A cross-hardware platform intelligent processing method, system and medium for embedded operating system

Abstract

The present application provides a method, system and medium for intelligent processing of an embedded operating system across hardware platforms. The method includes: obtaining the physical device feature information and communication parameter information of the target hardware platform for processing, obtaining the corresponding driver, and matching and detecting with the target hardware platform, correcting the driver according to the matching detection result to obtain an optimized driver, and then driving the target hardware platform to run, obtaining the corresponding running performance data and processing it, obtaining the running performance evaluation index, processing the average of the running performance evaluation index within the preset time period of the migration hardware platform with the running performance evaluation index, obtaining the running state of the target hardware platform, and adjusting the embedded operating system according to the running state; the present application obtains the adaptation driver for evaluation and optimization processing, evaluates the running state of the target hardware platform, and further detects the adaptability, so as to realize the efficient operation and intelligent processing of the embedded operating system across hardware platforms.

Description

Technical Field

[0001] The present application relates to the technical field of embedded operating systems, and in particular to a method, system and medium for intelligent processing of embedded operating systems across hardware platforms. Background Art

[0002] In the construction of smart construction sites, there are many different types of hardware equipment, such as various sensors (temperature sensors, humidity sensors, pressure sensors, etc.), monitoring equipment (cameras, drones, etc.), and actuators (automatic sprinkler devices, tower crane controllers, etc.); these hardware devices often run on different hardware platforms, and traditional embedded operating systems face many challenges in porting and compatibility between different hardware platforms: on the one hand, different hardware platforms have different processor architectures, hardware resources, and driver requirements; on the other hand, smart construction sites have high requirements for the real-time, accuracy, and stability of data processing, requiring embedded operating systems to quickly adapt to different hardware platforms and run efficiently. There is currently a lack of effective solutions.

[0003] In view of the above problems, effective technical solutions are urgently needed. Summary of the invention

[0004] The purpose of this application is to provide an embedded operating system cross-hardware platform intelligent processing method, system and medium, which can evaluate and optimize the processing by obtaining an adapter driver, evaluate the operating status of the target hardware platform, and further detect the adaptability, thereby realizing efficient operation and intelligent processing of the embedded operating system across hardware platforms.

[0005] The present application also provides an embedded operating system cross-hardware platform intelligent processing method, comprising the following steps:

[0006] Obtain physical device feature information and communication parameter information of the target hardware platform;

[0007] Acquire a corresponding driver according to the physical device feature information and the communication parameter information, perform a matching test on the driver and the target hardware platform, and modify the driver according to the matching test result to obtain an optimized driver;

[0008] Driving the target hardware platform to run according to the optimized driver, and obtaining the running performance data of the target hardware platform, and processing according to the running performance data to obtain the running performance evaluation index;

[0009] The average value of the operation performance evaluation index of the migration hardware platform within a preset time period is obtained, and the operation status of the target hardware platform is obtained according to the average value of the operation performance evaluation index and the operation performance evaluation index, and the embedded operating system is adjusted according to the operation status.

[0010] Optionally, in the embedded operating system cross-hardware platform intelligent processing method described in the present application, the obtaining of physical device feature information and communication parameter information of the target hardware platform includes:

[0011] Obtain physical device feature information and communication parameter information of the target hardware platform;

[0012] The physical device feature information includes chip model information, pin definition information and hardware identification information;

[0013] The communication parameter information includes communication protocol information and baud rate information.

[0014] Optionally, in the embedded operating system cross-hardware platform intelligent processing method described in the present application, the obtaining of a corresponding driver according to the physical device feature information and the communication parameter information, performing a matching detection on the driver and the target hardware platform, and correcting the driver according to the matching detection result to obtain an optimized driver includes:

[0015] According to the chip model information, pin definition information, hardware identification information, communication protocol information and baud rate information, a preset driver database is searched to obtain a corresponding driver;

[0016] The driver and the target hardware platform are respectively subjected to register read and write detection, interrupt response detection and communication interface communication detection through a preset matching detection method;

[0017] If the register read and write detection, interrupt response detection and communication interface communication detection are all passed, the driver is an optimized driver;

[0018] If one or more of the register read and write detection, interrupt response detection and communication interface communication detection results in failure, the target hardware platform setting parameters corresponding to the failed detection items are obtained, and the driver is corrected according to the target hardware platform setting parameters to obtain an optimized driver.

[0019] Optionally, in the embedded operating system cross-hardware platform intelligent processing method described in the present application, if the register read and write detection, interrupt response detection, communication interface communication detection and function detection are all passed, the driver is an optimized driver, and then further includes:

[0020] If the register read and write test, interrupt response test and communication interface communication test are all passed, the drive performance test data is obtained, including data transmission rate, data transmission accuracy, CPU occupancy rate and memory share;

[0021] The data transmission rate, data transmission accuracy, CPU occupancy rate and memory share are input into a preset driver performance evaluation model for processing to obtain a driver performance evaluation index of the driver;

[0022] Performing a threshold comparison between the driving performance evaluation index and a preset driving performance evaluation threshold;

[0023] If it is greater than or equal to the preset driver performance evaluation threshold, the driver performance is normal and the driver is an optimized driver;

[0024] If it is less than a preset driver performance evaluation threshold, the driver performance is abnormal, and the driver is optimized to obtain an optimized driver.

[0025] Optionally, in the embedded operating system cross-hardware platform intelligent processing method described in the present application, driving the target hardware platform to run according to the optimized driver, and obtaining the running performance data of the target hardware platform, and processing according to the running performance data to obtain the running performance evaluation index, include:

[0026] Driving the target hardware platform to run according to the optimized driver, and obtaining the running performance data of the target hardware platform, including the average value of processor operation speed, memory capacity data, bandwidth data and the average value of storage device read and write speed;

[0027] According to the processor operation speed average, memory capacity data, bandwidth data and storage device read and write speed average, respectively query the preset weight value list to obtain the corresponding processor operation speed weight value, memory capacity weight value, bandwidth weight value and storage device read and write speed weight value;

[0028] The processor operation speed average, memory capacity data, bandwidth data and storage device read and write speed average are respectively multiplied and accumulated with the corresponding processor operation speed weight value, memory capacity weight value, bandwidth weight value and storage device read and write speed weight value to obtain the operation performance evaluation index.

[0029] Optionally, in the embedded operating system cross-hardware platform intelligent processing method described in the present application, the obtaining of the average value of the operation performance evaluation index within a preset time period of the migration hardware platform, processing according to the average value of the operation performance evaluation index and the operation performance evaluation index, obtaining the operation status of the target hardware platform, and adjusting the embedded operating system according to the operation status include:

[0030] Obtain the average value of the operating performance evaluation index of the migration hardware platform within a preset time period;

[0031] If the running performance evaluation index is less than the running performance evaluation index mean, the running performance evaluation index mean is compared with the running performance evaluation index to obtain the performance deviation rate of the target hardware platform;

[0032] Performing a threshold comparison of the performance deviation rate with a preset performance deviation rate threshold;

[0033] If it is less than or equal to the preset performance deviation rate threshold, the operating status of the target hardware platform is normal;

[0034] If it is greater than the set performance deviation rate threshold, the operating state of the target hardware platform is abnormal, and the embedded operating system is adjusted.

[0035] Optionally, the embedded operating system cross-hardware platform intelligent processing method described in the present application further includes:

[0036] Obtaining the operating parameter data of the optimized driver, including the number of function calls, the mean execution time and the return error rate within a preset time period;

[0037] Compare the function call times, execution time averages and return error rates with preset function call benchmark times, standard execution time and return error tolerance rates, respectively, to obtain relative values ​​of function call times, execution time and return error rates;

[0038] Inputting the relative value of the number of function calls, the relative value of the execution time and the relative value of the return error rate into a preset reliability evaluation model for processing, and obtaining a reliability evaluation index of the optimized driver program;

[0039] Performing a threshold comparison between the reliability evaluation index and a preset reliability evaluation threshold;

[0040] If it is less than or equal to a preset reliability evaluation threshold, the optimized driving program has low reliability;

[0041] If it is greater than a preset reliability evaluation threshold, the optimized driving program is of high reliability.

[0042] Optionally, the embedded operating system cross-hardware platform intelligent processing method described in the present application further includes:

[0043] Processing is performed according to the number of function calls and the corresponding execution time to obtain the average execution time corresponding to the function;

[0044] Obtaining the throughput of the optimization driver within a preset time period;

[0045] Inputting the throughput and the reliability evaluation index into a preset driving effectiveness evaluation model for processing to obtain a driving effectiveness index corresponding to the optimized driving program;

[0046] The driving effectiveness indexes are sorted from large to small, and the optimized driving program corresponding to the maximum driving effectiveness index is determined.

[0047] In a second aspect, the present application provides an embedded operating system cross-hardware platform intelligent processing system, the system comprising: a memory and a processor, the memory comprising a program of an embedded operating system cross-hardware platform intelligent processing method, the program of the embedded operating system cross-hardware platform intelligent processing method when executed by the processor implements the following steps:

[0048] Obtain physical device feature information and communication parameter information of the target hardware platform;

[0049] Acquire a corresponding driver according to the physical device feature information and the communication parameter information, perform a matching test on the driver and the target hardware platform, and modify the driver according to the matching test result to obtain an optimized driver;

[0050] Driving the target hardware platform to run according to the optimized driver, and obtaining the running performance data of the target hardware platform, and processing according to the running performance data to obtain the running performance evaluation index;

[0051] Obtain the average value of the operating performance evaluation index of the migration hardware platform within a preset time period, process the average value of the operating performance evaluation index and the operating performance evaluation index to obtain the operating status of the target hardware platform, and adjust the embedded operating system according to the operating status

[0052] In a third aspect, the present application also provides a computer-readable storage medium, which stores a program for an embedded operating system's cross-hardware platform intelligent processing method. When the program for an embedded operating system's cross-hardware platform intelligent processing method is executed by a processor, the steps of an embedded operating system's cross-hardware platform intelligent processing method as described in any one of the above items are implemented.

[0053] From the above, it can be seen that the present application provides an embedded operating system cross-hardware platform intelligent processing method, system and medium, which obtains the adapter driver for evaluation and optimization processing, evaluates the operating status of the target hardware platform, and further detects the adaptability, thereby realizing the efficient operation and intelligent processing of the embedded operating system across hardware platforms.

[0054] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the embodiments of the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0056] Figure 1 A flowchart of an embedded operating system cross-hardware platform intelligent processing method provided in an embodiment of the present application;

[0057] Figure 2 A flowchart of obtaining an optimized driver program for an embedded operating system cross-hardware platform intelligent processing method provided in an embodiment of the present application;

[0058] Figure 3 A flowchart of obtaining an operating performance evaluation index for an embedded operating system cross-hardware platform intelligent processing method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0059] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0060] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0061] Please refer to Figure 1 , Figure 1 This is a flow chart of an embedded operating system cross-hardware platform intelligent processing method in some embodiments of the present application. The embedded operating system cross-hardware platform intelligent processing method is used in terminal devices, such as computers, mobile phone terminals, etc. The embedded operating system cross-hardware platform intelligent processing method includes the following steps:

[0062] S11, obtaining physical device feature information and communication parameter information of the target hardware platform;

[0063] S12, acquiring a corresponding driver according to the physical device feature information and the communication parameter information, performing a matching detection on the driver and the target hardware platform, and correcting the driver according to the matching detection result to obtain an optimized driver;

[0064] S13, driving the target hardware platform to run according to the optimized driver, and obtaining the running performance data of the target hardware platform, and processing according to the running performance data to obtain the running performance evaluation index;

[0065] S14, obtaining an average value of the operation performance evaluation index of the migration hardware platform within a preset time period, performing processing based on the average value of the operation performance evaluation index and the operation performance evaluation index to obtain the operation status of the target hardware platform, and adjusting the embedded operating system based on the operation status.

[0066] It should be noted that in order to achieve efficient and accurate cross-platform operation of the embedded operating system, the physical device feature information and communication parameter information of the target hardware platform are first obtained for matching the adapter driver, and a matching detection is performed between the obtained driver and the target hardware platform. The driver is corrected according to the matching detection result to obtain an optimized driver, and then the target hardware platform is driven to run. At the same time, the operating performance data of the target hardware platform is obtained, and the operating performance data is processed to obtain an operating performance evaluation index for evaluating the operating performance of the target hardware platform. The average operating performance evaluation index of the migration hardware platform within a preset time period is continued to be obtained, and the operating status of the target hardware platform is obtained according to the average operating performance evaluation index and the operating performance evaluation index. If the operating status is abnormal, the embedded operating system is adjusted.

[0067] According to an embodiment of the present invention, the obtaining of physical device feature information and communication parameter information of the target hardware platform includes:

[0068] Obtain physical device feature information and communication parameter information of the target hardware platform;

[0069] The physical device feature information includes chip model information, pin definition information and hardware identification information;

[0070] The communication parameter information includes communication protocol information and baud rate information.

[0071] It should be noted that in order to accurately obtain an adapted driver, it is necessary to identify the parameter information of the target hardware platform, including physical device feature information of the chip model information, pin definition information, and hardware identification information, and communication parameter information including communication protocol information and baud rate information, to provide a basis for matching the driver.

[0072] Please refer to Figure 2 , Figure 2 The present invention is a flowchart of an embedded operating system cross-hardware platform intelligent processing method for obtaining an optimized driver in some embodiments of the present application. According to an embodiment of the present invention, the corresponding driver is obtained according to the physical device feature information and communication parameter information, and the driver is matched with the target hardware platform. The driver is corrected according to the matching detection result to obtain the optimized driver, including:

[0073] S21, querying a preset driver database to obtain a corresponding driver according to the chip model information, pin definition information, hardware identification information, communication protocol information and baud rate information;

[0074] S22, performing register read and write detection, interrupt response detection and communication interface communication detection on the driver and the target hardware platform respectively through a preset matching detection method;

[0075] S23, if the register read and write detection, interrupt response detection and communication interface communication detection are all passed, the driver is an optimized driver;

[0076] S24. If one or more of the register read and write detection, interrupt response detection and communication interface communication detection results in failure, the target hardware platform setting parameters corresponding to the failed detection items are obtained, and the driver is corrected according to the target hardware platform setting parameters to obtain an optimized driver.

[0077] It should be noted that the corresponding driver is obtained by querying the preset driver database according to the obtained hardware platform parameter information, wherein the preset driver database is obtained by analyzing the chip model information, pin definition information, hardware identification information, communication protocol information and baud rate information of a large number of historical samples and the corresponding driver; then the obtained driver and the target hardware platform are subjected to register read and write detection, interrupt response detection and communication interface communication detection. If the matching detections are all passed, it means that the driver has good adaptability and does not need to be modified, that is, the driver is an optimized driver; if there are one or more matching detections that fail, it is necessary to modify the failed detection items according to the setting parameters of the target hardware platform, and the modified driver is used as the optimized driver to drive the target hardware platform to run.

[0078] According to an embodiment of the present invention, if the register read and write detection, interrupt response detection, communication interface communication detection and function detection are all passed, the driver is an optimized driver, and then further includes:

[0079] If the register read and write test, interrupt response test and communication interface communication test are all passed, the drive performance test data is obtained, including data transmission rate, data transmission accuracy, CPU occupancy rate and memory share;

[0080] The data transmission rate, data transmission accuracy, CPU occupancy rate and memory share are input into a preset driver performance evaluation model for processing to obtain a driver performance evaluation index of the driver;

[0081] Performing a threshold comparison between the driving performance evaluation index and a preset driving performance evaluation threshold;

[0082] If it is greater than or equal to the preset driver performance evaluation threshold, the driver performance is normal and the driver is an optimized driver;

[0083] If it is less than a preset driver performance evaluation threshold, the driver performance is abnormal, and the driver is optimized to obtain an optimized driver.

[0084] It should be noted that, in order to further evaluate the obtained driver operation performance, firstly, driver performance test data including data transmission rate, data transmission accuracy, CPU occupancy rate and memory share are obtained, and the obtained data transmission rate, data transmission accuracy, CPU occupancy rate and memory share are input into a preset driver performance evaluation model for processing to obtain the driver performance evaluation index of the driver;

[0085] The calculation formula of the driver performance evaluation index in the driver performance evaluation model is:

[0086] ;

[0087] in, To drive the performance evaluation index, , , , They are data transmission rate, data transmission accuracy, CPU occupancy and memory usage. , The characteristic coefficient is preset (the characteristic coefficient is obtained by intelligently processing database query through the embedded operating system across hardware platforms);

[0088] After the driver performance evaluation index is obtained, a threshold comparison is performed with the preset driver performance evaluation threshold. In this embodiment, the driver performance evaluation threshold is set to (0, 0.7) and [0.7, 1], which correspond to abnormal driver performance and normal driver performance, respectively. For example, if the obtained driver performance evaluation index is 0.6, it corresponds to abnormal driver performance, and the driver program needs to be optimized before it can be used to drive the target hardware platform to run. If the obtained driver performance evaluation index is 0.8, it corresponds to normal driver performance, and the driver program has good performance and does not need to be optimized. It can be directly used to drive the target hardware platform to run.

[0089] Please refer to Figure 3 , Figure 3 The present invention is a flowchart of obtaining an operation performance evaluation index of an embedded operating system cross-hardware platform intelligent processing method in some embodiments of the present application. According to an embodiment of the present invention, the operation of the target hardware platform is driven by the optimized driver, and the operation performance data of the target hardware platform is obtained, and the operation performance evaluation index is obtained by processing according to the operation performance data, including:

[0090] S31, driving the target hardware platform to run according to the optimized driver, and obtaining the running performance data of the target hardware platform, including the average value of processor operation speed, memory capacity data, bandwidth data and the average value of storage device reading and writing speed;

[0091] S32, querying the preset weight value list according to the processor operation speed average, memory capacity data, bandwidth data and storage device read and write speed average, and obtaining the corresponding processor operation speed weight value, memory capacity weight value, bandwidth weight value and storage device read and write speed weight value;

[0092] S33. Multiply and accumulate the processor operation speed average, memory capacity data, bandwidth data and storage device read and write speed average with the corresponding processor operation speed weight value, memory capacity weight value, bandwidth weight value and storage device read and write speed weight value respectively to obtain an operation performance evaluation index.

[0093] It should be noted that after obtaining the optimized driver, in order to detect the driving performance of the optimized driver for the target hardware platform, first obtain the operating performance data including the average processor operating speed, memory capacity data, bandwidth data and the average storage device read and write speed, wherein the average processor operating speed and the average storage device read and write speed are obtained by obtaining multiple processor operating speeds and storage device read and write speeds within a preset time period and then averaging them, and query the preset weight value list according to the obtained processor operating speed average, memory capacity data, bandwidth data and storage device read and write speed average, and obtain the corresponding processor operating speed weight value, memory capacity weight value, bandwidth weight value and storage device read and write speed weight value, wherein the preset weight value list is obtained by querying the embedded operating system cross-hardware platform intelligent processing database, and the obtained processor operating speed average, memory capacity data, bandwidth data and storage device read and write speed average are respectively multiplied with the corresponding processor operating speed weight value, memory capacity weight value, bandwidth weight value and storage device read and write speed weight value and accumulated to obtain the operating performance evaluation index;

[0094] The calculation formula of the operation performance evaluation index is:

[0095] ;

[0096] in, To run the performance evaluation index, , , , They are the average processor speed, memory capacity, bandwidth, and storage device read and write speed. , , , They are the processor operation speed weight value, memory capacity weight value, bandwidth weight value and storage device read and write speed weight value.

[0097] According to an embodiment of the present invention, the step of obtaining an average value of an operation performance evaluation index of a migration hardware platform within a preset time period, performing processing based on the average value of the operation performance evaluation index and the operation performance evaluation index to obtain an operation state of the target hardware platform, and adjusting the embedded operating system based on the operation state includes:

[0098] Obtain the average value of the operating performance evaluation index of the migration hardware platform within a preset time period;

[0099] If the running performance evaluation index is less than the running performance evaluation index mean, the running performance evaluation index mean is compared with the running performance evaluation index to obtain the performance deviation rate of the target hardware platform;

[0100] Performing a threshold comparison of the performance deviation rate with a preset performance deviation rate threshold;

[0101] If it is less than or equal to the preset performance deviation rate threshold, the operating status of the target hardware platform is normal;

[0102] If it is greater than the set performance deviation rate threshold, the operating state of the target hardware platform is abnormal, and the embedded operating system is adjusted.

[0103] It should be noted that in order to evaluate the performance optimization of the target hardware platform relative to the migration hardware platform, the average value of the running performance evaluation index of the migration hardware platform within the preset time period is obtained. If the obtained running performance evaluation index is greater than or equal to the average value of the running performance evaluation index, it means that the target hardware platform is running well and the running state is normal, and no further evaluation is required; if the obtained running performance evaluation index is less than the average value of the running performance evaluation index, the average value of the running performance evaluation index is compared with the running performance evaluation index to obtain the performance deviation rate of the target hardware platform;

[0104] The performance deviation rate calculation formula is:

[0105] ;

[0106] in, is the performance deviation rate, , are the mean value of the running performance evaluation index and the running performance evaluation index respectively; the obtained performance deviation rate is compared with the preset performance deviation rate threshold. In this embodiment, the performance deviation rate threshold is set to (0, 0.35] and (0.35, 1], which correspond to the normal state and the abnormal state respectively. For example, if the obtained performance deviation rate is 0.2, the running state of the target hardware platform is normal; if the obtained performance deviation rate is 0.4, the running state of the target hardware platform is abnormal, and the embedded operating system needs to be adjusted.

[0107] According to an embodiment of the present invention, it also includes:

[0108] Obtaining the operating parameter data of the optimized driver, including the number of function calls, the mean execution time and the return error rate within a preset time period;

[0109] Compare the function call times, execution time averages and return error rates with preset function call benchmark times, standard execution time and return error tolerance rates, respectively, to obtain relative values ​​of function call times, execution time and return error rates;

[0110] Inputting the relative value of the number of function calls, the relative value of the execution time and the relative value of the return error rate into a preset reliability evaluation model for processing, and obtaining a reliability evaluation index of the optimized driver program;

[0111] Performing a threshold comparison between the reliability evaluation index and a preset reliability evaluation threshold;

[0112] If it is less than or equal to a preset reliability evaluation threshold, the optimized driving program has low reliability;

[0113] If it is greater than a preset reliability evaluation threshold, the optimized driving program is of high reliability.

[0114] It should be noted that, in order to accurately obtain the running status of the optimized driver, a detection code is embedded in the driver to obtain the running parameter data including the number of function calls, the mean execution time and the return error rate within a preset time period, wherein the return error rate refers to the ratio of the sum of the number of failed executions of the driver function and the number of error codes to the total number of calls, and the obtained number of function calls, the mean execution time and the return error rate are respectively compared with the preset function call benchmark number, the standard execution time and the return fault tolerance rate to obtain the relative value of the number of function calls, the relative value of the execution time and the relative value of the return error rate. For example, if the number of function calls is 7 times and the function call benchmark number is 10 times, then 7 / 10=0.7 is the relative value of the number of function calls. Similarly, the relative value of the execution time and the relative value of the return error rate can be obtained; the obtained relative value of the number of function calls, the relative value of the execution time and the relative value of the return error rate are input into the preset reliability evaluation model for processing to obtain the reliability evaluation index of the optimized driver;

[0115] The reliability evaluation index calculation formula is:

[0116] ;

[0117] in, is the reliability evaluation index, , , They are the relative values ​​of function call times, execution time, and return error rate. , , The characteristic coefficient is preset (the characteristic coefficient is obtained by intelligently processing database query through the embedded operating system across hardware platforms);

[0118] Finally, the obtained reliability evaluation index is compared with the preset reliability evaluation threshold. In this embodiment, the reliability evaluation threshold is set to (0, 0.75] and (0.75, 1], which correspond to low reliability and high reliability respectively. For example, if the obtained reliability evaluation index is 0.65, the reliability of the optimized driver is insufficient, corresponding to low reliability; if the obtained reliability evaluation index is 0.85, the reliability of the optimized driver is good, corresponding to high reliability.

[0119] According to an embodiment of the present invention, it also includes:

[0120] Processing is performed according to the number of function calls and the corresponding execution time to obtain the average execution time corresponding to the function;

[0121] Obtaining the throughput of the optimization driver within a preset time period;

[0122] Inputting the throughput and the reliability evaluation index into a preset driving effectiveness evaluation model for processing to obtain a driving effectiveness index corresponding to the optimized driving program;

[0123] The driving effectiveness indexes are sorted from large to small, and the optimized driving program corresponding to the maximum driving effectiveness index is determined.

[0124] It should be noted that, based on the reliability of the optimized driver, further evaluating its performance efficiency is helpful to determine the optimal adaptive driver. First, the throughput of the optimized driver in a preset time period is obtained. The throughput refers to the number of operations completed per unit time. Then, the obtained throughput and reliability evaluation index are input into the preset driver effectiveness evaluation model for processing to obtain the driver effectiveness index corresponding to the optimized driver.

[0125] The driving effectiveness index calculation formula is:

[0126] ;

[0127] in, To drive the effectiveness index, , are the throughput and reliability evaluation indexes respectively, The characteristic coefficient is preset (the characteristic coefficient is obtained by querying the database through intelligent processing across hardware platforms of the embedded operating system); the driver effectiveness indexes corresponding to multiple optimized drivers are sorted from large to small, and the optimized driver corresponding to the maximum driver effectiveness index is determined to drive the target hardware platform to run.

[0128] It is worth mentioning that according to an embodiment of the present invention, if one or more of the register read and write detection, interrupt response detection and communication interface communication detection results in failure, then obtaining the target hardware platform setting parameters corresponding to the failed detection items, and correcting the driver according to the target hardware platform setting parameters to obtain the optimized driver, including:

[0129] If one or more of the register read and write detection, interrupt response detection and communication interface communication detection results in failure, then obtaining the target hardware platform setting parameters corresponding to the failed detection items, and correcting the driver program according to the target hardware platform setting parameters to obtain an optimized driver program;

[0130] The target hardware platform setting parameters include hardware register setting parameters, interrupt processing function setting parameters and communication interface setting parameters;

[0131] The hardware register setting parameters include register address setting parameters and register bit setting parameters;

[0132] The interrupt processing function setting parameters include interrupt number setting parameters, interrupt trigger condition setting parameters and interrupt priority setting parameters;

[0133] The communication interface setting parameters include communication protocol setting parameters, communication parameters and communication buffer parameters.

[0134] It should be noted that when performing a match check on the driver, if one or more match check items fail, it is necessary to modify it according to the setting parameters of the target hardware platform to obtain an optimized driver. The target hardware platform setting parameters include hardware register setting parameters, interrupt processing function setting parameters and communication interface setting parameters, among which the hardware register setting parameters include register address setting parameters and register bit setting parameters, the interrupt processing function setting parameters include register address setting parameters and register bit setting parameters, and the communication interface setting parameters include communication protocol setting parameters, communication parameters and communication buffer parameters; for example, if the address of a control register of the target hardware platform changes from 0x1000 to 0x1200, then all places in the driver that access the control register need to update the address.

[0135] The present invention also discloses an embedded operating system cross-hardware platform intelligent processing system, comprising a memory and a processor, wherein the memory comprises an embedded operating system cross-hardware platform intelligent processing method program, and when the embedded operating system cross-hardware platform intelligent processing method program is executed by the processor, the following steps are implemented:

[0136] Obtain physical device feature information and communication parameter information of the target hardware platform;

[0137] Acquire a corresponding driver according to the physical device feature information and the communication parameter information, perform a matching test on the driver and the target hardware platform, and modify the driver according to the matching test result to obtain an optimized driver;

[0138] Driving the target hardware platform to run according to the optimized driver, and obtaining the running performance data of the target hardware platform, and processing according to the running performance data to obtain the running performance evaluation index;

[0139] The average value of the operation performance evaluation index of the migration hardware platform within a preset time period is obtained, and the operation status of the target hardware platform is obtained according to the average value of the operation performance evaluation index and the operation performance evaluation index, and the embedded operating system is adjusted according to the operation status.

[0140] It should be noted that in order to achieve efficient and accurate cross-platform operation of the embedded operating system, the physical device feature information and communication parameter information of the target hardware platform are first obtained for matching the adapter driver, and a matching detection is performed between the obtained driver and the target hardware platform. The driver is corrected according to the matching detection result to obtain an optimized driver, and then the target hardware platform is driven to run. At the same time, the operating performance data of the target hardware platform is obtained, and the operating performance data is processed to obtain an operating performance evaluation index for evaluating the operating performance of the target hardware platform. The average operating performance evaluation index of the migration hardware platform within a preset time period is continued to be obtained, and the operating status of the target hardware platform is obtained according to the average operating performance evaluation index and the operating performance evaluation index. If the operating status is abnormal, the embedded operating system is adjusted.

[0141] According to an embodiment of the present invention, the obtaining of physical device feature information and communication parameter information of the target hardware platform includes:

[0142] Obtain physical device feature information and communication parameter information of the target hardware platform;

[0143] The physical device feature information includes chip model information, pin definition information and hardware identification information;

[0144] The communication parameter information includes communication protocol information and baud rate information.

[0145] It should be noted that in order to accurately obtain an adapted driver, it is necessary to identify the parameter information of the target hardware platform, including physical device feature information of the chip model information, pin definition information, and hardware identification information, and communication parameter information including communication protocol information and baud rate information, to provide a basis for matching the driver.

[0146] According to an embodiment of the present invention, the step of acquiring a corresponding driver according to the physical device feature information and the communication parameter information, performing a matching detection on the driver and the target hardware platform, and correcting the driver according to the matching detection result to obtain an optimized driver includes:

[0147] According to the chip model information, pin definition information, hardware identification information, communication protocol information and baud rate information, a preset driver database is searched to obtain a corresponding driver;

[0148] The driver and the target hardware platform are respectively subjected to register read and write detection, interrupt response detection and communication interface communication detection through a preset matching detection method;

[0149] If the register read and write detection, interrupt response detection and communication interface communication detection are all passed, the driver is an optimized driver;

[0150] If one or more of the register read and write detection, interrupt response detection and communication interface communication detection results in failure, the target hardware platform setting parameters corresponding to the failed detection items are obtained, and the driver is corrected according to the target hardware platform setting parameters to obtain an optimized driver.

[0151] It should be noted that the corresponding driver is obtained by querying the preset driver database according to the obtained hardware platform parameter information, wherein the preset driver database is obtained by analyzing the chip model information, pin definition information, hardware identification information, communication protocol information and baud rate information of a large number of historical samples and the corresponding driver; then the obtained driver and the target hardware platform are subjected to register read and write detection, interrupt response detection and communication interface communication detection. If the matching detections are all passed, it means that the driver has good adaptability and does not need to be modified, that is, the driver is an optimized driver; if there are one or more matching detections that fail, it is necessary to modify the failed detection items according to the setting parameters of the target hardware platform, and the modified driver is used as the optimized driver to drive the target hardware platform to run.

[0152] According to an embodiment of the present invention, if the register read and write detection, interrupt response detection, communication interface communication detection and function detection are all passed, the driver is an optimized driver, and then further includes:

[0153] If the register read and write test, interrupt response test and communication interface communication test are all passed, the drive performance test data is obtained, including data transmission rate, data transmission accuracy, CPU occupancy rate and memory share;

[0154] The data transmission rate, data transmission accuracy, CPU occupancy rate and memory share are input into a preset driver performance evaluation model for processing to obtain a driver performance evaluation index of the driver;

[0155] Performing a threshold comparison between the driving performance evaluation index and a preset driving performance evaluation threshold;

[0156] If it is greater than or equal to the preset driver performance evaluation threshold, the driver performance is normal and the driver is an optimized driver;

[0157] If it is less than a preset driver performance evaluation threshold, the driver performance is abnormal, and the driver is optimized to obtain an optimized driver.

[0158] It should be noted that, in order to further evaluate the obtained driver operation performance, firstly, driver performance test data including data transmission rate, data transmission accuracy, CPU occupancy rate and memory share are obtained, and the obtained data transmission rate, data transmission accuracy, CPU occupancy rate and memory share are input into a preset driver performance evaluation model for processing to obtain the driver performance evaluation index of the driver;

[0159] The calculation formula of the driver performance evaluation index in the driver performance evaluation model is:

[0160] ;

[0161] in, To drive the performance evaluation index, , , , They are data transmission rate, data transmission accuracy, CPU occupancy and memory usage. , The characteristic coefficient is preset (the characteristic coefficient is obtained by intelligently processing database query through the embedded operating system across hardware platforms);

[0162] After the driver performance evaluation index is obtained, a threshold comparison is performed with the preset driver performance evaluation threshold. In this embodiment, the driver performance evaluation threshold is set to (0, 0.7) and [0.7, 1], which correspond to abnormal driver performance and normal driver performance, respectively. For example, if the obtained driver performance evaluation index is 0.6, it corresponds to abnormal driver performance, and the driver program needs to be optimized before it can be used to drive the target hardware platform to run. If the obtained driver performance evaluation index is 0.8, it corresponds to normal driver performance, and the driver program has good performance and does not need to be optimized. It can be directly used to drive the target hardware platform to run.

[0163] According to an embodiment of the present invention, the step of driving the target hardware platform to run according to the optimized driver, obtaining the running performance data of the target hardware platform, and performing processing according to the running performance data to obtain the running performance evaluation index includes:

[0164] Driving the target hardware platform to run according to the optimized driver, and obtaining the running performance data of the target hardware platform, including the average value of processor operation speed, memory capacity data, bandwidth data and the average value of storage device read and write speed;

[0165] According to the processor operation speed average, memory capacity data, bandwidth data and storage device read and write speed average, respectively query the preset weight value list to obtain the corresponding processor operation speed weight value, memory capacity weight value, bandwidth weight value and storage device read and write speed weight value;

[0166] The processor operation speed average, memory capacity data, bandwidth data and storage device read and write speed average are respectively multiplied and accumulated with the corresponding processor operation speed weight value, memory capacity weight value, bandwidth weight value and storage device read and write speed weight value to obtain the operation performance evaluation index.

[0167] It should be noted that after obtaining the optimized driver, in order to detect the driving performance of the optimized driver for the target hardware platform, first obtain the operating performance data including the average processor operating speed, memory capacity data, bandwidth data and the average storage device read and write speed, wherein the average processor operating speed and the average storage device read and write speed are obtained by obtaining multiple processor operating speeds and storage device read and write speeds within a preset time period and then averaging them, and query the preset weight value list according to the obtained processor operating speed average, memory capacity data, bandwidth data and storage device read and write speed average, and obtain the corresponding processor operating speed weight value, memory capacity weight value, bandwidth weight value and storage device read and write speed weight value, wherein the preset weight value list is obtained by querying the embedded operating system cross-hardware platform intelligent processing database, and the obtained processor operating speed average, memory capacity data, bandwidth data and storage device read and write speed average are respectively multiplied with the corresponding processor operating speed weight value, memory capacity weight value, bandwidth weight value and storage device read and write speed weight value and accumulated to obtain the operating performance evaluation index;

[0168] The calculation formula of the operation performance evaluation index is:

[0169] ;

[0170] in, To run the performance evaluation index, , , , They are the average processor speed, memory capacity, bandwidth, and storage device read and write speed. , , , They are the processor operation speed weight value, memory capacity weight value, bandwidth weight value and storage device read and write speed weight value.

[0171] According to an embodiment of the present invention, the step of obtaining an average value of an operation performance evaluation index of a migration hardware platform within a preset time period, performing processing based on the average value of the operation performance evaluation index and the operation performance evaluation index to obtain an operation state of the target hardware platform, and adjusting the embedded operating system based on the operation state includes:

[0172] Obtain the average value of the operating performance evaluation index of the migration hardware platform within a preset time period;

[0173] If the running performance evaluation index is less than the running performance evaluation index mean, the running performance evaluation index mean is compared with the running performance evaluation index to obtain the performance deviation rate of the target hardware platform;

[0174] Performing a threshold comparison of the performance deviation rate with a preset performance deviation rate threshold;

[0175] If it is less than or equal to the preset performance deviation rate threshold, the operating status of the target hardware platform is normal;

[0176] If it is greater than the set performance deviation rate threshold, the operating state of the target hardware platform is abnormal, and the embedded operating system is adjusted.

[0177] It should be noted that in order to evaluate the performance optimization of the target hardware platform relative to the migration hardware platform, the average value of the running performance evaluation index of the migration hardware platform within the preset time period is obtained. If the obtained running performance evaluation index is greater than or equal to the average value of the running performance evaluation index, it means that the target hardware platform is running well and the running state is normal, and no further evaluation is required; if the obtained running performance evaluation index is less than the average value of the running performance evaluation index, the average value of the running performance evaluation index is compared with the running performance evaluation index to obtain the performance deviation rate of the target hardware platform;

[0178] The performance deviation rate calculation formula is:

[0179] ;

[0180] in, is the performance deviation rate, , are the mean value of the running performance evaluation index and the running performance evaluation index respectively; the obtained performance deviation rate is compared with the preset performance deviation rate threshold. In this embodiment, the performance deviation rate threshold is set to (0, 0.35] and (0.35, 1], which correspond to the normal state and the abnormal state respectively. For example, if the obtained performance deviation rate is 0.2, the running state of the target hardware platform is normal; if the obtained performance deviation rate is 0.4, the running state of the target hardware platform is abnormal, and the embedded operating system needs to be adjusted.

[0181] According to an embodiment of the present invention, it also includes:

[0182] Obtaining the operating parameter data of the optimized driver, including the number of function calls, the mean execution time and the return error rate within a preset time period;

[0183] Compare the function call times, execution time averages and return error rates with preset function call benchmark times, standard execution time and return error tolerance rates, respectively, to obtain relative values ​​of function call times, execution time and return error rates;

[0184] Inputting the relative value of the number of function calls, the relative value of the execution time and the relative value of the return error rate into a preset reliability evaluation model for processing, and obtaining a reliability evaluation index of the optimized driver program;

[0185] Performing a threshold comparison between the reliability evaluation index and a preset reliability evaluation threshold;

[0186] If it is less than or equal to a preset reliability evaluation threshold, the optimized driving program has low reliability;

[0187] If it is greater than a preset reliability evaluation threshold, the optimized driving program is of high reliability.

[0188] It should be noted that, in order to accurately obtain the running status of the optimized driver, a detection code is embedded in the driver to obtain the running parameter data including the number of function calls, the mean execution time and the return error rate within a preset time period, wherein the return error rate refers to the ratio of the sum of the number of failed executions of the driver function and the number of error codes to the total number of calls, and the obtained number of function calls, the mean execution time and the return error rate are respectively compared with the preset function call benchmark number, the standard execution time and the return fault tolerance rate to obtain the relative value of the number of function calls, the relative value of the execution time and the relative value of the return error rate. For example, if the number of function calls is 7 times and the function call benchmark number is 10 times, then 7 / 10=0.7 is the relative value of the number of function calls. Similarly, the relative value of the execution time and the relative value of the return error rate can be obtained; the obtained relative value of the number of function calls, the relative value of the execution time and the relative value of the return error rate are input into the preset reliability evaluation model for processing to obtain the reliability evaluation index of the optimized driver;

[0189] The reliability evaluation index calculation formula is:

[0190] ;

[0191] in, is the reliability evaluation index, , , They are the relative values ​​of function call times, execution time, and return error rate. , , The characteristic coefficient is preset (the characteristic coefficient is obtained by intelligently processing database query across hardware platforms through the embedded operating system);

[0192] Finally, the obtained reliability evaluation index is compared with the preset reliability evaluation threshold. In this embodiment, the reliability evaluation threshold is set to (0, 0.75] and (0.75, 1], which correspond to low reliability and high reliability respectively. For example, if the obtained reliability evaluation index is 0.65, the reliability of the optimized driver is insufficient, corresponding to low reliability; if the obtained reliability evaluation index is 0.85, the reliability of the optimized driver is good, corresponding to high reliability.

[0193] According to an embodiment of the present invention, it also includes:

[0194] Processing is performed according to the number of function calls and the corresponding execution time to obtain the average execution time corresponding to the function;

[0195] Obtaining the throughput of the optimization driver within a preset time period;

[0196] Inputting the throughput and the reliability evaluation index into a preset driving effectiveness evaluation model for processing to obtain a driving effectiveness index corresponding to the optimized driving program;

[0197] The driving effectiveness indexes are sorted from large to small, and the optimized driving program corresponding to the maximum driving effectiveness index is determined.

[0198] It should be noted that, based on the reliability of the optimized driver, further evaluating its performance efficiency is helpful to determine the optimal adaptive driver. First, the throughput of the optimized driver in a preset time period is obtained. The throughput refers to the number of operations completed per unit time. Then, the obtained throughput and reliability evaluation index are input into the preset driver effectiveness evaluation model for processing to obtain the driver effectiveness index corresponding to the optimized driver.

[0199] The driving effectiveness index calculation formula is:

[0200] ;

[0201] in, To drive the effectiveness index, , are the throughput and reliability evaluation indexes respectively, The characteristic coefficient is preset (the characteristic coefficient is obtained by querying the database through intelligent processing across hardware platforms of the embedded operating system); the driver effectiveness indexes corresponding to multiple optimized drivers are sorted from large to small, and the optimized driver corresponding to the maximum driver effectiveness index is determined to drive the target hardware platform to run.

[0202] It is worth mentioning that according to an embodiment of the present invention, if one or more of the register read and write detection, interrupt response detection and communication interface communication detection results in failure, then obtaining the target hardware platform setting parameters corresponding to the failed detection items, and correcting the driver according to the target hardware platform setting parameters to obtain the optimized driver, including:

[0203] If one or more of the register read and write detection, interrupt response detection and communication interface communication detection results in failure, then obtaining the target hardware platform setting parameters corresponding to the failed detection items, and correcting the driver program according to the target hardware platform setting parameters to obtain an optimized driver program;

[0204] The target hardware platform setting parameters include hardware register setting parameters, interrupt processing function setting parameters and communication interface setting parameters;

[0205] The hardware register setting parameters include register address setting parameters and register bit setting parameters;

[0206] The interrupt processing function setting parameters include interrupt number setting parameters, interrupt trigger condition setting parameters and interrupt priority setting parameters;

[0207] The communication interface setting parameters include communication protocol setting parameters, communication parameters and communication buffer parameters.

[0208] It should be noted that when performing a match check on the driver, if one or more match check items fail, it is necessary to modify it according to the setting parameters of the target hardware platform to obtain an optimized driver, including hardware register setting parameters such as register address setting parameters and register bit setting parameters, interrupt handling function setting parameters such as register address setting parameters and register bit setting parameters, and communication interface setting parameters such as communication protocol setting parameters, communication parameters and communication buffer parameters; for example, if the address of a control register of the target hardware platform changes from 0x1000 to 0x1200, then all places in the driver that access the control register need to update the address.

[0209] The third aspect of the present invention provides a readable storage medium, which stores a program for an embedded operating system's cross-hardware platform intelligent processing method. When the program for an embedded operating system's cross-hardware platform intelligent processing method is executed by a processor, the steps of the embedded operating system's cross-hardware platform intelligent processing method as described in any one of the above items are implemented.

[0210] The present invention discloses an embedded operating system cross-hardware platform intelligent processing method, system and medium, which obtain an adapter driver for evaluation and optimization processing, evaluate the operating status of the target hardware platform, and further detect the adaptability, thereby realizing the efficient operation and intelligent processing of the embedded operating system across hardware platforms.

[0211] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0212] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0213] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0214] Those skilled in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, the aforementioned program can be stored in a readable storage medium, and when the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0215] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

Claims

1. An embedded operating system cross-hardware platform intelligent processing method, characterized in that: The following steps are involved: Obtain physical device feature information and communication parameter information of the target hardware platform; Acquire a corresponding driver according to the physical device feature information and the communication parameter information, perform a matching test on the driver and the target hardware platform, and modify the driver according to the matching test result to obtain an optimized driver; Driving the target hardware platform to run according to the optimized driver, and obtaining the running performance data of the target hardware platform, and processing according to the running performance data to obtain the running performance evaluation index; Obtaining an average value of the operation performance evaluation index of the migration hardware platform within a preset time period, performing processing based on the average value of the operation performance evaluation index and the operation performance evaluation index to obtain the operation status of the target hardware platform, and adjusting the embedded operating system according to the operation status; The obtaining of physical device characteristic information and communication parameter information of the target hardware platform includes: Obtain physical device feature information and communication parameter information of the target hardware platform; The physical device feature information includes chip model information, pin definition information and hardware identification information; The communication parameter information includes communication protocol information and baud rate information; The step of acquiring a corresponding driver according to the physical device feature information and the communication parameter information, performing a matching detection on the driver and the target hardware platform, and correcting the driver according to the matching detection result to obtain an optimized driver includes: According to the chip model information, pin definition information, hardware identification information, communication protocol information and baud rate information, a preset driver database is searched to obtain a corresponding driver; The driver and the target hardware platform are respectively subjected to register read and write detection, interrupt response detection and communication interface communication detection through a preset matching detection method; If the register read and write detection, interrupt response detection and communication interface communication detection are all passed, the driver is an optimized driver; If one or more of the register read and write detection, interrupt response detection and communication interface communication detection results in failure, the target hardware platform setting parameters corresponding to the failed detection items are obtained, and the driver is corrected according to the target hardware platform setting parameters to obtain an optimized driver.

2. The embedded operating system cross-hardware platform intelligent processing method according to claim 1, characterized in that: If the register read and write test, interrupt response test, communication interface communication test and function test are all passed, the driver is an optimized driver, and then further includes: If the register read and write test, interrupt response test and communication interface communication test are all passed, the drive performance test data is obtained, including data transmission rate, data transmission accuracy, CPU occupancy rate and memory share; The data transmission rate, data transmission accuracy, CPU occupancy rate and memory share are input into a preset driver performance evaluation model for processing to obtain a driver performance evaluation index of the driver; Performing a threshold comparison between the driving performance evaluation index and a preset driving performance evaluation threshold; If it is greater than or equal to the preset driver performance evaluation threshold, the driver performance is normal and the driver is an optimized driver; If it is less than a preset driver performance evaluation threshold, the driver performance is abnormal, and the driver is optimized to obtain an optimized driver.

3. The embedded operating system cross-hardware platform intelligent processing method according to claim 2, characterized in that: The step of driving the target hardware platform to run according to the optimized driver, obtaining the running performance data of the target hardware platform, and processing the running performance data to obtain the running performance evaluation index includes: Driving the target hardware platform to run according to the optimized driver, and obtaining the running performance data of the target hardware platform, including the average value of processor operation speed, memory capacity data, bandwidth data and the average value of storage device read and write speed; According to the processor operation speed average, memory capacity data, bandwidth data and storage device read and write speed average, respectively query the preset weight value list to obtain the corresponding processor operation speed weight value, memory capacity weight value, bandwidth weight value and storage device read and write speed weight value; The processor operation speed average, memory capacity data, bandwidth data and storage device read and write speed average are respectively multiplied and accumulated with the corresponding processor operation speed weight value, memory capacity weight value, bandwidth weight value and storage device read and write speed weight value to obtain the operation performance evaluation index.

4. The embedded operating system cross-hardware platform intelligent processing method according to claim 3, characterized in that: The step of obtaining an average value of an operation performance evaluation index of the migration hardware platform within a preset time period, performing processing according to the average value of the operation performance evaluation index and the operation performance evaluation index to obtain an operation status of the target hardware platform, and adjusting the embedded operating system according to the operation status includes: Obtain the average value of the operating performance evaluation index of the migration hardware platform within a preset time period; If the running performance evaluation index is less than the running performance evaluation index mean, the running performance evaluation index mean is compared with the running performance evaluation index to obtain the performance deviation rate of the target hardware platform; Performing a threshold comparison of the performance deviation rate with a preset performance deviation rate threshold; If it is less than or equal to the preset performance deviation rate threshold, the operating status of the target hardware platform is normal; If it is greater than the set performance deviation rate threshold, the operating state of the target hardware platform is abnormal, and the embedded operating system is adjusted.

5. The embedded operating system cross-hardware platform intelligent processing method according to claim 4, characterized in that: Also includes: Obtaining the operating parameter data of the optimized driver, including the number of function calls, the mean execution time and the return error rate within a preset time period; Compare the function call times, execution time averages and return error rates with preset function call benchmark times, standard execution time and return error tolerance rates, respectively, to obtain relative values ​​of function call times, execution time and return error rates; Inputting the relative value of the number of function calls, the relative value of the execution time and the relative value of the return error rate into a preset reliability evaluation model for processing, and obtaining a reliability evaluation index of the optimized driver program; Performing a threshold comparison between the reliability evaluation index and a preset reliability evaluation threshold; If it is less than or equal to a preset reliability evaluation threshold, the optimized driving program has low reliability; If it is greater than a preset reliability evaluation threshold, the optimized driving program is of high reliability.

6. The embedded operating system cross-hardware platform intelligent processing method according to claim 5, characterized in that: Also includes: Obtaining the throughput of the optimization driver within a preset time period; Inputting the throughput and the reliability evaluation index into a preset driving effectiveness evaluation model for processing to obtain a driving effectiveness index corresponding to the optimized driving program; The driving effectiveness indexes are sorted from large to small, and the optimized driving program corresponding to the maximum driving effectiveness index is determined.

7. An embedded operating system cross-hardware platform intelligent processing system, characterized in that: The method comprises a memory and a processor, wherein the memory comprises a program of an embedded operating system cross-hardware platform intelligent processing method, and when the embedded operating system cross-hardware platform intelligent processing method program is executed by the processor, the following steps are implemented: Obtain physical device feature information and communication parameter information of the target hardware platform; Acquire a corresponding driver according to the physical device feature information and the communication parameter information, perform a matching test on the driver and the target hardware platform, and modify the driver according to the matching test result to obtain an optimized driver; Driving the target hardware platform to run according to the optimized driver, and obtaining the running performance data of the target hardware platform, and processing according to the running performance data to obtain the running performance evaluation index; Obtaining an average value of the operation performance evaluation index of the migration hardware platform within a preset time period, performing processing based on the average value of the operation performance evaluation index and the operation performance evaluation index to obtain the operation status of the target hardware platform, and adjusting the embedded operating system according to the operation status; The obtaining of physical device characteristic information and communication parameter information of the target hardware platform includes: Obtain physical device feature information and communication parameter information of the target hardware platform; The physical device feature information includes chip model information, pin definition information and hardware identification information; The communication parameter information includes communication protocol information and baud rate information; The step of acquiring a corresponding driver according to the physical device feature information and the communication parameter information, performing a matching detection on the driver and the target hardware platform, and correcting the driver according to the matching detection result to obtain an optimized driver includes: According to the chip model information, pin definition information, hardware identification information, communication protocol information and baud rate information, a preset driver database is searched to obtain a corresponding driver; The driver and the target hardware platform are respectively subjected to register read and write detection, interrupt response detection and communication interface communication detection through a preset matching detection method; If the register read and write detection, interrupt response detection and communication interface communication detection are all passed, the driver is an optimized driver; If one or more of the register read and write detection, interrupt response detection and communication interface communication detection results in failure, the target hardware platform setting parameters corresponding to the failed detection items are obtained, and the driver is corrected according to the target hardware platform setting parameters to obtain an optimized driver.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores an embedded operating system cross-hardware platform intelligent processing method program. When the embedded operating system cross-hardware platform intelligent processing method program is executed by a processor, the steps of an embedded operating system cross-hardware platform intelligent processing method as described in any one of claims 1 to 6 are implemented.

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