Access control method and system for industrial internet server

Abstract

The invention relates to an access control method and system for an industrial internet server. The method comprises the following steps: analyzing a plurality of round-trip delays and a plurality of response delays to obtain a failure coefficient of a target equipment execution instruction; determining an execution delay index according to the deviation and the failure coefficient between the response duration of each process variable of the target equipment for the plurality of instructions in the same time window and the corresponding preset duration; according to the relevancy between the execution delay indexes of the time windows and the change characteristic values of the process variables, the influence index of instruction delay execution on the process variables is determined; calculating a risk coupling coefficient corresponding to the instruction sequence according to the delay difference of each adjacent instruction in the instruction sequence; and adjusting the number of access instructions of the server according to the influence index and the risk coupling coefficient. According to the method, the interlocking amplification risk of instruction delay and process variable fluctuation can be effectively inhibited, and the stability and reliability of an industrial internet access control system are guaranteed.

Description

Technical Field

[0001] This application relates to the field of telecommunications technology, and in particular to an access control method and system for an industrial internet server. Background Technology

[0003] In an industrial internet environment, servers typically need to provide services to both internal industrial LAN users and external remote access users. Since industrial control networks often involve critical facilities such as SCADA (Supervisory Control and Data Acquisition) systems, PLC (Programmable Logic Controller) systems, and DCS (Distributed Control System) systems, vulnerabilities in access control mechanisms may lead to risks such as unauthorized access to perform malicious operations, the theft of confidential data, and even shutdown of industrial production lines.

[0004] Existing access control methods mostly rely on manually preset policies, lacking dynamic adjustment capabilities. They cannot automatically optimize policies based on real-time network conditions, device operating status, or changes in access behavior. For example, when a device is operating abnormally, the system cannot automatically tighten access permissions or switch to a stricter access mode. Furthermore, most existing systems are based on pre-emptive policy matching, lacking real-time access behavior analysis and prediction capabilities, and cannot utilize machine learning or big data analytics to identify potential abnormal access trends in advance. Summary of the Invention

[0006] To address the aforementioned technical problems, the purpose of this application is to provide an access control method and system for an industrial internet server, the specific technical solution of which is as follows: On the one hand, an access control method for an industrial internet server is provided, the method comprising: Analyze multiple round-trip delays and multiple response delays to obtain the failure coefficient of the target device's execution instructions; the round-trip delay indicates the time from when the server sends a test data packet to the target device to when it receives its response data packet, and the response delay indicates the time from when the server sends an instruction to the target device to when it receives its corresponding service confirmation response; The execution delay index is determined based on the deviation between the response time of each process variable of the target equipment to multiple instructions within the same time window and the corresponding preset time, and the failure coefficient. The impact index of instruction delay execution on process variables is determined based on the correlation between multiple execution delay indices across multiple time windows and the change characteristic values ​​of multiple process variables. The risk coupling coefficient corresponding to the instruction sequence is calculated based on the delay difference of each adjacent instruction in the instruction sequence; the delay of each instruction is obtained by calculating the deviation between the response time of multiple process variables for the same instruction and the corresponding preset time; the instruction sequence includes multiple instructions within multiple time windows; The number of access commands to the server is adjusted based on the impact index and the risk coupling coefficient.

[0007] Optionally, the analysis of multiple round-trip delays and multiple response delays to obtain the failure coefficient of the target device's execution instructions includes: Collect multiple round-trip delays and multiple response delays within the same time window; A coordinate system is established with multiple acquisition times within a time window as the horizontal axis and multiple round-trip delays as the vertical axis. Linear interpolation is performed on each data point in the coordinate system to obtain a round-trip delay polygon. The slope value between all adjacent data points in the round-trip delay polygon is calculated. Multiple acquisition times correspond one-to-one with multiple round-trip delays. The link degradation index is determined based on the range of round-trip delay within the time window and the absolute difference between each adjacent slope value. By analyzing the link degradation index and multiple response delays, the failure coefficient of the target device's execution commands is obtained.

[0008] Optionally, the analysis of the link degradation index and multiple response delays to obtain the failure coefficient of the target device's execution instructions includes: Obtain the time of issuance of each command sent by the server to the target device within the same time window, the response delay of the command, and the identification information of the command; For each instruction, in response to retrieving the corresponding service confirmation response within the same time window based on the instruction's identification information, the duration between the instruction's issuance time and the corresponding service confirmation response is determined as the target response delay. The failure coefficient is determined based on the standard deviation of multiple target response delays, the mean of multiple target response delays, and the link degradation index.

[0009] Optionally, determining the execution delay index based on the deviation between the response time of each process variable of the target equipment to multiple instructions within the same time window and the corresponding preset time, and the failure coefficient, includes: For each process variable, the average response time of each process variable to multiple instructions within the same time window is calculated to obtain the average response time of each process variable. The average of multiple preset times of each process variable to multiple instructions is also calculated to obtain the average preset time of each process variable. Each instruction corresponds to a preset time for each process variable it regulates. The response time indicates the time required for multiple process variables of the target device to change from the initial state to the target state after the target device receives each instruction. Calculate the difference between the average response time of each process variable and the corresponding preset average response time to obtain the response time difference; The execution delay index is determined based on the differences in response durations and failure coefficients within each time window; the differences in response durations correspond one-to-one with multiple process variables.

[0010] Optionally, determining the impact index of instruction delay execution on process variables based on the correlation between multiple execution delay indices across multiple time windows and the change characteristic values ​​of multiple process variables includes: A coordinate system is established with the time sequence of multiple time windows as the horizontal axis and the multiple execution delay indices corresponding to the multiple time windows as the vertical axis. Polynomial curve fitting is performed on each data point in the coordinate system and the vertical axis is normalized to obtain the execution curve. An independent coordinate system is established for each process variable, with the time sequence number of multiple time windows as the horizontal axis and the variance of multiple sampled values ​​of the process variable within each time window as the vertical axis. Polynomial curve fitting is performed on each data point in the coordinate system and the vertical axis is normalized to obtain each change characteristic curve corresponding to each process variable; each time window corresponds to multiple sampled values ​​of each process variable. The mean square error between multiple characteristic curves and the execution delay index curve is calculated separately, and the average of the obtained mean square errors is calculated to obtain the impact index of instruction delay execution on process variables; multiple process variables correspond one-to-one with multiple characteristic curves.

[0011] Optionally, calculating the risk coupling coefficient corresponding to the instruction sequence based on the latency difference between each adjacent instruction in the instruction sequence includes: The delay coefficient of each instruction is obtained by calculating the difference between the average response time of the multiple process variables controlled by each instruction and the average preset time of the multiple process variables controlled by each instruction. The risk coupling coefficient corresponding to the instruction sequence is calculated based on the difference in the delay coefficient of each adjacent instruction in the instruction sequence.

[0012] Optionally, calculating the risk coupling coefficient corresponding to the instruction sequence based on the difference in latency coefficients of each adjacent instruction in the instruction sequence includes: The ratio of the delay factors of adjacent instructions is calculated based on the ratio of the delay factor of the target instruction to the delay factor of the instruction preceding the target instruction; the target instruction is any instruction in the instruction sequence. The risk coupling coefficient corresponding to the instruction sequence is determined by averaging the ratios of the delay coefficients of all adjacent instructions in the instruction sequence.

[0013] Optionally, adjusting the number of server access commands based on the impact index and the risk coupling coefficient includes: The server access adjustment coefficient is obtained by multiplying the impact index and the risk coupling coefficient. The number of access commands to the server is adjusted based on the server's access adjustment factor.

[0014] Optionally, adjusting the number of access commands to the server based on the server's access adjustment coefficient includes: The batch adjustment value is obtained by summing the preset value and the access adjustment coefficient; The number of access commands to the server is adjusted based on the product of the absolute difference between the first threshold and the second threshold and the batch adjustment value, plus the second threshold. The first threshold indicates the maximum number of batch commands preset by the server, and the second threshold indicates the minimum number of batch commands preset by the server.

[0015] Secondly, an access control system for an industrial internet server is provided, the system comprising: The analysis module is used to analyze multiple round-trip delays and multiple response delays to obtain the failure coefficient of the target device's execution instructions; the round-trip delay indicates the time from when the server sends a test data packet to the target device to when it receives its response data packet, and the response delay indicates the time from when the server sends an instruction to the target device to when it receives its corresponding service confirmation; The first determining module is used to determine the execution delay index based on the deviation between the response time of each process variable of the target equipment to multiple instructions within the same time window and the corresponding preset time, and the failure coefficient. The second determining module is used to determine the impact index of instruction delay execution on process variables based on the correlation between multiple execution delay indices of multiple time windows and the change characteristic values ​​of multiple process variables; The calculation module is used to calculate the risk coupling coefficient corresponding to the instruction sequence based on the delay difference of each adjacent instruction in the instruction sequence; the delay of each instruction is obtained by calculating the deviation between the response time of multiple process variables for the same instruction and the corresponding preset time; the instruction sequence includes multiple instructions within multiple time windows; The adjustment module is used to adjust the number of access commands to the server based on the impact index and the risk coupling coefficient.

[0016] Based on common knowledge in the field, the above-mentioned preferred conditions can be combined arbitrarily to obtain various preferred embodiments of this application.

[0017] This application offers the following advantages: By integrating the stability of round-trip delay and the distribution characteristics of response delay, a failure coefficient is calculated to quantify the risk of command misordering or retransmission caused by momentary network link instability. The deviation of the response time of each process variable to multiple commands from the theoretical value is compared, and the failure coefficient is then superimposed to obtain the execution delay index, which directly reflects the execution lag of the target equipment. The correlation between the execution delay index and the characteristic values ​​of process variable changes across multiple time windows is statistically analyzed to generate an impact index, used to measure the amplification effect of command delay on process fluctuations. The delay difference between adjacent commands is calculated sequentially along the command sequence, and the risk coupling coefficient is accumulated to characterize the cascading amplification trend of delay among multiple commands. Based on the impact index and the risk coupling coefficient, the number of access commands to the server is adjusted, effectively suppressing the cascading amplification risk of command delay and process variable fluctuations, and ensuring the stability and reliability of the industrial internet access control system. Attached Figure Description

[0019] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of an access control method for an industrial internet server in one embodiment; Figure 2 This is a schematic diagram of the access control system of an industrial internet server in one embodiment; Figure 3 This is a schematic diagram of the structure of an electronic device in one embodiment. Detailed Implementation

[0022] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an access control method and system for an industrial internet server proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0024] The specific scheme of the access control method for an industrial internet server provided in this application is described below with reference to the accompanying drawings. For example... Figure 1 As shown, the method includes: S11. Analyze multiple round-trip delays and multiple response delays to obtain the failure coefficient of the target device's execution instructions.

[0025] The round-trip time (RTT) indicates the time from when the server sends a test packet to the target device to when it receives the response packet. The test packet is usually a link probe frame without any service load (such as a 0-byte TCP ACK, UDP Ping, or a custom heartbeat frame) used to measure link quality. After receiving the test packet, the target device immediately returns a response packet at the network protocol stack level. The response packet does not contain any service processing content.

[0026] The response delay indicates the time from when the server sends a command to the target device to when it receives the corresponding service confirmation response. The command is sent in the form of a command message (such as Modbus / TCP function code 03 / 06, OPC UA call, or custom control frame), carrying specific control parameters. The target device needs to execute the process action required by the command. After the process variables of the target device reach the target state, it returns a service confirmation response (including execution result or status word).

[0027] Servers may include: edge computing gateways, SCADA servers (Supervisory Control And Data Acquisition Server), MES servers (Manufacturing Execution System Server), ERP servers (Enterprise Resource Planning Server), cloud-side industrial platform as a service node, virtualized industrial control servers, industrial safety management center servers, etc.

[0028] Target equipment may include: frequency converters, servo drives, industrial robot controllers, smart sensors, smart meters, actuators, valve positioners, compressor controllers, photovoltaic inverters, digital twin terminals, edge industrial gateways, etc.

[0029] External operation and maintenance terminals or management platforms initiate access requests to the industrial internet server via TLS or IPsec encrypted channels. After verifying the permissions, the industrial internet server sends instruction messages to the target device via industrial Ethernet, 5G, or fieldbus. Once the target device completes the execution, it returns a service confirmation response, which is then transmitted back to the operation and maintenance terminal along the original path, thus forming a complete bidirectional access link.

[0030] When an external maintenance terminal or management platform initiates an access request, the access control module of the server (industrial internet server) needs to collect data related to the access request in real time, including request source information (source IP address, port number, etc.), terminal attribute information (such as device type, operating system version, etc.), user identity information (such as user ID, authentication method, etc.), and obtain the network quality status of the current area communication by real-time monitoring of data such as bandwidth occupancy, data packet loss, round-trip delay, and link jitter of the current network link.

[0031] While collecting data in real time, the server retrieves recent historical behavior records related to the access request, including the most recent login time, operation type, operation result, and historical alarm information. During the data collection process, encrypted transmission (such as TLS (Transport Layer Security) or Ipsec (Internet Protocol Security)) and data integrity verification (such as HMAC (Hash-based Message Authentication Code) or CRC (Cyclic Redundancy Check)) should be employed to ensure the confidentiality and tamper-proof capability of the collected data during cross-network transmission. Furthermore, key collected data should be timestamped to ensure traceability and timeliness.

[0032] To analyze the round-trip latency trends between the server and the target device (target industrial equipment) during the process of access requests passing through the industrial internet server, in order to better identify instruction inconsistency issues caused by network latency fluctuations and provide data support for subsequent dynamic adjustment of access control policies, in one embodiment, multiple round-trip latencies and multiple response latencies are analyzed to obtain the failure coefficient of the target device's instruction execution, including: Collect multiple round-trip delays and multiple response delays within the same time window; A coordinate system is established with multiple acquisition times within a time window as the horizontal axis and multiple round-trip delays as the vertical axis. Linear interpolation is performed on each data point in the coordinate system to obtain a round-trip delay polygon. The slope value between all adjacent data points in the round-trip delay polygon is calculated. Multiple acquisition times correspond one-to-one with multiple round-trip delays. The link degradation index is determined based on the range of round-trip delay within the time window and the absolute difference between each adjacent slope value. By analyzing the link degradation index and multiple response delays, the failure coefficient of the target device's execution commands is obtained.

[0033] For round-trip time (RTD), multiple measurements are required during access control. A time window, such as 5 minutes, can be set. Multiple RTDs are collected within this time window. A coordinate system is established with the multiple collection times within the time window as the horizontal axis and the corresponding RTDs as the vertical axis. Linear interpolation is performed on each data point in the coordinate system to obtain a RTD polygon. In this polygon, adjacent data points form a slope value, denoted as K. The slope values ​​between all adjacent data points in the RTD polygon are calculated. Based on the maximum range of RTDs within the time window and the absolute difference between each adjacent slope value, a link degradation index is determined. The calculation formula is: ; in, This is the link degradation index. This represents the number of slope values ​​in the round-trip time delay broken line. The first in the round-trip time delay broken line Groups of adjacent data points, This represents the range of round-trip delays in the round-trip delay graph, which is the difference between the maximum and minimum round-trip delays within this time window. The first in the round-trip time delay broken line The slope value between adjacent data points in a group The first in the round-trip time delay broken line The slope value between adjacent data points in a group. The larger the value, the more complex the round-trip latency fluctuations are during the process of the server sending the access request to the target device.

[0034] The stability of network latency can be measured at the link level by using the fluctuation of round-trip time (RTT). However, even if the RTT fluctuation is small, frequent packet loss or retransmission can still reduce the reliability of command execution. Therefore, in one embodiment, the link degradation index and multiple response delays are analyzed to obtain the failure coefficient of the target device's command execution, including: Obtain the time of issuance of each command sent by the server to the target device within the same time window, the response delay of the command, and the identification information of the command; For each instruction, in response to retrieving the corresponding service confirmation response within the same time window based on the instruction's identification information, the duration between the instruction's issuance time and the corresponding service confirmation response is determined as the target response delay. The failure coefficient is determined based on the standard deviation of multiple target response delays, the mean of multiple target response delays, and the link degradation index.

[0035] On the server side, the times of issuing multiple commands and receiving corresponding service acknowledgments within the same time window are recorded. This time window is the same as the time window used to collect multiple round-trip delays and multiple response delays. The difference between the time of receiving the corresponding service acknowledgment and the time of issuance is the response delay of the command. Identification information for each command (e.g., connection ID, message ID, or sequence number) is obtained. For each command, the corresponding service acknowledgment is located within the time window using the message ID or sequence number. If the corresponding service acknowledgment is received within the time window, the duration between the time of receiving the corresponding service acknowledgment and the time of issuance of the command is determined as the target response delay. If no corresponding service confirmation response is received within the specified time window, a timeout or packet loss is determined, and response latency is not calculated. A failure coefficient is determined based on the standard deviation of multiple target response latencies, the mean of multiple target response latencies, and the link degradation index. The calculation formula is: ; in, The failure coefficient for executing instructions on the target device. This is the link degradation index. The standard deviation of response delay for multiple targets. This is the average response delay for multiple targets. This represents the coefficient of variation of the target response delay distribution, reflecting the relative intensity of the target response delay. It indicates the overall uniformity and stability of the delay distribution, such as whether the overall network delay remains stable amidst fluctuations. The link degradation index... This reflects the absolute strength of the time delay distribution, such as peak deviation and extreme fluctuations. Round-trip time delays fluctuate greatly, and these fluctuations are very significant relative to the average time delay. The larger the value, the more unstable the network. In this case, the instructions in the access control process are more likely to experience delays, timeouts, or disordered sequences, and the more unreliable the instruction execution is.

[0036] S12. Determine the execution delay index based on the deviation between the response time of each process variable of the target equipment to multiple instructions within the same time window and the corresponding preset time, and the failure coefficient.

[0037] Process variables include, but are not limited to, variables with time-series characteristics such as temperature, pressure, flow rate, and rotational speed.

[0038] Each instruction corresponds to a preset duration for each process variable it regulates. That is, a preset duration is configured in the preset relationship between each process variable and each instruction. The preset duration for each process variable corresponding to each instruction can be obtained by looking up a table. The preset duration is set according to the actual situation. For example, the preset duration for the first process variable in relation to the first instruction is 3 seconds, and the preset duration for the first process variable in relation to the second instruction is 5 seconds. The preset duration indicates the theoretical time required for each process variable to change from its initial state to the target state after the target equipment receives each instruction. The response duration indicates the actual time required for multiple process variables of the target equipment to change from their initial state to the target state after receiving each instruction.

[0039] The above steps reveal the risk of instruction execution errors or retransmissions due to network link instability, thereby assessing the potential unreliability of instruction execution. However, the effectiveness of instruction execution in an industrial internet environment is not only affected by network latency, but the dynamic changes in these instruction execution latency directly affect the performance of process variables in industrial equipment. Therefore, in one embodiment, the execution latency index is determined based on the deviation between the response time of each process variable of the target equipment to multiple instructions within the same time window and the corresponding preset time, and the failure coefficient, including: For each process variable, the average response time of each process variable to multiple instructions within the same time window is calculated to obtain the average response time of each process variable. The average of multiple preset times of each process variable to multiple instructions is also calculated to obtain the average preset time of each process variable. Each instruction corresponds to a preset time for each process variable it regulates. The response time indicates the time required for multiple process variables of the target device to change from the initial state to the target state after the target device receives each instruction. Calculate the difference between the average response time of each process variable and the corresponding preset average response time to obtain the response time difference; The execution delay index is determined based on the differences in response durations and failure coefficients within each time window; the differences in response durations correspond one-to-one with multiple process variables.

[0040] The main purpose of this step is to conduct an in-depth analysis from the perspective of equipment physical response, thereby observing the impact of execution latency on the dynamic offset of process variables, verifying the actual impact of front-end network latency on field equipment control, and providing physical feedback basis for dynamic access control strategies.

[0041] Record the response time of the actuator of the target equipment from the initial state to the target state for each process variable after receiving each instruction. Based on this, calculate the average response time of each process variable from the initial state to the target state after receiving multiple instructions within the same time window, which is the average response time of each process variable. This time window is the same as the time window used to collect multiple round-trip delays and multiple response delays. Next, the preset duration for each process variable for each instruction is obtained; that is, the theoretical time required for each process variable to change from its initial state to its target state after the target device receives each instruction. Based on this, the average preset duration for each process variable for multiple instructions is calculated, thus obtaining the average preset duration for each process variable. .

[0042] Calculate the difference between the average response time of each process variable and the corresponding preset average response time to obtain the response time difference. Based on the multiple response time differences of multiple process variables within this time window and the failure coefficient, determine the execution delay index. The calculation formula is: ; in, To implement the delay index, The number of multiple process variables, For the first One process variable, The failure coefficient for executing instructions on the target device. The mean response time for each process variable. The preset duration average for each process variable.

[0043] Instruction No. The mean response time of the first process variable and the second process variable The absolute difference between the preset mean values ​​of each process variable reflects the time delay between when the equipment receives the instruction and when it should be completed and when it is actually completed. This is a quantifiable objective lag phenomenon. This indicates the unreliability of instruction execution, reflecting a decreased probability that instructions are correctly parsed, transmitted, and executed during the device's operation; in other words, there is potential instability. When both hysteresis and latency coexist and trend in the same direction, it can be inferred that the hysteresis is not random noise, but rather caused by a systemic problem in the device's execution mechanism or transmission link. The larger the value, the greater the execution latency index in the current access control phase.

[0044] S13. Determine the impact index of instruction delay execution on process variables based on the correlation between multiple execution delay indices of multiple time windows and the change characteristic values ​​of multiple process variables.

[0045] The control of the target equipment is highly dependent on real-time response. If the execution is delayed, the changes in process variables will be out of sync with the target trajectory in time or overshoot in amplitude, which can directly reflect the effect of the control command at the equipment execution layer.

[0046] In one embodiment, the impact index of instruction delay execution on process variables is determined based on the correlation between multiple execution delay indices across multiple time windows and the change characteristic values ​​of multiple process variables, including: A coordinate system is established with the time sequence of multiple time windows as the horizontal axis and the multiple execution delay indices corresponding to the multiple time windows as the vertical axis. Polynomial curve fitting is performed on each data point in the coordinate system and the vertical axis is normalized to obtain the execution curve. An independent coordinate system is established for each process variable, with the time sequence number of multiple time windows as the horizontal axis and the variance of multiple sampled values ​​of the process variable within each time window as the vertical axis. Polynomial curve fitting is performed on each data point in the coordinate system and the vertical axis is normalized to obtain each change characteristic curve corresponding to each process variable; each time window corresponds to multiple sampled values ​​of each process variable. The mean square error between multiple characteristic curves and the execution delay index curve is calculated separately, and the average of the obtained mean square errors is calculated to obtain the impact index of instruction delay execution on process variables; multiple process variables correspond one-to-one with multiple characteristic curves.

[0047] Multiple time windows include the aforementioned time windows for collecting multiple round-trip delays and multiple response delays, as well as at least one forward time window and / or at least one backward time window that are continuous on the time axis and have the same window length. The windows are either connected end-to-end or partially overlap. A coordinate system is established with the time sequence of the multiple time windows as the horizontal axis and the multiple execution delay indices corresponding to the multiple time windows as the vertical axis. Polynomial curve fitting is performed on each data point in the coordinate system, and the vertical axis is normalized to obtain the execution curve.

[0048] An independent coordinate system is established for each process variable, with the time sequence number of multiple time windows as the x-axis (i.e., the multiple time windows are sorted chronologically), and the sequence number of the multiple time windows as the x-axis. The variance of the multiple sampled values ​​of the process variable within each time window is the y-axis. Polynomial curve fitting is performed on each data point in the coordinate system, and the y-axis is normalized to obtain each characteristic curve corresponding to each process variable. The x-axis coordinates of the multiple process variables in the coordinate system are all one-to-one. In other words, each time window corresponds to multiple sampled values ​​of each process variable, and the variance of the multiple sampled values ​​of the process variable within the same time window can be calculated to obtain the y-axis value corresponding to the x-axis of that time window.

[0049] Map each characteristic curve and execution curve corresponding to each process variable to the same coordinate system, and calculate their mean square error. A smaller mean square error indicates that the variation of this process variable may fluctuate more significantly with increasing execution delay, suggesting a decreasing trend in system stability. Calculate the mean square error between multiple characteristic curves and the execution delay exponential curve, and average the obtained mean square errors to obtain the impact index of instruction delay execution on the process variable. The calculation formula is: ; in, This is an index representing the impact of instruction delay execution on process variables. The number of multiple process variables, For the first One process variable, To implement the delay index, For the first The mean squared error (MSE) between the characteristic curves of process variables and the execution curve. The MSE is a statistical correlation between changes in execution delay and the fluctuation trend of process variables; the correlation indicates the strength of the driving force of delay changes on the dynamic shift of process variables in the past. This represents the execution latency index during the current time window access control phase. The larger the value, the more sensitive the current delay is to the historical average impact on process variables.

[0050] The above steps, through the impact of execution delay in the access control process on process variables, illustrate that execution delay may cause dynamic shifts in process variables during the execution cycle. However, in the access control process of Internet servers, the executed instructions are often not independent, but rather have dependencies or parallel competition. When the impact of delay is high, the dependency relationship between instructions is more likely to cause system response instability.

[0051] S14. Calculate the risk coupling coefficient corresponding to the instruction sequence based on the delay difference between each adjacent instruction in the instruction sequence.

[0052] The delay of each instruction is obtained by calculating the deviation between the response time of multiple process variables to the same instruction and the corresponding preset time; the instruction sequence includes multiple instructions within multiple time windows.

[0053] The main purpose of this step is to analyze the impact of dependencies between multiple instructions on the access control system. In scenarios with multiple control links, latency is often not an isolated risk but rather propagates along the dependency chain, and the risk coupling of the instruction sequence can quantify this propagation capability. Therefore, in one embodiment, the risk coupling coefficient corresponding to the instruction sequence is calculated based on the latency difference between each adjacent instruction in the instruction sequence, including: The delay coefficient of each instruction is obtained by calculating the difference between the average response time of the multiple process variables controlled by each instruction and the average preset time of the multiple process variables controlled by each instruction. The risk coupling coefficient corresponding to the instruction sequence is calculated based on the difference in the delay coefficient of each adjacent instruction in the instruction sequence.

[0054] In the current access control process, the average response time of multiple process variables controlled by each instruction is calculated. Then, based on each preset time corresponding to each process variable controlled by each instruction, the average of multiple preset times corresponding to multiple process variables controlled by each instruction is calculated. The difference between the average response time of multiple process variables controlled by each instruction and the average of multiple preset times corresponding to multiple process variables controlled by each instruction is obtained, which is the latency coefficient of each instruction. .

[0055] In one embodiment, the risk coupling coefficient corresponding to the instruction sequence is calculated based on the difference in latency coefficients between each adjacent instruction in the instruction sequence, including: The ratio of the delay factors of adjacent instructions is calculated based on the ratio of the delay factor of the target instruction to the delay factor of the instruction preceding the target instruction; the target instruction is any instruction in the instruction sequence. The risk coupling coefficient corresponding to the instruction sequence is determined by averaging the ratios of the delay coefficients of all adjacent instructions in the instruction sequence.

[0056] In an access control system, instructions are executed in a fixed order. The execution of each subsequent instruction depends on the resources released by the preceding instructions (CPU, network bandwidth, database locks, etc.). If the delay of a preceding instruction increases, it will occupy resources for a longer period, causing the start time of the next instruction to be postponed. If this postponement continues to propagate among multiple instructions, the delay will gradually accumulate. The risk coupling coefficient of the instruction sequence in the current access control phase can be calculated, and the risk coupling coefficient corresponding to the instruction sequence can be determined. The calculation formula is: ; in, This represents the risk coupling coefficient corresponding to the instruction sequence. The number of instructions. For the first One instruction, For the first The latency factor of each instruction. For the first The latency factor of each instruction. A larger value indicates that the instruction latency is continuously increasing, meaning that the risk coupling coefficient of the instruction sequence is greater.

[0057] The gradual accumulation of delays is the most intuitive external manifestation of the risk coupling mechanism of instruction sequences. It reflects the continuous amplification of subsequent delays by preceding delays. Behind this is the physical mechanism of resource occupation, queue backlog, or retry amplification. Once the accumulation trend is formed, it will increase the instability of the access control system, which means that it is necessary to perform single-end batch processing, adjust scheduling, or change dynamic permissions and degrade services in advance.

[0058] S15. Adjust the number of server access commands based on the impact index and the risk coupling coefficient.

[0059] In one embodiment, adjusting the number of server access commands based on the impact index and the risk coupling coefficient includes: The server access adjustment coefficient is obtained by multiplying the impact index and the risk coupling coefficient. The number of access commands to the server is adjusted based on the server's access adjustment factor.

[0060] The purpose of this step is to address the need for dynamic permission adjustments in the access control process of industrial internet servers by combining the coupling risks of instruction sequences and the impact of execution latency on the dynamic offset of process variables during the aforementioned access control process. Considering only the risk coupling coefficient confirms that latency accumulates, but it's uncertain whether latency truly has a significant impact on process variables. Conversely, considering only the dynamic offset response of execution latency to process variables confirms that latency leads to process fluctuations, but it's uncertain whether these fluctuations are accidental or will be continuously amplified.

[0061] Therefore, the server access adjustment coefficient can be obtained by multiplying the impact index and the risk coupling coefficient. The calculation formula is: ;in, Adjustment factor for access, For normalization function, This represents the risk coupling coefficient corresponding to the instruction sequence. This is an index representing the impact of instruction delay execution on process variables. A larger access adjustment coefficient indicates a higher risk of system instability during access control, meaning that the maximum number of access instructions allowed per instance needs adjustment.

[0062] In one embodiment, adjusting the number of access commands to the server based on the server's access adjustment coefficient includes: The batch adjustment value is obtained by summing the preset value and the access adjustment coefficient; The number of access commands to the server is adjusted based on the product of the absolute difference between the first threshold and the second threshold and the batch adjustment value, plus the second threshold. The first threshold indicates the maximum number of batch commands preset by the server, and the second threshold indicates the minimum number of batch commands preset by the server.

[0063] The first and second thresholds can be set according to the actual situation, and the preset value can be 1.

[0064] If the server's preset maximum batch instruction count is That is, the maximum number of batch commands allowed in the Internet server access control process is The server's preset minimum batch instruction count is The maximum number of batch instructions is given to the server when the risk coupling coefficient is 0, and the minimum number of batch instructions is given when the risk coupling coefficient is 1. The number of batch instructions decreases linearly when the risk coupling coefficient is between (0, 1). The specific steps for adjusting the maximum number of batch instructions allowed during access control are as follows: Where ⌊.⌋ is the floor function. Number of access commands The minimum batch instruction count preset for the server. The maximum number of batch instructions preset for the server. Adjustment factor for access.

[0065] When the risk coupling coefficient increases, i.e., the risk increases, the batch limit is automatically tightened to effectively suppress the cascading amplification risk of instruction delays and process variable fluctuations. When the risk coupling coefficient decreases, i.e., the risk decreases, higher batch operation capabilities are gradually restored to improve production efficiency and network utilization. A minimum time interval and continuous stability judgment rules are set for adjusting the batch instruction count to ensure that the maximum newly calculated batch instruction count is only truly triggered when it remains consistent across multiple consecutive samples (e.g., 3 times) or continuously exceeds a preset threshold. The preset threshold is set automatically based on actual conditions. A hysteresis mechanism is also employed to avoid frequent adjustments to the batch instruction count due to fluctuations near the critical value, thereby improving system stability and the continuity of the access control policy.

[0066] This application integrates the stability of round-trip delay and the distribution characteristics of response delay to calculate a failure coefficient, quantifying the risk of command misordering or retransmission caused by momentary network link instability. It compares the deviation of the response time of each process variable to multiple commands from the theoretical value, and then superimposes the failure coefficient to obtain an execution delay index, directly reflecting the execution lag of the target equipment. It statistically analyzes the correlation between the execution delay index and the characteristic values ​​of process variable changes across multiple time windows to generate an impact index, used to measure the amplification effect of command delay on process fluctuations. The delay difference between adjacent commands is calculated sequentially along the command sequence, and the risk coupling coefficient is accumulated to characterize the cascading amplification trend of delay among multiple commands. Based on the impact index and the risk coupling coefficient, the number of access commands to the server is adjusted, effectively suppressing the cascading amplification risk of command delay and process variable fluctuations, ensuring the stability and reliability of the industrial internet access control system.

[0067] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0068] This application also provides an access control system for an industrial internet server, such as... Figure 2 As shown, the system includes: Analysis module 21 is used to analyze multiple round-trip delays and multiple response delays to obtain the failure coefficient of the target device's execution instructions; the round-trip delay indicates the time from when the server sends a test data packet to the target device to when it receives its response data packet, and the response delay indicates the time from when the server sends an instruction to the target device to when it receives its corresponding service confirmation. The first determining module 22 is used to determine the execution delay index based on the deviation between the response time of each process variable of the target equipment to multiple instructions within the same time window and the corresponding preset time, and the failure coefficient. The second determining module 23 is used to determine the impact index of instruction delay execution on process variables based on the correlation between multiple execution delay indices of multiple time windows and the change characteristic values ​​of multiple process variables; The calculation module 24 is used to calculate the risk coupling coefficient corresponding to the instruction sequence based on the delay difference of each adjacent instruction in the instruction sequence; the delay of each instruction is obtained by calculating the deviation between the response time of multiple process variables for the same instruction and the corresponding preset time; the instruction sequence includes multiple instructions within multiple time windows; The adjustment module 25 is used to adjust the number of access commands to the server based on the impact index and the risk coupling coefficient.

[0069] For the system embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs.

[0070] Figure 3 This is a schematic diagram of the structure of an electronic device according to an example embodiment of this application. The electronic device includes a memory, a processor, and a computer program stored in the memory and used to run on the processor. When the processor executes the computer program, it implements the method described in any of the above embodiments. Figure 3 The electronic device 30 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0071] like Figure 3 As shown, the electronic device 30 can be manifested as a general-purpose computing device, such as a server device. The components of the electronic device 30 may include, but are not limited to: at least one processor 31, at least one memory 32, and a bus 33 connecting different system components (including memory 32 and processor 31).

[0072] Bus 33 includes a data bus, an address bus, and a control bus.

[0073] The memory 32 may include volatile memory, such as random access memory (RAM) 321 and / or cache memory 322, and may further include read-only memory (ROM) 323.

[0074] The memory 32 may also include a program tool 325 (or utility) having a set (at least one) program module 324, such program module 324 including but not limited to: an operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0075] The processor 31 executes various functional applications and data processing, such as the methods provided in any of the above embodiments, by running computer programs stored in the memory 32.

[0076] Electronic device 30 can also communicate with one or more external devices 34 (e.g., keyboard, pointing device, etc.). This communication can be performed via input / output (I / O) interface 35. Furthermore, electronic device 30 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public network, such as the Internet) via network adapter 36. As shown, network adapter 36 communicates with other modules of electronic device 30 via bus 33. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with electronic device 30, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems.

[0077] It should be noted that although several units / modules or sub-units / modules of the electronic device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0078] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method provided in any of the above embodiments.

[0079] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0080] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0081] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the method described in any of the above embodiments.

[0082] The program code for executing the computer program product of this application can be written in any combination of one or more programming languages. The program code can be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on a remote device.

[0083] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0084] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these modifications and improvements all fall within the protection scope of this application.

[0085] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. An access control method for an industrial internet server, characterized in that, The method includes: Analyze multiple round-trip delays and multiple response delays to obtain the failure coefficient of the target device's execution instructions; the round-trip delay indicates the time from when the server sends a test data packet to the target device to when it receives its response data packet, and the response delay indicates the time from when the server sends an instruction to the target device to when it receives its corresponding service confirmation response; The execution delay index is determined based on the deviation between the response time of each process variable of the target equipment to multiple instructions within the same time window and the corresponding preset time, and the failure coefficient. The impact index of instruction delay execution on process variables is determined based on the correlation between multiple execution delay indices across multiple time windows and the change characteristic values ​​of multiple process variables. The risk coupling coefficient corresponding to the instruction sequence is calculated based on the delay difference of each adjacent instruction in the instruction sequence; the delay of each instruction is obtained by calculating the deviation between the response time of multiple process variables for the same instruction and the corresponding preset time; the instruction sequence includes multiple instructions within multiple time windows; The number of access commands to the server is adjusted based on the impact index and the risk coupling coefficient.

2. The access control method for an industrial internet server as described in claim 1, characterized in that, The analysis of multiple round-trip delays and multiple response delays to obtain the failure coefficient of the target device's executed commands includes: Collect multiple round-trip delays and multiple response delays within the same time window; A coordinate system is established with multiple acquisition times within a time window as the horizontal axis and multiple round-trip delays as the vertical axis. Linear interpolation is performed on each data point in the coordinate system to obtain a round-trip delay polygon. The slope value between all adjacent data points in the round-trip delay polygon is calculated. Multiple acquisition times correspond one-to-one with multiple round-trip delays. The link degradation index is determined based on the range of round-trip delay within the time window and the absolute difference between each adjacent slope value. By analyzing the link degradation index and multiple response delays, the failure coefficient of the target device's execution commands is obtained.

3. The access control method for an industrial internet server as described in claim 2, characterized in that, The analysis of the link degradation index and multiple response delays yields the failure coefficient of the target device's executed commands, including: Obtain the time of issuance of each command sent by the server to the target device within the same time window, the response delay of the command, and the identification information of the command; For each instruction, in response to retrieving the corresponding service confirmation response within the same time window based on the instruction's identification information, the duration between the instruction's issuance time and the corresponding service confirmation response is determined as the target response delay. The failure coefficient is determined based on the standard deviation of multiple target response delays, the mean of multiple target response delays, and the link degradation index.

4. The access control method for an industrial internet server as described in claim 1, characterized in that, The step of determining the execution delay index based on the deviation between the response time of each process variable of the target equipment to multiple instructions within the same time window and the corresponding preset time, and the failure coefficient, includes: For each process variable, the average response time of each process variable to multiple instructions within the same time window is calculated to obtain the average response time of each process variable. The average of multiple preset times of each process variable to multiple instructions is also calculated to obtain the average preset time of each process variable. Each instruction corresponds to a preset time for each process variable it regulates. The response time indicates the time required for multiple process variables of the target device to change from the initial state to the target state after the target device receives each instruction. Calculate the difference between the average response time of each process variable and the corresponding preset average response time to obtain the response time difference; The execution delay index is determined based on the differences in response durations and failure coefficients within each time window; the differences in response durations correspond one-to-one with multiple process variables.

5. The access control method for an industrial internet server as described in claim 1, characterized in that, The step of determining the impact index of instruction delay execution on process variables based on the correlation between multiple execution delay indices across multiple time windows and the change characteristic values ​​of multiple process variables includes: A coordinate system is established with the time sequence of multiple time windows as the horizontal axis and the multiple execution delay indices corresponding to the multiple time windows as the vertical axis. Polynomial curve fitting is performed on each data point in the coordinate system and the vertical axis is normalized to obtain the execution curve. An independent coordinate system is established for each process variable, with the time sequence number of multiple time windows as the horizontal axis and the variance of multiple sampled values ​​of the process variable within each time window as the vertical axis. Polynomial curve fitting is performed on each data point in the coordinate system and the vertical axis is normalized to obtain each change characteristic curve corresponding to each process variable; each time window corresponds to multiple sampled values ​​of each process variable. The mean square error between multiple characteristic curves and the execution delay index curve is calculated separately, and the average of the obtained mean square errors is calculated to obtain the impact index of instruction delay execution on process variables; multiple process variables correspond one-to-one with multiple characteristic curves.

6. The access control method for an industrial internet server as described in claim 4, characterized in that, The step of calculating the risk coupling coefficient corresponding to the instruction sequence based on the latency difference of each adjacent instruction in the instruction sequence includes: The delay coefficient of each instruction is obtained by calculating the difference between the average response time of the multiple process variables controlled by each instruction and the average preset time of the multiple process variables controlled by each instruction. The risk coupling coefficient corresponding to the instruction sequence is calculated based on the difference in the delay coefficient of each adjacent instruction in the instruction sequence.

7. The access control method for an industrial internet server as described in claim 6, characterized in that, The step of calculating the risk coupling coefficient corresponding to the instruction sequence based on the difference in latency coefficients of each adjacent instruction in the instruction sequence includes: The ratio of the delay factors of adjacent instructions is calculated based on the ratio of the delay factor of the target instruction to the delay factor of the instruction preceding the target instruction; the target instruction is any instruction in the instruction sequence. The risk coupling coefficient corresponding to the instruction sequence is determined by averaging the ratios of the delay coefficients of all adjacent instructions in the instruction sequence.

8. The access control method for an industrial internet server as described in claim 1, characterized in that, The adjustment of the number of server access commands based on the impact index and the risk coupling coefficient includes: The server access adjustment coefficient is obtained by multiplying the impact index and the risk coupling coefficient. The number of access commands to the server is adjusted based on the server's access adjustment factor.

9. The access control method for an industrial internet server as described in claim 8, characterized in that, The adjustment of the number of access commands to the server based on the server's access adjustment coefficient includes: The batch adjustment value is obtained by summing the preset value and the access adjustment coefficient; The number of access commands to the server is adjusted based on the product of the absolute difference between the first threshold and the second threshold and the batch adjustment value, plus the second threshold. The first threshold indicates the maximum number of batch commands preset by the server, and the second threshold indicates the minimum number of batch commands preset by the server.

10. An access control system for an industrial internet server, characterized in that, The system includes: The analysis module is used to analyze multiple round-trip delays and multiple response delays to obtain the failure coefficient of the target device's execution instructions; the round-trip delay indicates the time from when the server sends a test data packet to the target device to when it receives its response data packet, and the response delay indicates the time from when the server sends an instruction to the target device to when it receives its corresponding service confirmation; The first determining module is used to determine the execution delay index based on the deviation between the response time of each process variable of the target equipment to multiple instructions within the same time window and the corresponding preset time, and the failure coefficient. The second determining module is used to determine the impact index of instruction delay execution on process variables based on the correlation between multiple execution delay indices of multiple time windows and the change characteristic values ​​of multiple process variables; The calculation module is used to calculate the risk coupling coefficient corresponding to the instruction sequence based on the delay difference of each adjacent instruction in the instruction sequence; the delay of each instruction is obtained by calculating the deviation between the response time of multiple process variables for the same instruction and the corresponding preset time; the instruction sequence includes multiple instructions within multiple time windows; The adjustment module is used to adjust the number of access commands to the server based on the impact index and the risk coupling coefficient.

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