Resource allocation method and device of equipment, storage medium and electronic equipment

Abstract

This application discloses a resource allocation method, apparatus, storage medium, and electronic device for devices. Relating to the field of terminal management, the method includes: acquiring status data of multiple data acquisition devices; for each data acquisition device, determining health indicator data based on the status data; and allocating resources among the multiple data acquisition devices based on the health indicator data and the importance values ​​of the multiple data acquisition devices. This application solves the problem of low resource utilization caused by the static priority allocation method used in related technologies for device resource allocation.

Description

Technical Field

[0001] This application relates to the field of terminal management, and more specifically, to a resource allocation method, apparatus, storage medium, and electronic device for a device. Background Technology

[0002] In the current field of IoT terminal management, such as applications for intelligent monitoring, terminal devices are undertaking increasingly diverse tasks of real-time data acquisition and device management. Currently, in terms of resource scheduling, related technologies typically employ static priority or average allocation strategies to allocate resources (such as power and bandwidth), resulting in low resource utilization.

[0003] There is currently no effective solution to the aforementioned problems in the relevant technologies. Summary of the Invention

[0004] The main objective of this application is to provide a resource allocation method, apparatus, storage medium, and electronic device for a device, in order to solve the problem of low resource utilization caused by the use of static priority allocation in related technologies for resource allocation.

[0005] To achieve the above objectives, according to one aspect of this application, a method for resource allocation of devices is provided. The method includes: acquiring status data of multiple data acquisition devices; for each data acquisition device, determining health indicator data of that data acquisition device based on its status data; and allocating resources among the multiple data acquisition devices based on their health indicator data and their importance values.

[0006] Furthermore, the resource allocation method for the equipment also includes: determining the basic health indicator data of the data acquisition equipment based on the status indicators in the status data and the weight values ​​corresponding to the status indicators; determining the health indicator data of the data acquisition equipment based on the basic health indicator data and historical health indicator data of the data acquisition equipment, wherein the historical health indicator data is the health indicator data of the data acquisition equipment in the previous status data acquisition cycle.

[0007] Furthermore, the resource allocation method for the equipment also includes: calculating the product between the basic health indicator data and the first weight value to obtain a first value; calculating the product between the historical health indicator data and the second weight value to obtain a second value; and summing the first value and the second value to obtain the health indicator data.

[0008] Furthermore, the resource allocation method for the equipment also includes: detecting whether there are resource-limited events for multiple data acquisition devices; and, in the event that multiple data acquisition devices trigger resource-limited events, allocating resources to the multiple data acquisition devices based on the health indicator data of the multiple data acquisition devices and the importance values ​​of the multiple data acquisition devices.

[0009] Furthermore, the resource allocation method for the equipment also includes: obtaining the objective function and resource constraints corresponding to the restricted resources in the resource-constrained event, wherein the objective function aims to maximize the resource allocation utilization of the restricted resources, and the resource allocation utilization is determined based on the health index data, importance values, and amount of resources to be allocated of multiple data acquisition devices; solving the objective function according to the resource constraints to obtain the resource allocation method; and allocating resources to multiple data acquisition devices based on the resource allocation method.

[0010] Furthermore, the resource allocation method for the equipment also includes: after determining the health indicator data of the data acquisition device based on the status data of the data acquisition device, obtaining at least one preset early warning condition; determining whether the status data and / or health indicator data of the data acquisition device hit the early warning condition; and if there is a hit early warning condition, generating early warning information corresponding to the data acquisition device based on the early warning level corresponding to the early warning condition.

[0011] Furthermore, the resource allocation method for the equipment also includes: after determining the health indicator data of the data acquisition equipment based on the status data of the data acquisition equipment, obtaining at least one preset fault repair condition; determining whether the status data and / or health indicator data of the data acquisition equipment match the fault repair condition; and performing fault repair processing on the data acquisition equipment if a fault repair condition is matched.

[0012] To achieve the above objectives, according to another aspect of this application, a resource allocation apparatus for a device is provided. The apparatus includes: a first acquisition module for acquiring status data of a plurality of data acquisition devices; a determination module for determining health indicator data of each data acquisition device based on its status data; and a processing module for allocating resources among the plurality of data acquisition devices based on their health indicator data and their importance values.

[0013] Optionally, the determining module further includes: a first determining submodule, used to determine the basic health indicator data of the data acquisition device based on the status indicators in the status data and the weight values ​​corresponding to the status indicators; and a second determining submodule, used to determine the health indicator data of the data acquisition device based on the basic health indicator data and historical health indicator data of the data acquisition device, wherein the historical health indicator data is the health indicator data of the data acquisition device in the previous status data acquisition cycle.

[0014] Optionally, the second determining submodule further includes: a first calculation unit for calculating the product between basic health indicator data and a first weight value to obtain a first value; a second calculation unit for calculating the product between historical health indicator data and a second weight value to obtain a second value; and a third calculation unit for summing the first value and the second value to obtain health indicator data.

[0015] Optionally, the processing module also includes: a detection submodule, used to detect whether there are resource-limited events for multiple data acquisition devices; and a processing submodule, used to allocate resources to multiple data acquisition devices based on the health index data and importance values ​​of multiple data acquisition devices when multiple data acquisition devices trigger resource-limited events.

[0016] Optionally, the processing submodule further includes: an acquisition unit, used to acquire the objective function and resource constraints corresponding to the restricted resources in the resource-constrained event, wherein the objective function aims to maximize the resource allocation utilization of the restricted resources, and the resource allocation utilization is determined based on the health index data, importance value, and amount of resources to be allocated of multiple data acquisition devices; a first processing unit, used to solve the objective function according to the resource constraints to obtain the resource allocation method; and a second processing unit, used to allocate resources to multiple data acquisition devices based on the resource allocation method.

[0017] Optionally, the resource allocation device of the equipment further includes: a second acquisition module for acquiring at least one preset warning condition; a first judgment module for judging whether the status data and / or health indicator data of the data acquisition device hits the warning condition; and a generation module for generating warning information corresponding to the data acquisition device based on the warning level corresponding to the warning condition if a warning condition is hit.

[0018] Optionally, the resource allocation device of the equipment further includes: a second acquisition module, used to acquire at least one preset fault repair condition; a second judgment module, used to judge whether the status data and / or health indicator data of the data acquisition device hit the fault repair condition; and a fault repair module, used to perform fault repair processing on the data acquisition device when the fault repair condition is hit.

[0019] To achieve the above objectives, according to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the above-described device resource allocation method.

[0020] To achieve the above objectives, according to another aspect of this application, an electronic device is provided, the electronic device including a memory storing an executable program; and a processor for running the program, wherein the program executes the resource allocation method of the device described above when it runs.

[0021] To achieve the above objectives, according to another aspect of this application, a computer program product is provided, including computer instructions that, when executed by a processor, implement the steps of the resource allocation method of the device described above.

[0022] In this embodiment, by determining the health index data of the data acquisition device based on its status data, an effective assessment of the health status of the data acquisition device is achieved. By allocating resources based on the health index data and importance values ​​of multiple data acquisition devices, the allocation priority of the data acquisition devices is dynamically determined based on their health status and importance, thereby dynamically allocating resources and effectively improving resource utilization.

[0023] Therefore, the method provided in this application achieves the goal of dynamically allocating resources to the data acquisition equipment based on its health status and importance, thereby improving resource utilization and solving the technical problem of low resource utilization caused by the static priority allocation method used in related technologies. Attached Figure Description

[0024] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0025] Figure 1 This is a hardware structure block diagram of a computer terminal provided according to an embodiment of this application;

[0026] Figure 2 This is a flowchart of a resource allocation method for a device provided according to an embodiment of this application;

[0027] Figure 3 This is a schematic diagram of a resource allocation method for a device provided according to an embodiment of this application;

[0028] Figure 4 This is a schematic diagram of a resource allocation device for a device provided according to an embodiment of this application;

[0029] Figure 5 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] It should be noted that the information collected in this application (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) are information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of this data all comply with relevant regulations and standards, necessary confidentiality measures have been taken, and they do not violate public order and good morals. Corresponding operation entry points are provided for users to choose to authorize or refuse. For example, interfaces are set up between this system and relevant users or organizations, providing users with corresponding operation entry points for them to choose to agree to or refuse automated decision results; if the user chooses to refuse, the process proceeds to the expert decision-making stage.

[0033] Example 1

[0034] According to an embodiment of this application, an embodiment of a resource allocation method for a device is also 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.

[0035] The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 A hardware block diagram of a computer terminal (or mobile device) for implementing a resource allocation method for a device is shown. Figure 1 As shown, the computer terminal 10 (or mobile device) may include one or more processors 102 (shown as 102a, 102b, ..., 102n in the figure) 102 (processor 102 may include, but is not limited to, a microprocessor (MCU) or a field-programmable gate array (FPGA), etc.), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output (I / O) interface, a Universal Serial Bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. 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 aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0036] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0037] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the resource allocation method of the device in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the above-mentioned resource allocation method of the device. The memory 104 may include high-speed random access memory, and may also include 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 the computer terminal 10 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.

[0038] 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 the communication provider of the computer terminal 10. 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.

[0039] The display can be, for example, a touchscreen liquid crystal display (LCD), which allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0040] Under the aforementioned operating environment, this application provides the following: Figure 2 The resource allocation method for the device shown. Figure 2 This is a flowchart of a resource allocation method for a device according to Embodiment 1 of this application.

[0041] Step S201: Obtain status data from multiple data acquisition devices.

[0042] Optionally, electronic devices, application systems, servers, and other devices can be used as the execution subject of this application. In this embodiment, the target processing system is used as the execution subject to execute the above-mentioned device resource allocation method.

[0043] Data acquisition equipment refers to devices with data acquisition capabilities, such as sensors, cameras, etc. Data acquisition equipment can also be called intelligent terminals. In some implementations, multiple data acquisition devices are used within the same system. For example, multiple data acquisition devices belong to the same IoT monitoring system, and the target processing system can be this IoT monitoring system. The target processing system is used to manage multiple data acquisition devices, such as providing resources to multiple data acquisition devices, monitoring their status, allocating resources, and controlling their start and stop.

[0044] In an optional embodiment, the target processing system can periodically acquire status data from multiple data acquisition devices. For example, the target processing system acquires status data from each data acquisition device within each sampling period Δt.

[0045] Status data can also be called operational data. For example, status data can include the voltage Vi(t), current Ii(t), and temperature Ti(t) of the data acquisition device. In addition to temperature, current, and voltage, status data can also include the link status Li(t) of the data acquisition device. In addition to temperature, current, voltage, and link status, status data can also include link stability SLi(t). The link status takes a value of 1 or 0, which is used to represent the instantaneous link connection status between the target processing system and the data acquisition device at the sampling time. A value of 1 indicates a normal connection, and a value of 0 indicates that the link is disconnected. The link stability is a continuous value in the interval [0, 1], that is, the historical statistical value of the link status in the most recent sampling periods. For example, link stability = ("the number of times the link status = 1 in the last K sampling periods" / K). For example, if the link status = 1 7 times in the last 10 periods (i.e., K=10), then the stability is 0.7.

[0046] In an optional embodiment, after acquiring the state data, the target processing system can preprocess the state data and then apply the preprocessed state data to subsequent steps. For example, the state data can be denoised, normalized, and time-aligned to obtain a standardized input vector xi(t), xi(t) = [Vi(t)', Ii(t)', Ti(t)', Li(t)'], which is the preprocessed state data. In some implementations, to avoid misjudgments caused by instantaneous fluctuations, a combination of sliding window statistics and exponential smoothing can be used to denoise and stabilize the state data.

[0047] Step S202: For each data acquisition device, determine the health indicator data of the data acquisition device based on the status data of the data acquisition device.

[0048] In an optional embodiment, health indicator data is used to represent the overall health status of the data acquisition device across multiple acquisition cycles (e.g., all acquisition cycles). The health indicator data can be calculated based on the data acquisition device's basic health indicator data and historical health indicator data. Specifically, the basic health indicator data represents the health status of the data acquisition device in the current acquisition cycle (i.e., the latest acquisition cycle), while the historical health indicator data represents the health indicator data of the data acquisition device in the previous state data acquisition cycle.

[0049] For example, the target processing system can calculate the health score hi(t) of each port based on the standardized input vector xi(t), and combine it with the historical smoothed health score Hi(t-1) to obtain the smoothed health score Hi(t) for the current period. The aforementioned health score hi(t) is the basic health indicator data, and the smoothed health score Hi(t) is the health indicator data.

[0050] Step S203: Based on the health indicator data of multiple data acquisition devices and the importance values ​​of multiple data acquisition devices, allocate resources to multiple data acquisition devices.

[0051] The importance value of each data acquisition device can be preset in the target processing system, and the importance value can be used as the business priority weight of the data acquisition device.

[0052] The target processing system can prioritize resource allocation for data acquisition devices with higher health indicator data and higher importance values. For example, the system calculates the resource allocation priority of data acquisition devices based on their health indicator data and importance values, and then allocates resources accordingly. For instance, it allocates resources to data acquisition devices in descending order of priority, prioritizing the resource needs of those with higher priority. Another example is the system acquiring the objective function and resource constraints corresponding to the limited resources in a resource-constrained event. The objective function aims to maximize the utilization of the limited resources, which is determined based on the health indicator data, importance values, and the amount of resources to be allocated from multiple data acquisition devices. The system then solves the objective function based on the resource constraints to obtain the resource allocation method, and finally allocates resources to multiple data acquisition devices based on this method.

[0053] In this embodiment, by determining the health index data of the data acquisition device based on its status data, an effective assessment of the health status of the data acquisition device is achieved. By allocating resources based on the health index data and importance values ​​of multiple data acquisition devices, the allocation priority of the data acquisition devices is dynamically determined based on their health status and importance, thereby dynamically allocating resources and effectively improving resource utilization.

[0054] Therefore, the method provided in this application achieves the goal of dynamically allocating resources to the data acquisition equipment based on its health status and importance, thereby improving resource utilization and solving the technical problem of low resource utilization caused by the static priority allocation method used in related technologies.

[0055] Optionally, in the resource allocation method for the device provided in this application embodiment, determining the health indicator data of the data acquisition device based on the status data of the data acquisition device includes: determining the basic health indicator data of the data acquisition device based on the status indicators in the status data and the weight values ​​corresponding to the status indicators; and determining the health indicator data of the data acquisition device based on the basic health indicator data and historical health indicator data, wherein the historical health indicator data is the health indicator data of the data acquisition device in the previous status data acquisition cycle.

[0056] In some implementations, the status indicators in the status data may include voltage, current, temperature, link status, and link stability. For example, the target processing system can calculate basic health indicator data using the following formula:

[0057]

[0058] Where hi(t) represents the basic health indicator data, , , Here, SLi(t) represents the normalized deviations of voltage, current, and temperature, respectively, and wV, wI, wT, and wL represent the link stability. The target processing system can preset maximum, minimum, and standard values ​​for voltage, current, and temperature. Taking voltage as an example, the system calculates the difference between the acquired voltage and the standard voltage value to obtain the first difference. Then, it calculates the difference between the maximum and minimum voltage values ​​to obtain the second difference. Dividing the first difference by the second difference yields the normalized deviation of the voltage. The normalized deviations of current and temperature are calculated in the same way as the voltage normalized deviation, and therefore will not be repeated here. Through this method, the health score can comprehensively consider the normalized deviations of various indicators and link stability, and through smoothing calculations, form a reliable state assessment basis, making anomaly detection more accurate and robust.

[0059] In some implementations, the target processing system calculates the basic health indicator data for the current sampling period based on the status data of the current sampling period.

[0060] After calculating the baseline health indicator data for the current sampling period, the target processing system determines the health indicator data of the data acquisition device for the current sampling period based on the device's historical health indicator data and the baseline health indicator data for the current sampling period. The historical health indicator data refers to the health indicator data of the data acquisition device in the previous state data acquisition period, which is also the sampling period. In other words, the target processing system determines the health indicator data of the data acquisition device for the current sampling period based on the device's baseline health indicator data for the current sampling period and the health indicator data from the previous sampling period.

[0061] For example, the target processing system performs a weighted summation of the basic health indicator data for the current sampling period and the health indicator data for the previous sampling period to obtain the health indicator data for the current sampling period.

[0062] In some implementations, when the current sampling period is the first sampling period, the historical health indicator data corresponding to the current sampling period is a preset value, for example, the value is the same as the basic health indicator data of the first sampling period.

[0063] It should be noted that by integrating multi-source data and a health scoring mechanism, the health status of data collection devices can be effectively quantified, which can effectively improve the accuracy of the determined health indicator data.

[0064] Optionally, in the resource allocation method for the device provided in this application embodiment, determining the health indicator data of the data acquisition device based on the basic health indicator data and historical health indicator data of the data acquisition device includes: calculating the product between the basic health indicator data and the first weight value to obtain a first value; calculating the product between the historical health indicator data and the second weight value to obtain a second value; and summing the first value and the second value to obtain the health indicator data.

[0065] Optionally, the target processing system can calculate health indicator data using the following formula:

[0066]

[0067] Where Hi(t) represents health indicator data; This is the preset smoothing coefficient, also known as the first weight value; The second weight value is Hi(t-1), which represents historical health indicator data.

[0068] It should be noted that by combining historical values ​​with weighted averages, transient noise (such as communication jitter and voltage spikes) can be effectively filtered out, thereby reflecting the health status of data acquisition equipment more effectively and reliably, and improving the accuracy of the determined health indicator data.

[0069] Optionally, in the resource allocation method for the device provided in this application embodiment, resource allocation is performed on multiple data acquisition devices based on health indicator data and importance values ​​of multiple data acquisition devices, including: detecting whether there are resource-limited events on multiple data acquisition devices; and, if multiple data acquisition devices trigger resource-limited events, allocating resources on multiple data acquisition devices based on health indicator data and importance values ​​of multiple data acquisition devices.

[0070] Optionally, resource-constrained events can be power-constrained events, bandwidth-constrained events, or other resource-constrained events. If the total power budget of the target processing system is insufficient, multiple data acquisition devices are identified as having power-constrained events. If the total bandwidth of the target processing system is insufficient, multiple data acquisition devices are identified as having bandwidth-constrained events.

[0071] In some implementations, if the sum of the requested power from multiple data acquisition devices exceeds the total power budget of the system, it is determined that the total power budget of the target processing system is insufficient, and multiple data acquisition devices are experiencing power-limited events.

[0072] In some implementations, if the sum of the requested bandwidth from multiple data acquisition devices exceeds the total system bandwidth, it is determined that the total bandwidth of the target processing system is insufficient, and multiple data acquisition devices are experiencing bandwidth-limited events.

[0073] When multiple data acquisition devices trigger resource-constrained events, the target processing system can allocate resources to the multiple data acquisition devices based on their health indicators and importance values.

[0074] If no resource-limited events are triggered on multiple data acquisition devices, maintain the current resource allocation method for the multiple data acquisition devices.

[0075] It should be noted that by allocating resources when resources are limited, high-complexity calculations are avoided under normal conditions, thereby effectively reducing the load and energy consumption of the target processing system and reducing redundant operations.

[0076] Optionally, in the resource allocation method for the device provided in this application embodiment, resource allocation is performed on multiple data acquisition devices based on health indicator data and importance values ​​of multiple data acquisition devices. This includes: obtaining the objective function and resource constraints corresponding to the restricted resources in the resource-constrained event, wherein the objective function aims to maximize the resource allocation utilization of the restricted resources, and the resource allocation utilization is determined based on the health indicator data, importance values, and amount of resources to be allocated of multiple data acquisition devices; solving the objective function according to the resource constraints to obtain the resource allocation method; and allocating resources to the multiple data acquisition devices based on the resource allocation method.

[0077] In an optional embodiment, if the resource-limited event is a power-limited event, then the limited resource is power; if the resource-limited event is a bandwidth-limited event, then the limited resource is bandwidth.

[0078] For example, when the constrained resource is power, the objective function corresponding to the constrained resource is: Where N is the number of data acquisition devices. This represents the importance value of the i-th data acquisition device. This represents the health indicator data of the i-th data acquisition device in the current acquisition period. This represents the power to be allocated to the i-th data acquisition device. This represents the resource allocation utilization of the i-th data acquisition device. The resource constraints are as follows:

[0079] (1) Σpi≤Pbdg, where Pbdg is the total power budget of the target processing system;

[0080] (2) 0 ≤ pi ≤ Pimax, where Pimax represents the maximum power limit of the i-th data acquisition device. For example, the power requested by the i-th data acquisition device from the target processing system is determined as the maximum power limit of the device.

[0081] Optionally, the objective processing system solves the objective function based on resource constraints to obtain a resource allocation method. For example, this can be achieved using the water level method, or by using other optimization problem-solving algorithms from related technologies. The resource allocation method includes the expected amount of resources to be allocated to each data acquisition device.

[0082] For example, when the limited resource is bandwidth, the objective function corresponding to the limited resource is: Where N is the number of data acquisition devices. This represents the importance value of the i-th data acquisition device. This represents the bandwidth to be allocated to the i-th data acquisition device. This represents the resource allocation utilization of the i-th data acquisition device. The resource constraints are as follows:

[0083] (1) Σbi≤B, where B is the total bandwidth of the target processing system;

[0084] (2) bi≥bimin, where bimin represents the minimum bandwidth requirement of the i-th data acquisition device.

[0085] Optionally, the target processing system can employ a Weighted Fair Queuing (WFQ) algorithm to solve the objective function based on resource constraints, thereby obtaining a resource allocation method to allocate remaining bandwidth according to weights while ensuring bandwidth for critical services. Alternatively, the target processing system can also solve the problem using other optimization problem-solving algorithms from related technologies.

[0086] In some implementations... Unlike the UI, data acquisition devices have different importance values ​​depending on the resource. For example, It can be determined in the following ways:

[0087]

[0088] Here, ui represents the importance value of the data acquisition device at a given power level. In other words, the importance value of the data acquisition device at a given power level is the base importance value, while the importance value of the data acquisition device at a given bandwidth level is calculated based on the base importance value and the health indicator data from the health indicator data of the data acquisition device.

[0089] In some implementations, the target processing system can replace Hi(t) in the target function with hi(t), or replace Hi(t) in the target function with (Hi(t) + hi(t)) according to actual needs.

[0090] After determining the resource allocation method, the target processing system can allocate resources to multiple data acquisition devices based on the expected amount of resources to be allocated indicated in the resource allocation method.

[0091] It should be noted that dynamic optimization of resource allocation based on device health status and importance values ​​can effectively improve the rationality of resource allocation and increase resource utilization. Specifically, in power allocation, the optimization objective is to solve the problem in real time using health scores and importance values. Devices with high health and high priority can receive more resources, improving power utilization efficiency. In bandwidth scheduling, priority is given to ensuring the minimum bandwidth requirements of critical services, while remaining bandwidth is flexibly allocated according to health scores and weights using a weighted fair queue algorithm. This approach satisfies the stability requirements of critical services while improving overall bandwidth utilization.

[0092] Optionally, in the resource allocation method for the device provided in this application embodiment, after determining the health indicator data of the data acquisition device based on the status data of the data acquisition device, the method further includes: obtaining at least one preset warning condition; determining whether the status data and / or health indicator data of the data acquisition device hits the warning condition; and, if a warning condition is hit, generating warning information corresponding to the data acquisition device based on the warning level corresponding to the warning condition.

[0093] In an optional embodiment, the target processing system has at least one preset warning condition. The target processing system can combine fixed threshold detection and adaptive threshold detection to identify abnormalities in the data acquisition equipment, and generate graded alarms based on the duration and severity of the abnormalities in health indicator data Hi(t) and link status Li(t).

[0094] In some implementations, at least one warning condition is a tiered alarm. At least one warning condition may include:

[0095] (1) Level 1 alarm: when the health indicator data Hi(t) is lower than the first threshold. Triggered by time, such as the first threshold It is 0.7;

[0096] (2) Level 2 alarm: when the health indicator data Hi(t) is lower than the second threshold. And the second threshold is triggered when the link state Li(t) is 0. Below the first threshold For example, the second threshold It is 0.5;

[0097] (3) Level 3 alarm, triggered when the data acquisition device is detected as abnormal within M consecutive sampling periods. Specifically, when the value of the status indicator (such as voltage, current, temperature, etc.) of the data acquisition device exceeds the corresponding threshold (such as fixed threshold detection or adaptive threshold), the data acquisition device is determined to be detected as abnormal.

[0098] In some implementations, adaptive thresholds can be determined based on quantile statistics. For example, for voltage Vi(t), the dynamic threshold range is [Q0.05({Vi}t-K+1:t)-ΔV, Q0.95({Vi}t-K+1:t)+ΔV], where Q0.05 and Q0.95 are the 5th and 95th percentiles of the voltage data over the last K sampling periods, respectively, and ΔV is the tolerance offset.

[0099] In some implementations, when detecting at a fixed threshold, if Vi(t) If [Vmin, Vmax], or Ii(t) > Imax, or the link state Li(t) = 0, then the data acquisition device is determined to be abnormal. Here, Vmin, Vmax, and Imax are all preset thresholds.

[0100] If a certain status indicator has both a fixed threshold and an adaptive threshold, and the value of the status indicator exceeds either the fixed threshold or the adaptive threshold, then the data acquisition device can be determined to be abnormal.

[0101] If a triggering warning condition exists, a warning message corresponding to the data acquisition device is generated based on the warning level corresponding to the warning condition. Different warning levels can correspond to different warning messages, and the warning message must include at least the warning level. The warning message is used to instruct the user to check the data acquisition device.

[0102] No warning information will be generated if there is no warning that has been triggered.

[0103] It should be noted that the above methods enable timely warnings when equipment malfunctions, thereby improving the timeliness of fault identification and maintenance, and enhancing the reliability of data acquisition equipment operation.

[0104] Optionally, in the resource allocation method for the device provided in this application embodiment, after determining the health indicator data of the data acquisition device based on the status data of the data acquisition device, the method further includes: obtaining at least one preset fault repair condition; determining whether the status data and / or health indicator data of the data acquisition device match the fault repair condition; and performing fault repair processing on the data acquisition device if a fault repair condition is matched.

[0105] In an optional embodiment, in response to a link interruption (e.g., link status is 0) or a persistently low health indicator data Hi(t), a soft reboot or hard reboot operation is selected and performed. That is, at least one fault repair condition may include: (1) link status is 0; (2) health indicator data Hi(t) is persistently low, such as being below a certain preset threshold for P consecutive collection cycles.

[0106] For example, when a link is broken or the health score remains low for an extended period, the system enters self-healing mode (i.e., fault repair mode):

[0107] Strategy selection logic:

[0108] If Hi(t) < τH or Li(t) = 0 for P consecutive acquisition cycles, a soft reboot is performed first; if the number of consecutive soft reboot failures is ≥ 2, a hard reboot is performed. The aforementioned soft reboot and hard reboot constitute the fault repair process.

[0109] In an optional embodiment, if a fault repair condition is met, the decision to perform fault repair processing can be based on an expected reward function. For example, the restart success rate (pok) can be estimated based on historical statistics, and the expected reward for the action can be calculated: Where ΔSLi(t) represents the improved link stability following a successful action, which can be obtained based on historical data statistics; C(at) represents the action cost, with soft restart cost being lower (e.g., 0.1) and hard restart cost being higher (e.g., 0.3); 1[fail] = 1 - pok, , , Preset weights.

[0110] When the expected return (rt) is positive, a soft reboot or hard reboot is selected based on the hit fault repair conditions. When the expected return (rt) is negative, a reboot is not performed; only a corresponding warning is issued to avoid invalid reboots. This approach breaks through the traditional passive response mode, achieving intelligent self-healing through an expected return evaluation mechanism. When the system detects a link interruption or a persistently low health score, it does not mechanically execute a reboot but selects the optimal recovery strategy based on historical success rates and expected return analysis. The intelligent selection logic for soft and hard reboots, combined with action intervals and reboot count limits, effectively avoids invalid operations, shortens the average recovery time, and improves system availability and operational continuity.

[0111] It should be noted that the above methods enable effective identification and handling of faults in data acquisition equipment, thereby effectively improving the stability of faulty acquisition equipment.

[0112] In an optional embodiment, all operational data (e.g., health metric data, alarm levels, allocation results, recovery status) are periodically packaged and uploaded to the management platform. The platform can also remotely issue parameter update commands (e.g., thresholds, weights, smoothing coefficients) to achieve remote control and policy optimization. This not only helps reduce the burden of on-site maintenance but also provides complete data support for fault tracing and performance analysis through hierarchical alarm and log recording functions.

[0113] In an optional embodiment, the target processing system can dynamically update system parameters based on feedback results of executed actions and historical operational data to achieve adaptive system optimization. For example, based on execution feedback and historical data of resource allocation and fault self-healing, the health score weights, dynamic threshold parameters, and fault repair decision weights can be optimized and updated. In some embodiments, the learning and parameter update steps further include: periodically exporting system operation indicator reports and performing versioned management of fault repair decision weights, supporting policy rollback and A / B testing.

[0114] Through continuous feedback and parameter update mechanisms, the system possesses long-term optimization capabilities. It can dynamically adjust health score weights, dynamic threshold parameters, and decision weights based on historical operational data, gradually adapting to changes in the actual environment. Furthermore, the system supports policy versioning management and A / B testing, facilitating operations personnel to retrospectively compare the effects of different policies, further enhancing the system's maintainability and evolution potential.

[0115] In an optional embodiment, the actual application process of the device resource allocation method is illustrated by way of example. For example, Figure 3 This is a schematic diagram of a resource allocation method for a device provided according to an embodiment of this application, such as... Figure 3 As shown, the target processing system can perform the following steps:

[0116] S1, System initialization;

[0117] S1.1, Set Δt, K, α, Pbdg, B, Parameters such as these.

[0118] S1.2 Initialize Hi(0), logs and cache.

[0119] S1.3 Load thresholds and safeguard parameters such as Vmin / Vmax, Imax, and bimin.

[0120] S2, Data Acquisition;

[0121] S2.1. Collect Vi(t), Ii(t), Ti(t), Li(t), that is, collect state data.

[0122] S2.2. Write the timestamp to the cache; if the write fails, record the missing flag.

[0123] S2.3 Check data freshness; if timeout occurs, trigger a sampling anomaly warning.

[0124] S3, Pretreatment;

[0125] S3.1 Normalize the original quantities to a uniform scale.

[0126] S3.2 Sliding window statistics: mean / quantile of the last K samples.

[0127] S3.3. Apply smoothing or median filtering to abrupt change points.

[0128] S4, Health Score;

[0129] S4.1 Calculation , , With SLi(t).

[0130] S4.2, Obtaining hi(t) and .

[0131] S4.3 Archive Hi(t) and use it for subsequent decision-making, that is, save health indicator data.

[0132] S5, Link Assessment;

[0133] S5.1 Calculate SLi(t) and near-window availability.

[0134] S5.2 If SLi(t) is below the threshold, it is marked as unstable.

[0135] S6, Fixed threshold detection;

[0136] S6.1 Determine whether Vi(t) is within [Vmin, Vmax].

[0137] S6.2 Determine whether Ii(t) exceeds Imax.

[0138] S6.3 Determine whether Li(t) is 0.

[0139] S6.4 If any condition is not met, an early warning Ei(t) is generated.

[0140] S7, Adaptive threshold detection;

[0141] S7.1 Calculate Q0.05 and Q0.95 as dynamic thresholds.

[0142] S7.2, Vmin=Q0.05-ΔV, Vmax=Q0.95+ΔV.

[0143] S7.3 If the dynamic threshold is exceeded, an adaptive warning will be generated.

[0144] S8. Early Warning Classification and Reporting;

[0145] S8.1, Level-1: Hi(t) < Level-2: Hi(t) < And Li=0; Level-3: M consecutive anomalies.

[0146] S8.2 Write the data acquisition device ID, level, and time into the log.

[0147] S8.3 Trigger the reporting module and send the data to the platform.

[0148] S9, power distribution optimization;

[0149] S9.1 Under power-constrained conditions, collect ui, Hi(t), and Pimax.

[0150] S9.2 Solving the objective function based on resource constraints.

[0151] S9.3 Determine the resource allocation results.

[0152] S10, bandwidth allocation optimization;

[0153] S10.1 Solve the objective function based on resource constraints under bandwidth-limited conditions.

[0154] S10.2 Determine the resource allocation results.

[0155] S11, Self-healing enters judgment;

[0156] S11.1 If Hi < τH or Li = 0 for P consecutive acquisition cycles, enter the self-healing process.

[0157] S11.2 Read the most recently recovered record.

[0158] S12, soft reboot;

[0159] S12.1 Execute a soft reboot: power off - delay, ΔT - power on.

[0160] S12.2 Detect link recovery and Hi improvement, and record the results.

[0161] S12.3 If successful, the failure count is reset to zero; if unsuccessful, the failure count is incremented by 1.

[0162] S13, hard reboot;

[0163] S13.1 If the number of failures is ≥2, or the expected normal working time (probability-weighted) is less than or equal to the cost of a soft restart, a hard restart shall be performed.

[0164] S13.2. Power-on test after extending the power-off time.

[0165] S13.3 If it fails, it will be upgraded to Level-3 and reported to human intervention.

[0166] S14, Motion Assessment;

[0167] S14.1 Record the action type and duration, and store them.

[0168] S14.2 Update recovery success rate, failure count and log.

[0169] S15, Instruction Issuance;

[0170] S15.1, Issue the latest allocation instructions for pi and bi.

[0171] S15.2 Perform power / bandwidth adjustments on the data acquisition equipment.

[0172] S15.3 Confirm successful execution and provide feedback.

[0173] S16. Data reporting;

[0174] S16.1 Pack {Hi, threshold, pi, bi, level, logs}.

[0175] S16.2, Upload to the platform via wired / wireless link.

[0176] S17, Platform Interaction;

[0177] S17.1, The platform issues new parameters ( ,K, , 1, 2nd grade).

[0178] S17.2, The target processing system performs a local hot update and writes the data to disk.

[0179] S18, Learning and Adaptation;

[0180] S18.1 Optimization based on historical data Thresholds and weights.

[0181] S18.2 Conduct a review and adjust the grading strategy if necessary.

[0182] S19. Safety and rollback;

[0183] S19.1 Set the minimum action interval and restart limit.

[0184] S19.2 When anomalies occur frequently, enter protection mode, only report the anomaly and do not perform any actions.

[0185] S20, Periodic Review and Version Management;

[0186] S20.1, Periodically export indicator reports.

[0187] S20.2 Policy versioning management, supporting rollback and A / B comparison.

[0188] Therefore, this application constructs a complete "perception-judgment-decision-execution-learning" intelligent closed-loop architecture by integrating the algorithmic intelligent agent with the underlying hardware functions. This innovative design breaks through the limitations of traditional monitoring systems, achieving a leapfrog improvement in four core capabilities: at the perception level, it achieves precise monitoring through multi-source data fusion and a health scoring mechanism; at the decision-making level, it optimizes resource scheduling based on optimization models and weights; at the recovery level, it ensures efficient self-healing of the system by relying on expected return functions and intelligent selection mechanisms; and at the evolution level, it achieves long-term adaptive operation through continuous feedback and parameter update mechanisms. This application helps to solve the inherent problems of related technologies, such as single monitoring methods, lagging response mechanisms, and rigid resource scheduling, thereby enhancing the overall reliability, environmental adaptability, and intelligent decision-making level of intelligent terminals in complex scenarios such as building protection and industrial monitoring.

[0189] 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, and 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.

[0190] Example 2

[0191] This application also provides a device resource allocation apparatus. It should be noted that the device resource allocation apparatus of this application can be used to execute the device resource allocation method provided in this application. The device resource allocation apparatus provided in this application will be described below.

[0192] According to an embodiment of this application, an apparatus for implementing the resource allocation method of the above-described device is also provided, such as... Figure 4 As shown, the device includes:

[0193] The first acquisition module 401 is used to acquire status data from multiple data acquisition devices;

[0194] The determination module 402 is used to determine the health indicator data of each data acquisition device based on the status data of that data acquisition device.

[0195] The processing module 403 is used to allocate resources to multiple data acquisition devices based on the health indicator data of multiple data acquisition devices and the importance values ​​of multiple data acquisition devices.

[0196] In this embodiment, by determining the health index data of the data acquisition device based on its status data, an effective assessment of the health status of the data acquisition device is achieved. By allocating resources based on the health index data and importance values ​​of multiple data acquisition devices, the allocation priority of the data acquisition devices is dynamically determined based on their health status and importance, thereby dynamically allocating resources and effectively improving resource utilization.

[0197] Therefore, the method provided in this application achieves the goal of dynamically allocating resources to the data acquisition equipment based on its health status and importance, thereby improving resource utilization and solving the technical problem of low resource utilization caused by the static priority allocation method used in related technologies.

[0198] Optionally, in the resource allocation device of the device provided in the embodiments of this application, the determining module further includes: a first determining submodule, used to determine the basic health indicator data of the data acquisition device based on the status indicators in the status data and the weight values ​​corresponding to the status indicators; and a second determining submodule, used to determine the health indicator data of the data acquisition device based on the basic health indicator data and historical health indicator data of the data acquisition device, wherein the historical health indicator data is the health indicator data of the data acquisition device in the previous status data acquisition cycle.

[0199] Optionally, in the resource allocation device of the device provided in the embodiments of this application, the second determining submodule further includes: a first calculation unit, used to calculate the product between basic health indicator data and a first weight value to obtain a first value; a second calculation unit, used to calculate the product between historical health indicator data and a second weight value to obtain a second value; and a third calculation unit, used to sum the first value and the second value to obtain health indicator data.

[0200] Optionally, in the resource allocation device of the device provided in the embodiments of this application, the processing module further includes: a detection submodule, used to detect whether there is a resource-limited event for multiple data acquisition devices; and a processing submodule, used to allocate resources to multiple data acquisition devices based on the health index data of multiple data acquisition devices and the importance value of multiple data acquisition devices when multiple data acquisition devices trigger resource-limited events.

[0201] Optionally, in the resource allocation device of the device provided in this application embodiment, the processing submodule further includes: an acquisition unit, used to acquire the objective function and resource constraints corresponding to the restricted resources in the resource-constrained event, wherein the objective function aims to maximize the resource allocation utilization of the restricted resources, and the resource allocation utilization is determined based on the health index data, importance value, and amount of resources to be allocated of multiple data acquisition devices; a first processing unit, used to solve the objective function according to the resource constraints to obtain the resource allocation method; and a second processing unit, used to allocate resources to multiple data acquisition devices based on the resource allocation method.

[0202] Optionally, in the resource allocation device of the device provided in the embodiments of this application, the resource allocation device further includes: a second acquisition module, used to acquire at least one preset warning condition; a first judgment module, used to judge whether the status data and / or health indicator data of the data acquisition device hits the warning condition; and a generation module, used to generate warning information corresponding to the data acquisition device based on the warning level corresponding to the warning condition when there is a hit warning condition.

[0203] Optionally, in the resource allocation device of the device provided in the embodiments of this application, the resource allocation device further includes: a second acquisition module, used to acquire at least one preset fault repair condition; a second judgment module, used to judge whether the status data and / or health indicator data of the data acquisition device hits the fault repair condition; and a fault repair module, used to perform fault repair processing on the data acquisition device when there is a hit fault repair condition.

[0204] It should be noted that the first acquisition module 401, determination module 402, and processing module 403 mentioned above correspond to steps S201 to S203 in Embodiment 1. The three modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in Embodiment 1. It should be noted that the above modules or units can be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules can also be part of a device and run in the computer terminal 10 provided in Embodiment 1.

[0205] Example 3

[0206] Embodiments of this application may provide an electronic device. Figure 5 This is a structural block diagram of an electronic device according to an embodiment of this application. Figure 5 As shown, the electronic device may include: one or more ( Figure 5(Only one is shown) processor 1002, memory 1004, memory controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0207] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the methods and apparatus in the embodiments of this application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby implementing the above-described methods. The memory may include high-speed random access memory, and may also include 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 may further include memory remotely located relative to the processor, and these remote memories can be connected to the terminal 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.

[0208] The processor can access information and applications stored in memory via a transmission device to perform the following steps: acquire status data from multiple data acquisition devices; for each data acquisition device, determine its health indicator data based on its status data; and allocate resources to the multiple data acquisition devices based on their health indicator data and importance values.

[0209] The processor can also call the information and application programs stored in the memory through the transmission device to perform the following steps: determine the basic health indicator data of the data acquisition device based on the status indicators in the status data and the weight values ​​corresponding to the status indicators; determine the health indicator data of the data acquisition device based on the basic health indicator data and historical health indicator data, wherein the historical health indicator data is the health indicator data of the data acquisition device in the previous status data acquisition cycle; and determine the health indicator data based on the basic health indicator data and the health indicator data.

[0210] The processor can also call the information and application stored in the memory through the transmission device to perform the following steps: calculate the product between the basic health indicator data and the first weight value to obtain the first value; calculate the product between the historical health indicator data and the second weight value to obtain the second value; and sum the first value and the second value to obtain the health indicator data.

[0211] The processor can also access information and applications stored in the memory via a transmission device to perform the following steps: detect whether there are resource-limited events in multiple data acquisition devices; and, if multiple data acquisition devices trigger resource-limited events, allocate resources to the multiple data acquisition devices based on their health indicator data and importance values.

[0212] The processor can also access information and applications stored in the memory via a transmission device to perform the following steps: obtaining the objective function and resource constraints corresponding to the restricted resources in the resource-constrained event, wherein the objective function aims to maximize the resource allocation utilization of the restricted resources, and the resource allocation utilization is determined based on the health index data, importance values, and the amount of resources to be allocated of multiple data acquisition devices; solving the objective function according to the resource constraints to obtain the resource allocation method; and allocating resources to multiple data acquisition devices based on the resource allocation method.

[0213] The processor can also call the information and application program stored in the memory through the transmission device to perform the following steps: after determining the health indicator data of the data acquisition device based on the status data of the data acquisition device, obtain at least one preset warning condition; determine whether the status data and / or health indicator data of the data acquisition device hit the warning condition; if there is a hit warning condition, generate the warning information corresponding to the data acquisition device based on the warning level corresponding to the warning condition.

[0214] The processor can also call the information and application program stored in the memory through the transmission device to perform the following steps: after determining the health index data of the data acquisition device based on the status data of the data acquisition device, obtain at least one preset fault repair condition; determine whether the status data and / or health index data of the data acquisition device hit the fault repair condition; if the fault repair condition is hit, perform fault repair processing on the data acquisition device.

[0215] In this embodiment, by determining the health index data of the data acquisition device based on its status data, an effective assessment of the health status of the data acquisition device is achieved. By allocating resources based on the health index data and importance values ​​of multiple data acquisition devices, the allocation priority of the data acquisition devices is dynamically determined based on their health status and importance, thereby dynamically allocating resources and effectively improving resource utilization.

[0216] Therefore, the method provided in this application achieves the goal of dynamically allocating resources to the data acquisition equipment based on its health status and importance, thereby improving resource utilization and solving the technical problem of low resource utilization caused by the static priority allocation method used in related technologies.

[0217] Those skilled in the art will understand that Figure 5 The structure shown is for illustrative purposes only. Electronic devices can also be smartphones, tablets, handheld computers, mobile internet devices (MIDs), PADs, and other terminal devices. Figure 5 This does not limit the structure of the aforementioned electronic device. For example, electronic devices may also include components that are more... Figure 5 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 5 The different configurations shown.

[0218] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0219] Example 4

[0220] Embodiments of this application also provide a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the resource allocation method of the device provided in Embodiment 1.

[0221] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0222] This application also provides a computer program product, which, when executed on a data processing device, is adapted to perform the resource allocation method steps of the device.

[0223] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0224] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0225] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0226] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0227] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0228] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0229] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for allocating resources for equipment, characterized in that, include: Acquire status data from multiple data acquisition devices; For each data acquisition device, determine the health indicator data of the data acquisition device based on the status data of the data acquisition device; Based on the health indicator data of the multiple data acquisition devices and the importance values ​​of the multiple data acquisition devices, resources are allocated to the multiple data acquisition devices.

2. The method according to claim 1, characterized in that, Based on the status data of the data acquisition device, determine the health indicator data of the data acquisition device, including: Based on the status indicators and their corresponding weight values ​​in the status data, the basic health indicator data of the data acquisition device are determined. Based on the basic health indicator data and historical health indicator data of the data acquisition device, the health indicator data of the data acquisition device is determined, wherein the historical health indicator data is the health indicator data of the data acquisition device in the previous state data acquisition cycle.

3. The method according to claim 2, characterized in that, Based on the basic health indicator data and historical health indicator data of the data acquisition device, the health indicator data of the data acquisition device is determined, including: Calculate the product between the basic health indicator data and the first weight value to obtain the first value; The second value is obtained by multiplying the historical health indicator data with the second weight value. The health indicator data is obtained by summing the first value and the second value.

4. The method according to claim 1, characterized in that, Based on the health indicator data and importance values ​​of the multiple data acquisition devices, resource allocation is performed on the multiple data acquisition devices, including: Detect whether any resource-limited events occur in the multiple data acquisition devices; When multiple data acquisition devices trigger resource-limited events, resources are allocated to the multiple data acquisition devices based on their health indicator data and importance values.

5. The method according to claim 4, characterized in that, Based on the health indicator data and importance values ​​of the multiple data acquisition devices, resource allocation is performed on the multiple data acquisition devices, including: Obtain the objective function and resource constraints corresponding to the restricted resources in the resource-constrained event, wherein the objective function aims to maximize the resource allocation and utilization of the restricted resources, and the resource allocation and utilization is determined based on the health index data, importance value, and amount of resources to be allocated of the multiple data acquisition devices; The objective function is solved based on the resource constraints to obtain the resource allocation method; The resource allocation is performed on the multiple data acquisition devices based on the aforementioned resource allocation method.

6. The method according to claim 1, characterized in that, After determining the health indicator data of the data acquisition device based on its status data, the method further includes: Obtain at least one preset warning condition; Determine whether the status data and / or health indicator data of the data acquisition device meet the warning conditions; If a warning condition is met, a warning message corresponding to the data acquisition device is generated based on the warning level corresponding to the warning condition.

7. The method according to claim 1, characterized in that, After determining the health indicator data of the data acquisition device based on its status data, the method further includes: Obtain at least one preset fault repair condition; Determine whether the status data and / or health indicator data of the data acquisition device meet the fault repair conditions; If the fault repair conditions are met, the data acquisition device is subjected to fault repair processing.

8. A resource allocation device for an equipment, characterized in that, include: The first acquisition module is used to acquire status data from multiple data acquisition devices; The determination module is used to determine the health indicator data of each data acquisition device based on the status data of that data acquisition device. The processing module is used to allocate resources to the multiple data acquisition devices based on their health indicator data and importance values.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the computer-readable storage medium is located to perform the resource allocation method of the device according to any one of claims 1 to 7.

10. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, executes the resource allocation method of the device according to any one of claims 1 to 7.

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