An internet of things edge gateway data acquisition performance diagnosis system and method

Abstract

The application discloses a kind of for Internet of Things edge gateway data acquisition performance diagnosis system and method, including the following steps: by configuration storage module, pre-defined performance index, diagnostic rule and acquisition equipment network topology information are stored;Acquisition record module carries out multiple dimensions according to configuration file information Acquisition interactive data record and periodic storage;Index calculation module combines configuration file with acquisition record information and carries out acquisition index statistics and calculation;Rule engine module generates diagnostic data according to the result of index calculation module and pre-defined configuration information;Data publishing module is used to publish acquisition record data and diagnostic data and receive configuration information.The application can realize the monitoring and diagnosis to the whole process of data acquisition, make problem positioning more accurate, analysis more in-depth, output intuitive diagnostic report, provide basis for data acquisition quality control and parameter optimization.The system has wide application prospect for industrial field Internet of Things application.

Description

Technical Field

[0001] This invention belongs to the field of intelligent manufacturing control, specifically a system and method for diagnosing the data acquisition performance of IoT edge gateways. Background Technology

[0002] IoT edge gateways connect to industrial field data sources via various network devices in the south, mainly including programmable logic controllers, smart meters, information systems, and sensors. Data parsing, data caching, data computation, and northbound data forwarding are performed in the edge gateway.

[0003] In industrial settings, various systems, especially smart meters and sensors, are often networked via Ethernet, RS485, LoRa, or carrier waves and then connected to IoT edge gateways, forming a device-network-gateway structure. However, these systems are susceptible to various environmental and human-induced disturbances, such as sudden power outages, system shutdowns, electromagnetic interference, and vibrations. During actual operation, edge gateway data acquisition may experience various anomalies due to different reasons.

[0004] Currently, gateways typically use logs to record connection and read / write success statuses, making it difficult for users to efficiently obtain complete logs. Especially when analyzing and locating the cause of anomalies, users need to extract complex and tedious log records, while also considering the gateway's operation, network conversion devices, network conditions, and instrumentation, only reaching a conclusion after comprehensively considering the overall situation. General users often struggle to efficiently pinpoint specific causes of data collection anomalies, and the lack of recording and statistical methods makes it difficult to evaluate the actual data collection effectiveness over a period of time.

[0005] Evaluating data acquisition performance, accurately and efficiently diagnosing anomalies, and providing optimization suggestions for the application of the data acquisition system have become critical challenges that urgently need to be addressed. Summary of the Invention

[0006] To address the aforementioned technical issues, this invention provides a system and method for diagnosing the performance of data acquisition for IoT edge gateways. It periodically collects interactive data records from multiple dimensions, including gateways, links, data frames, and data model verification, and generates various statistical indicators. Based on a predefined rule engine, it processes the recorded data and statistical indicators, converting and outputting a text-based diagnostic report, allowing users to intuitively pinpoint problems.

[0007] The technical solution adopted by this invention to achieve the above objectives is: a data acquisition performance diagnosis system for IoT edge gateways, which calculates indicators for periodically recorded and stored multi-dimensional acquisition interaction data, diagnoses acquisition performance through performance evaluation rules, and outputs a text diagnostic report, including the following steps:

[0008] The configuration storage module is used to obtain configuration file information, including the set performance indicators, performance evaluation rules, and network topology information of the devices to be recorded, and to store them.

[0009] The data acquisition and recording module is used to obtain configuration file information from the configuration storage module and to collect and record interactive data from multiple dimensions and store it periodically based on the configuration file information.

[0010] The performance indicator calculation module is used to obtain configuration file information from the configuration storage module and perform performance indicator statistics and calculations based on the performance evaluation rules in the configuration file information, using the information recorded and stored by the collection and recording module.

[0011] The rules engine module is used to retrieve configuration file information from the configuration storage module and output a text-based diagnostic report based on the results of the metrics calculation module and performance evaluation rules.

[0012] The data publishing module is used to publish diagnostic reports and data stored in the data collection and recording module, and at the same time receive configuration file information and store it in the configuration storage module.

[0013] The configuration storage module includes:

[0014] The performance metrics storage module is used to store selected performance metrics and the calculation formulas containing these performance metrics.

[0015] The diagnostic rule storage module is used to store multiple performance evaluation rules that have been set.

[0016] The network topology information module is used to store the classification of links and devices selected from the actual gateway configuration parameters, as well as the hierarchical relationships of the links and devices.

[0017] The performance metrics include at least one of the following: gateway normal operating range, number of successful data collections, data collection success rate, expected number of receptions, response frame parsing success rate, response frame reception success rate, and network connection success rate.

[0018] The performance evaluation rules include at least one of the following: gateway operation status processing rules, network connection status processing rules, query frame processing rules, response frame processing rules, and data model verification processing rules; the rule logic includes several combinations of AND, OR, NOT, greater than, less than, not greater than, not less than, and equal to; the rule logic input values ​​are the calculated performance indicators and the default values ​​calculated according to the set parameters.

[0019] The data acquisition and recording module includes:

[0020] The operation status recording module is used to record the time interval during which the gateway operates normally;

[0021] The network link recording module is used to record the network link establishment status of the gateway access device, including the number of first connections, the number of reconnections, the number of successful connections, and the number of failed connections;

[0022] The query frame recording module is used to record the number of times the gateway first sends a query frame, the number of times it is repeatedly sent, and the time when the response frame is sent.

[0023] The response frame recording module is used to record the number of times the gateway receives response frames, the number of times the response frames are parsed correctly, the number of times the response frames are parsed unsuccessfully, and the number of times the response frames are parsed unsuccessfully of a certain type.

[0024] The data model validation record module is used to record the number of successful data model validations, the number of failed data model parsings, and the number of times the data model parsing failed for a specific type.

[0025] The data collection index calculation module includes:

[0026] The indicator rule reading module is used to read the set performance evaluation rules from the configuration storage parameters;

[0027] The data acquisition and record reading module is used to read multi-dimensional record data corresponding to the selected indicator from the data acquisition records;

[0028] The performance metric calculation module is used to perform statistics and calculations on multi-dimensional recorded information and assign values ​​to performance metrics.

[0029] The rule engine module includes:

[0030] The parameter reading module is used to read performance index values ​​and set performance evaluation rules;

[0031] The rule calculation module is used to calculate and generate text diagnostic results in layers according to performance evaluation rules;

[0032] The report generation module is used to generate a diagnostic report after statistically analyzing the diagnostic results at each level.

[0033] The data publishing module includes:

[0034] The data receiving module is used to wait for the diagnostic results output by the rule engine module to trigger the reception of the diagnostic report and to read the recorded data in the diagnostic report;

[0035] The data publishing module is used to publish diagnostic reports and collected data simultaneously.

[0036] A method for diagnosing the data acquisition performance of IoT edge gateways involves calculating metrics from periodically recorded and stored multi-dimensional acquisition and interaction data, diagnosing acquisition performance using performance evaluation rules, and outputting a text diagnostic report. The method includes the following steps:

[0037] The configuration storage module obtains configuration file information, including the set performance indicators, performance evaluation rules, and network topology information of the devices to be recorded, and stores it.

[0038] The data acquisition and recording module obtains configuration file information from the configuration storage module, and performs multi-dimensional data acquisition and interactive data recording and periodic storage based on the configuration file information;

[0039] The performance indicator calculation module retrieves configuration file information from the configuration storage module and performs statistical calculations on performance indicators based on the performance evaluation rules in the configuration file information, using the information recorded and stored by the data collection and recording module.

[0040] The rules engine module retrieves configuration file information from the configuration storage module and outputs a text-based diagnostic report based on the results of the metrics calculation module and the performance evaluation rules.

[0041] The data publishing module publishes diagnostic reports and data stored in the data collection and recording module, while also receiving configuration file information and storing it in the configuration storage module.

[0042] The data acquisition and recording module obtains configuration file information from the configuration storage module, and performs multi-dimensional data acquisition and interaction recording and periodic storage based on the configuration file information, including the following steps:

[0043] Read the set diagnostic cycle and data acquisition device network topology from the configuration storage module;

[0044] Record the gateway's operational status during the diagnostic cycle;

[0045] Record the link information of each network connection established between the gateway and the device being collected;

[0046] Record the query frame information sent by the gateway to the device being collected;

[0047] Record the reception and parsing results of each response frame;

[0048] Record the results of each successfully parsed variable being validated by the data model.

[0049] The present invention has the following beneficial effects and advantages:

[0050] Through the embodiments of the present invention, the textual evaluation and diagnostic results can be output to intuitively demonstrate the data acquisition performance of edge gateways in practical applications and efficiently locate the bottlenecks in the data acquisition performance of IoT edge gateways in practical applications. This helps users improve diagnostic efficiency and accuracy and provides strong technical support for the further development of edge gateway data acquisition applications. Attached Figure Description

[0051] Figure 1This is a block diagram illustrating the principle of a data acquisition performance diagnostic system for IoT edge gateways.

[0052] Figure 2 This is a flowchart of a method for diagnosing the data acquisition performance of IoT edge gateways. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of the present invention clearer and more explicit, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0054] To address the existing problems, this invention provides a data acquisition performance diagnosis system and method for IoT edge gateways. The principle is as follows: interactive data from multiple dimensions, including gateway, link, data frame, and data model verification, are periodically recorded. The interactive data and the system's default parameters within the current period are used to calculate various performance statistics according to device rules. The statistical indicators and data records are then processed by a predefined rule engine to output a text-based diagnostic report, which is then published, allowing users to efficiently and intuitively evaluate acquisition performance and locate the causes of anomalies.

[0055] See Figure 1 The present invention provides a data acquisition performance diagnosis system and method for IoT edge gateways, which mainly includes a configuration storage module, a data acquisition and recording module, an indicator calculation module, a rule engine module and a data publishing module inside the edge gateway.

[0056] The configuration storage includes a performance index storage module, a diagnostic rule storage module, and a network topology information module.

[0057] The performance index storage module stores the various performance indicators selected by the user and their calculation formulas.

[0058] The diagnostic rule storage module stores multiple performance evaluation rules set by the user.

[0059] The network topology information module stores the link-device classifications and hierarchical relationships selected by the user from the actual gateway configuration parameters.

[0060] The data collection records include a gateway data collection and operation status recording module, a network link recording module, an inquiry frame recording module, a response frame recording module, and a data model verification module.

[0061] The aforementioned operation status recording module records the time interval during which the gateway operates normally.

[0062] The aforementioned network link recording module records the network link establishment status of the gateway access device, including the number of initial connections, reconnections, successful connections, and failed connections.

[0063] The query frame recording module is responsible for recording the number of times the gateway first sends a query frame, the number of times it is repeatedly sent, and the time of each query frame transmission.

[0064] The aforementioned response frame recording module records the number of times the gateway receives response frames, the number of times the response frames are parsed correctly, the number of times the response frames are parsed unsuccessfully, and the number of times the response frames are parsed unsuccessfully of a subtype. The subtype counts include: the number of times the frame is short, the number of times the frame format is incorrect, and the number of times the frame address is incorrect.

[0065] The data model verification module mentioned above supports selected data verification rules by default in the gateway.

[0066] The aforementioned indicator calculation includes an indicator rule reading module, a data collection and record reading module, and a performance indicator calculation module.

[0067] The aforementioned indicator rule reading module refers to reading the performance indicator calculation rules set by the user from the configuration storage parameters;

[0068] The aforementioned data acquisition and record reading module refers to reading multi-dimensional record data related to the selected indicator from the data acquisition records.

[0069] The performance index calculation module refers to the statistical analysis and calculation of multi-dimensional recorded information to assign values ​​to performance indicators.

[0070] The rule engine includes a parameter reading module, a rule calculation module, and a report generation module.

[0071] The parameter reading module reads performance index values ​​and diagnostic rules set by the user.

[0072] The rule calculation module is used to calculate and generate textual diagnostic results in layers according to diagnostic rules.

[0073] The aforementioned report generation module refers to generating a diagnostic report after aggregating the diagnostic results from each level.

[0074] The data publishing process includes a data receiving module and a data publishing module.

[0075] The data receiving module refers to the module that waits for the rule engine module to output results to trigger the reception of diagnostic reports and the reading of relevant record data.

[0076] The data publishing module refers to the simultaneous publication of diagnostic reports and collected data records.

[0077] See Figure 1 The service-oriented data gateway configuration system provided by this invention mainly includes data within the data gateway.

[0078] See Figure 2 The present invention provides a method for diagnosing the data acquisition performance of an IoT edge gateway, comprising the following steps:

[0079] Step S1: Store the set performance indicators, diagnostic rules, and network topology information of the devices to be recorded;

[0080] Step S2: Collect and record interactive data from multiple dimensions and store it periodically according to the configuration file information;

[0081] Step S3: Combine the collected records with the configuration file to perform statistical analysis and calculation of the collected indicators;

[0082] Step S4: Generate diagnostic data based on the results of the indicator calculation module and predefined configuration information;

[0083] Step S5: Publish the collected and recorded data, diagnostic data, and receive configuration information;

[0084] Step S6: Repeat step S1.

[0085] The specific method for collecting and recording interactive data is as follows:

[0086] Record the time interval during which the gateway operates normally;

[0087] Record each network connection during the period when the gateway is operating normally.

[0088] If the network connection is successful, record the status of query frame transmission;

[0089] If the query frame is sent normally, record the parsing status of the response frame;

[0090] If the response frame is successfully parsed, record the data model comparison status.

[0091] The specific method for calculating the performance indicators is as follows:

[0092] 1. Read the user-defined performance metrics and their calculation rules from the configuration module;

[0093] 2. Read the multi-dimensional record information and system default parameters within the period stored in the data acquisition module;

[0094] 3. Perform statistics and calculations on multi-dimensional recorded information and assign values ​​to performance indicators.

[0095] The specific method for generating diagnostic data is as follows:

[0096] Read various diagnostic rules set by the user in the configuration module;

[0097] The system will read performance metrics from four levels: gateway, link, frame, and data verification. Based on the diagnostic rules, it will calculate and generate text-based diagnostic results.

[0098] The diagnostic results from four levels are aggregated to generate a diagnostic report.

[0099] The working principle and specific implementation methods of the present invention will be further described in detail below.

[0100] The objects collected in industrial settings mainly include industrial instruments, programmable logic controllers, sensors, and other industry equipment. In practical applications, the collected devices usually need to be converted and networked in various ways, and then connected to the edge gateway through the network conversion device. That is, there is usually a device-network-gateway structure.

[0101] In this embodiment, the network topology consists of a gateway, a serial server, and a 485 bus. Ten smart meters are connected sequentially via a single 485 bus, numbered D1-D10. D1 is then connected to one serial port of a multi-channel serial server. The serial server is configured in TCP-Server mode, and the edge gateway connects to the serial server's network port via Ethernet. In this embodiment, the meters collect data using the DLT645-2007 protocol, with communication parameters of 2400 baud rate and even parity. The data acquisition process involves the edge gateway acquiring data from the meters on two buses in parallel according to a set period. Within a single bus, serial communication with the meters is used, while network communication utilizes short-connection methods.

[0102] The edge gateway first reads the parameters from the configuration module and begins recording the gateway's operating range (Start-End Range). Then, the edge gateway establishes a network link with the serial server, recording the number of network connections (NCC), including the first connection count (NCCF), reconnection count (NCCR), and successful connection count (NSC). After a successful network connection, the edge gateway sends an inquiry frame request to a specific data acquisition device through the serial server. The request requests commands to retrieve certain data and records the number of inquiry frames sent (TXC), including the first transmission count (TXCF) and retransmission count (TXCR), and the inquiry frame transmission time (TXTIME). Then, within the "network connection timeout" period, the edge gateway waits for the data acquisition device to send the corresponding data back in the form of an acknowledgment frame. If there is no acknowledgment, the number of failed acknowledgment frame returns (ERXC) is recorded. If there is an acknowledgment, the number of acknowledgment frames received (RXC) and the time (RXTIME) are recorded. Upon receiving the acknowledgment frame data packet, the edge gateway parses the packet according to the corresponding protocol. If parsing fails, record the received response frame, the number of response frame parsing failures (EPSC), and the number of failure types, including: Truncated (frame short error), BadCheck (frame format error), and Badadd (frame address error). If parsing succeeds, record the number of correct response frame parsings (PSC). Forward the parsed result to the gateway's own data service model for verification. If the data model verification fails, record the result and the number of collection failures (EDSC). If the data model verification succeeds, record the number of successful collections (DSC). Thus, the edge gateway completes the entire "question and answer and verification" process for a single data collection. Within a set time frame, the edge gateway records relevant information about each interaction process and the edge gateway's own operational status through multiple data collection processes from multiple devices.

[0103] Once the recording period is reached, the performance indicator calculation module will perform calculations according to the set rules and assign values ​​to the set indicators. These include: Expected Reception Count (PRXC), Successful Acquisition Count (DSC), Acquisition Success Rate (PV), Data Verification Success Rate (DSR), Response Frame Parsing Success Rate (PSR), Response Frame Reception Success Rate (RSR), and Network Connection Success Rate (NCSR). Among these:

[0104] PV=DSC / PTXC; DSR=DSC / PSC; PSR=PSC / RXC; RSR=RXC / TXC; NCSR=NSC / NCC.

[0105] After calculating and generating the various performance indicators, the system outputs text-based diagnostic results through a predefined rule engine.

[0106] If the user sets a normal 1-hour data collection cycle, all variable points will be collected at a fixed frequency of 1 minute. According to the protocol, under normal circumstances, each electron needle needs to send 4 query frames to obtain complete data for a single collection, with a single needle response time in the hundreds of milliseconds. The network link timeout is set to 3 seconds, and the repetition count is set to 1. The single response frame reception timeout is 3 seconds, and the repetition count is set to 3.

[0107] During the simulation, the collected and recorded data is shown in Table 1:

[0108] As shown in Table 1

[0109] D1 240 60 60 240 240 240 240 D2 240 60 60 240 240 240 240 D3 240 60 60 240 240 240 240 D4 240 60 60 240 240 240 240 D5 240 60 60 240 240 240 240 D6 240 60 60 240 240 240 240 D7 240 60 60 240 240 240 240 D8 240 60 60 720 0 0 0 D9 240 60 60 480 120 120 120 D10 240 30 30 120 120 120 120

[0110] The performance index calculation data is shown in Table 2:

[0111] Table 2

[0112] D1 240 100.00％ 100.00％ 100.00％ 100.00％ 100.00％ D2 240 100.00％ 100.00％ 100.00％ 100.00％ 100.00％ D3 240 100.00％ 100.00％ 100.00％ 100.00％ 100.00％ D4 240 100.00％ 100.00％ 100.00％ 100.00％ 100.00％ D5 240 100.00％ 100.00％ 100.00％ 100.00％ 100.00％ D6 240 100.00％ 100.00％ 100.00％ 100.00％ 100.00％ D7 240 100.00％ 100.00％ 100.00％ 100.00％ 100.00％ D8 240 100.00％ 0.00％ 100.00％ 1000.00％ 100.00％ D9 240 100.00％ 25.00％ 100.00％ 100.00％ 50.00％ D10 240 100.00％ 100.00％ 100.00％ 100.00％ 50.00％

[0113] This example focuses on network connectivity and data transmission / reception, and the relevant rules are set as follows:

[0114] 1. If PV is less than 99%, output "Low collection success rate, anomaly exists"; otherwise, output "Collection is normal".

[0115] 2. If NCC is less than PTXC and NCSR is equal to 1, output "There is a timeout in the acquisition cycle and no connection was established".

[0116] 3. If NCSR is less than 1, output "Network connection failure exists".

[0117] 4. If NCSR is greater than 0 and RXC is equal to 0, output "The instrument has no response and the overall link delay is 4*3*3 seconds".

[0118] 5. If NCSR is greater than 0 and RXC is less than NCC*4, output "The instrument is in a no-response state. In the case of no response, the link delay is (NCC*4-RXC)*3 seconds".

[0119] 6. If NCSR is less than 1 and RXC is equal to NCC*4, output "The instrument has a situation where commands need to be sent repeatedly".

[0120] 7. If the PSR is less than 99%, there is a failure to parse the response frame, and the number of frame short errors is Truncated, the number of frame format errors is BadCheck, and the number of frame address errors is BadAdd; otherwise, output "Response frame parsing success rate is normal".

[0121] 8. If the DSR is less than 99%, output "There is a data model validation failure"; otherwise, output "The model validation success rate is normal".

[0122] Based on the collected data and performance indicator calculation data, conclusions are output according to the set rules:

[0123] 1. The gateway is operating normally within this area.

[0124] 2. Low data collection success rate, with anomalies present.

[0125] 3. D10 has a situation where the acquisition cycle timed out and no connection was established.

[0126] 4. Instrument D6 remained unresponsive with a delay; Instrument D7 also experienced an unresponsive state with a delay.

[0127] 5. The success rate of parsing response frames is normal.

[0128] 6. The model validation success rate is normal.

[0129] The diagnostic report generated from the aggregation of data from multiple links is sent to the front end or the cloud via the publishing module. Users can intuitively evaluate the acquisition performance through the report and further pinpoint anomalies by combining frame-level recordings.

Claims

1. A data acquisition performance diagnostic system for IoT edge gateways, characterized in that, For the periodically recorded and stored multi-dimensional data collection and interaction data, metric calculations are performed, and data collection performance is diagnosed using performance evaluation rules, resulting in a text diagnostic report. This includes the following steps: The configuration storage module is used to obtain configuration file information, including the set performance indicators, performance evaluation rules, and network topology information of the devices to be recorded, and to store them. The data acquisition and recording module is used to obtain configuration file information from the configuration storage module and to collect and record interactive data from multiple dimensions and store it periodically based on the configuration file information. The performance indicator calculation module is used to obtain configuration file information from the configuration storage module and perform performance indicator statistics and calculations based on the performance evaluation rules in the configuration file information, using the information recorded and stored by the collection and recording module. The rules engine module is used to retrieve configuration file information from the configuration storage module and output a text-based diagnostic report based on the results of the metrics calculation module and performance evaluation rules. The data publishing module is used to publish diagnostic reports and data stored in the data collection and recording module, and at the same time receive configuration file information and store it in the configuration storage module.

2. The data acquisition performance diagnostic system for IoT edge gateways according to claim 1, characterized in that, The configuration storage module includes: The performance metrics storage module is used to store selected performance metrics and the calculation formulas containing these performance metrics. The diagnostic rule storage module is used to store multiple performance evaluation rules that have been set. The network topology information module is used to store the classification of links and devices selected from the actual gateway configuration parameters, as well as the hierarchical relationships of the links and devices.

3. A data acquisition performance diagnostic system for IoT edge gateways according to claim 1 or 2, characterized in that, The performance metrics include at least one of the following: gateway normal operating range, number of successful data collections, data collection success rate, expected number of receptions, response frame parsing success rate, response frame reception success rate, and network connection success rate.

4. A data acquisition performance diagnostic system for IoT edge gateways according to claim 1 or 2, characterized in that, The performance evaluation rules include at least one of the following: gateway operation status processing rules, network connection status processing rules, query frame processing rules, response frame processing rules, and data model verification processing rules; the rule logic includes several combinations of AND, OR, NOT, greater than, less than, not greater than, not less than, and equal to; the rule logic input values ​​are the calculated performance indicators and the default values ​​calculated according to the set parameters.

5. The data acquisition performance diagnostic system for IoT edge gateways according to claim 1, characterized in that, The data acquisition and recording module includes: The operation status recording module is used to record the time interval during which the gateway operates normally; The network link recording module is used to record the network link establishment status of the gateway access device, including the number of first connections, the number of reconnections, the number of successful connections, and the number of failed connections; The query frame recording module is used to record the number of times the gateway first sends a query frame, the number of times it is repeatedly sent, and the time when the response frame is sent. The response frame recording module is used to record the number of times the gateway receives response frames, the number of times the response frames are parsed correctly, the number of times the response frames are parsed unsuccessfully, and the number of times the response frames are parsed unsuccessfully of a certain type. The data model validation record module is used to record the number of successful data model validations, the number of failed data model parsings, and the number of times the data model parsing failed for a specific type.

6. The data acquisition performance diagnostic system for IoT edge gateways according to claim 1, characterized in that, The indicator calculation module includes: The indicator rule reading module is used to read the set performance evaluation rules from the configuration storage parameters; The data acquisition and record reading module is used to read multi-dimensional record data corresponding to the selected indicator from the data acquisition records; The performance metric calculation module is used to perform statistics and calculations on multi-dimensional recorded information and assign values ​​to performance metrics.

7. The data acquisition performance diagnostic system for IoT edge gateways according to claim 1, characterized in that, The rule engine module includes: The parameter reading module is used to read performance index values ​​and set performance evaluation rules; The rule calculation module is used to calculate and generate text diagnostic results in layers according to performance evaluation rules; The report generation module is used to generate a diagnostic report after statistically analyzing the diagnostic results at each level.

8. The data acquisition performance diagnosis system for IoT edge gateways according to claim 1, characterized in that, The data publishing module includes: The data receiving module is used to wait for the diagnostic results output by the rule engine module to trigger the reception of the diagnostic report and to read the recorded data in the diagnostic report; The data publishing module is used to publish diagnostic reports and collected data simultaneously.

9. A method for diagnosing the data acquisition performance of an IoT edge gateway, characterized in that, For the periodically recorded and stored multi-dimensional data collection and interaction data, metric calculations are performed, and data collection performance is diagnosed using performance evaluation rules, resulting in a text diagnostic report. This includes the following steps: The configuration storage module obtains configuration file information, including the set performance indicators, performance evaluation rules, and network topology information of the devices to be recorded, and stores it. The data acquisition and recording module obtains configuration file information from the configuration storage module, and performs multi-dimensional data acquisition and interactive data recording and periodic storage based on the configuration file information; The performance indicator calculation module retrieves configuration file information from the configuration storage module and performs statistical calculations on performance indicators based on the performance evaluation rules in the configuration file information, using the information recorded and stored by the data collection and recording module. The rules engine module retrieves configuration file information from the configuration storage module and outputs a text-based diagnostic report based on the results of the metrics calculation module and the performance evaluation rules. The data publishing module publishes diagnostic reports and data stored in the data collection and recording module, while also receiving configuration file information and storing it in the configuration storage module.

10. A method for diagnosing the data acquisition performance of an IoT edge gateway according to claim 9, characterized in that, The data acquisition and recording module obtains configuration file information from the configuration storage module, and performs multi-dimensional data acquisition and interaction recording and periodic storage based on the configuration file information, including the following steps: Read the set diagnostic cycle and data acquisition device network topology from the configuration storage module; Record the gateway's operational status during the diagnostic cycle; Record the link information of each network connection established between the gateway and the device being collected; Record the query frame information sent by the gateway to the device being collected; Record the reception and parsing results of each response frame; Record the results of each successfully parsed variable being validated by the data model.

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