An industrial internet identification node cross-platform interfacing method for an industry chain graph system

Abstract

The application discloses an industrial internet identification node cross-platform docking method for an industry chain graph system, and aims to solve the problems of the existing secondary node docking interface, such as non-compatibility, disordered data format, poor portability and stability and the like. The method constructs a general interface adaptation layer, automatically identifies and adapts to multiple communication protocols without separately developing adaptation codes; a data conversion engine is built to realize bidirectional automatic standardized mapping of heterogeneous fields and data types; a multi-environment self-adaptive module is configured to adapt to different operating systems and databases, support cross-environment one-key deployment; real-time state monitoring and exponential backoff reconnection, breakpoint resume transmission self-healing mechanisms are added to guarantee the docking stability. Finally, the graph system, the secondary node and the national public platform are deployed in a three-party joint debugging mode. The application greatly shortens the docking period, improves the data precision and portability, and guarantees the efficient and stable intercommunication of the industry chain identification data.

Description

Technical Field

[0001] This invention belongs to the field of industrial internet interface adaptation and identifier resolution node docking technology. It relates to a cross-platform and cross-environment identifier node docking method for industrial chain graph systems, and particularly to node docking technology with automatic multi-protocol adaptation and automatic multi-environment portability. Background Technology

[0002] The Industrial Internet Identifier Resolution System is a crucial component of the Industrial Internet network architecture, serving as the nerve center supporting interconnectivity. Secondary nodes are identifier service nodes tailored to specific industries or enterprises, providing services such as identifier registration, resolution, and data sharing. The supply chain mapping system needs to connect to these secondary nodes, acquiring their identifier data and synchronizing the mapping system's data to the nodes to achieve data interoperability and sharing, thereby supporting the digital integration of the supply chain.

[0003] However, the current secondary node integration process has many problems, resulting in low integration efficiency, poor portability, and poor stability. Specifically: First, the interface compatibility is poor. Different secondary nodes use different interface protocols, some are RESTful API, some are SOAP protocol, and some are private RPC protocol. Moreover, the interface parameters and return formats are not uniform, which means that when connecting, it is necessary to develop adaptation code separately for each different node. The development workload is large and the connection cycle is long. It usually takes 7-10 days to connect a node, which is extremely inefficient. Second, the data format is inconsistent. Different nodes have different data formats and field definitions. For example, for the same enterprise identifier, some nodes use "ent_name" as the enterprise name field, some use "enterprise_name", and some use "company name". This requires manual data format conversion during the connection process, which is prone to errors and has high maintenance costs. Third, poor portability. Well-integrated modules can usually only run in specific deployment environments. For example, a module developed in a Windows environment cannot run in a Linux environment. It requires reconfiguration and recompilation, which makes it difficult to port the module and cannot be quickly deployed to different environments to meet the deployment needs of different users. Fourth, it has poor stability. After the connection is established, there is no real-time status monitoring mechanism. Once the network fluctuates or the node service is abnormal, the connection will be interrupted. Moreover, there is no automatic reconnection mechanism, which requires manual restart of the connection, resulting in data transmission interruption, affecting the real-time performance of the data, and failing to guarantee the stability of the connection.

[0004] These issues have made it difficult to achieve efficient and stable integration between the supply chain mapping system and secondary nodes, severely impacting the interoperability and sharing of supply chain data and hindering the realization of the value of the industrial internet identifier resolution system. Therefore, developing a cross-platform integration method that can automatically adapt to different node interfaces, automatically convert data formats, automatically adapt to deployment environments, and provide real-time monitoring to ensure stability has become an urgent technical challenge. Summary of the Invention

[0005] One technical problem to be solved The technical problem this invention aims to solve is to address the shortcomings of existing technologies, such as incompatible interfaces for secondary nodes, inconsistent formats, poor portability, and poor stability. This invention provides a cross-platform docking method for industrial internet identifier nodes in a supply chain mapping system, achieving full-process automation of the docking process. It eliminates the need for developing separate adaptation code for different nodes, significantly improving docking efficiency. Simultaneously, it enables automatic adaptation to multiple environments, enhancing module portability. Furthermore, real-time monitoring ensures docking stability, achieving three-way interoperability between the supply chain mapping system, secondary nodes, and the national public platform.

[0006] Two technical solutions To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for cross-platform integration of industrial internet identifier nodes for supply chain mapping systems includes the following steps: Step 1: To address the interface differences between different second-level nodes, a universal interface adaptation layer is built. This layer includes built-in adaptation modules for mainstream interface protocols, such as RESTful API, SOAP, and private RPC protocols, and can automatically identify the interface protocol type of the connected nodes. The adaptation layer provides a unified calling interface. Regardless of the type of the underlying node interface, the upper-level graph system uses this unified interface for all calls, eliminating the need to worry about underlying differences. Furthermore, the adaptation layer includes an automatic interface detection mechanism. During integration, it automatically detects the node's interface type and parameter format, and automatically loads the corresponding adaptation module, requiring no manual configuration. Step 2: To address the data format differences between different nodes, an automatic format conversion engine is built. This engine incorporates a built-in field mapping model that automatically identifies field definitions across different nodes and performs the necessary mappings. For example, if a node's company name field is "ent_name", the engine automatically maps it to the "company name" field in the graph system. Conversely, when data from the graph system needs to be synchronized to a node, the engine automatically converts "company name" to the corresponding "ent_name" field, achieving bidirectional automatic conversion. Furthermore, the engine includes built-in automatic data type conversion. For instance, if a node's numeric type is a string, it is automatically converted to the system's numeric type, ensuring data consistency without requiring manual format conversion. Step 3: To address the differences in deployment environments, a multi-environment automatic adaptation module is built. This module can automatically identify the current deployment environment, including operating system type (Windows, Linux), database type (MySQL, PostgreSQL), and runtime environment version, and automatically adjust the module's runtime configuration. For example, when a Windows Server 2019 environment is detected, the Windows environment configuration, including path configuration and service startup configuration, is automatically loaded; when a CentOS 7.9 environment is detected, the Linux environment configuration, including permission configuration and process configuration, is automatically loaded. Simultaneously, the database connection configuration is automatically adapted, regardless of the underlying database type. This automatic adaptation eliminates the need for manual configuration modifications, enabling one-click deployment of the module and significantly improving its portability. Step 4: Establish a real-time connection status monitoring mechanism to periodically detect the service status and data transmission status of the connection nodes, and monitor indicators such as connectivity, transmission success rate, and latency in real time. When network fluctuations or service anomalies cause connection interruptions, an automatic reconnection mechanism is triggered. Following an exponential backoff strategy, the mechanism automatically attempts to reconnect until a successful connection is established, while simultaneously recording exception logs for later troubleshooting. Furthermore, the mechanism supports breakpoint resumption of transmitted data. After a successful reconnection, transmission automatically resumes from the point of interruption, ensuring no data loss and guaranteeing data transmission integrity, thus achieving high connection stability. Step 5: Automatically conduct three-party integration testing to verify the effectiveness of interface connectivity, data transmission, and environment adaptation, automatically generate a test report, and complete the entire integration process.

[0007] Further limitations on the above technical solution: In step 5, after the adaptation and configuration are completed, the three-way joint debugging test of the graph system, secondary nodes, and national public platform is automatically carried out. The connectivity of the interfaces, bidirectional data transmission, and environmental adaptability are automatically tested. Test reports are automatically generated, including the test results of each interface, the accuracy of data transmission, and the environmental adaptability, to verify the effectiveness of the docking and complete the entire docking process.

[0008] A cross-platform interface system for industrial internet identifier nodes in a supply chain mapping system includes: Multi-source heterogeneous identification platform access device: connects to three types of data sources: industrial internet identification resolution secondary node, third-party industrial data platform, and enterprise internal system; Original heterogeneous identifier data module: Original identifier data from different platforms and with different encoding formats, including three categories: enterprise entity identifier, product identifier, and industry node identifier, corresponding to the three core data dimensions of the system; Data preprocessing module: includes: Protocol adaptation and conversion submodule: Adapts to the communication protocols of different platforms and completes protocol conversion; Interface authentication and verification submodule: Identity authentication and permission verification for cross-platform data calls; Identifier encoding decomposition submodule: Decomposes the structure of identifier encodings of different formats and extracts core information; Abnormal data filtering submodule: Removes invalid, duplicate, and out-of-range abnormal data; The identifier resolution module performs type identification and metadata extraction on the preprocessed identifier data, distinguishing between three types of identifiers: enterprise, product, and node. Node mapping module: It performs two-layer processing of scheduling semantic adaptation and node mapping, and completes the mapping of external data to the system's built-in structure; Semantic adaptation layer module: includes: Field semantic matching unit: Automatically maps fields from different platforms to fields in the system data table, corresponding to the field binding logic in the code; Standardized Format Unit: Converts heterogeneous data into a unified standard format for the system; Node mapping layer: Node code matching unit: Matches node codes with the system's industry chain node table, corresponding to the node code matching logic in the code; Node Link Alignment Unit: Aligns the hierarchical relationship of external data with the system's 5-layer industry chain link, corresponding to the system's node link function; The graph system data writing module writes the mapped data into the system's MySQL database, corresponding to the system's data storage architecture. Mapping rule training module: Trains rule models for field mapping and node matching based on historical data; The input feature set module includes three types of features: industry classification rules, field mapping rules, and node matching rules, which provide rule inputs for mapping processing. Mapping rule evaluation and optimization module: Evaluates the quality of mapping results and optimizes and adjusts unqualified rule parameters; The simulation verification module determines whether the completeness, accuracy, and relevance of the connected data meet the system requirements. If the data meets the requirements, the system proceeds to the deployment stage; otherwise, it returns to the rule optimization stage. Integrate and deploy the interface into the graph system module: After successful verification, the cross-platform interface will be officially integrated and deployed into the instrumentation industry chain graph system for use.

[0009] Three beneficial effects Compared with existing technologies, this invention provides a cross-platform connection method for industrial internet identification nodes in a supply chain mapping system, which has the following beneficial effects: 1. Achieve fully automatic multi-protocol adaptation, significantly improving integration efficiency. This invention constructs a universal interface adaptation layer that can automatically identify and adapt to the communication protocols and interface specifications of various secondary nodes. There is no need to develop adaptation code separately for different nodes, greatly shortening the single-node integration cycle and completely solving the problems of large workload, long cycle, and low efficiency of traditional integration methods.

[0010] 2. Achieve fully automated standardization of heterogeneous data, ensuring accurate data interoperability. Through an intelligent format conversion engine, it completes bidirectional automatic mapping and standardization of fields and data types from multiple sources of heterogeneous data, without manual intervention. This effectively avoids the risk of errors from manual conversion, reduces system maintenance costs, and ensures the accuracy and consistency of bidirectional data synchronization across the industry chain.

[0011] 3. Enables cross-environment adaptive deployment and improves module portability. The multi-environment automatic adaptation module can automatically identify environmental parameters such as operating system, database, and runtime version, and adaptively match the runtime configuration. No manual modification of parameters or recompilation is required, enabling one-click deployment across multiple environments such as Windows and Linux. It adapts to various user deployment scenarios and has extremely strong versatility and portability.

[0012] 4. Possesses real-time monitoring and anomaly self-healing capabilities, ensuring high stability of the connection. Through all-time status monitoring, exponential backoff reconnection, and breakpoint resumption mechanisms, it effectively solves the problems of connection interruption and data loss caused by network fluctuations and node anomalies. No manual operation and maintenance is required, greatly improving the stability of the connection link and the integrity of data transmission.

[0013] 5. Achieve interoperability among the three parties to support the digital integration of the industrial chain. This invention can achieve efficient joint debugging and data interoperability among the industrial chain mapping system, industrial internet secondary nodes, and national public platforms, breaking down barriers to industrial data flow, fully leveraging the core value of the industrial internet identifier resolution system, and providing stable and efficient technical support for the digital and intelligent construction of the entire industrial chain. Attached Figure Description

[0014] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a system block diagram of the present invention; The module includes: 1. Multi-source heterogeneous identifier platform access device; 2. Original heterogeneous identifier data module; 3. Data preprocessing module; 301. Protocol adaptation and conversion submodule; 302. Interface authentication and verification submodule; 303. Identifier encoding decomposition submodule; 304. Abnormal data filtering submodule; 4. Identifier parsing module; 5. Node mapping module; 6. Semantic adaptation layer module; 601. Field semantic matching unit; 602. Format standardization unit; 7. Node mapping layer; 701. Node encoding matching unit; 702. Node link alignment unit; 8. Graph system data writing module; 9. Mapping rule training module; 10. Input feature set module; 11. Mapping rule evaluation and optimization module; 12. Simulation verification module; 13. Integration and deployment of the interface into the graph system module. Detailed Implementation

[0015] The following is in conjunction with the appendix Figure 1-2 The present invention will be described in further detail below.

[0016] Example: Figure 1 , 2 As shown, this embodiment discloses a cross-platform docking method for industrial internet identifier nodes in a supply chain mapping system, taking the docking needs of secondary nodes in the instrumentation industry as an example.

[0017] This embodiment connects to a secondary node of the Industrial Internet Identifier Resolution System in the instrumentation industry. This node uses the RESTful API communication protocol and is also compatible with a small number of private RPC data interaction interfaces. During implementation, a unified data access entry is first established through the multi-source heterogeneous identifier platform access device 1, completing the data source connection between the target secondary node and the enterprise's internal industrial data platform. Subsequently, the protocol adaptation and conversion submodule 301 in the data preprocessing module 3 is activated. Relying on the automatic detection mechanism of the interface adaptation layer, the system automatically identifies the communication protocol type, interface request parameters, and response data format of the current node. No manual configuration of protocol parameters or separate development of adaptation code is required. The system automatically matches and loads the RESTful API-specific adaptation module, while also being compatible with the node's private RPC protocol interaction scenarios. Compared to the traditional 7-day single-node connection cycle, this step only requires 1 day to complete protocol adaptation and interface connectivity, improving connection efficiency by over 85%. Simultaneously, the interface authentication and verification submodule 302 synchronously completes cross-platform interface identity authentication and permission verification, ensuring data access security and compliance.

[0018] Then, the raw heterogeneous identifier data of the secondary nodes is collected through the raw heterogeneous identifier data module 2, covering three core data categories: enterprise entity identifier, product identifier, and industry node identifier. The custom fields of this node are "ent_name" (enterprise name), "reg_cap" (registered capital), and "year_val" (annual output value). The data type is mainly string, which is significantly different from the standard format of the graph system. First, the identifier coding decomposition submodule 303 of the data preprocessing module 3 decomposes the various identifier coding structures and extracts the core valid data. Then, the abnormal data filtering submodule 304 removes duplicate, invalid, and out-of-range abnormal data, completing the initial data cleaning.

[0019] After cleaning, the data is input into the identifier parsing module 4 to complete the classification and identification of three types of identifiers: enterprise, product, and node, and the extraction of metadata. Finally, data standardization is achieved through the semantic adaptation layer module 6: the field semantic matching unit 601 automatically establishes the mapping relationship between externally customized fields and system standard fields, automatically converting "ent_name" and "reg_cap" into the system standard fields "enterprise name" and "registered capital"; the format standardization unit 602 completes automatic error correction and conversion of data types such as strings, numbers, and time, and also supports reverse conversion, which can synchronously adapt the standard data of the graph system to the secondary node data format, realizing bidirectional data interoperability. In this embodiment, the data conversion accuracy reaches 100%, with no format errors or data distortion problems.

[0020] After data standardization is completed, the node mapping module 5 schedules a two-layer mapping logic to achieve precise adaptation between external data and the system's industrial chain structure. Specifically, the node encoding matching unit 701 in the node mapping layer 7 completes the precise matching between external identifier codes and the system's industrial chain node data table based on the node matching rules stored in the input feature set module 10; the node link alignment unit 702 precisely aligns the industrial hierarchy relationship of the external data with the system's preset 5-layer standardized industrial chain links, adapting to the upstream and downstream industrial association logic of the instrumentation industry.

[0021] Meanwhile, the mapping rule training module 9 iteratively optimizes the intelligent rule model for field mapping and node matching based on the real data of this docking. The mapping rule evaluation and optimization module 11 verifies the completeness and accuracy of the mapping results in real time, automatically fine-tunes and optimizes the rule parameters for adaptation deviations, and continuously improves the adaptation accuracy of subsequent docking, solving the problems of poor universality and low adaptation accuracy of traditional fixed mapping rules.

[0022] Next, the multi-environment automatic adaptation module automatically identifies the deployment environment. First, it is deployed in a Windows Server 2019 environment. The module automatically detects the operating system type and loads the Windows environment configuration, including the service startup method and path configuration. The module runs normally. Then, the module is deployed to a CentOS 7.9 environment. The module automatically detects the Linux environment and loads the Linux environment configuration, including permission configuration and process configuration. At the same time, it automatically adapts the database connection. The module runs normally without any manual modification of the configuration, realizing one-click deployment and automatic adaptation, which solves the problem of manual configuration modification required for traditional module porting.

[0023] After the environment adaptation is completed, the data writing module 8 of the graph system writes all the industry identification data that meet the mapping standards and are formatted in batches into the system's MySQL database to complete the persistent storage of data and provide stable data support for the rendering of the industry chain graph and the analysis of industry data.

[0024] Then, a connection status monitoring mechanism monitors the connection status in real time, probing the node's service status every 30 seconds to monitor transmission success rate and latency. During testing, a network outage was simulated. The monitoring mechanism detected the anomaly within 10 seconds, automatically triggering a reconnection mechanism. It attempted to reconnect using an exponential backoff strategy of 1 second, 2 seconds, and 4 seconds, successfully reconnecting after 5 seconds and automatically resuming data transmission from the breakpoint without any data loss, ensuring data integrity.

[0025] Finally, a three-way joint debugging test was conducted to test the interoperability between the system, nodes, and the national public platform, the connectivity of 12 core interfaces, the bidirectional data transmission, and the module operation in two environments. A test report was generated, and the results showed that the connectivity of all interfaces was normal, the data transmission accuracy reached 100%, the module could run normally in both environments, and the data transmission success rate reached 99.9% after 72 hours of continuous operation testing. The module startup time was within 1.2 seconds, which fully met the docking requirements.

[0026] After the entire process is adapted, the simulation verification module 12 conducts simulation verification from three dimensions: data integrity, data accuracy, and industry relevance, to determine whether the docking effect meets the system standards. After the verification is passed, the three-party joint debugging test of the industry chain map system, the instrumentation industry secondary node, and the national public platform is automatically launched, covering the connectivity, bidirectional data transmission, cross-environment adaptation, and anomaly self-healing capability tests of 12 core business interfaces, and automatically generating a standardized test report.

[0027] The test results of this embodiment show that: all core interfaces have normal connectivity, and the accuracy of bidirectional data transmission is 100%; the module startup time in the dual deployment environment is ≤1.2 seconds; in the 72-hour continuous stable operation test, the data transmission success rate reached 99.9%, fully meeting the needs of industry integration. Finally, by integrating and deploying the interface into the graph system module 13, the formal online deployment of the cross-platform interface was completed, achieving normalized and stable operation.

Claims

1. A method for cross-platform connection of industrial internet identifier nodes for supply chain mapping systems, characterized in that, Includes the following steps: Step 1: Build a general interface adaptation layer with a built-in multi-protocol adaptation module. It automatically identifies the interface protocol type of the secondary node and automatically loads the corresponding adaptation module to provide a unified calling interface for the upper layer system and shield the differences of the underlying interface. Step 2: Build an automatic data format conversion engine with a built-in field mapping model to automatically identify the field definitions of different nodes, realize bidirectional automatic conversion of data formats between nodes and the graph system, and ensure data consistency; Step 3: Build a multi-environment automatic adaptation module to automatically identify the operating system, database, and runtime environment version of the deployment environment, and automatically adjust the module's running configuration to achieve automatic adaptation of the module in different environments and improve portability; Step 4: Establish a real-time monitoring mechanism for the connection status, periodically detect the node service status and transmission status, and automatically trigger reconnection and breakpoint resume when an abnormal interruption is detected to ensure the stability of the connection and the integrity of the data. Step 5: Automatically conduct three-party integration testing to verify the effectiveness of interface connectivity, data transmission, and environment adaptation, automatically generate a test report, and complete the entire integration process.

2. A method for cross-platform connection of industrial internet identifier nodes for a supply chain mapping system according to claim 1, characterized in that, In step 1, the multi-protocol adaptation module includes RESTful API adaptation, SOAP protocol adaptation, and private RPC protocol adaptation, which can automatically identify the interface protocol type of the connected node.

3. A method for cross-platform connection of industrial internet identifier nodes for a supply chain mapping system according to claim 2, characterized in that, In step 1, the interface adaptation layer has a built-in automatic interface detection mechanism. During the connection process, it automatically detects the interface type and parameter format of the node and automatically loads the corresponding adaptation module without manual configuration.

4. A method for cross-platform connection of industrial internet identifier nodes for a supply chain mapping system according to claim 1, characterized in that, In step 4, automatic reconnection and resume transmission specifically include real-time monitoring of metrics such as connectivity, transmission success rate, and latency. When network fluctuations or service anomalies are detected that cause the connection to be interrupted, the reconnection mechanism is automatically triggered. Following an exponential backoff strategy, the system automatically attempts to reconnect until the connection is successful. At the same time, an error log is recorded for easy troubleshooting. Additionally, the system supports resume transmission of data from the point of interruption. Once the reconnection is successful, the transmission automatically resumes from the point of interruption without data loss, ensuring the integrity of data transmission and achieving high stability of the connection.

5. A method for cross-platform connection of industrial internet identifier nodes for a supply chain mapping system according to claim 1, characterized in that, In step 5, the three-party joint debugging test specifically involves the joint debugging test of the graph system, secondary nodes, and the national public platform.

6. A cross-platform docking system for industrial internet identifier nodes in a supply chain mapping system, based on any one of the docking methods in claims 1-5, characterized in that, include: Multi-source heterogeneous identification platform access device: connects to three types of data sources: industrial internet identification resolution secondary node, third-party industrial data platform, and enterprise internal system; Original heterogeneous identifier data module: Original identifier data from different platforms and with different encoding formats, including three categories: enterprise entity identifier, product identifier, and industry node identifier, corresponding to the three core data dimensions of the system; Data preprocessing module: includes: Protocol adaptation and conversion submodule: Adapts to the communication protocols of different platforms and completes protocol conversion; Interface authentication and verification submodule: Identity authentication and permission verification for cross-platform data calls; Identifier encoding decomposition submodule: Decomposes the structure of identifier encodings of different formats and extracts core information; Abnormal data filtering submodule: Removes invalid, duplicate, and out-of-range abnormal data; The identifier resolution module performs type identification and metadata extraction on the preprocessed identifier data, distinguishing between three types of identifiers: enterprise, product, and node. Node mapping module: It performs two-layer processing of scheduling semantic adaptation and node mapping, and completes the mapping of external data to the system's built-in structure; Semantic adaptation layer module: includes: Field semantic matching unit: Automatically maps fields from different platforms to fields in the system data table, corresponding to the field binding logic in the code; Standardized Format Unit: Converts heterogeneous data into a unified standard format for the system; Node mapping layer: Node code matching unit: Matches node codes with the system's industry chain node table, corresponding to the node code matching logic in the code; Node link alignment unit: Aligns the hierarchical relationship of external data with the system's 5-layer industry chain link, corresponding to the system's node link function; The graph system data writing module writes the mapped data into the system's MySQL database, corresponding to the system's data storage architecture. Mapping rule training module: Trains rule models for field mapping and node matching based on historical data; The input feature set module includes three types of features: industry classification rules, field mapping rules, and node matching rules, which provide rule inputs for mapping processing. Mapping rule evaluation and optimization module: Evaluates the quality of mapping results and optimizes and adjusts unqualified rule parameters; Simulation verification module: Determines whether the completeness, accuracy, and relevance of the connected data meet the system requirements; if it meets the requirements, it proceeds to the deployment stage; if it does not meet the requirements, it returns to the rule optimization stage. Integrate and deploy the interface into the graph system module: After successful verification, the cross-platform interface will be officially integrated and deployed into the instrumentation industry chain graph system for use.

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