Information interaction optimization method and electronic device

Abstract

This application discloses an information interaction optimization method and electronic device, relating to the field of information interaction technology. The method includes: when the initial interaction duration of the baseboard management controller is greater than or equal to a first interaction duration threshold, counting the number of initial interaction retries; when the number of initial interaction retries is greater than or equal to the first retry threshold and the initial interaction retry duration corresponding to each retry is greater than or equal to the first interaction duration threshold, adjusting the first interaction duration threshold and the first retry threshold to obtain a second interaction duration threshold and a second interaction retry threshold; when the current interaction duration is greater than or equal to the second interaction duration threshold, if the current interaction retries are greater than or equal to the second interaction retry threshold, determining an interaction anomaly; and triggering the baseboard management controller and the target external device to execute an anomaly recovery mechanism. By shortening the waiting time and reducing the number of retries, resource waste is avoided, and interaction efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of information interaction technology, and in particular to an information interaction optimization method and an electronic device. Background Technology

[0002] When faced with unstable communication with external devices, BMCs typically employ fixed reliability measures, such as retry mechanisms and delay strategies. While these strategies can ensure data transmission integrity to a certain extent, they can prove inefficient in certain situations and may even introduce system-level risks. For example, when a device frequently experiences response delays or becomes completely unresponsive, the BMC's fixed timeout and retry count may cause it to waste excessive resources on ineffective tasks, thus affecting the monitoring and management of other critical devices. In extreme cases, it could even trigger an abnormal restart of the BMC itself, further threatening the overall stability and availability of the server.

[0003] Therefore, to date, there is no perfect solution that can maintain the basic functions of BMC while coping with the ever-changing operating environment. Summary of the Invention

[0004] This application provides an information interaction optimization method and electronic device to at least solve the problem in the related art where the Baseboard Management Controller (BMC) system uses a fixed number of retries and waiting time, which cannot adapt to abnormal scenarios, resulting in invalid waiting and retries, which may cause the system to hang up or crash.

[0005] According to one aspect of the embodiments of this application, an information interaction optimization method is provided, comprising: when the initial interaction duration between a baseboard management controller and a target external device is greater than or equal to a first interaction duration threshold, counting the number of initial interaction retries between the baseboard management controller and the target external device; when the number of initial interaction retries is greater than or equal to the first retry threshold and the initial interaction retry duration corresponding to each retry is greater than or equal to the first interaction duration threshold, adjusting the first interaction duration threshold and the first retry threshold to obtain a second interaction duration threshold and a second interaction retry threshold; when the current interaction duration between the management controller and the target external device is greater than or equal to the second interaction duration threshold, if the current interaction retries between the baseboard management controller and the target external device are greater than or equal to the second interaction retry threshold, determining that the interaction between the baseboard management controller and the target external device is abnormal; and triggering the baseboard management controller and the target external device to execute an abnormal recovery mechanism.

[0006] According to another aspect of the embodiments of this application, an electronic device is also provided, including: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include methods for performing the information interaction optimization method described in any one of the foregoing.

[0007] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein the program executes the information interaction optimization method described in any one of the above.

[0008] According to another aspect of the embodiments of this application, a processor is also provided, the processor being used to run a program, wherein the program, when running, executes the information interaction optimization method described in any one of the above.

[0009] According to another aspect of the embodiments of this application, a computer program product is also provided, including computer instructions, which, when executed by a processor, perform the information interaction optimization method described in any one of the above.

[0010] This application utilizes the analysis of real-time and historical data to adapt to the current state of devices and the network. When external devices exhibit abnormal responses or network latency increases, the BMC relaxes thresholds, giving devices more time to respond and increasing the number of retries to improve the probability of successful interaction. Conversely, when devices respond quickly or network conditions are stable, the BMC shortens waiting times and reduces the number of retries, avoiding resource waste and improving interaction efficiency. This adaptive adjustment mechanism optimizes resource utilization while maintaining BMC management functions, improving the overall stability and operational efficiency of the server system. It solves the problem in related technologies where the BMC system uses fixed retries and waiting times, which cannot adapt to abnormal scenarios, leading to invalid waiting and retries, potentially causing system crashes or freezes. Attached Figure Description

[0011] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a hardware structure block diagram of the information interaction optimization method according to an embodiment of this application;

[0013] Figure 2This is a flowchart of an information interaction optimization method according to an embodiment of this application;

[0014] Figure 3 This is a flowchart of another information interaction optimization method according to an embodiment of this application;

[0015] Figure 4 This is a flowchart of anomaly recovery according to an embodiment of this application;

[0016] Figure 5 This is a schematic diagram of an information interaction optimization device according to an embodiment of this application. Detailed Implementation

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

[0018] It should be noted that, in the description of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. The terms "first," "second," etc., in this application are used to distinguish similar objects and are not used to describe a specific order or sequence.

[0019] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] In server management within data center and cloud computing environments, the Baseboard Management Controller (BMC) plays a crucial role. As an embedded system within the server, the BMC is responsible for monitoring and managing the status of hardware components, including but not limited to temperature, voltage, and fan speed, and provides remote management and fault detection capabilities. With the increasing complexity of server architectures and the growing diversity of network devices, the BMC needs to frequently communicate and interact with various peripheral devices and network interfaces to maintain server stability and performance.

[0021] However, in existing technologies, BMCs typically employ fixed reliability measures, such as retry mechanisms and delay strategies, when facing unstable communication with external devices. While these strategies can ensure data transmission integrity to a certain extent, they prove inefficient in certain situations and may even trigger system-level risks. For example, when a device frequently experiences response delays or complete unresponsiveness, the BMC's fixed timeout and retry count may cause it to waste excessive resources on ineffective tasks, thus affecting the monitoring and management of other critical devices. In extreme cases, it may even cause the BMC itself to restart abnormally, further threatening the overall stability and availability of the server.

[0022] Specifically, the limitations of existing technology are reflected in the following aspects:

[0023] 1) Limitations of fixed parameters: The fixed number of retries and waiting time set in BMC may not perform well when dealing with different devices and network conditions, especially in scenarios with high device failure rates or large network fluctuations.

[0024] 2) Waste of resources: In the event of equipment failure, long waiting times and multiple retries will lead to a significant waste of BMC resources, affecting the overall responsiveness and efficiency of the system.

[0025] 3) System-level risks: As mentioned above, excessive waiting and retries may trigger thread timeout and restart mechanisms within the BMC. This problem is more serious when using a serial bus and may interrupt the management of other critical devices, such as fan control, leading to major failures such as server overheating.

[0026] As described in the background section, the Baseboard Management Controller (BMC) system in related technologies uses a fixed number of retries and waiting time, which cannot adapt to abnormal scenarios, resulting in invalid waiting and retries, and may cause system hangs or crashes. The embodiments of this application provide an information interaction optimization method and apparatus, an electronic device, a computer-readable storage medium, and a computer program product.

[0027] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0028] The specific application environment architecture or specific hardware architecture on which the execution of the information interaction optimization method depends is described here.

[0029] The methods and embodiments provided in this application can be executed on a server device or a similar computing device. Taking running on a server device as an example, Figure 1This is a hardware structure block diagram of the information interaction optimization method according to an embodiment of this application, such as... Figure 1 As shown, the server device may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The server device may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the server equipment described above. For example, the server equipment may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0030] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the information interaction optimization method in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thus implementing the above-described method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to server devices via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0031] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider for the server device. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0032] According to an embodiment of this application, a method embodiment for optimizing information interaction is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0033] Figure 2 This is a flowchart of an information interaction optimization method according to an embodiment of this application, such as... Figure 2 As shown, the information interaction optimization method includes the following steps:

[0034] Step S202: When the first interaction duration between the baseboard management controller and the target external device is greater than or equal to the first interaction duration threshold, count the number of retries for the first interaction between the baseboard management controller and the target external device.

[0035] Optional, Baseboard Management Controller (BMC): This is an embedded processor used to monitor and manage the server hardware status, including temperature, voltage, fan speed, etc., and supports remote control and fault diagnosis.

[0036] Optionally, the initial interaction duration threshold refers to the maximum allowed waiting time when the BMC interacts with the target device for the first time. This threshold is usually set based on historical interaction data or a preset value to prevent the BMC from wasting too much time on invalid interactions. The initial interaction retry threshold refers to the maximum number of times the BMC can attempt to interact with the target device again after the initial interaction fails. This threshold is also based on historical data or a preset value to balance the probability of successful interaction with the consumption of system resources.

[0037] In this embodiment, when the BMC interacts with the target external device for the first time, the system monitors the interaction latency in real time. If the latency is greater than or equal to a preset first interaction duration threshold (e.g., 500 milliseconds), the system begins to count the number of retries for the first interaction. This requires the BMC to accurately record the latency and result of each interaction for subsequent analysis and threshold adjustment.

[0038] Step S204: When the number of first interaction retries is greater than or equal to the first retry number threshold and the duration of the first interaction retry corresponding to each retry is greater than or equal to the first interaction duration threshold, the first interaction duration threshold and the first retry number threshold are adjusted to obtain the second interaction duration threshold and the second interaction retry number threshold.

[0039] In this embodiment, if the number of retries for the initial interaction (e.g., 5 times) all reach or exceed the first retry threshold, and the latency of each retry exceeds the first interaction duration threshold, the system will trigger a threshold adjustment process. The adjusted second interaction duration threshold (e.g., 1000 milliseconds) and second retry threshold (e.g., 7 times) will be more lenient, allowing the BMC to continue attempting interactions with longer latency and fewer retry attempts to determine if there are deeper issues. This dynamic adjustment continues during real-time interactions, ensuring that the BMC can promptly identify and respond to abnormal changes in external devices or the network environment.

[0040] Step S206: When the current interaction duration between the management controller and the target external device is greater than or equal to the second interaction duration threshold, if the current interaction retry count between the baseboard management controller and the target external device is greater than or equal to the second interaction retry count threshold, it is determined that the interaction between the baseboard management controller and the target external device is abnormal.

[0041] Step S208: Trigger the abnormal recovery mechanism between the baseboard management controller and the target external device.

[0042] By dynamically adjusting the threshold when the initial interaction fails frequently, the system can more quickly identify abnormal states, avoid being in a state of ineffective interaction attempts for a long time, and thus trigger the abnormal recovery mechanism to ensure that the server system can resume normal operation in a timely manner, reducing the risk of service interruption caused by abnormal device interaction.

[0043] For example, during the initial interaction between the BMC (Baseboard Management Controller) and an external device, a first interaction duration threshold of 100ms and a first retry threshold of 2 times are set. If the initial interaction takes longer than 100ms (equal to or greater than 100ms), the number of retryes is recorded. If the number of retries reaches or exceeds 2, and each retry wait time is 100ms or more, the system adjusts the first interaction duration threshold to 150ms and the first retry threshold to 3, forming a second interaction duration threshold and a second interaction retry threshold. During subsequent interactions, if the time still exceeds 150ms and 3 retries fail, the system considers the interaction abnormal and triggers an abnormality recovery mechanism. This improves the robustness and efficiency of the BMC's interaction with the device. Through this dynamic threshold adjustment, the system can better adapt to changes in device status and network conditions.

[0044] As described above, in this embodiment, when the baseboard management controller interacts with the target external device, a first interaction duration threshold and a first retry count threshold can be generated based on the historical interaction information of the baseboard management controller to determine the interaction status between the baseboard management controller and the target external device. Specifically, the interaction duration (first interaction duration) between the baseboard management controller and the target external device is compared with the first interaction duration threshold. If the first interaction duration is greater than or equal to the first interaction duration threshold, the number of first interaction retries between the baseboard management controller and the target external device is counted. If the number of first interaction retries is greater than or equal to the first retry count threshold and each retry... If the duration of the first retry for each interaction is greater than or equal to the first interaction duration threshold, the first interaction duration threshold and the first retry count threshold will be adjusted to obtain the second interaction duration threshold and the second retry count threshold. If the current interaction duration between the management controller and the target external device is greater than or equal to the second interaction duration threshold, and if the current retry count between the management controller and the target external device is greater than or equal to the second retry count threshold, an interaction anomaly between the management controller and the target external device is determined. This triggers the anomaly recovery mechanism between the management controller and the target external device, achieving the goal of adapting to the current state of the device and network by analyzing real-time interaction data and historical data. When an external device exhibits an abnormal response or network latency increases, the BMC relaxes the thresholds to give the device more time to respond and increases the number of retries to improve the probability of successful interaction. Conversely, when the device responds quickly or network conditions are stable, the BMC shortens the waiting time and reduces the number of retries, avoiding resource waste and improving interaction efficiency. This mechanism, through adaptive adjustment, optimizes resource utilization and improves the overall stability and operating efficiency of the server system while ensuring the BMC's management functions.

[0045] Therefore, the technical solution provided by the embodiments of this application solves the technical problem in the related art where the Baseboard Management Controller (BMC) system uses a fixed number of retries and waiting time, which cannot adapt to abnormal scenarios, resulting in invalid waiting and retries, which may cause the system to hang up or crash.

[0046] According to the above embodiments of this application, when the first interaction duration between the baseboard management controller and the target external device is greater than or equal to a first interaction duration threshold, before counting the number of first interaction retries between the baseboard management controller and the target external device, the information interaction optimization method further includes: obtaining historical interaction information between the baseboard management controller and the external device; determining a first interaction duration threshold based on the duration of multiple interaction responses with a successful interaction status in the historical interaction information; and determining a first retry count threshold based on the number of multiple interaction retries with a successful interaction status in the historical interaction information.

[0047] In this embodiment, interaction data between the BMC and the target device over the past month can be collected, including the response time and retries of successful interactions. This collected historical interaction information can be used to determine a first interaction duration threshold and a first interaction duration threshold.

[0048] Figure 3 This is a flowchart of another information interaction optimization method according to an embodiment of this application, such as... Figure 3 As shown, the system can record the latency and number of retries for normal interactions. That is, the current system needs to record the response time of each normal interaction action, the result of each interaction, and the number of retries required to obtain the interaction result. For example, each time the system interacts with the outside world, it records the interaction response time, whether the interaction was successful, and the number of interaction attempts. For example, for a successful interaction: the interaction result is recorded as: Information interaction successful; number of attempts: 3; time taken: first attempt failed, time taken 100ms; second interaction failed, time taken 100ms; third interaction succeeded, time taken 10ms. For a failed interaction: the interaction result is recorded as: Information interaction failed; number of attempts: 3; time taken: first attempt failed, time taken 100ms; second interaction failed, time taken 100ms; third interaction failed, time taken 100ms.

[0049] This threshold setting based on historical data reduces the probability of initial misjudgment and ensures the scientific validity and effectiveness of the threshold setting.

[0050] According to the above embodiments of this application, determining a first interaction duration threshold based on the durations of multiple successful interaction responses in historical interaction information includes: deleting the maximum and minimum interaction response durations from the multiple interaction response durations to obtain the remaining interaction response durations; determining the average interaction duration corresponding to the remaining interaction response durations; and determining a predetermined multiple of the average interaction duration as the first interaction duration threshold.

[0051] In this embodiment, the fastest and slowest response times are removed from these successful interactions, and the average response time of the remaining data is calculated, assumed to be 150 milliseconds. The first interaction duration threshold is set to 225 milliseconds (average * 1.5).

[0052] That is, in this embodiment, such as Figure 3As shown, based on the above record analysis, the system has the ability to smoothly wait and smoothly retry for a certain peripheral device interaction strategy. For example, based on the analysis and sampling of successful data, a scientific averaging method is adopted for the successful data, such as "double-sided truncated averaging," which removes the highest and lowest successful communication times to obtain a scientific average of successful communication. The system timeout time is adjusted according to the average. If the time required for most successful communication is within 10ms, then a timeout exceeding 10ms can be judged as an abnormal state. The maximum timeout waiting time of the system is taken as 15 milliseconds (for safety, it is generally not taken close to the average value; this value can be adjusted according to the established strategy, such as twice the average value, etc. Here, 1.5 times is used as an example). Communication timeout is immediately considered when the communication time is 15 milliseconds, and the next task is entered. Compared with the currently hard-coded waiting value, such as 200 milliseconds, each abnormal communication can quickly avoid meaningless waiting by using the system's experience average, thereby improving efficiency.

[0053] In addition, the system will randomly calculate smoothing delays and smoothing retries; if the system still experiences frequent interaction failures based on the processing after smoothing delays and smoothing retries, it will enter the abnormal recovery mechanism; otherwise, it will continue to run.

[0054] According to the above embodiments of this application, determining a first retry threshold based on multiple retry counts of interactions with a successful interaction status in historical interaction information includes: deleting the maximum and minimum retry counts of interactions from the multiple retry counts to obtain the remaining retry counts; determining the average retry count corresponding to the remaining retry counts; and determining a predetermined multiple of the average retry counts as the first retry threshold.

[0055] In this embodiment, the maximum and minimum number of retries are removed, and the average number of retries for the remaining data is calculated, assumed to be 2. The first retry threshold is set to 3.

[0056] A similar mechanism is used for retries. When the majority of successful communications occur within two attempts, and more than two retries fail, the average number of retries will be used to attempt only the average number of retries in subsequent communications. This avoids a large number of attempts that are unlikely to succeed. For a system with a timeout of 200ms and 5 retries, this can save at least 0.6 seconds (3 * 200ms).

[0057] In one alternative embodiment, smooth waiting and smooth retries can be combined to save a lot of time for the entire system (because most interactions beyond the smooth timeout time and smooth timeout number are unlikely to succeed), and the smooth timeout time and smooth timeout number need to be dynamically adjusted continuously based on the latest collected time and number data.

[0058] A dynamic smoothing mechanism is implemented here to minimize the consumption of inefficient time, that is, interactions that exceed the smoothing timeout time and smoothing timeout count. Since the success rate is extremely low, the system should avoid wasting too much time on such interactions. Moreover, when the dynamic smoothing mechanism determines that a device interaction is inefficient, it can adjust the BMC's interaction strategy in real time, such as shortening the timeout waiting time of subsequent interactions or reducing the number of retries, to avoid further time waste and potential system blockage.

[0059] This dynamic smoothing mechanism intelligently predicts and adjusts the BMC's interaction strategy by combining real-time updated smoothing timeout time and smoothing timeout count with the latest data on device response, in order to achieve optimal resource allocation and utilization.

[0060] "Smoothed waiting time" and "smoothed retries" are dynamic parameters derived from historical interaction data through statistical analysis, particularly the two-sided truncated averaging method. Smoothed waiting time refers to the optimal time for the BMC to wait for a device response during an interaction, while smoothed retries refer to the optimal number of times the BMC should attempt to communicate again after the initial interaction failure to achieve the predetermined communication goal.

[0061] "Overlapping" means that when calculating the total interaction cost, not only the waiting time of each interaction should be considered, but also the additional waiting time added by the retry mechanism. For example, if the smoothed waiting time for a communication is 15 milliseconds, and the smoothed retries are 2, then the total interaction cost will be the base waiting time plus the cumulative waiting time of the two retryes. This overlapping takes into account all the waiting times that may be encountered during the interaction, which helps to more accurately assess the actual efficiency of the interaction.

[0062] In this embodiment of the invention, the smoothed timeout time and smoothed retries are not fixed, but dynamically adjusted based on the latest time and retry data. This means the system continuously learns and adapts. For example, if recent interaction data shows a significant slowdown in device response speed, the system will automatically extend the smoothed waiting time to reduce the number of retries caused by premature timeouts; conversely, if the device responds quickly, the system will shorten the waiting time and retries to speed up the interaction process. This mechanism allows the system to better match the actual operating environment, avoid resource waste, and enhance the system's flexibility and adaptability.

[0063] By implementing dynamic optimization strategies and precisely controlling smoothing wait times and retries, system resources can be saved, unnecessary communication attempts reduced, and system response speed and robustness improved, while potential system failures and risks mitigated. This is crucial for the stability and efficiency of BMC management server hardware, especially in high-speed, high-concurrency, and volatile network environments.

[0064] By dynamically adjusting the smoothing wait time and smoothing retries, BMC can intelligently optimize the interaction strategy with external devices, avoiding wasting system resources on inefficient communication attempts, thereby improving overall operating efficiency and stability.

[0065] According to the above embodiments of this application, when the number of initial interaction retries is greater than or equal to a first retry number threshold and the duration of the initial interaction retry corresponding to each retry is greater than or equal to a first interaction duration threshold, the first interaction duration threshold is adjusted to obtain a second interaction duration threshold. This includes: acquiring current interaction data generated during the interaction between the baseboard management controller and the target external device; analyzing the current interaction data to obtain the current response speed of the target external device; extending the first interaction duration threshold to obtain the second interaction duration threshold when the current response speed indicates that the response speed of the target external device is slowing down; and shortening the first interaction duration threshold to obtain the second interaction duration threshold when the current response speed indicates that the response speed of the target external device is accelerating.

[0066] In this embodiment, the first interaction duration threshold can be dynamically adjusted. Based on the latest collected time data and number of interactions, the parameters are iteratively optimized to obtain an updated second interaction duration threshold. This dynamic adjustment mechanism allows the BMC to automatically adjust the timeout waiting and number of attempts according to the real-time response performance of the device, so as to adapt to the changing operating environment and improve communication efficiency and system robustness.

[0067] For example, the latest interaction data can be collected first, including response time, interaction results, and number of retries; then the data can be analyzed to identify changes in device response patterns and network conditions; then, based on the analysis results, the first interaction duration threshold can be adjusted to reflect the optimal parameters of the current environment, resulting in a second interaction duration threshold; the updated threshold parameters can be implemented to optimize the BMC's interaction strategy, reduce invalid waiting and retries caused by device anomalies or network fluctuations, and improve the overall system operating efficiency.

[0068] When device response times generally increase, the interaction duration threshold is dynamically increased to reduce the frequency of timeout checks and avoid unnecessary retries. When the system detects an abnormal state, the interaction duration threshold is adjusted to the maximum tolerance value to reassess device performance and network conditions, and data is collected to update the smoothing parameters.

[0069] According to the above embodiments of this application, when the number of initial interaction retries is greater than or equal to a first retry threshold and the duration of the initial interaction retry corresponding to each retry is greater than or equal to a first interaction duration threshold, the first retry threshold is adjusted to obtain a second interaction retry threshold. This includes: acquiring current interaction data generated during the interaction between the baseboard management controller and the target external device; analyzing the current interaction data to obtain the current average number of interaction retries; decreasing the first retry threshold when the current average number of interaction retries is less than the first retry threshold to obtain the second interaction retry threshold; and increasing the first retry threshold when the current average number of interaction retries is greater than the first retry threshold to obtain the second interaction retry threshold.

[0070] In this embodiment, the first retry threshold can be dynamically adjusted. Based on the latest collected time data and retry count data, the parameters are iteratively optimized to obtain an updated second interaction duration threshold. This dynamic adjustment mechanism allows the BMC to automatically adjust the timeout waiting and retry count according to the real-time response performance of the device to adapt to the changing operating environment and improve communication efficiency and system robustness.

[0071] For example, the latest interaction data can be collected first, including response time, interaction results, and number of retries; then the data can be analyzed to identify changes in device response patterns and network conditions; then, based on the analysis results, the first retry threshold can be adjusted to reflect the optimal parameters of the current environment, resulting in a second retry threshold; the updated threshold parameters can be implemented to optimize the BMC's interaction strategy, reduce invalid waiting and retries caused by device anomalies or network fluctuations, and improve the overall system operating efficiency.

[0072] When device response stability decreases, the retry threshold is dynamically reduced to avoid prolonged invalid communication and save system resources. When the system detects an abnormal state, the interaction duration threshold is adjusted to the maximum tolerance value to reassess device performance and network conditions, and data is collected to update smoothing parameters.

[0073] According to the above embodiments of this application, when the number of initial interaction retries is greater than or equal to a first retry number threshold and the duration of the initial interaction retry corresponding to each retry is greater than or equal to a first interaction duration threshold, the first interaction duration threshold and the first retry number threshold are adjusted to obtain a second interaction duration threshold and a second interaction retry number threshold. This includes: acquiring current interaction data generated during the interaction between the baseboard management controller and the target external device; inputting the current interaction data, the first interaction duration threshold, and the first retry number threshold into a dynamic adjustment model, so as to process the current interaction data, the first interaction duration threshold, and the first retry number threshold using the dynamic adjustment model to obtain the second interaction duration threshold and the second interaction retry number threshold, wherein the dynamic adjustment model is a model trained by machine learning using multiple sets of training data.

[0074] In this embodiment, a machine learning model is used. Inputs include current interaction data, historical interaction duration, and a retry threshold. The model outputs adjusted second interaction duration thresholds and second interaction retry thresholds. Assume the model outputs a second interaction duration threshold of 250 milliseconds and a second interaction retry threshold of 4 times.

[0075] Machine learning models can predict optimal interaction duration and retry thresholds based on historical data and real-time interaction patterns. This improves the intelligence of threshold adjustment, enhances the system's adaptability to complex environments, and further improves interaction efficiency and robustness.

[0076] According to the above embodiments of this application, triggering the baseboard management controller and the target external device to execute an abnormal recovery mechanism includes: adjusting the second interaction duration threshold to the maximum allowed interaction duration value, adjusting the second interaction retry number threshold to the maximum allowed retry number value, and controlling the baseboard management controller and the target external device to interact according to the maximum allowed interaction duration value and the maximum allowed retry number value.

[0077] In this embodiment, if the current interaction duration exceeds the second interaction duration threshold of 250 milliseconds and the retries fail after 4 attempts, the abnormal recovery mechanism is triggered.

[0078] The aforementioned anomaly recovery mechanism can help the system identify and handle abnormal interaction situations in a timely manner, avoid prolonged blocking or invalid attempts, and maintain the overall efficiency and stability of the system.

[0079] When the system fails to perform smooth retries and smooth waiting delays multiple times, it indicates that there are some disturbances in the system or external environment that exceed the current equilibrium state. The system should have the ability to adjust and get out of the abnormal state. The system can evaluate the current scenario in the most lenient mode, such as maximizing the delay time and the number of retries to observe the current system state with the maximum tolerance. In this way, the system can re-record the smooth delay parameters and smooth retry parameters required by the system within the large tolerance. If it relies on the smooth parameters to adjust slowly, it may take an abnormally long time to adjust and may never get out of this adjustment. Therefore, it is essential for the system to have the ability to adjust to abnormal states.

[0080] Figure 4 This is a flowchart of anomaly recovery according to an embodiment of this application, such as... Figure 4 As shown, if the system fails frequently, it will retry and collect data with the maximum grace period to calculate the latest smoothed data; then, it will determine whether it seriously affects the operation of the system. If so, it will skip or abandon the process.

[0081] The aforementioned "relaxed mode" is a special operating state adopted by the BMC (Baseboard Management Controller) when the system encounters a series of abnormal situations that cannot be resolved through conventional means. Its goal is to delve deeper into and understand the nature of the problem in the current environment by relaxing the restrictions on latency and retry counts for device interactions, thereby finding a solution and enabling the system to return to stable operation. The operating mechanism of the BMC in relaxed mode is explained in detail below:

[0082] 1) Increase latency and retry count: In relaxed mode, BMC adjusts the thresholds for latency and retry count to the maximum allowed value. This means that for each device interaction, BMC is willing to wait longer and, after the initial failure, is willing to make more retries until the new maximum threshold is reached.

[0083] 2) Data Collection and Analysis: During the grace period for delays and retries, the BMC continuously collects data such as device response time, interaction results, and number of retries. This data will be used to analyze the current status of devices and the network, and identify potential problems, such as increased device failure rates or abnormally increased network latency.

[0084] 3) Anomaly Root Cause Locating: By analyzing the data collected in relaxed mode, the system attempts to pinpoint the root cause of the anomaly. If device interactions still frequently fail under relaxed latency and number of attempts, this usually points to a hardware failure in the device itself or a deeper network infrastructure problem.

[0085] 4) Strategy reassessment and update: Based on the data analysis results under the relaxed mode, the system will reassess whether the current smoothing delay parameters and smoothing retry parameters are still applicable. If they are not applicable, a new strategy will be generated and these parameters will be adjusted to adapt to the current environment.

[0086] 5) Gradually return to normal mode: After the system confirms that the abnormal situation has been effectively alleviated or resolved through a series of attempts and analyses in the relaxed mode, it will gradually adjust the threshold of delay time and number of retries back to the normal level.

[0087] This process may not be completed in one step, but rather through several iterations, gradually tightening the threshold to ensure that the system can avoid potential recurrence of anomalies while restoring normal operation.

[0088] The experience and data collected under relaxed mode can help the system establish more comprehensive preventative measures and emergency response strategies to cope with similar anomalies that may occur in the future. Based on findings from relaxed mode, the system may optimize hardware configurations, adjust network parameters, or improve software code to enhance overall robustness and response speed.

[0089] The existence of the relaxed mode provides BMC with an effective means of handling extreme and unpredictable anomalies. Under normal, strict thresholds, a system may become stuck due to a series of failures, making it impossible to effectively diagnose the problem. By entering relaxed mode, the system sacrifices some efficiency in interaction in exchange for deeper fault detection opportunities, enabling timely measures to be taken to prevent the system from remaining in an abnormal state for extended periods, protecting the server from potential damage and interruption, and ensuring service continuity and user experience quality. The relaxed mode reflects the intelligence and flexibility of BMC design and is a key component for achieving dynamic reliability optimization.

[0090] According to the above embodiments of this application, triggering the baseboard management controller and the target external device to execute an abnormal recovery mechanism includes: calculating the necessary efficiency duration of the interaction between the baseboard management controller and the target external device based on a second interaction duration threshold and a second interaction retry count threshold; and skipping the interaction between the baseboard management controller and the target external device when the score of the necessary efficiency duration is greater than a predetermined score, wherein the score is calculated by the difference between the actual interaction duration and the second interaction duration threshold and the actual interaction retry count.

[0091] In this embodiment, if the current interaction duration exceeds the second interaction duration threshold of 250 milliseconds and fails after 4 retries, an exception recovery mechanism is triggered. A necessary efficiency duration score is calculated; if the score exceeds a preset value of 100, the interaction with the target device is skipped to avoid wasting resources.

[0092] When an interaction fails, the second interaction duration threshold is adjusted to the maximum allowed value of 2000 milliseconds, and the second interaction retry count threshold is adjusted to the maximum allowed value of 10 times, for a final attempt.

[0093] Simultaneously, a necessary efficiency time score is calculated. If the score exceeds a preset value of 50 (e.g., determined by calculating the square of the difference between the actual interaction time and the threshold, and the absolute value of the difference between the actual number of retries and the threshold), the device interaction is skipped to avoid wasting system resources on low-efficiency interactions. For example, the product of the deviations between the latency time and the number of retries and the ideal value can be integral = (latency time - ideal time) * (actual number of retries - 1). The threshold for the integral is determined by the system using this solution. For systems with low time sensitivity, such as some software service providers like router backends, the threshold can be larger, while for systems with high time sensitivity, such as a cooling system controller that requires timely and precise control, the threshold should be smaller.

[0094] By using a necessary efficiency duration score, the system intelligently decides whether to skip interactions, avoiding the waste of system resources on inefficient interactions. In other words, this anomaly recovery mechanism ensures that when device interactions are abnormal, it attempts to restore the connection by relaxing the threshold, while intelligently determining whether to skip inefficient interactions through the calculation of the necessary efficiency duration score, thereby improving the overall robustness and resource utilization of the system.

[0095] By dynamically adjusting the interaction duration and retry thresholds, intelligent resource management is achieved, ensuring the execution of management functions while preventing unreasonable resource consumption. Furthermore, leveraging historical data and machine learning techniques, the system can automatically adapt to changes in device status and network environment, improving its adaptability and robustness. In addition, in this embodiment, the combined effect of dynamic threshold adjustment and anomaly recovery strategies significantly improves the success rate and overall efficiency of information interaction, reduces management costs, and enhances server operation and maintenance.

[0096] Furthermore, it should be noted that in the embodiments of this application, the scoring mechanism for smooth waiting and smooth retry counts calculates the necessary efficiency time required for this type of interactive communication based on these two data points. The necessary efficiency time for this communication type is obtained by multiplying the smooth waiting time by the smooth retry count. Moreover, the necessary efficiency time score must be managed separately according to different communication types. For example, the necessary efficiency time for simple devices and complex devices cannot be simply grouped together and judged solely by the score. For instance, the interaction time between a server system's BMC and EEPROM (Electrically Erasable Programmable Read-Only Memory) is very short, perhaps only 1 millisecond, but a single communication with complex devices such as RAID cards can take 500ms. Therefore, the communication efficiency time for EEPROM and RAID cards cannot be managed under the same standard.

[0097] Here, BMC uses the necessary efficiency time as the basis for task scheduling, prioritizing the processing of device interactions with lower necessary efficiency time, thereby completing critical tasks faster and improving overall operational efficiency.

[0098] When faced with resource allocation decisions, necessary efficiency time can serve as an important indicator for measuring the priority of device interactions, helping BMC to rationally allocate limited computing resources and ensure that cost-effective tasks are executed first.

[0099] The aforementioned necessary efficiency time is used for anomaly detection. Once the interaction time of a device significantly exceeds its necessary efficiency time, the system will trigger an anomaly detection process to analyze whether device failure, network latency, or other adverse factors have occurred. Based on the anomaly detection mechanism of necessary efficiency time, BMC can quickly identify problematic devices or interactions and take corresponding intervention measures, such as skipping interactions, adjusting timeout and trial count thresholds, to avoid system bottlenecks or task blockages and reduce overall system risk.

[0100] By continuously iterating and updating the necessary efficiency time, BMC can optimize the communication strategy with each device, reducing unnecessary waiting time and retries. This dynamic adjustment of the strategy helps to complete the interaction process quickly and shorten the response time, especially for devices with a high interaction frequency, where the improvement is particularly significant, thereby significantly improving the overall communication efficiency of the system.

[0101] Furthermore, the application of necessary efficiency time also manifests in resource conservation. BMC can dynamically manage necessary efficiency time to avoid consuming excessive CPU cycles, memory, and other system resources during interactions with low-performance, low-cost devices. This efficient use of resources not only helps improve server performance but also indirectly reduces costs, power consumption, and hardware wear and tear.

[0102] Given the differences in required efficiency times for different devices and communication types, BMC adopts a categorized management strategy, setting independent required efficiency time thresholds for each type of device or communication.

[0103] This personalized management not only takes into account the characteristics of the equipment and the complexity of communication, but also better adapts to changing operating environments, ensuring the robustness and flexibility of the BMC in complex scenarios.

[0104] Furthermore, by continuously collecting and analyzing the latest time and frequency data, BMC can dynamically adjust necessary efficiency time thresholds, achieving self-learning and adaptation. This mechanism ensures that BMC can autonomously optimize management strategies based on changes in internal and external conditions without human intervention, enhancing the system's adaptability and improving its ability to cope with unknown challenges.

[0105] For example, the necessary efficiency time might be set to a few milliseconds for interactions between the BMC and simple devices on the server (such as fans); while for interactions with complex devices (such as RAID cards), it might be set to hundreds of milliseconds or even several seconds. In this way, during server operation, the BMC can quickly determine which interactions are efficient and worthwhile, and which interactions might be uneconomical due to device failure or network anomalies, based on these pre-set necessary efficiency times. This allows the BMC to adopt skip or adjustment strategies as needed, achieving maximum management effectiveness at minimal cost.

[0106] It's important to note that the system needs to have the ability to skip or abandon exceptions. This functionality primarily relies on an exception scoring mechanism, categorizing and judging exceptions. When the exception score for a certain type of communication interaction exceeds a certain limit, the system can choose to temporarily skip the interaction (this skipping could be done for a period of time, or it could be repeated after several task cycles to reduce the frequency of problematic task interactions and indirectly reduce the impact) or permanently abandon the interaction. For example, if a significant interaction exception occurs in EEPROM communication, such as exceeding the normal level by several times, the system can choose to temporarily skip the interaction, allowing other tasks to continue running. For example, in RAID card interactions, each data transaction takes more than 2 seconds to complete. Because the RAID card is located in a PCIe replaceable component slot, such a large latency results in a very high anomaly score. Furthermore, since other devices often need to communicate with each other in the PCIe slot, the system remaining on the RAID card for an extended period can pose a systemic risk. In such cases, the system can directly remove the RAID interaction task to prevent it from negatively impacting the overall system operation. Of course, these skipping and abandonment decisions must be based on system policies. For instance, in the RAID card example above, if the RAID card does not share a physical link with other devices, then it is also acceptable not to abandon the interaction during anomalies.

[0107] Furthermore, it should be noted that the interactive communication in this application embodiment includes not only the acquisition of information from the outside world, but also the management settings of the outside world, such as power settings, RAID card settings, and other scenarios.

[0108] The technical solutions provided in this application can record the abnormal times and results of interactions with server components and peripherals in real time; dynamically adjust waiting times and retry counts based on historical data, implementing a smooth waiting and smooth retry mechanism; introduce anomaly scoring judgment, identifying abnormal device states by calculating anomaly scores, and taking different management measures based on the scores; when the anomaly score reaches a preset threshold, the system automatically adjusts to the maximum tolerance mode, collects the latest data, and recalculates the smoothing parameters; finally, based on the device's anomaly score and type, decide whether to skip or abandon interactions with specific devices to ensure the efficient and stable operation of the server management firmware. This solution aims to improve the response speed and robustness of the server BMC in abnormal situations, reduce invalid waiting and retries through intelligent adjustment strategies, and enhance system management capabilities.

[0109] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method.

[0110] According to an embodiment of this application, an information interaction optimization apparatus for implementing the above-described information interaction optimization method is also provided. Figure 5 This is a schematic diagram of an information interaction optimization device according to an embodiment of this application, such as... Figure 5 As shown, the device includes: a statistics unit 501, an adjustment unit 503, a first determination unit 505, and a triggering unit 507. The information interaction optimization device will now be described.

[0111] The statistics unit 501 is used to count the number of retries of the first interaction between the baseboard management controller and the target external device when the first interaction duration between the baseboard management controller and the target external device is greater than or equal to a first interaction duration threshold.

[0112] The adjustment unit 503 is used to adjust the first interaction duration threshold and the first retry threshold when the number of first interaction retries is greater than or equal to the first retry number threshold and the duration of the first interaction retries corresponding to each retry is greater than or equal to the first interaction duration threshold, so as to obtain the second interaction duration threshold and the second interaction retries threshold.

[0113] The first determining unit 505 is used to determine that the interaction between the baseboard management controller and the target external device is abnormal when the current interaction duration between the management controller and the target external device is greater than or equal to the second interaction duration threshold and the current interaction retry count between the baseboard management controller and the target external device is greater than or equal to the second interaction retry count threshold.

[0114] Trigger unit 507 is used to trigger the baseboard management controller and the target external device to execute the abnormal recovery mechanism.

[0115] It should be noted that the above-mentioned statistical unit 501, adjustment unit 503, first determination unit 505 and triggering unit 507 correspond to steps S202 to S208 in the above embodiments. The four units and the corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in the above embodiments.

[0116] As can be seen from the above, in the scheme described in the above embodiments of this application, the statistics unit can count the number of first interaction retries between the baseboard management controller and the target external device when the first interaction duration between the baseboard management controller and the target external device is greater than or equal to the first interaction duration threshold; the adjustment unit can adjust the first interaction duration threshold and the first retry threshold when the number of first interaction retries is greater than or equal to the first retry threshold and the first interaction retry duration corresponding to each retry is greater than or equal to the first interaction duration threshold, to obtain the second interaction duration threshold and the second interaction retry threshold; the first determination unit can determine that the interaction between the baseboard management controller and the target external device is abnormal when the current interaction duration between the management controller and the target external device is greater than or equal to the second interaction duration threshold and the current interaction retries between the baseboard management controller and the target external device are greater than or equal to the second interaction retry threshold; and the triggering unit can trigger the baseboard management controller and the target external device to execute the abnormal recovery mechanism, thereby realizing the purpose of adapting to the current state of the device and the network by analyzing real-time interaction data and historical data. When external devices exhibit abnormal responses or network latency increases, the BMC relaxes thresholds, giving devices more time to respond and increasing the number of retries to improve the probability of successful interaction. Conversely, when devices respond quickly or network conditions are stable, the BMC shortens waiting times and reduces the number of retries, avoiding resource waste and improving interaction efficiency. This adaptive adjustment mechanism optimizes resource utilization and improves the overall stability and operational efficiency of the server system while maintaining the BMC's management functions.

[0117] Therefore, the technical solution provided by the embodiments of this application solves the technical problem in the related art where the Baseboard Management Controller (BMC) system uses a fixed number of retries and waiting time, which cannot adapt to abnormal scenarios, resulting in invalid waiting and retries, which may cause the system to hang up or crash.

[0118] Optionally, the information interaction optimization device further includes: a first acquisition unit, configured to acquire historical interaction information between the baseboard management controller and the target external device before counting the number of retries of the first interaction between the baseboard management controller and the target external device when the first interaction duration between the baseboard management controller and the target external device is greater than or equal to a first interaction duration threshold; a second determination unit, configured to determine the first interaction duration threshold based on the duration of multiple interaction responses with a successful interaction status in the historical interaction information; and a third determination unit, configured to determine the first retry count threshold based on the number of retries of multiple interaction responses with a successful interaction status in the historical interaction information.

[0119] Optionally, the third determining unit includes: a first deletion module, used to delete the maximum and minimum interaction response durations among multiple interaction response durations to obtain the remaining interaction response duration; a first determining module, used to determine the average interaction duration corresponding to the remaining interaction response duration; and a second determining module, used to determine a predetermined multiple of the average interaction duration as a first interaction duration threshold.

[0120] Optionally, the third determining unit includes: a second deletion module, used to delete the maximum and minimum number of interaction retries from multiple interaction retries to obtain the remaining number of interaction retries; a third determining module, used to determine the average number of interaction retries corresponding to the remaining number of interaction retries; and a fourth determining module, used to determine a predetermined multiple of the average number of interaction retries as the first retry threshold.

[0121] Optionally, the adjustment unit includes: a second acquisition unit, used to acquire current interaction data generated during the interaction between the baseboard management controller and the target external device; a first analysis unit, used to analyze the current interaction data to obtain the current response speed of the target external device; a third acquisition unit, used to extend a first interaction duration threshold to obtain a second interaction duration threshold when the current response speed indicates that the response speed of the target external device has slowed down; and a fourth acquisition unit, used to shorten the first interaction duration threshold to obtain the second interaction duration threshold when the current response speed indicates that the response speed of the target external device has accelerated.

[0122] Optionally, the adjustment unit includes: a fifth acquisition unit for acquiring current interaction data generated during the interaction between the baseboard management controller and the target external device; a second analysis unit for analyzing the current interaction data to obtain the current average number of interaction retries; a sixth acquisition unit for decreasing the first retry threshold when the current average number of interaction retries is less than the first retry threshold to obtain a second retry threshold; and a seventh acquisition unit for increasing the first retry threshold when the current average number of interaction retries is greater than the first retry threshold to obtain a second retry threshold.

[0123] Optionally, the adjustment unit includes: an eighth acquisition unit, used to acquire current interaction data generated during the interaction between the baseboard management controller and the target external device; and a ninth acquisition unit, used to input the current interaction data, a first interaction duration threshold, and a first retry count threshold into a dynamic adjustment model, so as to process the current interaction data, the first interaction duration threshold, and the first retry count threshold using the dynamic adjustment model to obtain a second interaction duration threshold and a second interaction retry count threshold, wherein the dynamic adjustment model is a model trained by machine learning using multiple sets of training data.

[0124] Optionally, the triggering unit includes: a control module, configured to adjust the second interaction duration threshold to the maximum allowed interaction duration value, adjust the second interaction retry count threshold to the maximum allowed retry count value, and control the baseboard management controller to interact with the target external device according to the maximum allowed interaction duration value and the maximum allowed retry count value.

[0125] Optionally, the triggering unit includes: a calculation module, configured to calculate the necessary efficiency duration for interaction between the baseboard management controller and the target external device based on a second interaction duration threshold and a second interaction retry count threshold; and a skip module, configured to skip the interaction between the baseboard management controller and the target external device when the score of the necessary efficiency duration is greater than a predetermined score, wherein the score is calculated by the difference between the actual interaction duration and the second interaction duration threshold and the actual interaction retry count.

[0126] According to another aspect of the embodiments of this application, an electronic device is also provided, including: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include an information interaction optimization method for performing any of the above.

[0127] According to another aspect of the embodiments of this application, a processor is also provided, which is used to run a program, wherein the program executes any of the above-described information interaction optimization methods during runtime.

[0128] According to another aspect of the embodiments of this application, a computer program product is also provided, including computer instructions, which, when executed by a processor, perform any of the above-described information interaction optimization methods.

[0129] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein the program executes the information interaction optimization method of any one of the above.

[0130] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0131] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0132] The above provides a detailed description of the information interaction optimization method provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and its core ideas. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from its principles, and these improvements and modifications also fall within the protection scope of the claims of this application.

Claims

1. An information interaction optimization method, characterized in that, include: When the first interaction duration between the baseboard management controller and the target external device is greater than or equal to the first interaction duration threshold, the number of retries for the first interaction between the baseboard management controller and the target external device is counted. When the number of first interaction retries is greater than or equal to the first retry number threshold and the duration of the first interaction retry corresponding to each retry is greater than or equal to the first interaction duration threshold, the first interaction duration threshold and the first retry number threshold are adjusted to obtain the second interaction duration threshold and the second interaction retry number threshold. When the current interaction duration between the management controller and the target external device is greater than or equal to the second interaction duration threshold, if the current interaction retry count between the baseboard management controller and the target external device is greater than or equal to the second interaction retry count threshold, it is determined that the interaction between the baseboard management controller and the target external device is abnormal. Trigger the abnormal recovery mechanism of the baseboard management controller and the target external device; Wherein, when the number of initial interaction retries is greater than or equal to a first retry number threshold and the duration of the initial interaction retry corresponding to each retry is greater than or equal to a first interaction duration threshold, the first interaction duration threshold is adjusted to obtain a second interaction duration threshold, including: Acquire the current interaction data generated during the interaction between the baseboard management controller and the target external device; The current interaction data is analyzed to obtain the current response speed of the target external device; When the current response speed indicates that the response speed of the target external device has slowed down, the first interaction duration threshold is extended to obtain the second interaction duration threshold; When the current response speed indicates that the response speed of the target external device has increased, the first interaction time threshold is shortened to obtain the second interaction time threshold; Wherein, when the number of initial interaction retries is greater than or equal to a first retry number threshold and the duration of the initial interaction retry corresponding to each retry is greater than or equal to the first interaction duration threshold, the first retry number threshold is adjusted to obtain a second interaction retry number threshold, including: Acquire the current interaction data generated during the interaction between the baseboard management controller and the target external device; The current interaction data is analyzed to obtain the current average number of interaction retries; When the current average number of interaction retries is less than the first retry threshold, the first retry threshold is reduced to obtain the second interaction retry threshold; When the current average number of interaction retries is greater than the first retry threshold, the first retry threshold is increased to obtain the second interaction retry threshold.

2. The information interaction optimization method according to claim 1, characterized in that, Before counting the number of retries for the first interaction between the baseboard management controller and the target external device when the initial interaction duration is greater than or equal to a first interaction duration threshold, the information interaction optimization method further includes: Obtain historical interaction information between the baseboard management controller and external devices; The first interaction duration threshold is determined based on the duration of multiple successful interaction responses in the historical interaction information. The first retry threshold is determined based on the number of retries for multiple interactions with a successful interaction status in the historical interaction information.

3. The information interaction optimization method according to claim 2, characterized in that, The first interaction duration threshold is determined based on the durations of multiple successful interaction responses in the historical interaction information, including: Delete the maximum and minimum interaction response durations from the multiple interaction response durations to obtain the remaining interaction response durations; Determine the average interaction duration corresponding to the remaining interaction response duration; A predetermined multiple of the average interaction duration is determined as the first interaction duration threshold.

4. The information interaction optimization method according to claim 2, characterized in that, The first retry threshold is determined based on the number of retries for multiple interactions with a successful interaction status in the historical interaction information, including: Remove the maximum and minimum number of interaction retries from the multiple interaction retries to obtain the remaining number of interaction retries; Determine the average number of interaction retries corresponding to the remaining number of interaction retries; A predetermined multiple of the average number of interaction retries is determined as the first retry threshold.

5. The information interaction optimization method according to claim 1, characterized in that, When the number of initial interaction retries is greater than or equal to a first retry number threshold and the duration of the initial interaction retry corresponding to each retry is greater than or equal to a first interaction duration threshold, the first interaction duration threshold and the first retry number threshold are adjusted to obtain a second interaction duration threshold and a second interaction retry number threshold, including: Acquire the current interaction data generated during the interaction between the baseboard management controller and the target external device; The current interaction data, the first interaction duration threshold, and the first retry count threshold are input into the dynamic adjustment model to process the current interaction data, the first interaction duration threshold, and the first retry count threshold using the dynamic adjustment model to obtain the second interaction duration threshold and the second interaction retry count threshold. The dynamic adjustment model is a model trained by machine learning using multiple sets of training data.

6. The information interaction optimization method according to any one of claims 1 to 5, characterized in that, Triggering the abnormal recovery mechanism of the baseboard management controller and the target external device includes: The second interaction duration threshold is adjusted to the maximum allowed interaction duration value, and the second interaction retry number threshold is adjusted to the maximum allowed retry number value. The baseboard management controller is then controlled to interact with the target external device according to the maximum allowed interaction duration value and the maximum allowed retry number value.

7. The information interaction optimization method according to any one of claims 1 to 5, characterized in that, Triggering the abnormal recovery mechanism of the baseboard management controller and the target external device includes: The necessary efficiency duration for the interaction between the baseboard management controller and the target external device is calculated based on the product of the second interaction duration threshold and the second interaction retry number threshold. When the score for the necessary efficiency duration is greater than a predetermined score, the interaction between the baseboard management controller and the target external device is skipped. The score is calculated by multiplying the difference between the delay time and the ideal time by the actual number of interaction retries.

8. An electronic device, characterized in that, include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including methods for performing the information interaction optimization method according to any one of claims 1 to 7.

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