Resource management method and embedded operating system for industrial control

Abstract

The present invention relates to the technical field of resource data processing, and discloses a resource management method and embedded operating system for industrial control. The method collects system resource information and received industrial control information in real time from the embedded operating system, constructs a system model, analyzes and processes the received industrial control information through data processing, and constructs an industrial control information execution queue based on the processed industrial control information. After the execution queue is constructed, a scheduling algorithm of the embedded operating system is set, and the constructed industrial control information execution queue is calculated and adjusted based on the set scheduling algorithm. Finally, real-time adjustments are made by monitoring the industrial control information collected from the embedded operating system in real time, thereby improving the real-time performance of resource management.

Description

Technical Field

[0001] The present invention relates to the technical field of resource data processing, and in particular to a resource management method and an embedded operating system for industrial control. Background Art

[0002] Currently, in terms of computing resource management, most resource scheduling management methods are static scheduling. However, static scheduling algorithms are prone to cause problems such as uneven allocation of computer resources, long waiting times for computer tasks, and resource scheduling deadlocks, resulting in waste of computer resource management.

[0003] The existing patent application CN115562838A is publicly available. This invention collects shared resources and threads in the system in real time. If there are multiple threads currently waiting to call a target shared resource in an occupied state, the number of call instructions for each thread in the multiple threads to call the target shared resource is obtained; and the multiple threads are sorted according to the number of instructions corresponding to each thread to obtain a waiting thread queue; if the target shared resource changes from an occupied state to a non-occupied state, each thread is controlled to call the target shared resource in turn according to the queue order of the threads in the waiting thread queue. However, since the execution is sorted only by the number of instructions corresponding to each thread, the correlation between tasks and the system call time and thread time are ignored, resulting in an inability to stably improve system resource utilization, which has great limitations. Summary of the Invention

[0004] (1) Technical problems solved

[0005] In response to the shortcomings of the existing technology, the present invention provides a resource management method and embedded operating system for industrial control, which has the advantages of accuracy, real-time and high efficiency, and solves the problems of uneven distribution of computer resources and long waiting time for computer tasks.

[0006] (2) Technical solution

[0007] In order to solve the above-mentioned technical problems of unbalanced allocation of computer resources and long waiting time for computer tasks, the present invention provides the following technical solutions:

[0008] The present invention discloses a resource management method for industrial control, which specifically includes the following steps:

[0009] S1, real-time collection of system resource information in the embedded operating system and received industrial control information, and building a system model based on the collected system resource information;

[0010] S2. Analyze and process the received industrial control information through a data processing method to obtain processed industrial control information;

[0011] S3. Building an industrial control information execution queue based on the processed industrial control information;

[0012] S4. Setting a scheduling algorithm of the embedded operating system, and calculating and adjusting the constructed industrial control information execution queue based on the set scheduling algorithm, and outputting a determined industrial control information adjustment queue;

[0013] S5. Execute the output determined industrial control information adjustment queue, and monitor the industrial control information collected in the embedded operating system in real time. If an emergency occurs, recalculate the industrial control information adjustment queue.

[0014] The present invention collects system resource information and received industrial control information in an embedded operating system in real time and constructs a system model. At the same time, the received industrial control information is analyzed and processed by a data processing method, and an industrial control information execution queue is constructed based on the processed industrial control information. After the execution queue is constructed, a scheduling algorithm of the embedded operating system is set, and the constructed industrial control information execution queue is calculated and adjusted based on the set scheduling algorithm. Finally, real-time adjustments are made by real-time monitoring of the industrial control information collected in the embedded operating system, thereby improving the real-time performance of resource management.

[0015] Preferably, the real-time collection of system resource information in the embedded operating system and the received industrial control information, and the construction of a system model based on the collected system resource information includes the following steps:

[0016] System resource information includes: embedded operating system computing core and computing power resources;

[0017] Industrial control information includes: data access information, data analysis information, and data control information;

[0018] The system model is constructed as follows:

[0019] SM={P,S};

[0020] Where P={P0,P1,…,P i ,…,P n-1}, P represents the set of n embedded operating system computing cores, P i represents the computing core of the i-th embedded operating system, S={S 1,2 ,S 1,3 ,…,S i,n-1}, S represents the communication rate between the computing cores of the embedded operating system, S i,n-1 It represents the communication rate between the i-th embedded operating system computing core and the n-1-th embedded operating system computing core.

[0021] The present invention collects system resource information and received industrial control information in an embedded operating system in real time, and constructs a system model based on the system resource information and the communication rate between the embedded operating system computing cores, thereby improving the accuracy of resource management calculations.

[0022] Preferably, the step of analyzing and processing the received industrial control information by data processing to obtain the processed industrial control information comprises the following steps:

[0023] S21. Setting a corresponding instruction code according to the type of industrial control information;

[0024] S22, converting the received industrial control information into binary data, matching the converted binary data with a set instruction code, and classifying the currently received industrial control information based on the matching result;

[0025] S23. Set the classified industrial control information as processed industrial control information.

[0026] The present invention realizes classification of received industrial control information by setting instruction codes and matching the set instruction codes with converted binary data, thereby improving the accuracy of industrial control information classification.

[0027] Preferably, the step of constructing an industrial control information execution queue based on the processed industrial control information includes the following steps:

[0028] S31. Setting the processing priority of various types of industrial control information in the processed industrial control information;

[0029] S32. Construct an industrial control information execution queue based on the set processing priorities of various types of industrial control information and the received processed industrial control information.

[0030] Preferably, the step of setting the processing priority of each type of industrial control information in the processed industrial control information comprises the following steps:

[0031] A set of industrial control information execution processes includes: embedded operating system computing core processing and I / O operations;

[0032] The computing core processing of embedded operating systems includes: instruction fetch cycle, execution cycle, and interrupt cycle;

[0033] However, since data access information in various types of industrial control information does not perform I / O operations, data control information needs to provide feedback after performing I / O operations, which takes a longer period than data analysis information;

[0034] It is assumed that when data access information, data control information, and data analysis information are received at the same time, the data control information has the highest priority and the data access information has the lowest priority.

[0035] Preferably, the step of constructing an industrial control information execution queue based on the set processing priorities of various types of industrial control information and the received processed industrial control information includes the following steps:

[0036] Calculate average completion time and communication time;

[0037] The average completion time is calculated as follows:

[0038] ;

[0039] Among them, W j represents the average completion time of the jth industrial control information in the embedded operating system computing core P, w j,i represents the weight of the jth industrial control information on the i-th embedded operating system computing core;

[0040] Calculating Communication Time The communication time is as follows:

[0041] ;

[0042] Among them, L represents the average response time of the embedded operating system computing core, data j,k represents the data transmission volume from the jth industrial control information to the kth industrial control information, B represents the data transmission rate, C j,k represents the time cost of transmitting the j-th industrial control information to the k-th industrial control information;

[0043] Set the pre-task and post-task. When the second set of industrial control information requires the first set of industrial control information data, the pre-task is executed first and the post-task is executed later. When the pre-task and post-task are executed on the same embedded operating system computing core, the communication time is 0.

[0044] The final completion time of each group of processed industrial control information is collected, and an industrial control information execution queue is constructed based on the calculated average completion time, communication time, reception time of each group of industrial control information, and the predecessor and successor tasks in the industrial control information.

[0045] The present invention sets the processing priority of various types of industrial control information in the processed industrial control information, calculates the average completion time and communication time at the same time, and finally collects the final completion time of each group of processed industrial control information. Based on the calculation results, the industrial control information execution queue is constructed, thereby improving the reliability of the construction of the industrial control information execution queue.

[0046] Preferably, the step of setting a scheduling algorithm of the embedded operating system, calculating and adjusting the constructed industrial control information execution queue based on the set scheduling algorithm, and outputting the determined industrial control information adjustment queue comprises the following steps:

[0047] S41, enabling saturation scheduling calculation, assigning a unique embedded operating system computing core to perform separate calculations for each group of processed industrial control information in the industrial control information execution queue, and obtaining a saturation scheduling set for the industrial control information execution queue;

[0048] S42. Summarize the saturated schedule set in S41, merge any two schedules in the saturated schedule set, calculate the new schedule formed by the merger, determine the savings value of the new schedule compared to the sum of the schedules before the merger, and sort the savings values ​​in descending order;

[0049] Since a set of industrial control information execution processes include: embedded operating system computing core processing and I / O operations;

[0050] When the first set of industrial control information performs an I / O operation, the embedded operating system executes the second set of industrial control information during an idle period of the computing core;

[0051] Savings = total scheduling cost before the merger - total new scheduling cost after the merger;

[0052] S43. Based on the final completion time of each group of processed industrial control information, analyze whether the two groups of schedules that can be merged meet the final completion time of each group of processed industrial control information. If the completion time of the merged new schedule meets the final completion time, merge the two groups of schedules into a new schedule and execute S44. If not, cancel the merge and repeat S43.

[0053] S44, initializing the population;

[0054] Set the new scheduling set after aggregation to {1,2,…,h}, where h represents the hth group of scheduling, and each group of chromosome encoding represents a group of industrial control information execution data. Set the population size and the maximum number of iterations d max ;

[0055] S45, establishing a fitness function;

[0056] The fitness function is set as follows:

[0057] ;

[0058] Among them, Fit(x) represents the fitness of the xth group of industrial control information execution data in the initialized population, and F represents the total scheduling cost;

[0059] S46. selecting a genetic operator based on the established fitness function;

[0060] S47, performing chromosome crossover on the selected genetic operator;

[0061] Randomly select crossover points in the selected genetic operator, perform pairwise crossover by sequential crossover and generate a new pair of chromosome codes;

[0062] The generated new chromosome code is also used as a schedule to participate in the iteration;

[0063] S48, iteratively execute steps S44-S47 until the maximum number of iterations d is reached max , output industrial control information adjustment queue.

[0064] Preferably, the selecting of the genetic operator based on the established fitness function comprises the following steps:

[0065] ,x=1,2,3,…,X;

[0066] Where X represents the population size, and Y(x) represents the probability of the x-th group of industrial control information execution data being selected in the initialized population.

[0067] The present invention obtains a saturated scheduling set of an industrial control information execution queue by enabling saturated scheduling calculation, updates the industrial control information execution queue by calculating a saving value, and iteratively calculates the updated industrial control information execution queue through a genetic algorithm to further determine the industrial control information adjustment queue, thereby improving the efficiency of industrial control information resource management.

[0068] Preferably, the step of executing the output determined industrial control information adjustment queue and monitoring the industrial control information collected in the embedded operating system in real time, and recalculating the industrial control information adjustment queue if an emergency occurs, comprises the following steps:

[0069] When the embedded operating system is executing the process of adjusting the queue of industrial control information, an urgent request is received;

[0070] The embedded operating system suspends and saves industrial control information and executes emergency requests;

[0071] When the emergency request is completed, the suspended industrial control information is continued to be executed, and the subsequent industrial control information adjustment queue is recalculated.

[0072] The present invention also discloses an embedded real-time operating system for industrial control, which is used to implement a resource management method for industrial control. The system includes: a data acquisition module, a data analysis and processing module, an execution queue construction module, and an execution queue adjustment module;

[0073] The data acquisition module is used to collect system resource information in the embedded operating system and received industrial control information in real time;

[0074] The data analysis and processing module is used to analyze and process the received industrial control information through data processing;

[0075] The execution queue construction module is used to construct an industrial control information execution queue according to the processed industrial control information;

[0076] The execution queue adjustment module is used to set the scheduling algorithm of the embedded operating system and adjust the constructed industrial control information execution queue in real time according to the scheduling algorithm.

[0077] (3) Beneficial effects

[0078] Compared with the prior art, the present invention provides a resource management method and embedded operating system for industrial control, which has the following beneficial effects:

[0079] 1. The invention collects system resource information and received industrial control information in an embedded operating system in real time and builds a system model. At the same time, the received industrial control information is analyzed and processed through data processing, and an industrial control information execution queue is constructed based on the processed industrial control information. After the execution queue is constructed, the scheduling algorithm of the embedded operating system is set, and the constructed industrial control information execution queue is calculated and adjusted based on the set scheduling algorithm. Finally, real-time adjustments are made by real-time monitoring of the industrial control information collected in the embedded operating system, thereby improving the real-time performance of resource management.

[0080] 2. This invention improves the accuracy of resource management calculations by collecting system resource information and received industrial control information in the embedded operating system in real time, and building a system model based on the system resource information and the communication rate between the embedded operating system computing cores.

[0081] 3. The invention achieves classification of received industrial control information by setting instruction codes and matching the set instruction codes with converted binary data, thereby improving the accuracy of industrial control information classification.

[0082] 4. The invention sets the processing priority of various types of industrial control information in the processed industrial control information, calculates the average completion time and communication time at the same time, and finally collects the final completion time of each group of processed industrial control information, and constructs an industrial control information execution queue based on the calculation results, thereby improving the reliability of the construction of the industrial control information execution queue.

[0083] 5. This invention obtains the saturated scheduling set of the industrial control information execution queue by enabling saturated scheduling calculation, updates the industrial control information execution queue by calculating the saving value, and iteratively calculates the updated industrial control information execution queue through a genetic algorithm to further determine the industrial control information adjustment queue, thereby improving the efficiency of industrial control information resource management. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 It is a schematic diagram of the resource management process structure of the embedded real-time operating system of the present invention. DETAILED DESCRIPTION

[0085] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0086] Example 1

[0087] See also Figure 1 This embodiment discloses a resource management method for industrial control, which specifically includes the following steps:

[0088] S1, real-time collection of system resource information in the embedded operating system and received industrial control information, and building a system model based on the collected system resource information;

[0089] S2. Analyze and process the received industrial control information through a data processing method to obtain processed industrial control information;

[0090] S3. Building an industrial control information execution queue based on the processed industrial control information;

[0091] S4. Setting a scheduling algorithm of the embedded operating system, and calculating and adjusting the constructed industrial control information execution queue based on the set scheduling algorithm, and outputting a determined industrial control information adjustment queue;

[0092] S5. Execute the output determined industrial control information adjustment queue, and monitor the industrial control information collected in the embedded operating system in real time. If an emergency occurs, recalculate the industrial control information adjustment queue.

[0093] Further, see Figure 1 ,real-time collection of system resource information in the embedded operating system and the received industrial control information, and building a system model based on the collected system resource information includes the following steps:

[0094] System resource information includes: embedded operating system computing core and computing power resources;

[0095] Industrial control information includes: data access information, data analysis information, and data control information;

[0096] The system model is constructed as follows:

[0097] SM={P,S};

[0098] Where P={P0,P1,…,P i ,…,P n-1}, P represents the set of n embedded operating system computing cores, P i represents the computing core of the i-th embedded operating system, S={S 1,2 ,S 1,3 ,…,S i,n-1}, S represents the communication rate between the computing cores of the embedded operating system, S i,n-1 represents the communication rate between the i-th embedded operating system computing core and the n-1-th embedded operating system computing core;

[0099] Further, see Figure 1 , analyzing and processing the received industrial control information by data processing to obtain the processed industrial control information includes the following steps:

[0100] S21. Setting a corresponding instruction code according to the type of industrial control information;

[0101] S22, converting the received industrial control information into binary data, matching the converted binary data with a set instruction code, and classifying the currently received industrial control information based on the matching result;

[0102] S23, setting the classified industrial control information as processed industrial control information;

[0103] Further, see Figure 1 , constructing an industrial control information execution queue based on the processed industrial control information includes the following steps:

[0104] S31. Setting the processing priority of various types of industrial control information in the processed industrial control information;

[0105] A set of industrial control information execution processes includes: embedded operating system computing core processing and I / O operations;

[0106] Furthermore, the embedded operating system computing core processing includes: instruction fetch cycle, execution cycle, and interrupt cycle;

[0107] However, since data access information in various types of industrial control information does not perform I / O operations, data control information needs to provide feedback after performing I / O operations, which takes a longer period than data analysis information;

[0108] It is set that when data access information, data control information and data analysis information are received at the same time, data control information has the highest priority and data access information has the lowest priority;

[0109] S32. Building an industrial control information execution queue based on the set processing priorities of various types of industrial control information and the received processed industrial control information;

[0110] Calculate average completion time and communication time;

[0111] The average completion time is calculated as follows:

[0112] ;

[0113] Among them, W j represents the average completion time of the jth industrial control information in the embedded operating system computing core P, w j,i represents the weight of the jth industrial control information on the i-th embedded operating system computing core;

[0114] Calculating Communication Time The communication time is as follows:

[0115] ;

[0116] Among them, L represents the average response time of the embedded operating system computing core, data j,k represents the data transmission volume from the jth industrial control information to the kth industrial control information, B represents the data transmission rate, C j,k represents the time cost of transmitting the j-th industrial control information to the k-th industrial control information;

[0117] Set the pre-task and post-task. When the second set of industrial control information requires the first set of industrial control information data, the pre-task is executed first and the post-task is executed later. When the pre-task and post-task are executed on the same embedded operating system computing core, the communication time is 0.

[0118] Furthermore, the final completion time of each group of processed industrial control information is collected, and an industrial control information execution queue is constructed based on the calculated average completion time, communication time, reception time of each group of industrial control information, and the preceding and succeeding tasks in the industrial control information;

[0119] Further, see Figure 1, setting the scheduling algorithm of the embedded operating system, and calculating and adjusting the constructed industrial control information execution queue based on the set scheduling algorithm, and outputting the determined industrial control information adjustment queue includes the following steps:

[0120] S41, enabling saturation scheduling calculation, assigning a unique embedded operating system computing core to perform separate calculations for each group of processed industrial control information in the industrial control information execution queue, and obtaining a saturation scheduling set for the industrial control information execution queue;

[0121] S42. Summarize the saturated schedule set in S41, merge any two schedules in the saturated schedule set, calculate the new schedule formed by the merger, determine the savings value of the new schedule compared to the sum of the schedules before the merger, and sort the savings values ​​in descending order;

[0122] Since a set of industrial control information execution processes include: embedded operating system computing core processing and I / O operations;

[0123] When the first set of industrial control information performs an I / O operation, the embedded operating system executes the second set of industrial control information during an idle period of the computing core;

[0124] Savings = total scheduling cost before the merger - total new scheduling cost after the merger;

[0125] S43. Based on the final completion time of each group of processed industrial control information, analyze whether the two groups of schedules that can be merged meet the final completion time of each group of processed industrial control information. If the completion time of the merged new schedule meets the final completion time, merge the two groups of schedules into a new schedule and execute S44. If not, cancel the merge and repeat S43.

[0126] S44, initializing the population;

[0127] Set the new scheduling set after aggregation to {1,2,…,h}, where h represents the hth group of scheduling, and each group of chromosome encoding represents a group of industrial control information execution data. Set the population size and the maximum number of iterations d max ;

[0128] S45, establishing a fitness function;

[0129] The fitness function is set as follows:

[0130] ;

[0131] Among them, Fit(x) represents the fitness of the xth group of industrial control information execution data in the initialized population, and F represents the total scheduling cost;

[0132] S46. selecting a genetic operator based on the established fitness function;

[0133] By randomly selecting the genetic operator in a roulette wheel manner, the probability of each group of industrial control information execution data being selected is proportional to the fitness, and a group of industrial control information execution data with high fitness is selected;

[0134] The probability formula for the genetic operator to be selected is as follows:

[0135] ,x=1,2,3,…,X;

[0136] Where X represents the population size, and Y(x) represents the probability of the xth group of industrial control information execution data being selected in the initialized population;

[0137] S47, performing chromosome crossover on the selected genetic operator;

[0138] Randomly select crossover points in the selected genetic operator, perform pairwise crossover by sequential crossover and generate a new pair of chromosome codes;

[0139] The generated new chromosome code is also used as a schedule to participate in the iteration;

[0140] S48, iteratively execute steps S44-S47 until the maximum number of iterations d is reached max , output industrial control information adjustment queue;

[0141] Further, see Figure 1 , execute the output determined industrial control information adjustment queue, and monitor the industrial control information collected in the embedded operating system in real time, and recalculate the industrial control information adjustment queue if an emergency occurs;

[0142] When the embedded operating system is executing the process of adjusting the queue of industrial control information, an urgent request is received;

[0143] The embedded operating system suspends and saves industrial control information and executes emergency requests;

[0144] When the emergency request is completed, the suspended industrial control information is continued and the subsequent industrial control information adjustment queue is recalculated;

[0145] Example 2

[0146] See also Figure 1 ,This embodiment also discloses an embedded operating system for industrial control, which is used to implement a resource management method for industrial control.,The system includes: a data acquisition module, a data analysis and processing module, an execution queue construction module, and an execution queue adjustment module;

[0147] The data acquisition module is used to collect system resource information in the embedded operating system and received industrial control information in real time;

[0148] The data analysis and processing module is used to analyze and process the received industrial control information through data processing;

[0149] The execution queue construction module is used to construct an industrial control information execution queue according to the processed industrial control information;

[0150] The execution queue adjustment module is used to set the scheduling algorithm of the embedded operating system and adjust the constructed industrial control information execution queue in real time according to the scheduling algorithm.

[0151] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A resource management method for industrial control, characterized in that: The specific steps include: S1, real-time collection of system resource information in the embedded operating system and received industrial control information, and building a system model based on the collected system resource information; S2. Analyze and process the received industrial control information through a data processing method to obtain processed industrial control information; S3. Building an industrial control information execution queue based on the processed industrial control information; S4. Setting a scheduling algorithm of the embedded operating system, and calculating and adjusting the constructed industrial control information execution queue based on the set scheduling algorithm, and outputting a determined industrial control information adjustment queue; The S4 comprises the following steps: S41, enabling saturation scheduling calculation, assigning a unique embedded operating system computing core to perform separate calculations for each group of processed industrial control information in the industrial control information execution queue, and obtaining a saturation scheduling set for the industrial control information execution queue; S42. Summarize the saturated schedule set in S41, merge any two schedules in the saturated schedule set, calculate the new schedule formed by the merger, determine the savings value of the new schedule compared to the sum of the schedules before the merger, and sort the savings values ​​in descending order; S43. Based on the final completion time of each group of processed industrial control information, analyze whether the two groups of schedules that can be merged meet the final completion time of each group of processed industrial control information. If the completion time of the merged new schedule meets the final completion time, merge the two groups of schedules into a new schedule and execute S44. If not, cancel the merge and repeat S43. S44, initializing the population; Set the new scheduling set after aggregation to {1,2,…,h}, where h represents the hth group of scheduling, and each group of chromosome encoding represents a group of industrial control information execution data. Set the population size and the maximum number of iterations d max ; S45, establishing a fitness function; The fitness function is set as follows: ； Among them, Fit(x) represents the fitness of the xth group of industrial control information execution data in the initialized population, and F represents the total scheduling cost; S46. selecting a genetic operator based on the established fitness function; S47, performing chromosome crossover on the selected genetic operator; Randomly select crossover points in the selected genetic operator, perform pairwise crossover by sequential crossover and generate a new pair of chromosome codes; The generated new chromosome code is also used as a schedule to participate in the iteration; S48, iteratively execute steps S44-S47 until the maximum number of iterations d is reached max , output industrial control information adjustment queue; S5. Execute the output determined industrial control information adjustment queue, and monitor the industrial control information collected in the embedded operating system in real time. If an emergency occurs, recalculate the industrial control information adjustment queue.

2. A resource management method for industrial control according to claim 1, characterized in that: The real-time collection of system resource information in the embedded operating system and the received industrial control information, and the construction of a system model based on the collected system resource information includes the following steps: System resource information includes: embedded operating system computing core and computing power resources; Industrial control information includes: data access information, data analysis information, and data control information; The system model is constructed as follows: SM={P,S}; Where P={P0,P1,…,P i ,…,P n-1 }, P represents the set of n embedded operating system computing cores, P i represents the computing core of the i-th embedded operating system, S={S 1,2 ,S 1,3 ,…,S i,n-1 }, S represents the communication rate between the computing cores of the embedded operating system, S i,n-1 It represents the communication rate between the i-th embedded operating system computing core and the n-1-th embedded operating system computing core.

3. A resource management method for industrial control according to claim 1, characterized in that: The step of analyzing and processing the received industrial control information by means of data processing to obtain the processed industrial control information comprises the following steps: S21. Setting a corresponding instruction code according to the type of industrial control information; S22, converting the received industrial control information into binary data, matching the converted binary data with a set instruction code, and classifying the currently received industrial control information based on the matching result; S23. Set the classified industrial control information as processed industrial control information.

4. A resource management method for industrial control according to claim 1, characterized in that: The process of constructing an industrial control information execution queue based on the processed industrial control information includes the following steps: S31. Setting the processing priority of various types of industrial control information in the processed industrial control information; S32. Construct an industrial control information execution queue based on the set processing priorities of various types of industrial control information and the received processed industrial control information.

5. A resource management method for industrial control according to claim 4, characterized in that: The step of setting the processing priority of various types of industrial control information in the processed industrial control information comprises the following steps: A set of industrial control information execution processes includes: embedded operating system computing core processing and I / O operations; The computing core processing of embedded operating systems includes: instruction fetch cycle, execution cycle, and interrupt cycle; However, since data access information in various types of industrial control information does not perform I / O operations, data control information needs to provide feedback after performing I / O operations, which takes a longer period than data analysis information; It is assumed that when data access information, data control information, and data analysis information are received at the same time, the data control information has the highest priority and the data access information has the lowest priority.

6. A resource management method for industrial control according to claim 4, characterized in that: The process of constructing an industrial control information execution queue based on the set processing priorities of various types of industrial control information and the received processed industrial control information includes the following steps: Calculate average completion time and communication time; The average completion time is calculated as follows: ； Among them, W j represents the average completion time of the jth industrial control information in the embedded operating system computing core P, w j,i represents the weight of the jth industrial control information on the i-th embedded operating system computing core; The communication time is calculated as follows: ； Among them, L represents the average response time of the embedded operating system computing core, data j,k represents the data transmission volume from the jth industrial control information to the kth industrial control information, B represents the data transmission rate, C j,k represents the time cost of transmitting the j-th industrial control information to the k-th industrial control information; Set the pre-task and post-task. When the second set of industrial control information requires the first set of industrial control information data, the pre-task is executed first and the post-task is executed later. When the pre-task and post-task are executed on the same embedded operating system computing core, the communication time is 0. The final completion time of each group of processed industrial control information is collected, and an industrial control information execution queue is constructed based on the calculated average completion time, communication time, reception time of each group of industrial control information, and the predecessor and successor tasks in the industrial control information.

7. A resource management method for industrial control according to claim 1, characterized in that: The step of selecting a genetic operator based on the established fitness function comprises the following steps: ， ； Where X represents the population size, and Y(x) represents the probability of the x-th group of industrial control information execution data being selected in the initialized population.

8. The resource management method for industrial control according to claim 1, characterized in that: The step of executing the output determined industrial control information adjustment queue and monitoring the industrial control information collected in the embedded operating system in real time, and recalculating the industrial control information adjustment queue if an emergency occurs, comprises the following steps: When the embedded operating system is executing the process of adjusting the queue of industrial control information, an urgent request is received; The embedded operating system suspends and saves industrial control information and executes emergency requests; When the emergency request is completed, the suspended industrial control information is continued to be executed, and the subsequent industrial control information adjustment queue is recalculated.

9. An embedded operating system for implementing the resource management method for industrial control according to any one of claims 1 to 8, characterized in that: include: Data collection module, data analysis and processing module, execution queue construction module and execution queue adjustment module; The data acquisition module is used to collect system resource information in the embedded operating system and received industrial control information in real time; The data analysis and processing module is used to analyze and process the received industrial control information through data processing; The execution queue construction module is used to construct an industrial control information execution queue according to the processed industrial control information; The execution queue adjustment module is used to set the scheduling algorithm of the embedded operating system and adjust the constructed industrial control information execution queue in real time according to the scheduling algorithm.

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