Edge computing node deployment method and system suitable for 5G industrial private network

Abstract

The invention provides an edge computing node deployment method and system suitable for a 5G industrial private network, and relates to the technical field of computing node deployment, and the method comprises the steps: displaying an MEC node configuration page, obtaining MEC node basic configuration information and industrial service resource configuration information, generating deployment parameters, and sending the deployment parameters to a target terminal. An MEC operation environment supporting network slice logic isolation, multi-WAN port route backup and GRE tunnel main and standby disaster recovery is deployed; performing a network quality test and a disaster recovery switching test in response to the debugging instruction, and if an industrial-grade preset operation condition is met, constructing an edge computing node; registering node metadata, and identifying slice affiliation, disaster recovery link information and hardware identification; the system correspondingly comprises a configuration display module, a configuration information acquisition module, a deployment parameter generation module, a deployment execution module, a debugging and construction module and a node registration module. According to the invention, automatic deployment and verification are realized, the problems of low industrial scene deployment efficiency and poor reliability are solved, and the requirements of ultralow time delay, high bandwidth and high reliability are met.

Description

A method and system for deploying edge computing nodes for 5G industrial private networks Technical Field

[0001] This invention relates to the field of computing node deployment technology, and in particular to a method and system for deploying edge computing nodes suitable for 5G industrial private networks. Background Technology

[0002] Edge computing technology, by offloading computing, storage, and network resources to the industrial park or workshop, provides localized services for industrial applications such as machine vision analysis, AGV scheduling, and PLC control command issuance, effectively reducing business latency and improving data security. In a 5G standalone network architecture, achieving local data offloading through UPF (User Plane Function) offloading is a key technical path for industrial private networks. However, in actual deployment and operation, the configuration and management of edge computing nodes face severe challenges. Currently, the deployment of industrial edge computing nodes mostly adopts traditional IT deployment methods, lacking dedicated optimization for industrial scenarios. Specifically, in typical industrial fields such as intelligent manufacturing and energy power, business operations have extremely high requirements for real-time performance and reliability. For example, in the welding robot control system of an automobile manufacturing plant, the end-to-end latency of control commands must be stable within 10 milliseconds, the packet loss rate cannot exceed 0.01%, and any network failure must be completed within 20 seconds to avoid production accidents. However, existing technologies have the following specific pain points that are difficult to solve: First, the problem of fragmented configuration is prominent. Edge node deployment involves multi-dimensional configurations, including network slicing QoS parameters, multi-network access disaster recovery strategies, and QUIC protocol optimization. These configurations are often handled separately by different management systems; for example, the network management system is responsible for slice configuration, while the edge platform is responsible for service deployment. This leads to difficulties in configuration coordination, potential parameter inconsistencies or conflicts, and extended deployment time. Secondly, the debugging and verification process is weak. The lack of automated testing tools after deployment makes it impossible to quickly verify whether node performance meets standards. Manual intervention is required for network quality testing and disaster recovery drills, which is inefficient, subjective, and makes it difficult to guarantee industrial-grade SLAs. Thirdly, the disaster recovery mechanism is inadequate. Existing methods often employ simple hardware redundancy, which cannot achieve multi-WAN port routing backup and GRE tunnel primary / backup disaster recovery based on network slices. In the event of 5G wireless link fluctuations or wired failures, the switching latency is high, and the risk of service interruption is high. Furthermore, resource utilization is low; MEC node instances are often dedicated to specific services, failing to support multi-service sharing and increasing hardware costs and operational complexity. Taking a real-world PCB solder joint quality inspection scenario as an example, the visual analysis service needs to process 1080p video streams in real time. A latency exceeding 10ms may lead to missed detections. However, existing deployment methods often suffer from latency fluctuations or disaster recovery failures due to complex configurations and insufficient debugging, affecting production quality. Therefore, developing an integrated and automated edge computing node deployment method and system has become an urgent need for the implementation of 5G industrial private networks in industrial settings. Summary of the Invention

[0003] The purpose of this invention is to provide a method and system for deploying edge computing nodes in 5G industrial private networks, to solve the problems in existing technologies such as complex and fragmented configurations, lack of automated testing and verification methods, insufficient reliability of disaster recovery mechanisms, and low resource utilization, which lead to low deployment efficiency of industrial edge computing nodes and difficulty in meeting the stringent service level protocol requirements of industrial applications for ultra-low latency, high reliability, and high bandwidth. The specific technical solution is as follows: This invention provides a method for deploying edge computing nodes in 5G industrial private networks, including: S101: Displaying an MEC node configuration page through a deployment management module running on an edge computing management platform. The configuration page includes MEC multiplexing parameter configuration items, network slicing QoS parameter configuration items, multi-network access disaster recovery configuration items, and QUIC protocol optimization parameter configuration items; S102: Obtaining user-determined basic configuration information of the MEC node and industrial service resource configuration information associated with the basic configuration information of the MEC node through the MEC node configuration page. The industrial service resource configuration information includes 5G... LAN Layer 2 networking parameters, multi-link redundancy strategy, industrial service traffic forwarding rules, and security encryption strategy based on independently controllable chips; S103: Based on the basic configuration information of MEC nodes and the configuration information of industrial service resources, generate deployment parameters for running MEC nodes and industrial service resources. The deployment parameters also include hardware driver parameters adapted to industrial-grade terminals in the energy industry and network slicing resource reservation parameters; S104: Send the deployment parameters to the target industrial-grade edge terminal so that the target industrial-grade edge terminal can deploy the MEC operating environment based on the deployment parameters. The operating environment supports network slicing logical isolation, multi-WAN port routing backup, and GRE tunnel primary and backup disaster recovery functions; S105: Respond to industrial... The service resource debugging command performs network quality testing and disaster recovery switching testing based on the operating environment to obtain debugging results. When the debugging results indicate that the industrial service resources meet the industrial-grade preset operating conditions, an edge computing node construction request is sent to the target industrial-grade edge terminal so that the target industrial-grade edge terminal can construct an edge computing node in a pending state based on the edge computing node construction request. S106: Receive the node metadata sent by the target industrial-grade edge terminal and register the node metadata in the edge computing management platform. The node metadata is used to identify the slice affiliation, disaster recovery link information and industrial business scheduling routing rules of the edge computing node. The node metadata also contains hardware identification information of the autonomous and controllable network elements.

[0004] Furthermore, prior to S101, it also includes responding to user-triggered node creation commands and displaying the MEC node configuration page through the deployment management module; the node creation command is triggered by the new node control in the service list page, which is used to display existing edge computing node information and includes a search box and category controls.

[0005] Furthermore, obtaining basic configuration information for MEC nodes includes validating the initial information of MEC nodes and obtaining the validation result. If the validation result indicates that the initial information of MEC nodes has passed the validation, basic configuration information of MEC nodes is generated in the edge computing management platform based on the initial information of MEC nodes. The validity validation includes at least one of the following methods: verifying the matching between the communication protocol type and the management IP address, and determining whether the protocol type and IP address format conform to preset rules; testing the compatibility between the network access method and the industrial private network security policy, ensuring that the access method complies with firewall rules and data security requirements; and confirming the uniqueness of the node identifier in the platform to avoid identifier conflicts.

[0006] Further, obtaining industrial service resource configuration information includes: in response to an industrial service resource registration instruction for MEC node basic configuration information, generating an industrial service resource registration context environment to limit the interaction constraint parameters between industrial service resources and MEC node basic configuration information; in the industrial service resource registration context environment, loading a 5G LAN networking parameter configuration component, a multi-link redundancy policy configuration component, and an industrial service traffic rule editing component corresponding to the industrial service resource; obtaining user-determined 5G LAN Layer 2 networking parameters through the 5G LAN networking parameter configuration component, obtaining a multi-link redundancy policy through the multi-link redundancy policy configuration component, and obtaining industrial service traffic forwarding rules through the industrial service traffic rule editing component; integrating and processing the 5G LAN Layer 2 networking parameters, multi-link redundancy policy, and industrial service traffic forwarding rules to obtain industrial service resource configuration information associated with MEC node basic configuration information.

[0007] Furthermore, the network quality test includes tests for latency, packet loss rate, and bandwidth stability indicators; the disaster recovery switching test includes simulating a primary link failure to measure the backup link switching time and service continuity; the industrial-grade preset operating conditions include: latency not exceeding 10 milliseconds, packet loss rate not exceeding 0.01%, and disaster recovery switching time not exceeding 20 seconds.

[0008] Furthermore, it also includes: responding to a modification request for industrial service resources, displaying a service resource modification page, and obtaining second modification information through the service resource modification page; updating deployment parameters based on the second modification information, and re-executing the deployment and testing processes from S104 to S106; in S105, testing based on debugging instructions includes: displaying a debugging page, which includes a network quality test configuration area, a disaster recovery test trigger area, a real-time indicator display area, and a detailed log viewing area; generating an example test data stream based on industrial business traffic forwarding rules, and displaying the example test data stream on the debugging page; after detecting a user's confirmation instruction for the example test data stream, encapsulating the example test data stream into a test message, and initiating a debugging call request to the target industrial-grade edge terminal to trigger network quality testing and disaster recovery switching testing; obtaining the test output data returned by the target industrial-grade edge terminal, parsing and processing the test output data according to the network quality assessment rules and disaster recovery switching assessment rules, and generating debugging results; the example test data stream is generated based on the service type defined in the industrial business traffic forwarding rules, including simulated data of control instruction services, video stream services, or sensor data services.

[0009] Furthermore, the process of generating deployment parameters in S103 includes: parsing the basic configuration information of the MEC node to obtain the basic parameters required for the operation of the MEC node, including the container image address, runtime dependency library list, system service startup order and log storage path; determining the deployment specifications of industrial service resources by combining industrial service resource configuration information, including 5G LAN networking script, multi-link routing table configuration, traffic policy rule set and security policy loading instructions; and integrating and formatting the above information to generate a structured deployment parameter file or executable deployment script.

[0010] Furthermore, if the debugging results indicate that the industrial service resources do not meet the industrial-grade preset operating conditions, the method further includes: determining the MEC operation configuration anomaly based on the debugging results; displaying the operation configuration anomaly through the anomaly configuration modification page and obtaining the first modification information determined for the operation configuration anomaly; updating the deployment parameters based on the first modification information to generate updated deployment parameters; and returning to execute S104 and S105 based on the updated deployment parameters to redeploy the MEC operation environment and perform testing.

[0011] This invention also provides an edge computing node deployment system suitable for 5G industrial private networks, used to implement the method, comprising: a configuration display module, used to display an MEC node configuration page through a deployment management module running on an edge computing management platform, the configuration page including MEC multiplexing parameter configuration items, network slicing QoS parameter configuration items, multi-network access disaster recovery configuration items, and QUIC protocol optimization parameter configuration items; and a configuration information acquisition module, used to acquire user-determined basic configuration information of the MEC node and industrial service resource configuration information associated with the basic configuration information of the MEC node through the MEC node configuration page, the industrial service resource configuration information including 5G... The system includes: LAN Layer 2 networking parameters, multi-link redundancy strategies, industrial service traffic forwarding rules, and security encryption strategies based on independently controllable chips; a deployment parameter generation module, used to generate deployment parameters for running MEC nodes and industrial service resources based on MEC node basic configuration information and industrial service resource configuration information, including hardware driver parameters adapted to industrial-grade terminals in the energy industry and network slicing resource reservation parameters; a deployment execution module, used to send the deployment parameters to the target industrial-grade edge terminal, enabling the target industrial-grade edge terminal to deploy the MEC operating environment based on the deployment parameters, the operating environment supporting network slicing logical isolation, multi-WAN port routing backup, and GRE tunnel primary / backup disaster recovery functions; and a debugging and building module, used to respond to the industrial service... The system sends debugging instructions for industrial service resources, performs network quality testing and disaster recovery switching testing based on the operating environment, and obtains debugging results. If the debugging results indicate that the industrial service resources meet the preset industrial-grade operating conditions, it sends an edge computing node construction request to the target industrial-grade edge terminal, so that the target industrial-grade edge terminal can construct an edge computing node in a pending-call state based on the edge computing node construction request. A node registration module is used to receive node metadata sent by the target industrial-grade edge terminal and register the node metadata with the edge computing management platform. The node metadata is used to identify the slice affiliation, disaster recovery link information, and industrial business scheduling routing rules of the edge computing node. The node metadata also includes hardware identification information of independently controllable network elements.

[0012] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, performs the steps of the method described herein.

[0013] A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method.

[0014] The beneficial effects of this invention are as follows: This invention manages MEC node parameters and industrial service resources in a unified manner through an integrated graphical configuration interface, realizing the standardization and automation of the deployment process; by utilizing the built-in network quality testing and disaster recovery switching verification functions, it ensures that node performance strictly meets the industrial-grade SLA requirements of latency ≤10ms and packet loss rate ≤0.01%; by supporting network slicing isolation, multi-WAN port routing backup, and GRE tunnel disaster recovery mechanism, it significantly improves business continuity; and finally, it realizes rapid deployment, highly reliable operation and maintenance, and optimized resource utilization of edge computing nodes, effectively solving the core pain points of fragmented edge node deployment and difficulty in ensuring reliability in 5G industrial private network environments.

[0015] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0016] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 is a schematic diagram of the steps of an edge computing node deployment method suitable for 5G industrial private networks according to the present invention; Figure 2 is a schematic diagram of the structure of an edge computing node deployment system suitable for 5G industrial private networks according to the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] The edge computing node deployment method provided in this application embodiment can be applied to an application environment, wherein the edge computing management platform device, the target industrial-grade edge terminal and the industrial business terminal device communicate through a 5G industrial private network.

[0019] The edge computing management platform device can run an MEC (Multi-access Edge Computing) management platform, which is a dedicated edge node service management and configuration system for industrial scenarios. It can be used for unified configuration, deployment, debugging, and metadata registration of MEC nodes and their associated industrial service resources (such as machine vision analysis services, AGV scheduling services, PLC control command services, etc.). Deployed in a factory network or regional central data center, the platform has centralized management and control capabilities for distributed MEC nodes.

[0020] The target industrial-grade edge terminal can be a physical entity that deploys MEC nodes, typically an industrial-grade server, a high-strength embedded computer, or a lightweight, integrated network element device that combines UPF (User Plane Functions) and MEP (Multi-Access Edge Computing Platform). It can be deployed inside factory workshops, near production lines, or even co-located with 5G base stations to ensure extremely close proximity to industrial business terminals and guarantee service latency of no more than 10 milliseconds. Based on deployment parameters issued by the edge computing management platform, the target industrial-grade edge terminal constructs a MEC operating environment that supports network slicing logical isolation, multi-WAN port routing backup, and GRE tunnel primary / backup disaster recovery. Its hardware is compatible with domestically developed and controllable chips and integrates specific industrial protocol drivers. In some implementation schemes, to reduce cost and power consumption, a lightweight distributed MEC architecture can be adopted, integrating the UPF module and MEP platform onto the same network element device, and dynamically selecting modules such as SR-IOV, DPDK, and hardware acceleration according to the specific functional requirements of the industrial scenario, while removing unnecessary functions.

[0021] Industrial business terminal devices can be field devices used to initiate industrial business requests, such as industrial robots, AGVs, high-definition industrial cameras, PLC controllers, and sensor instruments. They access the 5G network via 5G industrial gateways or built-in 5G modules and communicate with MEC nodes running on the target industrial edge terminal through interfaces such as N3 / N6 to invoke corresponding industrial service resources, enabling low-latency data interaction, visual analysis, or control command issuance. The local data network accessed by the industrial business terminal devices can be the factory's local data center or application server.

[0022] Network Communication Architecture: The entire system is based on a 5G SA architecture industrial private network. By deploying the UPF (User Packet Provider) inside the park or workshop, local data offloading and processing are achieved, meeting the security requirement of data not leaving the factory. At the network bearer layer, the base station BBU (Base Station Unit) directly connects to the deployed UPF through transmission equipment, reducing data routing and lowering latency. The wireless access layer can adopt customized indoor distribution and macro base station coverage, and may further optimize air interface performance through technologies such as wireless pre-scheduling and uplink enhancement. To improve reliability, MEC (Multi-access Edge Computing) node disaster recovery solutions can be deployed, such as multiple shared MEC nodes in a cross-site POOL disaster recovery group, or a primary / backup disaster recovery system between resident MEC nodes and regionally shared MEC nodes.

[0023] It is understood that the aforementioned edge computing management platform devices and industrial business terminal devices can be implemented by a single device or a cluster of multiple devices. The target industrial-grade edge terminal can be a single edge server or a cluster of multiple edge servers, and the specific deployment mode can be determined according to the actual needs and cost considerations of industrial enterprises.

[0024] Through the above application environment settings, the method of this application can effectively support the efficient, flexible and highly reliable deployment of edge computing nodes in the 5G industrial private network environment, and meet the stringent requirements of industrial applications for ultra-low latency, high bandwidth and high reliability.

[0025] In an embodiment of the present invention, a method for deploying edge computing nodes suitable for 5G industrial private networks is provided. Please refer to Figure 1. The method includes the following steps: S101: Displaying the MEC node configuration page through the deployment management module running on the edge computing management platform. The configuration page includes MEC reuse parameter configuration items, network slice QoS parameter configuration items, multi-network access disaster recovery configuration items, and QUIC protocol optimization parameter configuration items.

[0026] The edge computing management platform is deployed in the factory network or a regional central computer room. Its deployment management module is a dedicated edge node service management and configuration system for industrial scenarios, providing MEC node configuration functions in a graphical interface. The MEC node configuration page is a visual editing interface within the deployment management module, used to collect user-inputted MEC node deployment parameters. Optionally, the user can be an administrator, accessing this configuration page through a platform client device.

[0027] Optionally, the MEC reuse parameter configuration item is used to configure the resource sharing and reuse strategy of MEC nodes, such as supporting multiple industrial business terminal devices to share the same MEC node instance to improve resource utilization; the network slice QoS parameter configuration item is used to define the service quality requirements at the slice level, including bandwidth guarantee, latency limit (e.g., ≤10 milliseconds), packet loss rate threshold (e.g., ≤0.01%), and priority strategy; the multi-network access disaster recovery configuration item is used to set the redundancy strategy for multi-mode access such as 5G / 4G / wired / Wi-Fi, including primary and backup link switching conditions, heartbeat detection interval, and fault return mechanism; the QUIC protocol optimization parameter configuration item is used to configure transmission optimization parameters based on the QUIC protocol, such as forward error correction strength, connection migration sensitivity, and 0-RTT session recovery threshold, to improve transmission reliability in wireless environments. Through the above configuration items, fine-grained parameter customization can be performed for the high reliability and low latency requirements of industrial scenarios.

[0028] S102: Obtain the basic configuration information of the MEC node determined by the user through the MEC node configuration page, as well as the industrial service resource configuration information associated with the basic configuration information of the MEC node. The industrial service resource configuration information includes 5G LAN Layer 2 networking parameters, multi-link redundancy strategy, industrial service traffic forwarding rules, and security encryption strategy based on independently controllable chips.

[0029] The basic configuration information of the MEC node describes the identity and operating environment attributes of the MEC node, such as node identifier, deployment location, hardware specifications, operating system type, and UPF instance parameters. Optionally, the basic configuration information may also include the network slice identifier to which the MEC node belongs, management IP address, and operation and maintenance interface protocol.

[0030] The industrial service resource configuration information is used to define the functional attributes and interface rules of the specific industrial services carried by the MEC node. Optionally, the 5G LAN Layer 2 networking parameters are used to configure Layer 2 communication rules based on 5G LAN technology, such as VLAN identifiers, multicast group addresses, and terminal device MAC address binding strategies, to achieve direct Layer 2 communication between industrial terminals; the multi-link redundancy strategy is used to specify the primary and backup priorities, load balancing weights, and fault switching trigger conditions (such as automatic switching when the signal strength is below -100dBm) for multi-mode access such as 5G, 4G, wired Ethernet, and Wi-Fi, to ensure high availability of links; the industrial service traffic forwarding rules are used to define the classification, marking, and routing strategies for service data packets, such as priority queue mapping based on DSCP or traffic routing rules based on five-tuples, to ensure low-latency forwarding of critical control services; the security encryption strategy based on domestically controlled chips is used to configure the key length of the national cryptographic algorithm, the certificate revocation list, and the hardware encryption / decryption engine enable switch to ensure secure and controllable data communication.

[0031] In one embodiment, the industrial service resource configuration information may further include a service resource identifier, resource name, resource description information, and resource access permissions. For example, taking machine vision analysis service as an example, its resource configuration information may include a service name (e.g., "production line vision inspection service"), a service identifier (unique ID), a service description (e.g., "used for PCB board solder joint quality inspection"), and a permission level (e.g., only authorized AGV vehicles are allowed to use it). Through the above configuration, unified management and access control of industrial service resources can be achieved.

[0032] S103: Based on the basic configuration information of the MEC node and the configuration information of the industrial service resources, generate deployment parameters for running the MEC node and the industrial service resources. The deployment parameters also include hardware driver parameters adapted to industrial-grade terminals in the energy industry and network slice resource reservation parameters.

[0033] The deployment parameters refer to the full configuration information and initialization scripts required to successfully deploy and run MEC nodes and associated industrial service resources on the target industrial edge terminal. The deployment parameters not only determine how the MEC node's operating environment is constructed, but also affect the loading, registration, and scheduling logic of industrial service resources.

[0034] For example, the process of generating deployment parameters includes: First, based on the basic configuration information of the MEC node, parsing out the basic parameters required for the operation of the MEC node, such as the container image address, runtime dependency library list, system service startup order, and log storage path; Second, combining the industrial service resource configuration information, determining the deployment specifications of the industrial service resources, including 5G LAN networking scripts, multi-link routing table configurations, traffic policy rule sets, and security policy loading instructions; Finally, the deployment management module of the edge computing management platform integrates and formats the above information to generate a structured deployment parameter file or an executable deployment script.

[0035] Optionally, the hardware driver parameters adapted to the industrial-grade terminals in the energy industry include industrial protocol driver configurations, interface card driver versions, and compatibility settings specific to energy scenarios (such as substations and oil and gas pumping stations) to ensure that MEC nodes can communicate normally with energy terminals; the network slice resource reservation parameters are used to pre-allocate the wireless resource blocks, transmission bandwidth, and computing resource quotas required for slices, for example, reserving dedicated physical resource blocks and edge computing resources for uRLLC slices to ensure the isolation and deterministic performance of critical services.

[0036] In one embodiment, deployment parameters may further include high availability configuration of MEC nodes, network slice QoS policy binding information, and disaster recovery tunnel configuration. These deployment parameters guide the target industrial edge terminal to automatically complete the initialization of the MEC operating environment, the deployment of industrial service resources, and the activation of network functions, thereby quickly building a usable edge computing node.

[0037] S104: Send the deployment parameters to the target industrial-grade edge terminal so that the target industrial-grade edge terminal can deploy an MEC operating environment based on the deployment parameters. The operating environment supports network slicing logical isolation, multi-WAN port route backup, and GRE tunnel primary and backup disaster recovery functions.

[0038] In one embodiment, in response to a user's confirmation instruction regarding deployment parameters (e.g., triggered by a "Deploy" button on the edge computing management platform), the edge computing management platform sends the deployment parameters to the target industrial-grade edge terminal via a secure network transmission protocol. Optionally, the deployment parameters are encapsulated in a structured data format and include a digital signature to ensure integrity. After receiving the deployment parameters, the target industrial-grade edge terminal parses and executes the initialization instructions in the deployment parameters using its built-in deployment engine, automatically completing the construction of the MEC runtime environment.

[0039] Optionally, the MEC operating environment refers to the basic software and hardware environment used to run MEC nodes and industrial service resources, including but not limited to: a lightweight operating system, container runtime, hardware driver modules, network protocol stack, and disaster recovery components. The operating environment implements the following core functions through the configuration defined in the deployment parameters: logical isolation of network slices (e.g., dividing slices into dedicated channels via VLANs or VxLANs), multi-WAN port route backup (automatic switching during link failures based on BGP or OSPF protocols), and GRE tunnel primary / backup disaster recovery (setting primary / backup tunnel endpoint IPs and a heartbeat detection mechanism). Through the above deployment, the target industrial-grade edge terminal can provide a low-latency, highly reliable execution foundation for industrial service resources.

[0040] S105: In response to the debugging instruction for the industrial service resource, network quality testing (including latency, packet loss rate, and bandwidth stability indicators) and disaster recovery switching testing are performed based on the operating environment to obtain debugging results; if the debugging results indicate that the industrial service resource meets the industrial-grade preset operating conditions (latency ≤ 10ms, packet loss rate ≤ 0.01%, disaster recovery switching time ≤ 20s), an edge computing node construction request is sent to the target industrial-grade edge terminal so that the target industrial-grade edge terminal can construct an edge computing node in a pending state based on the edge computing node construction request. The edge computing node is used to carry the industrial service resource and respond to the call requests of industrial control and data acquisition services based on network slicing QoS policies and multi-link redundancy policies.

[0041] The debugging commands can be manually triggered by the user through the debugging interface of the edge computing management platform, or automatically generated by the system as standardized test scripts after deployment. The debugging commands include test parameters, such as the IP address of the target industrial business terminal device, the size of the test data packet, disaster recovery triggering conditions, and expected output results.

[0042] Optionally, network quality testing measures end-to-end latency, packet loss rate, and bandwidth stability by sending UDP or ICMP probe packets. Specific metrics include: latency (round-trip time from the industrial service terminal equipment to the MEC node), packet loss rate (the percentage of data packets lost during the test), and bandwidth fluctuation range (such as the variance of the transmission rate per second). Disaster recovery switching testing verifies the switching time and service continuity of the backup link (such as wired or Wi-Fi) by simulating a primary link failure (such as disabling the 5G module). Debugging results are returned in a structured report format, including test data, pass / fail flags, and detailed logs.

[0043] The industrial-grade preset operating conditions are quantitative standards used to determine whether industrial service resources are qualified for formal deployment, including: latency ≤ 10 milliseconds (meeting uRLLC service requirements), packet loss rate ≤ 0.01% (ensuring the reliability of control commands), and disaster recovery switchover time ≤ 20 seconds (ensuring rapid fault recovery). If the debugging results meet all the above conditions, the edge computing management platform automatically sends an edge computing node construction request to the target industrial-grade edge terminal; otherwise, a debugging failure report is generated and the user is prompted to correct the configuration.

[0044] Optionally, the edge computing node construction request includes the deployment mirror address of industrial service resources, network slice binding information, and resource scheduling strategy. Based on this request, the target industrial-grade edge terminal encapsulates the industrial service resources into an independently runnable edge computing node instance and configures network slice QoS policies (such as priority queues based on 5QI) and multi-link redundancy policies (such as automatic routing switching in case of failure). The constructed edge computing node is in a pending state, that is, it has loaded industrial service resources but has not yet received external requests. Once it receives a call request from industrial control or data acquisition services (such as PLC control commands or sensor data uploads), it can respond in real time based on slice QoS and redundancy policies.

[0045] S106: Receive node metadata sent by the target industrial-grade edge terminal, and register the node metadata with the edge computing management platform. The node metadata is used to identify the slice affiliation, disaster recovery link information and industrial business scheduling routing rules of the edge computing node. The node metadata also includes hardware identification information of autonomous and controllable network elements.

[0046] Node metadata is a structured descriptive information generated by the target industrial-grade edge terminal after successfully building an edge computing node. It is used to register the node's identity and capabilities in the edge computing management platform. Optionally, the process of receiving node metadata is implemented through a secure API interface, and the edge computing management platform verifies and parses the metadata.

[0047] Optionally, node metadata includes, but is not limited to: slice ownership, disaster recovery link information (primary and backup GRE tunnel endpoints, link priority), industrial business scheduling routing rules (such as routing weights based on business type), and hardware identification information (serial number or digital certificate of domestically controlled chip). During registration, the edge computing management platform writes the node metadata into the service management database and establishes a call routing table, enabling industrial business terminal devices to accurately access edge computing nodes through routing rules (such as based on IP or domain name).

[0048] In one embodiment, the registered node metadata is also used for monitoring and maintenance, such as verifying the legitimacy of network elements based on hardware identification information, or performing automatic failover based on disaster recovery link information. Metadata registration enables unified discovery, management, and scheduling of edge computing nodes, ensuring the maintainability and security of industrial private network services. This embodiment details another implementation of an edge computing node deployment method applicable to 5G industrial private networks, comprising steps S201 to S210.

[0049] S201: In response to a user-triggered node creation command, the MEC node configuration page is displayed through the deployment management module running on the edge computing management platform.

[0050] In some embodiments, users can trigger node creation commands through the service list page of the edge computing management platform. The service list page displays currently existing edge computing nodes and related information. Optionally, the service list page may include a navigation bar, including category controls such as "Nodes I Manage," "Nodes I Can See," and "All Nodes," for categorizing edge computing nodes according to their permission scope. The service list page may also display existing edge computing node entries, such as "Production Line Visual Inspection Nodes," "AGV Scheduling Nodes," and "PLC Control Nodes." Each node entry is displayed in card format, including the node name, node identifier, node description, and user permission information. The service list page also includes a search box to receive user-input search information for quick node location. Furthermore, the service list page includes a new node control; when the user triggers this control, a node creation command is triggered, subsequently displaying the MEC node configuration page.

[0051] S202: Obtain initial information about the MEC node through the MEC node configuration page.

[0052] The initial information for a MEC node refers to the basic descriptive parameter settings that users configure on the MEC node configuration page for the MEC node they wish to create or manage. This initial information includes, but is not limited to: node name, node identifier, version information, node description, node type, node permissions, management IP address, communication protocol type, dependent middleware information, log configuration parameters, and network access method. Optionally, node types include: shared MEC (indicating a shared operating environment pre-provided by the platform, supporting multiple industrial businesses sharing the same MEC node resources), onboarded MEC (indicating a user-owned operating environment, providing independent resource isolation), and custom type (supporting users to bind third-party operating environments by entering a custom URL).

[0053] S203: Perform a validity check on the initial information of the MEC node and obtain the verification result.

[0054] In one embodiment, the legitimacy verification includes at least one of the following verification methods: verifying the matching of the communication protocol type and the management IP address to determine whether the protocol type and IP address format conform to preset rules; detecting the compatibility of the network access method with the industrial private network security policy to ensure that the access method complies with firewall rules and data security requirements; and confirming the uniqueness of the node identifier in the platform to avoid identifier conflicts. Optionally, the verification result indicates whether the MEC node initial information verification passed or failed. If the verification fails, a specific error reason is returned (such as "node identifier already exists" or "IP address format error"). For example, a verification pass result is generated when the MEC node initial information meets the following conditions: the communication protocol type and IP address format match correctly and the IP address is not occupied; the network access method conforms to the industrial private network security policy; and the node identifier is unique in the platform.

[0055] S204: If the verification result indicates that the initial information of the MEC node has passed the verification, generate the basic configuration information of the MEC node in the edge computing management platform based on the initial information of the MEC node.

[0056] The edge computing management platform stores and maps the initial information of MEC nodes in a structured manner according to predefined configuration templates, forming standardized basic configuration information for MEC nodes. This configuration information is not only used to distinguish different MEC node instances, but also provides basic metadata support for subsequent industrial service resource configuration, deployment parameter generation, and node construction.

[0057] S205: In response to the industrial service resource registration instruction for the basic configuration information of MEC nodes, generate an industrial service resource registration context environment to limit the interaction constraint parameters between industrial service resources and the basic configuration information of MEC nodes.

[0058] The industrial service resource registration command is triggered by the user. The industrial service resource registration context is a logical container that defines the boundaries and constraints to be followed during registration, such as allowed data formats, interface call methods, and authentication rules. Interaction constraint parameters include input / output data format compatibility, call frequency limits, and security authentication methods. For example, the edge computing management platform generates a corresponding context identifier based on the node type and permission configuration in the MEC node's basic configuration information, and binds it to the boundary conditions of the input / output mapping rules and interface description information to form the industrial service resource registration context.

[0059] S206: In the context of industrial service resource registration, load the 5G LAN networking parameter configuration component, multi-link redundancy policy configuration component, and industrial business traffic rule editing component corresponding to the industrial service resource.

[0060] In one embodiment, after generating the industrial service resource registration context, a resource configuration page is displayed. This page includes a new resource control; when the user triggers this control, the aforementioned configuration components are loaded into the context. The 5G LAN networking parameter configuration component is used to configure Layer 2 communication rules, such as VLAN identifiers, multicast group addresses, and terminal device MAC address binding policies; the multi-link redundancy policy configuration component is used to set the primary / backup priority and fault switching conditions for multi-mode access such as 5G / 4G / wired / Wi-Fi; and the industrial service traffic rule editing component is used to define the classification, labeling, and routing policies for service data packets. Optionally, a unified configuration interface is generated by automatically matching the corresponding configuration template based on the type of industrial service resource.

[0061] S207: Obtain the user-defined 5G LAN Layer 2 networking parameters through the 5G LAN networking parameter configuration component, obtain the multi-link redundancy policy through the multi-link redundancy policy configuration component, and obtain the industrial service traffic forwarding rules through the industrial service traffic rule editing component.

[0062] Users can interactively configure 5G LAN networking parameters, multi-link redundancy policies, and industrial service traffic forwarding rules through various configuration components. For example, in the 5G LAN networking parameter configuration component, the VLAN ID is set to 100 and the multicast address is set to 239.0.0.1; in the multi-link redundancy policy configuration component, 5G is set as the primary link and the wired network as the backup link; and in the industrial service traffic rule editing component, priority mapping rules based on DSCP are defined.

[0063] S208: Integrates and processes 5G LAN Layer 2 networking parameters, multi-link redundancy strategies, and industrial service traffic forwarding rules to obtain industrial service resource configuration information associated with the basic configuration information of MEC nodes.

[0064] The edge computing management platform integrates the above parameters into structured industrial service resource configuration information. Specifically, this includes: converting 5G LAN networking parameters into standard networking configuration scripts; converting multi-link redundancy policies into routing table configuration instructions; and formatting industrial service traffic forwarding rules into traffic policy rule sets. The integrated configuration information also includes security encryption policies based on domestically developed and controllable chips, such as the key length of national cryptographic algorithms and certificate configuration.

[0065] S209: Generate deployment parameters for running MEC nodes and industrial service resources based on MEC node basic configuration information and industrial service resource configuration information.

[0066] The edge computing management platform parses the basic configuration information of MEC nodes to obtain the basic parameters required for MEC node operation; combined with industrial service resource configuration information, it determines the deployment specifications of industrial service resources. Subsequently, the above information is integrated and formatted to generate a structured deployment parameter file or executable deployment script. The deployment parameters also include hardware driver parameters adapted to industrial-grade terminals in the energy sector and network slicing resource reservation parameters.

[0067] S210: Send deployment parameters to the target industrial-grade edge terminal so that the target industrial-grade edge terminal can deploy the MEC operating environment based on the deployment parameters.

[0068] In response to the user's confirmation command, the edge computing management platform sends deployment parameters to the target industrial-grade edge terminal via a secure transmission protocol. After receiving the deployment parameters, the target industrial-grade edge terminal's deployment engine parses and executes initialization commands, automatically building an MEC operating environment that supports network slicing logical isolation, multi-WAN port routing backup, and GRE tunnel primary / backup disaster recovery functions.

[0069] This application embodiment ensures the legality and uniqueness of MEC node configuration through fully automated management of the entire process from node creation, initial information verification, service resource registration to deployment parameter generation. It supports standardized binding and flexible expansion of industrial service resources, thereby improving the efficiency and reliability of 5G industrial private network edge computing node deployment.

[0070] This embodiment provides a detailed description of another implementation of a method for deploying edge computing nodes suitable for 5G industrial private networks, which includes steps S301 to S315.

[0071] S301: The MEC node configuration page is displayed through the deployment management module running on the edge computing management platform. For details, please refer to S101 above.

[0072] S302: Obtain the user-defined basic configuration information of the MEC node and the industrial service resource configuration information associated with the basic configuration information of the MEC node through the MEC node configuration page. The industrial service resource configuration information includes 5G LAN Layer 2 networking parameters, multi-link redundancy strategy, industrial service traffic forwarding rules and security encryption strategy based on independently controllable chips; refer to S102 above for details.

[0073] S303: Generate deployment parameters for running MEC nodes and industrial service resources based on MEC node basic configuration information and industrial service resource configuration information; refer to S103 above for details.

[0074] S304: Send the deployment parameters to the target industrial-grade edge terminal so that the target industrial-grade edge terminal can deploy the MEC operating environment based on the deployment parameters. See S104 above for details.

[0075] S305: In response to a commissioning command for an industrial service resource, display the commissioning page.

[0076] The debug page is an interactive interface provided by the edge computing management platform after the industrial service resources are configured. It is used to verify the correctness of the configuration and the availability of functions. The debug page allows users to input test parameters, execute network quality tests and disaster recovery switchover tests, and view the test results in real time. Optionally, the debug page includes a network quality test configuration area, a disaster recovery test trigger area, a real-time indicator display area, and a detailed log viewing area.

[0077] S306: Generate sample test data streams based on industrial business traffic forwarding rules and display the sample test data streams on the debug page.

[0078] The edge computing management platform generates sample test data streams that conform to the characteristics of various business operations based on the business types defined in the industrial business traffic forwarding rules. For example, for control command business operations, it generates sample data packets containing PLC control commands; for video stream business operations, it generates test data streams simulating video frames. The sample test data streams contain standard field structures, data formats, and business identifiers, and are displayed in the sample data area of ​​the debugging page for user reference or direct use.

[0079] S307: After detecting the user's confirmation instruction for the sample test data stream, the sample test data stream is encapsulated into a test message and a debug call request is sent to the target industrial edge terminal to trigger network quality testing and disaster recovery switching testing.

[0080] Once the user confirms the sample test data stream, the edge computing management platform encapsulates it into test packets that meet 5G network transmission requirements according to industrial business traffic forwarding rules. Subsequently, a debug call request is sent to the target industrial-grade edge terminal. This request simultaneously triggers two types of tests: network quality testing (continuously sending test packets to measure latency, packet loss rate, and other metrics) and disaster recovery handover testing (simulating primary link failure during testing and measuring backup link handover time). The target industrial-grade edge terminal executes the tests in the MEC operating environment and collects test data in real time.

[0081] S308: Obtain the test output data returned by the target industrial-grade edge terminal, parse and process the test output data according to the network quality assessment rules and disaster recovery switching assessment rules, and generate debugging results.

[0082] The test output data returned by the target industrial-grade edge terminal includes raw test metrics. The edge computing management platform aggregates and analyzes the raw data according to preset network quality assessment rules and disaster recovery switching assessment rules, generating structured debugging results. These results clearly indicate whether each metric meets the preset industrial-grade operating conditions.

[0083] S309: If the debugging results indicate that the industrial service resources meet the industrial-grade preset operating conditions, send an edge computing node construction request to the target industrial-grade edge terminal.

[0084] When the debugging results confirm that latency ≤10ms, packet loss rate ≤0.01%, and disaster recovery switchover time ≤20s are all met, the edge computing management platform automatically sends an edge computing node construction request to the target industrial-grade edge terminal. This request includes the formal deployment image address of industrial service resources, network slice binding information, and resource scheduling strategy.

[0085] S310: Receives node metadata sent by the target industrial-grade edge terminal and registers the node metadata with the edge computing management platform.

[0086] After successfully building an edge computing node on the target industrial-grade edge terminal, node metadata is generated, including slice affiliation, disaster recovery link information, industrial service scheduling routing rules, and the identifier of independently controllable network element hardware, and sent to the edge computing management platform. The platform registers the node metadata to the service management database and establishes a complete call routing table.

[0087] S311: If the debugging results indicate that the industrial service resources do not meet the industrial-grade preset operating conditions, determine the MEC operation configuration anomalies based on the debugging results.

[0088] If any metric fails to meet the standards during debugging, the edge computing management platform automatically analyzes the debugging data to identify the specific operational configuration anomalies. For example, excessive latency may correspond to insufficient QoS parameter configuration for network slices; excessive disaster recovery switchover time may correspond to unreasonable multi-link redundancy strategy configuration.

[0089] S312: Display runtime configuration exceptions on the exception configuration modification page and obtain the first modification information determined for the runtime configuration exceptions.

[0090] The edge computing management platform visually displays identified runtime configuration anomalies on an anomaly configuration modification page, including an anomaly description, current configuration value, and recommended modifications. Users adjust relevant parameters based on the anomalies, and the platform collects these modifications as primary modification information.

[0091] S313: Update the deployment parameters based on the first modification information to generate updated deployment parameters.

[0092] The edge computing management platform dynamically updates the corresponding configuration items in the deployment parameters based on the first modification information. For example, it modifies the bandwidth guarantee value in the network slice QoS parameters and updates the switching conditions in the multi-link redundancy policy. The update process retains historical versions and supports rollback.

[0093] S314: Based on the updated deployment parameters, return to execute the steps of sending the deployment parameters to the target industrial edge terminal and redeploy the MEC runtime environment.

[0094] The updated deployment parameters are sent to the target industrial edge terminal, triggering a redeployment of the runtime environment. The target industrial edge terminal updates its network configuration, slicing strategy, and disaster recovery settings based on the new parameters.

[0095] S315: In response to a modification request for an industrial service resource, display the service resource modification page, obtain the second modification information through the service resource modification page, update the deployment parameters based on the second modification information, and re-execute the deployment and testing process.

[0096] When industrial business requirements change, users can adjust the configuration of industrial service resources through the service resource modification page. After the platform receives the second modification information, it incrementally updates the deployment parameters and automatically triggers the redeployment and testing process until the debugging results meet the preset industrial-grade operating conditions.

[0097] This application embodiment achieves efficient deployment and verification of 5G industrial private network edge computing nodes through a complete debugging page interaction, automated test execution, intelligent anomaly diagnosis, and closed-loop modification process, ensuring that industrial service resources meet strict real-time and reliability requirements.

[0098] This embodiment provides a detailed description of another implementation of an edge computing node deployment method applicable to 5G industrial private networks, the method including steps S401 to S413.

[0099] S401: Display the MEC node configuration page through the deployment management module running on the edge computing management platform; refer to S101 above for details.

[0100] S402: Obtain the user-defined basic configuration information of the MEC node and the industrial service resource configuration information associated with the basic configuration information of the MEC node through the MEC node configuration page; for details, refer to S102 above.

[0101] S403: Generate deployment parameters for running MEC nodes and industrial service resources based on MEC node basic configuration information and industrial service resource configuration information; refer to S103 above for details.

[0102] S404: Send deployment parameters to the target industrial-grade edge terminal so that the target industrial-grade edge terminal can deploy the MEC runtime environment based on the deployment parameters. See S104 above for details.

[0103] S405: In response to a commissioning command for an industrial service resource, display the commissioning page.

[0104] The debug page is an interactive interface provided by the edge computing management platform after the industrial service resources are configured. It is used to verify the correctness of the network quality test and disaster recovery switchover test configurations. The debug page allows users to configure test parameters, execute test calls, view real-time test results, and troubleshoot anomalies.

[0105] Optionally, the debugging page includes a network quality test configuration area, a disaster recovery test trigger area, a real-time indicator display area, and a detailed log viewing area. The network quality test configuration area is used to set parameters such as test duration, packet size, and sampling frequency; the disaster recovery test trigger area includes a link switching trigger control and a switching time measurement component; the real-time indicator display area dynamically displays latency, packet loss rate, and bandwidth stability indicators in a dashboard format; and the detailed log area records detailed event logs during the test process.

[0106] S406: Generate sample test data streams based on industrial business traffic forwarding rules and display the sample test data streams on the debug page.

[0107] The edge computing management platform automatically generates sample test data streams that conform to the characteristics of various industrial businesses, based on the business type features defined in the industrial business traffic forwarding rules. For example, for control command businesses, it generates sample data packets containing typical PLC control commands; for machine vision businesses, it generates test data streams simulating video detection frames. The sample test data streams contain complete business identifiers, data formats, and standardized field structures, and are output in the sample data display area of ​​the debugging page for user reference or direct use.

[0108] S407: After detecting the user's confirmation instruction for the sample test data stream, the sample test data stream is converted into a standardized test message through the industrial business traffic forwarding rules, and a debug call request is initiated to the target industrial edge terminal.

[0109] Once the user confirms the sample test data stream, the edge computing management platform standardizes the sample data according to industrial business traffic forwarding rules, including adding network slice identifiers, setting QoS priority tags, and encapsulating service type labels. The processed data is then assembled into test packets that meet the transmission requirements of 5G industrial private networks and sent to the target industrial-grade edge terminal through a secure debugging channel. The test packets contain complete link tracing identifiers for subsequent debugging result analysis.

[0110] S408: Obtain the test output data returned by the target industrial-grade edge terminal, and parse and process the test output data according to the network quality assessment algorithm and disaster recovery switching assessment rules to generate debugging results.

[0111] The test output data returned by the target industrial-grade edge terminal includes the original latency sequence, packet loss event records, bandwidth sampling values, and disaster recovery switchover timestamps. The edge computing management platform uses a sliding window algorithm to calculate the average latency and jitter range, calculates the packet loss rate based on statistical methods, and analyzes bandwidth stability indicators. Simultaneously, it calculates the time interval from main link failure to full service recovery according to disaster recovery switchover evaluation rules, generating a structured debugging result report.

[0112] S409: If the debugging results indicate that the industrial service resources meet the industrial-grade preset operating conditions, send an edge computing node construction request to the target industrial-grade edge terminal.

[0113] When the debugging results confirm that all indicators meet the industrial-grade requirements of latency ≤10ms, packet loss rate ≤0.01%, and disaster recovery switchover time ≤20s, the edge computing management platform automatically generates and sends an edge computing node construction request. This request includes the formal deployment image address of industrial service resources, network slicing binding strategy, and resource scheduling parameters.

[0114] S410: Receives node metadata sent by the target industrial-grade edge terminal and registers the node metadata with the edge computing management platform.

[0115] After successfully building an edge computing node on the target industrial-grade edge terminal, node metadata is generated, including slice ownership information, disaster recovery link configuration, industrial service scheduling routing rules, and the identifier of independently controllable network element hardware. The edge computing management platform registers the node metadata to the service management database, establishing a complete service discovery and invocation routing mechanism.

[0116] S411: If the debugging results indicate that the industrial service resources do not meet the industrial-grade preset operating conditions, determine the MEC operation configuration anomalies based on the debugging results.

[0117] If any metric fails to meet the standards during debugging, the edge computing management platform uses root cause analysis algorithms to identify specific operational configuration anomalies. For example, if latency exceeds the standard, possible causes include insufficient network slice bandwidth reservation, improper QoS policy configuration, or mismatched hardware driver parameters; if disaster recovery switchover time exceeds the standard, the platform checks the switchover threshold settings of the multi-link redundancy policy or the GRE tunnel configuration parameters.

[0118] S412: Display runtime configuration exceptions on the exception configuration modification page and obtain the first modification information determined for the runtime configuration exceptions.

[0119] The edge computing management platform visually displays identified runtime configuration anomalies through an anomaly configuration modification page, including an anomaly description, current configuration value, impact analysis, and recommended modification solutions. Users adjust relevant parameters based on the diagnostic results, and the platform collects these modifications as primary modification information. The modification process supports version comparison and rollback functions to ensure the controllability of configuration changes.

[0120] S413: Update the deployment parameters based on the first modification information, generate updated deployment parameters, and return to execute the step of sending the deployment parameters to the target industrial-grade edge terminal based on the updated deployment parameters.

[0121] The edge computing management platform incrementally updates the corresponding configuration items in the deployment parameters based on the first modification information, while retaining historical versions for auditing and rollback support. The updated deployment parameters are sent to the target industrial-grade edge terminal through a secure channel, triggering redeployment and configuration updates of the runtime environment. The system automatically enters a new round of testing and verification until all indicators meet the preset industrial-grade operating conditions.

[0122] This application embodiment achieves refined deployment and verification of 5G industrial private network edge computing nodes through a complete debugging page interaction mechanism, intelligent anomaly diagnosis algorithm, and closed-loop configuration modification process, ensuring that industrial service resources operate stably under strict real-time, reliability, and security requirements.

[0123] This application embodiment also provides an edge computing node deployment system suitable for 5G industrial private networks. Referring to Figure 2, the system includes: a configuration display module 21, used to display the MEC node configuration page through the deployment management module running on the edge computing management platform. The configuration page includes MEC reuse parameter configuration items, network slicing QoS parameter configuration items, multi-network access disaster recovery configuration items, and QUIC protocol optimization parameter configuration items. The edge computing management platform is deployed in a factory network or a regional central computer room, and its deployment management module is a dedicated edge node service management and configuration system for industrial scenarios, providing MEC node configuration functions in a graphical interface. A configuration information acquisition module 22 is used to acquire the user-determined basic configuration information of the MEC node and the industrial service resource configuration information associated with the basic configuration information of the MEC node through the MEC node configuration page. The industrial service resource configuration information includes 5G... The system includes: LAN Layer 2 networking parameters, multi-link redundancy strategies, industrial service traffic forwarding rules, and security encryption strategies based on independently controllable chips; a deployment parameter generation module 23, used to generate deployment parameters for running the MEC node and the industrial service resources based on the basic configuration information of the MEC node and the configuration information of the industrial service resources. The deployment parameters also include hardware driver parameters adapted to industrial-grade terminals in the energy industry and network slicing resource reservation parameters; a deployment execution module 24, used to send the deployment parameters to the target industrial-grade edge terminal, so that the target industrial-grade edge terminal can deploy the MEC operating environment based on the deployment parameters. The operating environment supports network slicing logical isolation, multi-WAN port routing backup, and GRE tunnel primary / backup disaster recovery functions; and a debugging and building module 25, used to respond to... The debugging instructions for the industrial service resources are based on the operating environment to perform network quality testing and disaster recovery switching testing, and obtain debugging results. When the debugging results indicate that the industrial service resources meet the industrial-grade preset operating conditions, an edge computing node construction request is sent to the target industrial-grade edge terminal, so that the target industrial-grade edge terminal can construct an edge computing node in a pending state based on the edge computing node construction request. The node registration module 26 is used to receive node metadata sent by the target industrial-grade edge terminal and register the node metadata with the edge computing management platform. The node metadata is used to identify the slice affiliation, disaster recovery link information and industrial business scheduling routing rules of the edge computing node. The node metadata also includes hardware identification information of autonomous and controllable network elements.

[0124] The edge computing node deployment system for 5G industrial private networks shown in Figure 2 can execute the edge computing node deployment method described in the foregoing embodiments. Its implementation principle and technical effects will not be repeated here. The specific methods by which each module performs its operations in the edge computing node deployment system described in the above embodiments have been described in detail in the embodiments related to this method, and will not be elaborated upon here.

[0125] This application also provides a computer storage medium storing a computer program, which, when executed by a computer, can implement the edge computing node deployment method described in the foregoing embodiments.

[0126] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for deploying edge computing nodes suitable for 5G industrial private networks, characterized in that, include: S101: The MEC node configuration page is displayed through the deployment management module running on the edge computing management platform. The configuration page includes MEC reuse parameter configuration items, network slicing QoS parameter configuration items, multi-network access disaster recovery configuration items, and QUIC protocol optimization parameter configuration items. S102: The user-defined basic configuration information of the MEC node, as well as the industrial service resource configuration information associated with the basic configuration information of the MEC node, are obtained through the MEC node configuration page. The industrial service resource configuration information includes 5G... S103: Based on the MEC node's basic configuration information and industrial service resource configuration information, generate deployment parameters for running the MEC node and industrial service resources. The deployment parameters also include hardware driver parameters adapted to industrial-grade terminals in the energy industry and network slice resource reservation parameters. S104: Send the deployment parameters to the target industrial-grade edge terminal so that the target industrial-grade edge terminal can deploy the MEC operating environment based on the deployment parameters. The operating environment supports network slice logical isolation, multi-WAN port route backup, and GRE tunnel primary and backup disaster recovery functions. S105: In response to the debugging command for industrial service resources, perform network quality testing and disaster recovery switching testing based on the operating environment to obtain debugging results. If the debugging results indicate that the industrial service resources meet the industrial-grade preset operating conditions, an edge computing node construction request is sent to the target industrial-grade edge terminal so that the target industrial-grade edge terminal can construct an edge computing node in a pending state based on the edge computing node construction request; S106: Receive the node metadata sent by the target industrial-grade edge terminal and register the node metadata with the edge computing management platform. The node metadata is used to identify the slice ownership, disaster recovery link information and industrial business scheduling routing rules of the edge computing node. The node metadata also contains the hardware identification information of the autonomous and controllable network element.

2. The deployment method as described in claim 1, characterized in that, Prior to S101, there is also a node creation command triggered by the user, which displays the MEC node configuration page through the deployment management module; the node creation command is triggered by the new node control in the service list page, which is used to display the information of existing edge computing nodes and includes a search box and category control.

3. The deployment method as described in claim 1, characterized in that, Obtaining basic configuration information for MEC nodes includes validating the initial information of MEC nodes and obtaining the validation results; If the verification result indicates that the initial information of the MEC node has passed the verification, the basic configuration information of the MEC node is generated in the edge computing management platform based on the initial information of the MEC node. The legality verification includes at least one of the following methods: verifying the matching of the communication protocol type and the management IP address, and determining whether the protocol type and IP address format conform to the preset rules; detecting the compatibility of the network access method with the industrial private network security policy, and ensuring that the access method complies with the firewall rules and data security requirements; and confirming the uniqueness of the node identifier in the platform to avoid identifier conflicts.

4. The deployment method as described in claim 1, characterized in that, Obtaining industrial service resource configuration information includes: in response to an industrial service resource registration instruction for MEC node basic configuration information, generating an industrial service resource registration context environment to limit the interaction constraint parameters between industrial service resources and MEC node basic configuration information; in the industrial service resource registration context environment, loading a 5G LAN networking parameter configuration component, a multi-link redundancy policy configuration component, and an industrial service traffic rule editing component corresponding to the industrial service resource; obtaining user-determined 5G LAN Layer 2 networking parameters through the 5G LAN networking parameter configuration component, obtaining multi-link redundancy policies through the multi-link redundancy policy configuration component, and obtaining industrial service traffic forwarding rules through the industrial service traffic rule editing component; integrating and processing the 5G LAN Layer 2 networking parameters, multi-link redundancy policies, and industrial service traffic forwarding rules to obtain industrial service resource configuration information associated with MEC node basic configuration information.

5. The deployment method as described in claim 1, characterized in that, The network quality test includes tests for latency, packet loss rate, and bandwidth stability; the disaster recovery switching test includes simulating a primary link failure to measure the backup link switching time and service continuity. Industrial-grade preset operating conditions include: latency not exceeding 10 milliseconds, packet loss rate not exceeding 0.01%, and disaster recovery switching time not exceeding 20 seconds.

6. The deployment method as described in claim 1, characterized in that, Also includes: In response to a modification request for an industrial service resource, a service resource modification page is displayed, through which second modification information can be obtained; The deployment parameters are updated based on the second modification information, and the deployment and testing processes from S104 to S106 are re-executed. In S105, testing based on debugging commands includes: displaying a debugging page, which includes a network quality test configuration area, a disaster recovery test trigger area, a real-time indicator display area, and a detailed log viewing area; generating a sample test data stream based on industrial business traffic forwarding rules and displaying the sample test data stream on the debugging page; after detecting a user's confirmation command for the sample test data stream, encapsulating the sample test data stream into a test message and initiating a debugging call request to the target industrial-grade edge terminal, triggering network quality testing and disaster recovery switching testing; obtaining the test output data returned by the target industrial-grade edge terminal, parsing and processing the test output data according to network quality assessment rules and disaster recovery switching assessment rules, and generating debugging results; the sample test data stream is generated based on the service type defined in the industrial business traffic forwarding rules, including simulated data of control command services, video stream services, or sensor data services.

7. The deployment method as described in claim 1, characterized in that, The process of generating deployment parameters in S103 includes: parsing the basic configuration information of the MEC node to obtain the basic parameters required for the operation of the MEC node, including the container image address, runtime dependency library list, system service startup order and log storage path; determining the deployment specifications of industrial service resources by combining industrial service resource configuration information, including 5G LAN networking script, multi-link routing table configuration, traffic policy rule set and security policy loading instructions; and integrating and formatting the above information to generate a structured deployment parameter file or executable deployment script.

8. The deployment method as described in claim 1, characterized in that, If the debugging results indicate that the industrial service resources do not meet the industrial-grade preset operating conditions, the method further includes: determining the MEC operation configuration anomaly based on the debugging results; displaying the operation configuration anomaly through the anomaly configuration modification page and obtaining the first modification information determined for the operation configuration anomaly; updating the deployment parameters based on the first modification information and generating updated deployment parameters; and returning to execute S104 and S105 based on the updated deployment parameters to redeploy the MEC operation environment and perform testing.

9. An edge computing node deployment system suitable for 5G industrial private networks, used to implement the method according to any one of claims 1-8, characterized in that, include: The configuration display module is used to display the MEC node configuration page through the deployment management module running on the edge computing management platform. The configuration page includes MEC reuse parameter configuration items, network slicing QoS parameter configuration items, multi-network access disaster recovery configuration items, and QUIC protocol optimization parameter configuration items. The configuration information acquisition module is used to acquire the basic configuration information of the MEC node determined by the user through the MEC node configuration page, as well as the industrial service resource configuration information associated with the basic configuration information of the MEC node. The industrial service resource configuration information includes 5G LAN Layer 2 networking parameters, multi-link redundancy strategy, industrial service traffic forwarding rules and security encryption strategy based on independently controllable chips. The deployment parameter generation module is used to generate deployment parameters for running the MEC node and the industrial service resources based on the basic configuration information of the MEC node and the configuration information of the industrial service resources. The deployment parameters also include hardware driver parameters adapted to industrial-grade terminals in the energy industry and network slice resource reservation parameters. The deployment execution module is used to send deployment parameters to the target industrial-grade edge terminal so that the target industrial-grade edge terminal can deploy an MEC operating environment based on the deployment parameters. The operating environment supports network slicing logical isolation, multi-WAN port routing backup, and GRE tunnel primary and backup disaster recovery functions. The debugging and building module is used to respond to the debugging instructions for the industrial service resources, perform network quality testing and disaster recovery switching testing based on the operating environment, and obtain debugging results; when the debugging results indicate that the industrial service resources meet the industrial-grade preset operating conditions, it sends an edge computing node building request to the target industrial-grade edge terminal, so that the target industrial-grade edge terminal builds an edge computing node in a ready-to-be-called state based on the edge computing node building request. The node registration module is used to receive node metadata sent by the target industrial-grade edge terminal and register the node metadata with the edge computing management platform. The node metadata is used to identify the slice affiliation, disaster recovery link information and industrial business scheduling routing rules of the edge computing node. The node metadata also includes hardware identification information of autonomous and controllable network elements.

10. 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 method as described in any one of claims 1-8.

Images