Server hardware state monitoring method and electronic equipment

Abstract

The invention discloses a server hardware state monitoring method and electronic equipment, and relates to the technical field of server hardware monitoring, distributed agent nodes are deployed in a server according to physical partitions, and the agent nodes are provided with monitoring agent programs. Accurate acquisition of slave device data is realized by utilizing an agent node through an internal integrated circuit bus, a bus load rate is monitored in real time by adopting a monitoring agent program, and the acquired data is correspondingly processed according to the bus load rate and then uploaded to a management controller, so that data acquisition and processing tasks are undertaken through the distributed agent node; the system response efficiency is greatly improved, the management controller does not need to poll all slave devices, and the problem that polling time is too long due to the fact that the number of device nodes is too large is effectively solved; and the bus load is reasonably distributed, so that the centralized data transmission pressure is reduced, the data transmission conflict phenomenon caused by excessive bus mounting equipment is avoided, and the performance limitation of centralized monitoring is broken through.

Description

Technical Field

[0001] The present invention relates to the technical field of server hardware monitoring, and in particular to a server hardware status monitoring method and electronic equipment. Background Art

[0002] Server systems typically connect various external devices via serial communication. This typically employs a two-wire design, supporting a multi-master / multi-slave architecture, enabling shared access and data transmission across the same line. However, when a centralized management controller is used to connect various devices via a single line, the line load increases significantly as the number of connected devices increases, leading to response delays and reduced data transmission efficiency. Large numbers of devices can also lead to data transmission conflicts and prolonged polling times. Summary of the Invention

[0003] The present invention provides a server hardware status monitoring method and electronic device, which at least solve the problems of low data transmission efficiency, easy occurrence of data transmission conflicts and long polling time in related technologies.

[0004] The present invention provides a server hardware status monitoring method, wherein distributed proxy nodes are deployed inside the server according to physical partitions, and the proxy nodes are provided with a monitoring agent program; the server hardware status monitoring method comprises: After the proxy node is connected to the corresponding slave device, using the proxy node to collect the corresponding slave device data through the internal integrated circuit bus; Using the monitoring agent program to monitor the load rate of the internal integrated circuit bus; According to the load rate of the internal integrated circuit bus, the agent node is used to process the collected slave device data accordingly, and the processed data is uploaded to the management controller.

[0005] The present invention also provides an electronic device, comprising: a memory for storing a computer program; and a processor for implementing the steps of any of the above-mentioned server hardware status monitoring methods when executing the computer program.

[0006] Through the present invention, since the server is internally deployed with distributed proxy nodes according to physical partitions, the proxy nodes are provided with monitoring agent programs, and the proxy nodes are used to realize accurate collection of slave device data through the internal integrated circuit bus. The monitoring agent program is used to monitor the bus load rate in real time and perform targeted processing on the collected data before uploading it to the management controller. In this way, not only the distributed proxy nodes are used to undertake data collection and processing tasks, the system response efficiency is greatly improved, the management controller does not need to poll all slave devices, and only needs to access the proxy nodes to obtain the required data, effectively solving the problem of long polling time caused by too many device nodes; it also avoids the data transmission conflict caused by too many bus-mounted devices by reasonably allocating bus loads and reducing the pressure of centralized data transmission, breaking through the performance limitations of centralized monitoring. Under this distributed collaborative architecture, the system can give full play to the local data processing capabilities of each proxy node, significantly enhance the overall scalability and real-time response capabilities, and perfectly adapt to server application scenarios with strict requirements for hardware status monitoring. It is especially suitable for the actual needs of the increasingly complex server operating environment, and the whole process will not affect the integrity of the distributed system.

[0007] In addition, the present invention also provides a corresponding electronic device for the server hardware status monitoring method, which has the same or corresponding technical features as the above-mentioned server hardware status monitoring method and has the same effect as above. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the embodiments of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0009] Figure 1 A flowchart of a server hardware status monitoring method provided by an embodiment of the present invention; Figure 2 A schematic diagram of the architecture corresponding to the server hardware status monitoring method provided by an embodiment of the present invention; Figure 3 A signaling interaction diagram between a management controller, a master-slave agent node, and a slave device provided in an embodiment of the present invention; Figure 4 A schematic diagram of the relationship between the management controller, master-slave proxy nodes and slave devices provided in an embodiment of the present invention; Figure 5 This is a structural diagram of a server hardware status monitoring device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0010] In computer hardware design systems, the internal integrated circuit bus, as a serial communication protocol with low cost and low power consumption, has been widely used. It is mainly used to connect and manage key hardware components and realize low-speed control and status monitoring between devices. However, because all sensors share a single internal integrated circuit bus (e.g., a bandwidth of only 100-400Kbps), when the number of monitoring devices (e.g., greater than 20) reaches a certain scale, the bus utilization rate will climb to a high level (e.g., greater than 90%). At the same time, its multi-master device sharing bus feature is prone to bus conflicts and operational failures. In the traditional centralized architecture model, if the master node or the bus itself fails, it will directly cause the entire monitoring system to become paralyzed. The present invention provides a server hardware status monitoring method that can solve the above problems.

[0011] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0012] It should be noted that, in the description of the present invention, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. The terms "first," "second," etc., in the present invention are used to distinguish similar objects, and are not used to describe a particular order or precedence.

[0013] In order to enable those skilled in the art to better understand the solutions of the present invention, the present invention is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0014] In conjunction with the specific application environment architecture or specific hardware architecture on which the execution of the server hardware status monitoring method depends, the specific application environment architecture or specific hardware architecture is described herein.

[0015] An embodiment of the present invention provides a server hardware status monitoring method. Distributed agent nodes are deployed inside the server according to physical partitions. The agent nodes are provided with a monitoring agent program. The method is described in detail in conjunction with the execution process of the server hardware status monitoring method. Figure 1 The flowchart of the server hardware status monitoring method provided by the embodiment of the present invention is as follows Figure 1 As shown, the method includes: S101 : After the proxy node is connected to the corresponding slave device, the proxy node is used to collect data of the corresponding slave device through an internal integrated circuit bus.

[0016] It should be noted that the present invention is aimed at scenarios where the server environment is becoming increasingly complex. Distributed proxy nodes are deployed within the server according to physical partitions. The distributed proxy nodes are used to collect and report slave device data. Each proxy node can connect to a corresponding slave device, and the connection to the corresponding slave device is through an internal integrated circuit bus. This can avoid the defect of low efficiency of sequential access by the master device, solve the problem of long device polling time caused by too many device nodes, and avoid data conflicts caused by too many bus devices. Through the deployment of distributed proxy nodes, the present invention upgrades the traditional centralized monitoring architecture to a distributed collaborative mode, which not only retains the low power consumption and easy deployment characteristics of the internal integrated circuit bus, but also improves the system scalability and real-time performance through the local processing capabilities of the proxy nodes. It is suitable for server scenarios with high requirements for hardware status monitoring.

[0017] S102: Use a monitoring agent program to monitor the load rate of the internal integrated circuit bus.

[0018] In practical applications, the present invention can install a monitoring agent program in each proxy node. The monitoring agents installed in each proxy node can communicate with each other based on relevant protocols, aggregate monitoring data, and monitor the load rate of the internal integrated circuit bus. The load rate of the internal integrated circuit bus directly reflects the busyness of the communication channel. When the load rate is too high, indiscriminate data upload may exacerbate bus congestion, resulting in the delay or loss of critical information. On the other hand, when the load rate is low, the rational use of bandwidth can improve the timeliness of data transmission.

[0019] S103 : Based on the load rate of the internal integrated circuit bus, the proxy node is used to process the collected slave device data accordingly, and the processed data is uploaded to the management controller.

[0020] In summary, the present invention uses proxy nodes to perform targeted processing on data collected from devices based on the load rate of the internal integrated circuit bus and upload it to the management controller. As an intermediate processing link, the proxy node can dynamically adjust the data processing strategy based on the real-time monitoring of the bus load rate. Through the dynamic processing and scheduling of the proxy node, communication resources can be flexibly allocated according to the actual bus load, effectively reducing the risk of bus overload and minimizing data transmission conflicts and delays. Simultaneously, the processed and streamlined data reduces the reception and calculation pressure on the management controller, improving the overall efficiency of the data processing link.

[0021] In the above-mentioned server hardware status monitoring method provided by the embodiment of the present invention, since the server is internally deployed with distributed proxy nodes according to physical partitions, the proxy nodes are provided with a monitoring agent program, and the proxy nodes are used to realize accurate collection of slave device data through the internal integrated circuit bus, and the monitoring agent program is used to monitor the bus load rate in real time and perform targeted processing on the collected data before uploading it to the management controller. In this way, not only the distributed proxy nodes undertake data collection and processing tasks, greatly improving the system response efficiency, but also the management controller does not need to poll all slave devices, but only needs to access the proxy nodes to obtain the required data, effectively solving the problem of long polling time caused by too many device nodes; and by reasonably allocating the bus load and reducing the pressure of centralized data transmission, the data transmission conflict caused by too many bus-mounted devices is avoided, breaking through the performance limitations of centralized monitoring. Under this distributed collaborative architecture, the system can give full play to the local data processing capabilities of each proxy node, significantly enhance the overall scalability and real-time response capabilities, and perfectly adapt to server application scenarios with strict requirements for hardware status monitoring, especially suitable for the actual needs of the increasingly complex server operating environment, and the whole process will not affect the integrity of the distributed system.

[0022] Furthermore, in specific implementation, in the above-mentioned server hardware status monitoring method provided in an embodiment of the present invention, distributed agent nodes are deployed inside the server according to physical partitions, which may specifically include: the server is divided into multiple physical partitions according to hardware functions, layout and heat dissipation requirements; the physical partitions include processor areas, storage areas, power supply areas and fan areas; and distributed agent nodes are deployed in the divided physical partitions.

[0023] In practice, physical partitions are not external units independent of the server, but rather physical sub-areas within the server divided according to hardware functionality, layout, or cooling requirements. For example, the processor zone corresponds to the installation area of ​​the server's processor and surrounding core computing components; the storage zone corresponds to the deployment space for storage devices such as hard drives and solid-state drives; and the power zone is the independent area where the power modules and power supply circuits are located. These physical partitions together constitute the overall hardware structure of the server and are subdivided components of the server's physical entity.

[0024] This invention divides the server into physical partitions—processor, storage, power, and fan zones—based on hardware functions, layout, and cooling requirements. Distributed proxy nodes are deployed within each partition. By defining functional boundaries, physical partitioning allows for targeted optimization of cooling designs for each zone (e.g., configuring independent air ducts for the high-heat-producing processor and power zones), reducing thermal interference between different hardware modules, lowering the risk of local overheating, and ensuring stable hardware operation. Furthermore, the partitioned layout facilitates centralized management and maintenance of hardware resources. The deployment of distributed proxy nodes within each partition enables accurate, real-time monitoring of hardware status within the partition (e.g., processor load, storage read / write speed, power supply voltage, fan speed, etc.), avoiding the limitations and latency of single-node monitoring. This architecture not only improves the reliability and cooling efficiency of server hardware through physical partitioning, but also enhances the ability to perceive the status of each zone through distributed proxy nodes.

[0025] Figure 2 Schematic diagram of the architecture corresponding to the server hardware status monitoring method provided by the embodiment of the present invention. Figure 2 As shown, multiple proxy nodes can be connected to the management controller. Each proxy node can be connected to a corresponding sensor. For example, the first sensor can be a central processing unit (CPU) sensor, the second sensor can be a memory sensor, and the third sensor can be a graphics processing unit (GPU) sensor. The proxy nodes collect data from each sensor, perform preliminary processing, and then transmit it to the management controller. This eliminates the need for the management controller to poll all slave devices, allowing the server to expand the number of monitoring slave nodes.

[0026] Furthermore, in a specific implementation, in the above-mentioned server hardware status monitoring method provided in an embodiment of the present invention, step S102 uses a monitoring agent program to monitor the load rate of the internal integrated circuit bus, which may specifically include: using a monitoring agent program to obtain the effective working time of the internal integrated circuit bus within a set statistical period; obtaining the load rate of the internal integrated circuit bus based on the ratio between the obtained effective working time of the internal integrated circuit bus within the set statistical period and the set statistical period.

[0027] In practice, the load rate of the inter-IC bus can be obtained using the following formula: L = (T_active / T_total) × 100%; Where L is the load rate of the internal integrated circuit bus, T_active is the effective operating time of the internal integrated circuit bus within a set statistical period (i.e., the low level time of the serial clock line), and T_total is the set statistical period. The present invention can directly collect bus timing data from the internal integrated circuit bus state machine register of the microcontroller unit (MCU) to obtain T_active, thereby achieving real-time monitoring and dynamic control of the bus load rate.

[0028] Furthermore, in a specific implementation, in the above-mentioned server hardware status monitoring method provided in an embodiment of the present invention, step S103 uses a proxy node to perform corresponding processing on the collected slave device data according to the load rate of the internal integrated circuit bus, which may specifically include: using the proxy node to perform corresponding filtering processing on the collected slave device data through a built-in algorithm according to the load rate of the internal integrated circuit bus; identifying unexpected states on the slave device data after filtering to obtain data characteristics of the unexpected states; and compressing the data characteristics of the unexpected states.

[0029] In practice, this invention utilizes proxy nodes to perform targeted filtering of collected slave device data using a built-in algorithm based on the load rate of the inter-IC bus. The filtered data is then identified for unexpected conditions, and its characteristics are extracted and compressed. After locally filtering, detecting anomalies, and compressing the sensor data, the proxy node transmits only valid data or abnormal events to the management controller. Furthermore, this invention supports sensor-triggered alarms (e.g., sudden temperature rise). The proxy node reports emergency data directly via interrupts, without waiting for polling from the master node. This significantly reduces fault response time compared to traditional solutions. The proxy node possesses hardware-level arbitration capabilities for the inter-IC bus, enabling priority-preemptive communication. This local data processing and selective transmission significantly reduces bus data volume, alleviates high load pressure, and improves bus communication efficiency. The active alarm and interrupt reporting mechanism enhances the system's response to emergencies and improves the timeliness of fault resolution. Hardware-level arbitration and priority communication ensure the transmission priority of critical data, preventing core information delays caused by bus congestion, and comprehensively improving the reliability and real-time performance of the inter-IC bus in multi-device collaboration scenarios.

[0030] Furthermore, in a specific implementation, in the server hardware status monitoring method provided in an embodiment of the present invention, when the slave device is a temperature sensor, step S101 may include using a proxy node to collect data from the corresponding slave device via an inter-IC bus. This may specifically include using the proxy node to collect temperature sensor data at set time intervals via the inter-IC bus. For example, the temperature sensor may sample 10 times per second, and the proxy node may only report when the temperature change exceeds a threshold, reducing the amount of bus data by over 80%.

[0031] Correspondingly, in the above steps, the unexpected state of the slave device data after filtering is identified, which may specifically include: comparing the temperature sensor data after filtering; if the temperature sensor data is higher than the first preset temperature threshold or lower than the second preset temperature threshold, the temperature sensor data is determined to be in an unexpected state; if the temperature sensor data is between the second preset temperature threshold and the first preset temperature threshold but changes suddenly within the set time period, the temperature sensor data is determined to be in an unexpected state; if the temperature sensor data is between the second preset temperature threshold and the first preset temperature threshold and does not change suddenly within the set time period, the temperature sensor data is determined to be in an expected state.

[0032] During implementation, the filtered temperature sensor data is compared and judged in multiple dimensions. When the data exceeds the upper limit of the first preset temperature threshold or is lower than the lower limit of the second preset temperature threshold, it is directly judged to be abnormal. Even if the data is within the threshold range, if a sudden change occurs within the set time period, it is still judged to be an unexpected state. Only when the data is stable in the threshold range and there is no sudden change is it considered to be an expected state. In this way, through the monitoring of threshold boundaries and dynamic time dimensions, comprehensive coverage of temperature anomalies is achieved, which not only avoids the risks caused by data exceeding the safety range without being detected, but also can timely capture abnormal fluctuations within the threshold (such as a sudden temperature rise before a sudden equipment failure), greatly improving the accuracy and sensitivity of anomaly identification; and accurate status judgment can reduce invalid data uploads, so that the system only focuses on the processing and response of unexpected status information, reducing bus transmission pressure and main controller computing load, while providing a reliable basis for equipment fault warning and abnormal tracing.

[0033] Furthermore, in the specific implementation, in the above steps, according to the load rate of the internal integrated circuit bus, the proxy node is used to perform corresponding filtering processing on the collected slave device data through the built-in algorithm, including: when the load rate of the internal integrated circuit bus exceeds the first preset load rate threshold, the proxy node is used to perform targeted filtering processing on the collected slave device data through the built-in algorithm to filter out non-critical data in the corresponding range; when the load rate of the internal integrated circuit bus is lower than the second preset load rate threshold, it enters sleep mode.

[0034] In implementation, the present invention can execute differentiated data processing strategies for the load rate of the internal integrated circuit bus: when the load rate exceeds a first preset load rate threshold (such as >80%), the emergency mode is immediately triggered, and the data collected from the device is targeted filtered through the built-in algorithm of the proxy node, and non-critical data is discarded first to reduce the bus transmission pressure, thereby ensuring the continuity and reliability of core data communication; when the load rate is less than a second preset load rate threshold (such as ≤30%), the system maintains the current operating state and can enter sleep mode according to energy consumption optimization requirements; when the load rate is between the first preset load rate threshold and the second preset load rate threshold (that is, 30%<load rate≤80%), the normal monitoring mechanism is started to ensure efficient utilization of bus resources by optimizing the data sampling frequency.

[0035] Furthermore, in a specific implementation, in the above-mentioned server hardware status monitoring method provided by an embodiment of the present invention, each agent node includes a master agent node and a slave agent node.

[0036] In step S101, the proxy node is used to collect corresponding slave device data through the internal integrated circuit bus. In step S103, the proxy node is used to perform corresponding processing on the collected slave device data. Specifically, the process may include: using the master proxy node to collect corresponding slave device data through the internal integrated circuit bus, and using the master proxy node to perform corresponding processing on the collected slave device data. At this time, the slave proxy node is in a dormant state; when the management controller detects that the heartbeat signal of the master proxy node fails, an activation instruction is sent to the slave proxy node, and the slave proxy node executes data collection tasks and data processing tasks after being activated.

[0037] Figure 3 The signaling interaction diagram between the management controller, master-slave agent node and slave device provided in the embodiment of the present invention. Figure 3 As shown, the proxy nodes can adopt a dual-node redundant design. While the master proxy node is operating normally, the slave proxy nodes are dormant, with the master node responsible for all data collection and processing. The dormant slave nodes reduce system energy consumption, while the master node's operation ensures stable and efficient data processing. The management controller continuously monitors the master proxy node's regular heartbeat signals. If an abnormal heartbeat signal is detected (indicating a master proxy node failure), it immediately sends an activation command to the slave proxy node, causing it to switch to an active state and take over data collection and processing tasks. This enables seamless switching between data collection and processing, avoiding data interruptions or business stagnation caused by single points of failure, significantly improving the system's fault tolerance and operational reliability.

[0038] Furthermore, in a specific implementation, in the above-mentioned server hardware status monitoring method provided in an embodiment of the present invention, while executing data collection tasks and data processing tasks after the slave agent node is activated, it can also include: performing a reset operation on the master agent node; if the master agent node recovers, the management controller switches back to the master agent node in the next collection cycle to execute data collection tasks and data processing tasks, and sends a sleep instruction to the slave agent node.

[0039] During implementation, the present invention can reset the master agent node while taking over data collection and processing tasks from the slave agent node. If the master agent node returns to normal operation after the reset, the management controller will automatically switch back to the master agent node for data collection during the next collection cycle. If the master agent node cannot resume normal operation, the system will proactively report the fault information and wait for human intervention.

[0040] Furthermore, in specific implementation, the deployment of distributed agent nodes may specifically include: using an independent power supply mechanism to deploy each agent node; wherein, the agent node integrates a main control microcontroller unit and a power module; the power module provides power supply for the agent node; at the same time, the main control microcontroller unit controls the agent node to interact with data and coordinates the data collection tasks and data processing tasks of the agent node.

[0041] In practice, distributed proxy nodes can use independent power supplies and communication links. A single proxy node failure only impacts the local sensor area, while other nodes continue to operate normally. For example, a failure in the proxy node corresponding to a power module will not affect the monitoring of the processor cooling zone.

[0042] Figure 4 Schematic diagram of the relationship between the management controller, master-slave agent nodes and slave devices provided in the embodiment of the present invention. Figure 4As shown, agent nodes are divided into master and slave nodes. Both master and slave nodes perform data collection and contain a master control module (optionally an MCU module) and a power supply module to ensure their operation. Both master and slave nodes can exchange data with slave devices (including Device 1, Device 2, Device 3, and Device 4) through upper and lower interfaces. Due to their close physical proximity to the slave devices and their focused data collection objectives, they achieve low-load, high-response data acquisition. The master control module supports direct execution of hardware control policies. For example, if it detects a high processor temperature, it can immediately respond and trigger countermeasures such as processor frequency reduction. It also reports this information to the basic management controller for aggregated feedback, improving responsiveness. This standardized configuration of master and slave agent nodes ensures stable and consistent data collection and enhances data acquisition efficiency. The master control module's local hardware control capabilities significantly shorten exception response time, avoid delays caused by reliance on upper-level controller decisions, and enhance the ability to quickly resolve device failures.

[0043] The server hardware status monitoring method provided by the present invention is described below with a specific example: Taking the 8-GPU node as an example, the hardware deployment adopts a partitioned agent node architecture: agent node 1 is deployed in the power area to monitor the power module; agent node 2 is deployed in the CPU area to monitor the CPU and memory temperature; agent node 3 is deployed in the GPU area to monitor the core and video memory temperature of the 8 GPUs; agent node 4 is deployed in the storage area to monitor the solid-state drive and backplane temperature; agent node 5 is deployed in the fan area to monitor the fan node status.

[0044] The above architecture uses distributed proxy nodes to achieve data collection and localized management of slave devices in each partition. The relevant data does not need to be centrally aggregated to the Baseboard Management Controller (BMC) for processing, which significantly improves response efficiency. At the same time, the BMC does not need to poll all slave devices and only needs to interact with each proxy node to obtain the global status, which greatly reduces its own load pressure. In addition, because each proxy node monitors a single device, it can perform targeted collection optimization based on the device characteristics, improving data collection efficiency; when an abnormality occurs in the device, it can achieve rapid response and localized handling. For example, when the GPU overheats, proxy node 3 can immediately perform a frequency reduction operation and simultaneously report the overtemperature event to the BMC. After receiving the information, the BMC sends a command to proxy node 5 to increase the fan speed, forming a coordinated and linked abnormality handling mechanism to ensure stable node operation.

[0045] When a master agent node fails, the BMC detects through the heartbeat detection mechanism that the master agent node has not returned a heartbeat signal. After actively querying and confirming that it is unresponsive, it will immediately activate the slave agent node, which will take over the data collection task to ensure business continuity. At the same time, the BMC restarts the master agent node. If the master agent node returns to normal after the restart, the BMC will automatically switch to the master agent node in the next collection cycle and put the slave agent node into standby mode. This seamless switching mechanism ensures that the data collection process is not interrupted. If the master agent node still cannot be restored after the restart, the slave agent node will be maintained in operation until the fault is eliminated. This process achieves high availability of the agent node redundant architecture through clear fault detection, switching, and recovery logic.

[0046] The proxy node has the ability to monitor its own load data in real time and execute dynamic control strategies accordingly: when the load data is lower than 30%, it automatically switches to sleep mode and reduces energy consumption by reducing the sampling frequency; if the load data suddenly climbs above 80%, the proxy node will start the data priority screening mechanism, discard non-critical data such as manufacturer information, and extend each round of sampling cycle to alleviate load pressure, and report the abnormal status to the BMC. After receiving the information, the BMC triggers the prompt mechanism, and manual intervention is performed to determine whether the phenomenon is a temporary fluctuation, an abnormal working condition, or a potential server failure, so as to take targeted measures. This dynamic load management mechanism not only achieves energy efficiency optimization, but also ensures the effective transmission of core data in high-load scenarios through hierarchical response, and at the same time improves the accuracy of abnormal handling by combining manual decision-making.

[0047] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method.

[0048] The embodiment of the present invention further provides a server hardware status monitoring device, wherein distributed agent nodes are deployed inside the server according to physical partitions, and the agent nodes are provided with monitoring agent programs. Figure 5 This is a schematic diagram of the structure of the server hardware status monitoring device provided by the embodiment of the present invention. This embodiment is based on the perspective of functional modules, such as Figure 5 As shown, the device includes: The data acquisition module 11 is used to collect the corresponding slave device data through the internal integrated circuit bus using the proxy node after the proxy node is connected to the corresponding slave device; A load rate monitoring module 12, configured to monitor the load rate of the internal integrated circuit bus using a monitoring agent program; The data processing module 13 is used to process the collected slave device data using the proxy node according to the load rate of the internal integrated circuit bus, and upload the processed data to the management controller.

[0049] In the above-mentioned server hardware status monitoring device provided by the embodiment of the present invention, distributed proxy nodes are deployed inside the server according to physical partitions, and the proxy nodes are provided with monitoring agent programs. The proxy nodes are used to realize accurate collection of slave device data through the internal integrated circuit bus, and the monitoring agent program is used to monitor the bus load rate in real time and perform targeted processing on the collected data before uploading it to the management controller. In this way, not only the distributed proxy nodes are used to undertake data collection and processing tasks, which greatly improves the system response efficiency, but the management controller does not need to poll all slave devices, but only needs to access the proxy nodes to obtain the required data, which effectively solves the problem of long polling time caused by too many device nodes; it also avoids the data transmission conflict caused by too many bus-mounted devices by reasonably allocating bus loads and reducing the pressure of centralized data transmission, breaking through the performance limitations of centralized monitoring. Under this distributed collaborative architecture, the local data processing capabilities of each proxy node can be fully utilized, significantly enhancing the overall scalability and real-time response capabilities, and perfectly adapting to server application scenarios with strict requirements for hardware status monitoring. It is especially suitable for the actual needs of the increasingly complex server operating environment without affecting the integrity of the distributed system.

[0050] Since the embodiments of the server hardware status monitoring device correspond to the embodiments of the server hardware status monitoring method, the description of the features of the corresponding embodiments of the server hardware status monitoring device can be found in the description of the corresponding embodiments of the server hardware status monitoring method, and will not be repeated here. The embodiments of the server hardware status monitoring device have the same beneficial effects as the aforementioned server hardware status monitoring method.

[0051] Furthermore, in the specific implementation, in the above-mentioned server hardware status monitoring device provided in the embodiment of the present invention, the server is divided into multiple physical partitions according to the hardware functions, layout and heat dissipation requirements; the physical partitions include processor area, storage area, power supply area and fan area; and distributed agent nodes are deployed in the divided physical partitions.

[0052] Furthermore, in specific implementation, in the above-mentioned server hardware status monitoring device provided in an embodiment of the present invention, the load rate monitoring module 12 can be specifically used to adopt a monitoring agent program to obtain the effective working time of the internal integrated circuit bus within a set statistical period; based on the ratio between the obtained effective working time of the internal integrated circuit bus within the set statistical period and the set statistical period, the load rate of the internal integrated circuit bus is obtained.

[0053] Furthermore, in specific implementation, in the above-mentioned server hardware status monitoring device provided in an embodiment of the present invention, the data processing module 13 can be specifically used to perform corresponding filtering processing on the collected slave device data using the proxy node through the built-in algorithm according to the load rate of the internal integrated circuit bus; perform unexpected state identification on the slave device data after filtering to obtain data characteristics of the unexpected state; and perform compression processing on the data characteristics of the unexpected state.

[0054] Furthermore, in specific implementation, in the above-mentioned server hardware status monitoring device provided in an embodiment of the present invention, when the slave device is a temperature sensor, the data acquisition module 11 can be specifically used to use the proxy node to collect data from the temperature sensor at set time intervals through the internal integrated circuit bus.

[0055] Correspondingly, the data processing module 13 can be specifically used to compare the temperature sensor data after filtering; if the temperature sensor data is higher than the first preset temperature threshold or lower than the second preset temperature threshold, the temperature sensor data is determined to be in an unexpected state; if the temperature sensor data is between the second preset temperature threshold and the first preset temperature threshold but changes suddenly within the set time period, the temperature sensor data is determined to be in an unexpected state; if the temperature sensor data is between the second preset temperature threshold and the first preset temperature threshold and does not change suddenly within the set time period, the temperature sensor data is determined to be in an expected state.

[0056] The data processing module 13 can be specifically used to use the proxy node to perform targeted filtering on the collected slave device data through the built-in algorithm when the load rate of the internal integrated circuit bus exceeds the first preset load rate threshold, filtering out non-critical data in the corresponding range; when the load rate of the internal integrated circuit bus is lower than the second preset load rate threshold, it enters sleep mode.

[0057] Furthermore, in a specific implementation, in the above-mentioned server hardware status monitoring device provided in an embodiment of the present invention, each agent node includes a master agent node and a slave agent node. The data acquisition module 11 can be specifically used to use the master agent node to collect corresponding slave device data through the internal integrated circuit bus. The data processing module 13 can be specifically used to use the master agent node to perform corresponding processing on the collected slave device data; the slave agent node is in a dormant state; when the management controller detects that the heartbeat signal of the master agent node fails, it sends an activation instruction to the slave agent node, and the slave agent node executes data acquisition tasks and data processing tasks after activation. After the slave agent node is activated, while executing the data acquisition tasks and data processing tasks, it performs a reset operation on the master agent node; if the master agent node recovers, the management controller switches back to the master agent node in the next acquisition cycle to execute the data acquisition tasks and data processing tasks, and sends a dormancy instruction to the slave agent node.

[0058] Furthermore, in specific implementation, in the above-mentioned server hardware status monitoring device provided in an embodiment of the present invention, an independent power supply mechanism is adopted to deploy each agent node; wherein, the agent node integrates a main control micro control unit and a power supply module; the power supply module provides power supply for the agent node; at the same time, the main control micro control unit controls the agent node to perform data interaction and coordinates the data collection tasks and data processing tasks of the agent node.

[0059] An embodiment of the present invention further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any of the above server hardware status monitoring method embodiments.

[0060] An embodiment of the present invention further provides a computer-readable storage medium, in which a computer program is stored. The computer program is configured to execute the steps of any of the above-mentioned server hardware status monitoring method embodiments when running.

[0061] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk, or an optical disk.

[0062] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of any of the above-mentioned server hardware status monitoring method embodiments are implemented.

[0063] An embodiment of the present invention also provides another computer program product, including a non-volatile computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of any of the above-mentioned server hardware status monitoring method embodiments.

[0064] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0065] The above is a detailed introduction to a server hardware status monitoring method and electronic device provided by the present invention. This article uses specific examples to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the scope of protection of the present invention.

Claims

1. A server hardware status monitoring method, characterized in that: Distributed agent nodes are deployed inside the server according to physical partitions, and the agent nodes are provided with a monitoring agent program; the server hardware status monitoring method includes: After the proxy node is connected to the corresponding slave device, using the proxy node to collect the corresponding slave device data through the internal integrated circuit bus; Using the monitoring agent program to monitor the load rate of the internal integrated circuit bus; According to the load rate of the internal integrated circuit bus, the agent node is used to process the collected slave device data accordingly, and the processed data is uploaded to the management controller.

2. The server hardware status monitoring method according to claim 1, characterized in that: The monitoring agent program is used to monitor the load rate of the internal integrated circuit bus, including: Using a monitoring agent program to obtain the effective working time of the internal integrated circuit bus within a set statistical period; The load rate of the inter-integrated circuit bus is obtained according to the ratio of the effective working time of the inter-integrated circuit bus within the set statistical period to the set statistical period.

3. The server hardware status monitoring method according to claim 1, wherein: According to the load rate of the internal integrated circuit bus, the agent node is used to perform corresponding processing on the collected slave device data, including: According to the load rate of the internal integrated circuit bus, using the proxy node to perform corresponding filtering processing on the collected slave device data through a built-in algorithm; Perform unexpected state recognition on the filtered slave device data to obtain data features of the unexpected state; Compress data features in unexpected states.

4. The server hardware status monitoring method according to claim 3, characterized in that: When the slave device is a temperature sensor, using the proxy node to collect corresponding slave device data through the internal integrated circuit bus includes: Using the proxy node to collect data from the temperature sensor at set time intervals through an internal integrated circuit bus; Identify unexpected status of the filtered slave device data, including: The filtered temperature sensor data is compared; if the temperature sensor data is higher than a first preset temperature threshold or lower than a second preset temperature threshold, the temperature sensor data is determined to be in an unexpected state; if the temperature sensor data is between the second preset temperature threshold and the first preset temperature threshold but changes suddenly within a set time period, the temperature sensor data is determined to be in an unexpected state; if the temperature sensor data is between the second preset temperature threshold and the first preset temperature threshold and does not change suddenly within a set time period, the temperature sensor data is determined to be in an expected state.

5. The server hardware status monitoring method according to claim 3, wherein: According to the load rate of the internal integrated circuit bus, the proxy node is used to perform corresponding filtering processing on the collected slave device data through a built-in algorithm, including: When the load rate of the internal integrated circuit bus exceeds a first preset load rate threshold, the proxy node is used to perform targeted filtering on the collected slave device data using a built-in algorithm to filter out non-critical data within a corresponding range; When the load rate of the inter-IC bus is lower than a second preset load rate threshold, the system enters a sleep mode.

6. The server hardware status monitoring method according to claim 1, wherein: Each of the proxy nodes includes a master proxy node and a slave proxy node; Using the proxy node to collect corresponding slave device data through the internal integrated circuit bus, and using the proxy node to perform corresponding processing on the collected slave device data, including: Using the master agent node to collect corresponding slave device data through the internal integrated circuit bus, and using the master agent node to perform corresponding processing on the collected slave device data; the slave agent node is in a dormant state; When the management controller detects that the heartbeat signal of the master agent node fails, it sends an activation instruction to the slave agent node, and the slave agent node performs data collection tasks and data processing tasks after being activated.

7. The server hardware status monitoring method according to claim 6, characterized in that: When the slave agent node is activated and performs data collection and processing tasks, it also includes: Performing a reset operation on the master agent node; If the master agent node recovers, the management controller switches back to the master agent node in the next acquisition cycle to perform data acquisition tasks and data processing tasks, and sends a sleep instruction to the slave agent node.

8. The server hardware status monitoring method according to claim 1, wherein: Distributed proxy nodes are deployed within the server according to physical partitions, including: The server is divided into multiple physical partitions based on hardware functions, layout and heat dissipation requirements; the physical partitions include processor area, storage area, power supply area and fan area; Distributed proxy nodes are deployed in the divided physical partitions.

9. The server hardware status monitoring method according to claim 1, wherein: Deploy distributed agent nodes, including: An independent power supply mechanism is adopted to deploy each of the proxy nodes; wherein, the proxy node integrates a main control micro-control unit and a power supply module; the power supply module is used to provide power supply for the proxy node; the main control micro-control unit is used to control the proxy node to perform data interaction and coordinate the data collection tasks and data processing tasks of the proxy node.

10. An electronic device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the server hardware status monitoring method according to any one of claims 1 to 9 when executing the computer program.

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