fields to standard fields in a set of standard fields; and outputting the network element data of different network element types in a unified data format according to the mapping results and the network element types corresponding to the network element data.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a network data processing method, program product, electronic device, and storage medium. Background Technology

[0002] In related technologies, network data is presented separately. If data metrics from different network elements, such as core network elements and IoT network elements, need to be retrieved and parsed twice to obtain usable data. This results in low data retrieval efficiency and a difficult data parsing process, significantly increasing economic and time costs. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a network data processing method, a program product, an electronic device, and a storage medium.

[0004] The technical solution of this invention is implemented as follows: On one hand, embodiments of the present invention provide a network data processing method, the method comprising: Based on multiple defined network element data models, network element data of multiple network element types are obtained from the source database; Field mapping is performed on specified fields in network element data of multiple network element types. The field mapping is used to map the specified fields to standard fields in the standard field set. Based on the mapping results and the network element types corresponding to the network element data, the network element data of different network element types are output in a unified data format.

[0005] The method in the above scheme further includes: Perform Chinese-English mapping for common fields in network element data of multiple network element types.

[0006] The method in the above scheme further includes: Classify the network elements in the source database; Determine the network data containing the specified fields based on the classification results.

[0007] In the above scheme, the classification of network elements in the source database includes: Multiple network elements belonging to the same network function type are grouped into the same enumeration type.

[0008] In the above scheme, the step of outputting network element data of different network element types in a unified data format according to the mapping result and the network element type corresponding to the network element data includes: Determine the entity class corresponding to the network element type; Based on the entity class and the mapping result, network data in a unified data format is generated.

[0009] In the above scheme, after outputting network element data of different types in a unified data format, the method further includes: Receive data query requests; Based on the data query request, network element data in a unified data format, including multiple network element types, will be used as the query result.

[0010] In the above scheme, the mapping of common fields in network element data of multiple network element types to Chinese and English includes: Map the English indicators in the public fields to Chinese character types.

[0011] On the other hand, embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described network data processing method.

[0012] On the other hand, embodiments of the present invention provide an electronic device including a processor and a memory interconnected thereto, wherein the memory is used to store a computer program, the computer program including program instructions, and the processor is configured to invoke the program instructions to execute the steps of the network data processing method provided in the first aspect of the present invention.

[0013] On the other hand, embodiments of the present invention provide a computer-readable storage medium, comprising: the computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the steps of the network data processing method provided in the first aspect of the present invention.

[0014] The solution of this invention, based on multiple defined network element data models, obtains network element data of multiple network element types from a source database; performs field mapping on defined fields in the network element data of multiple network element types, mapping the defined fields to standard fields in a standard field set; and outputs the network element data of different network element types in a unified data format according to the mapping results and the network element types corresponding to the network element data. This invention, by unifying the data format of network element data of different types of network elements, allows users to obtain the desired network element data with a single query, and also enables data retrieval for different network elements without requiring multiple data retrievals, thus improving data retrieval efficiency. Attached Figure Description

[0015] Figure 1 This is a schematic diagram illustrating the implementation flow of a network data processing method provided in an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the implementation flow of another network data processing method provided in an embodiment of the present invention; Figure 3This is a flowchart illustrating a special field processing method provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of a data mapping process provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of a data modeling process provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] In a mobile network architecture, various network elements are embedded, each with its own specific function and playing a crucial role. These elements are categorized based on their functions, such as IoT network elements, Network Functions Virtualization (NFV) network elements, and 5G (5GC) network elements. These network elements contain numerous key metrics, such as qosReq (total number of QoS guarantees within 30 minutes) and qosSuccess (number of successful QoS guarantees within 30 minutes). These metrics are vital for mobile network communication, ensuring normal operation and facilitating troubleshooting. While these metrics are exceptionally important, the sheer number of network elements and metrics can lead to data redundancy and even invalid data. Furthermore, with the proliferation of data metrics for various network elements, a unified and meaningful model is essential. Therefore, obtaining a common dataset for multiple network element data metrics is urgently needed. By using data modeling methods to filter and assemble key data metrics before presentation, the data becomes more intuitive. The key protection indicators are clear at a glance, providing an intuitive understanding of the network element's operating status, enabling timely location of faulty network elements and problem repair. Furthermore, based on shared data, a large visualization dashboard can be created to enrich the data status display.

[0018] To address the shortcomings of the aforementioned related technologies, embodiments of the present invention provide a network data processing method. To illustrate the technical solution described in the present invention, specific embodiments are described below.

[0019] Figure 1This is a schematic diagram illustrating the implementation flow of a network data processing method provided in an embodiment of the present invention. The executing entity of the network data processing method is an electronic device. (Reference) Figure 1 Network data processing methods include: S101, based on multiple configured network element data models, obtains network element data of multiple network element types from the source database.

[0020] Here, the network element data model can be a Structured Query Language (SQL) query statement or query command for network element data. A network element data model is used to query network element data of a certain type.

[0021] For example, by importing different network metadata models (Upload SQL), these SQL statements rely on existing network metadata models and are used to query source data. Because these network metadata models exist in different business systems, it is necessary to first integrate the network metadata models that need to be shared into SQL statements and define them as Upload SQL.

[0022] The source database includes network element data of various network element types, and the network element data in the source database is obtained by querying SQL statements.

[0023] S102, perform field mapping on the set fields in the network data of multiple network element types, wherein the field mapping is used to map the set fields to standard fields in the standard field set.

[0024] Because the data indicators of different network elements differ, special processing operations are required for special fields in some special network elements.

[0025] Here, field mapping is used to integrate special field mappings of different types of network data into a standard set required for a unified model, and to set a preset relationship between the fields and the standard fields in the standard field set.

[0026] For example, LO_NAME_FIELD for NFV and FGC type network elements needs to be mapped to loName; LO_NAME and PROVINCE_NAME represent the region name and province name, respectively, such as North China Region and Hebei Province. This is a field that needs to be processed for all network element types, mapping LO_NAME to LO_ID and PROVINCE_NAME to PROVINCE_ID.

[0027] By mapping the specified fields in network element data of different network element types to standard fields, the field naming of network element data can be standardized, making it easier to search and manage uniformly.

[0028] S103. Based on the mapping results and the network element types corresponding to the network element data, output the network element data of different network element types in a unified data format.

[0029] Different network element types correspond to different data containers. The mapping results are written into the corresponding data containers to obtain network element data in a unified data format.

[0030] For example, different network element types correspond to different entity classes. The mapping results are filled into the corresponding entity classes, and finally the network element data is reassembled to obtain network element data in a unified data format.

[0031] An entity class is a class used to represent a specific entity or object. It typically contains a set of attributes (fields) and methods. Entity classes are often used for data persistence, that is, storing data in a database or file system.

[0032] By standardizing the data format of network element data for different types of network elements and using a unified interface, users can obtain the desired network element data with a single query, enabling the output of various types of network element indicator data and completing the parsing and data retrieval functions in one go. Furthermore, data can be retrieved from different network elements, achieving resource reuse.

[0033] The solution of this invention, based on multiple defined network element data models, obtains network element data of multiple network element types from a source database; performs field mapping on defined fields in the network element data of multiple network element types, mapping the defined fields to standard fields in a standard field set; and outputs the network element data of different network element types in a unified data format according to the mapping results and the network element types corresponding to the network element data. This invention, by unifying the data format of network element data of different types of network elements, allows users to obtain the desired network element data with a single query, and also enables data retrieval for different network elements without requiring multiple data retrievals, thus improving data retrieval efficiency.

[0034] In one embodiment, the method further includes: Perform Chinese-English mapping for common fields in network element data of multiple network element types.

[0035] For fields that do not require special processing, data mapping is performed directly to map the English and Chinese characters in the received source data fields, making it convenient for use in subsequent processing.

[0036] For fields that require special handling, the Chinese / English mapping should be performed after the field mapping is completed.

[0037] For example, a Map can be used to map the English metrics of common fields in network data, converting them into Chinese characters for easier viewing and subsequent processing. A Map is an iterable key / value pair structure where all values ​​can be retrieved using the key.

[0038] In one embodiment, the method further includes: Classify the network elements in the source database; Determine the network data containing the specified fields based on the classification results.

[0039] Because the network elements in the source dataset are of different types and the data indicators of different network elements are not the same, it is necessary to classify the network element types to distinguish whether there are network element data indicators that require special processing.

[0040] The network element types in this embodiment include: Internet of Things (IoT) network elements, Network Functions Virtualization (NFV) network elements, Core Network (5GC) network elements, Service Capability Endpoint (SCEP) network elements, Service Capability Exposure Function (SCEF) network elements, and File Storage Cloud Endpoint (FSCEP) network elements.

[0041] The classification of network elements in the source database includes: Multiple network elements belonging to the same network function type are grouped into the same enumeration type.

[0042] For example, the enumeration type is IoT network element type, which can include the following network element types: IoT Home Subscriber Server (HSS), IoT Gateway GPRS Support Node (GGSN), IoT Policy and Charging Rules Function (PCRF), IoT Packet Data Network Gateway (PGW), IoT Home Location Register (HLR), IoT Super Mini-slot Allocation (SMSA), and IOTCE certification (CEcertification).

[0043] For example, an enumeration type of NFV network element type can include the following network element types: The NFV core network includes the Evolved Packet Core Domain Name System (EPCDNS), NFV Policy and Charging Rules Function (PCRF), NFV Packet Data Network Gateway Control Plane (PGWC), NFV Packet Data Network Gateway User Plane (PGWU), NFV Serving Gateway Control Plane (SGWC), NFV Serving Gateway User Plane (SGWU), NFV IP Media Gateway (IPSMGW), Network Functions Virtualization Cloud Endpoint (NFVSCEP), NFV Short Message Service Center (SMSC), NFV Service Capability Exposure Function (SCEF), NFV Service Communication Proxy (SCP), NFV Virtual Machine Mobile Switching Center (VMMSC), and NFV Telephony Application. Server (TAS), NFV Telephone URI Mapping Domain Name System (ENUM (E.164 Number URI Mapping Domain Name System, ENUMDNS), NFV Call Session Control Function (CSCF), NFV Virtual Subscriber Exchange (CENTREX), NFV Session Border Controller Control Plane (PSBCC), NFV Session Border Controller User Plane (PSBCU), NFV Mobility Management Entity (MME).

[0044] For example, an enumeration type of FGC network element type can include the following network element types: The FGC functions include: Access and Mobility Management Function (AMF), Session Management Function (SMF), User Plane Function (UPF), Unified Data Management (UDM), Policy Control Function (PCF), Network Repository Function (NRF), Network Slice Selection Function (NSSF), Interworking Function (IWF), Charging Function (CHF), and Short Message Service (SMS).

[0045] Different network element types can be received through an enumeration class, which facilitates their use in subsequent processing.

[0046] In one embodiment, the step of outputting network element data of different network element types in a unified data format according to the mapping result and the network element type corresponding to the network element data includes: Determine the entity class corresponding to the network element type; Based on the entity class and the mapping result, network data in a unified data format is generated.

[0047] First, based on different network element types, corresponding return entity classes are generated. Then, the network element type is determined by enumeration, and the mapping results are mapped to the entity classes corresponding to different network element types. Finally, these data are reassembled as network element data in a unified data format for the final output.

[0048] For example, one example of a returned entity is as follows (for HSS network elements): { @IndicatorDescription(name="HSS 4G User Count", unit="units", interval=15, isDeviceDimension=0) private Long subEpssubsinhss; @IndicatorDescription(name="HSS 4G Current User Count", unit="number", interval=15, isDeviceDimension=0) private Long subEpsactsubsinhss; @IndicatorDescription(name="HSS location update success count", unit="times", interval=15, isDeviceDimension=0) private Long diamUpdatelocationanssucc; @IndicatorDescription(name="HSS location update request count", unit="times", interval=15, isDeviceDimension=0) private Long diamUpdatelocationreq; @IndicatorDescription(name="HSS location update success rate", unit="%", interval=15, isDeviceDimension=0) private Double diamUpdatelocationanssuccRate; @IndicatorDescription(name="Number of location update failures_Unknown users", unit="times", interval=15, isDeviceDimension=0) private Long diamUpdatelocationansfail5001; @IndicatorDescription(name="Number of location update failures_Roaming not allowed", unit="times", interval=15, isDeviceDimension=0) private Long diamUpdatelocationansfail5004; @IndicatorDescription(name="Number of Location Update Failures_No EPS Contract", unit="times", interval=15, isDeviceDimension=0) private Long diamUpdatelocationansfail5420; @IndicatorDescription(name="Number of location update failures_RAT not allowed", unit="times", interval=15, isDeviceDimension=0) private Long diamUpdatelocationansfail5421; @IndicatorDescription(name="Success rate of location update excluding HSS causes", unit="%", interval=15, isDeviceDimension=0) private Double diamUpdatelocationanssuccexcepthssRate; @IndicatorDescription(name="HSS authentication information query success count", unit="times", interval=15, isDeviceDimension=0) private Long diamAucinfoanssucc; @IndicatorDescription(name="HSS authentication information query request count", unit="times", interval=15, isDeviceDimension=0) private Long diamAucinforeq; @IndicatorDescription(name="HSS authentication information query success rate", unit="%", interval=15, isDeviceDimension=0) private Double diamAucinfoanssuccRate; @IndicatorDescription(name="Number of Authentication Information Query Failures_Unknown Users", unit="times", interval=15, isDeviceDimension=0) private Long diamAucinfoansfail5001; @IndicatorDescription(name="Number of Authentication Information Query Failures_No EPS Contract", unit="times", interval=15, isDeviceDimension=0) private Long diamAucinfoansfail5420; @IndicatorDescription(name="Authentication success rate excluding HSS reasons", unit="%", interval=15, isDeviceDimension=0) private Double diamAucinfoanssuccexcepthssRate; @IndicatorDescription(name="HSS location cancellation success count", unit="times", interval=15, isDeviceDimension=0) private Long diamCancellocationanssucc; @IndicatorDescription(name="HSS Cancellation of Location Requests", unit="times", interval=15, isDeviceDimension=0) private Long diamCancellocationreq; @IndicatorDescription(name="HSS Cancellation Location Success Rate", unit="%", interval=15, isDeviceDimension=0) private Double diamCancellocationanssuccRate; @IndicatorDescription(name="HSS User Data Insertion Success Count", unit="times", interval=15, isDeviceDimension=0) private Long diamInsertsubdataanssucc; @IndicatorDescription(name="HSS Insert User Data Request Count", unit="times", interval=15, isDeviceDimension=0) private Long diamInsertsubdatareq; @IndicatorDescription(name="HSS User Data Insertion Success Rate", unit="%", interval=15, isDeviceDimension=0) private Double diamInsertsubdataanssuccRate; @IndicatorDescription(name="HSS User Data Deletion Success Count", unit="times", interval=15, isDeviceDimension=0) private Long diamDeletesubdatanssucc; @IndicatorDescription(name="HSS User Data Deletion Request Count", unit="times", interval=15, isDeviceDimension=0) private Long diamDeletesubdatareq; @IndicatorDescription(name="HSS User Data Deletion Success Rate", unit="%", interval=15, isDeviceDimension=0) private Double diamDeletesubdatanssuccRate; @IndicatorDescription(name="HSS successfully cleared UE count", unit="times", interval=15, isDeviceDimension=0) private Long diamPurgeueanssucc; @IndicatorDescription(name="HSS Clear UE Request Count", unit="times", interval=15, isDeviceDimension=0) private Long diamPurgeuereq; @IndicatorDescription(name="HSS UE Clearance Success Rate", unit="%", interval=15, isDeviceDimension=0) private Double diamPurgeueanssuccRate; @IndicatorDescription(name="SCTP Coupling Retransmission Data Block Count", unit="block", interval=15, isDeviceDimension=0) private Long sigSctpdatachunkresent; @IndicatorDescription(name="SCTP Linked Data Blocks", unit="Blocks", interval=15, isDeviceDimension=0) private Long sigSctpdatachunksent; @IndicatorDescription(name="SCTP Coupled Data Block Retransmission Rate", unit="%", interval=15, isDeviceDimension=0) private Double sigSctpdatachunkresentRate; } The data enumerated by HSS network elements (other network elements are similar, and a data field corresponding to the network element needs to be defined first).

[0049] The format of the network data after being uniformly assembled according to the entity class is as follows: { "neType": "HSS", "Interval": 60, "kpiDetailList": [{ "kpiName": "HSS UE clearance success rate", "enKpiName": "diamPurgeueanssuccRate", "unit": "%", "kpiDataList": [{ "time": 2018052511, "province": "Jiangsu", "neName": "QDAHSS17FE02BHW", "value": "100.0" }, { "time": 2018052810, "province": "Zhejiang", "neName": "QDAHSS17FE02BHW", "value": "100.0" } }, { "kpiName": "Number of successful HSS user data deletions", "enKpiName": "diamDeletesubdatanssucc", "unit": "pcs", "kpiDataList": [{ "time": 2018052511, "province": "Jiangsu", "neName": "QDAHSS17FE02BHW", "value": "0" }, { "time": 2018052810, "province": "Zhejiang", "neName": "QDAHSS17FE02BHW", "value": "0" } In one embodiment, after uniformly outputting the network element data of different network element types in a unified data format, the method further includes: Receiving a data query request; According to the data query request, using the network element data in a unified data format including multiple network element types as a query result.

[0050] Here, the data query request includes request parameters for requesting shared data, and is used to request the result of shared data, which are fixed request parameters.

[0051] ​This embodiment can output various types of network element indicator data through a unified interface call, completing the function of parsing and data retrieval in one go. Moreover, it can also retrieve data from different network elements, realizing the reuse of resources.

[0052] In one embodiment, the step of mapping common fields in network element data of multiple network element types to Chinese and English includes: Map the English indicators in the public fields to Chinese character types.

[0053] For example, the mapping relationship between English indicators and Chinese characters is as follows: put("loname", "region name"); put("dcname", "data center name"); put("vimname", "resource pool name"); put("userlabel", "Network element name"); put("province", "province name").

[0054] See Figure 2 , Figure 2 This is a flowchart illustrating the implementation of a network data processing method provided in an embodiment of the present invention, including: 1. Upload SQL.

[0055] The first step is to import different network metadata models (Upload SQL). These SQL statements rely on existing network metadata models and are used to query source data. Because these data models exist in different business systems, when using a unified method for sharing network metadata, the network metadata models that need to be shared must first be integrated into SQL statements and defined as Upload SQL.

[0056] 2. Query SQL The source data (network data) is obtained by querying SQL statements. For the network data model SQL imported in the first step, some data indicators need to be calculated. To facilitate use in the final data modeling stage, a query SQL step is introduced. The imported SQL fields are then recalculated to obtain the actual source dataset.

[0057] 3. Source dataset The source dataset is obtained by querying SQL, which contains network data retrieved from the source database based on the SQL query.

[0058] 4. Network Element Classification Because the network elements in the source dataset are of different types and the data indicators of different network elements are not the same, it is necessary to classify the network element types to distinguish whether there are network element data indicators that require special processing.

[0059] Different network element types are received through an enumeration class, which facilitates their use in subsequent processing. Currently, it covers six major categories: IOT, NFV, FGC, SCEP, SCEF, and FSCEP. It is also extensible, and other types of network elements can be added if needed.

[0060] For example, IoT network element types include: IOTHSS, IOTGGSN, IOTPCRF, IOTPGW, IOTHLR, IOTSMSA, IOTSMSB, and IOTCE.

[0061] NFV network element types include: NFVEPCDNS, NFVPCRF, NFVPGWC, NFVPGWU, NFVSGWC, NFVSGWU, NFVFSCEP, NFVIPSMGW, NFVSCEP, NFVSMSC, NFVSCEF, NFVSCP, NFVVMMSC, NFVTAS, NFVENUMDNS, NFVCSCF, NFVCENTREX, NFVPSBCC, NFVPSBCU, NFVMME.

[0062] FGC network element types include: FGCAMF, FGCSMF, FGCUPF, FGCUDM, FGCPCF, FGCNRF, FGCNSSF, FGCIWF, FGCCHF, FGCSMS.

[0063] 5. Determine if special treatment is required. 6. Field processing (x) Because the data metrics of different network elements vary, special processing is required for some specific network elements, mainly through... The (x) function is used for processing. The field processing here corresponds to the field mapping defined in the above embodiments, through... The (x) function needs to map and integrate special fields of different types of network data into a standard set required by a unified model.

[0064] The processing flow of the (x) function is as follows Figure 3As shown, for special network element fields, such as LO_NAME_FIELD for NFV and FGC type network elements, it needs to be mapped to loName; LO_NAME and PROVINCE_NAME represent the region name and province name, respectively, such as North China Region and Hebei Province. Map LO_NAME to LO_ID, and PROVINCE_NAME to PROVINCE_ID.

[0065] 7. Data mapping δ(x) For fields that do not require special processing, data mapping is performed directly. The δ(x) function maps the English and Chinese characters in the received source data fields for easy use in subsequent processing.

[0066] That is, the δ(x) function uses a map to map the English indicators of the public fields, converting them into Chinese characters for easy viewing and subsequent processing.

[0067] The δ(x) processing flow is as follows Figure 4 As shown, for fields in the network element classification results that do not require special processing, the Chinese-English mapping can be directly performed using the δ(x) function; for fields that require special processing, the mapping is first performed using... After processing by the (x) function, the Chinese and English characters are mapped using the δ(x) function.

[0068] For example, in the above example of entities returned by the HSS network element, "HSS", "60", "2018052511", "Jiangsu", and "HSS UE clearing success rate" are all output results of δ(x).

[0069] 8. Data modeling ω(x) After obtaining the data mapping results, the ω(x) function begins data modeling according to the input dataset and a specified pattern. This process mainly unifies the input and output models of network element shared data. The input consists of request parameters for requesting shared data, and the result of requesting shared data is a fixed request parameter. The modeling process for the output parameters is as follows: Figure 5 As shown.

[0070] The ω(x) function first generates the return entity class for each network element based on different network element types, maps the output of δ(x) to the entity class corresponding to different network element types, and finally reassembles these data as the final output.

[0071] 9. Return result set The output is network data in a unified data format. The final output result set can be represented by y, y=ω(δ( (x))), where x is the dataset after the source dataset has been classified by network elements. δ(x) is a special indicator field processing function used for a unified field during data mapping. δ(x) is a data mapping function, which mainly maps different network data fields through Map. ω(x) is a data modeling function, which mainly models response parameters and reorganizes network data into a unified output as the final result.

[0072] This embodiment uses network element enumeration to query data for different network elements. By defining the naming format for the network elements being queried, various types of network element data can be queried. The system achieves data sharing of network elements only after the entity classes and Mappers are written; only the SQL command for querying network elements needs to be rewritten, and other code does not require rewriting. After importing existing network element data into the database, it can be output in a unified format through a proprietary data model, enabling the sharing of various network element data in mobile networks.

[0073] This invention establishes a unified data model and a standard network element data format, then uses a unified interface to output various types of network element indicator data, completing the parsing and data retrieval functions in a single operation. Furthermore, it can retrieve data from different network elements, enabling resource reuse.

[0074] By using data modeling methods, key data indicators are selected and assembled before presentation, making the data more intuitive. Critical protection indicators are readily apparent, providing an intuitive understanding of network element operating status, enabling timely location of faulty network elements and problem repair. Furthermore, based on shared data, visual dashboards can be created, enriching the data status display.

[0075] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0076] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0077] It should be noted that the technical solutions described in the embodiments of the present invention can be combined arbitrarily without conflict.

[0078] In addition, in the embodiments of the present invention, "first," "second," etc. are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0079] In practical applications, the method steps of the above embodiments can be implemented by processors in electronic devices, such as central processing units (CPUs), digital signal processors (DSPs), microcontroller units (MCUs), or field-programmable gate arrays (FPGAs).

[0080] To implement the methods of the embodiments of this application, an electronic device is also provided. Figure 6 This is a schematic diagram of the hardware structure of the electronic device according to an embodiment of this application, as shown below. Figure 6 As shown, the electronic device includes: A communication interface enables information exchange with other devices, such as network devices. The processor, connected to the communication interface, enables information interaction with other devices and, when running a computer program, executes the methods provided by one or more technical solutions on the electronic device side. The computer program is stored in memory.

[0081] Of course, in practical applications, the various components in an electronic device are coupled together through a bus system. It can be understood that the bus system is used to achieve communication and connection between these components. In addition to the data bus, the bus system also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, in... Figure 6 The general will label all buses as bus systems.

[0082] The memory in this application embodiment is used to store various types of data to support the operation of the electronic device. Examples of such data include any computer program used to operate on the electronic device.

[0083] It is understood that memory can be volatile or non-volatile, or both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), ferromagnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); magnetic surface memory can be disk storage or magnetic tape storage. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memories described in the embodiments of this application are intended to include, but are not limited to, these and any other suitable types of memories.

[0084] The methods disclosed in the embodiments of this application can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor may be a general-purpose processor, a DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of this application can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, which is located in memory. The processor reads the program from the memory and, in conjunction with its hardware, completes the steps of the aforementioned method.

[0085] Optionally, when the processor executes the program, it implements the corresponding processes implemented by the electronic device in the various methods of the embodiments of this application. For the sake of brevity, these will not be described in detail here.

[0086] In an exemplary embodiment, this application also provides a computer program product, including a computer program that can be executed by a processor of an electronic device to perform the steps described in the method of this application embodiment.

[0087] In an exemplary embodiment, this application also provides a storage medium, namely a computer storage medium, specifically a computer-readable storage medium, such as a first memory storing a computer program, which can be executed by a processor of an electronic device to complete the steps described in the aforementioned method. The computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disc, or CD-ROM.

[0088] In the several embodiments provided in this application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components may be combined, or integrated into another system, or some features may be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0089] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0090] In addition, each functional unit in the various embodiments of this application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0091] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0092] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to related technologies, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0093] It should be noted that the technical solutions described in the embodiments of this application can be combined arbitrarily without conflict.

[0094] In addition, in this application example, terms such as "first" and "second" are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0095] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for processing network data, characterized in that, The method includes: Based on multiple defined network element data models, network element data of multiple network element types are obtained from the source database; Field mapping is performed on specified fields in network element data of multiple network element types. The field mapping is used to map the specified fields to standard fields in the standard field set. Based on the mapping results and the network element types corresponding to the network element data, the network element data of different network element types are output in a unified data format.

2. The method according to claim 1, characterized in that, The method further includes: Perform Chinese-English mapping on common fields in network element data for multiple network element types.

3. The method according to claim 1, characterized in that, The method further includes: Classify the network elements in the source database; Determine the network data containing the specified fields based on the classification results.

4. The method according to claim 3, characterized in that, The classification of network elements in the source database includes: Multiple network elements belonging to the same network function type are grouped into the same enumeration type.

5. The method according to claim 1, characterized in that, The step of outputting network element data of different network element types in a unified data format based on the mapping results and the network element types corresponding to the network element data includes: Determine the entity class corresponding to the network element type; Based on the entity class and the mapping result, network data in a unified data format is generated.

6. The method according to claim 1, characterized in that, After outputting network element data of different types in a unified data format, the method further includes: Receive data query requests; Based on the data query request, network element data in a unified data format, including multiple network element types, will be used as the query result.

7. The method according to claim 2, characterized in that, The mapping of common fields in network element data of multiple network element types to Chinese and English includes: Map the English indicators in the public fields to Chinese character types.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the network data processing method as described in any one of claims 1 to 7.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the network data processing method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions that, when executed by a processor, cause the processor to perform the steps of the network data processing method as described in any one of claims 1 to 7.

Images