WO2022252546A1

WO2022252546A1 - Information adjusting method and device, and storage medium

Info

Publication number: WO2022252546A1
Application number: PCT/CN2021/136434
Authority: WO
Inventors: 邓城初
Original assignee: 深圳前海微众银行股份有限公司
Priority date: 2021-06-04
Filing date: 2021-12-08
Publication date: 2022-12-08
Also published as: CN113326132A; CN113326132B

Abstract

Embodiments of the present application disclose an information adjusting method. The method comprises: determining at least one first data transmission interface currently in a current-limiting mode; determining a first current current-limiting threshold corresponding to current-limiting parameters of each first data transmission interface to obtain at least one first current current-limiting threshold; analyzing the occupancy rate of a central processing unit (CPU) on the at least one first current current-limiting threshold, and determining a current-limiting threshold to be adjusted of each corresponding first data transmission interface; adjusting the values of the current-limiting parameters of each first data transmission interface to be the corresponding current-limiting thresholds. The embodiments of the present application also disclose an information adjusting device and a storage medium.

Description

An information adjustment method, device and storage medium

Cross References to Related Applications

This application is based on a Chinese patent application with application number 202110624327.6 and a filing date of June 4, 2021, and claims the priority of this Chinese patent application. The entire content of this Chinese patent application is hereby incorporated by reference into this application.

technical field

The present application relates to the field of artificial intelligence, and in particular to an information adjustment method, device and storage medium.

Background technique

With the rapid development of computer technology, more and more technologies are applied in the financial field, and the traditional financial industry is gradually transforming into financial technology (Fintech). However, due to the security and real-time requirements of the financial industry, more and more technical requirements high demands. In the communication process, in order to ensure better business services for users, in the process of business process realization, flow limiting is usually used to prevent sudden data traffic floods from causing resource exhaustion and collapse of the communication system or downstream systems. In the currently commonly used current-limiting threshold configuration process, the single-interface pressure test is usually used to measure the CPU usage of the transactions per second (Transactions Per Second, TPS) of a single interface on a single machine, and then calculate the target TPS and TPS of all interfaces. The CPU usage of a single machine, single interface, and single TPS is multiplied and summed, and then the single machine CPU does not exceed 45% as the baseline, and the single machine current limiting configuration of the single machine is obtained.

However, in the above configuration process, the actual production environment cannot be fully restored when the single-port stress test is implemented, resulting in a certain discrepancy between the CPU usage of the single-machine single-port TPS obtained from the single-port stress test and the actual CPU usage in the actual production environment. Error, resulting in a large error in the single-machine current-limiting configuration, and the set single-machine current-limiting configuration error is poor in real-time.

Contents of the invention

In order to solve the above technical problems, the embodiment of the present application expects to provide an information adjustment method, device and storage medium, which solves the problem of low flexibility in the current limit configuration process and realizes an intelligent automatic adjustment of the current limit threshold. , by dynamically adjusting the current limiting parameter value of the data transmission interface according to the real-time transmission conditions of all data transmission interfaces, the flexibility and adjustment efficiency of the current limiting configuration process are effectively improved.

The technical scheme of the present application is realized like this:

In the first aspect, an information adjustment method, the method includes:

Determine at least one first data transmission interface that is currently in a current-limiting mode;

determining a first current current limiting threshold corresponding to the current limiting parameter of each of the first data transmission interfaces, to obtain at least one first current current limiting threshold;

Analyzing the CPU occupancy rate of the central processing unit for at least one of the first current limiting thresholds, and determining the corresponding current limiting thresholds to be adjusted for each of the first data transmission interfaces;

The value of the current limiting parameter of each of the first data transmission interfaces is adjusted to the corresponding value of the current limiting threshold to be adjusted.

In a second aspect, an information conditioning device, the device comprising: a memory, a processor, and a communication bus; wherein:

The memory is used to store executable instructions;

The communication bus is used to realize the communication connection between the processor and the memory;

The processor is configured to execute the information adjustment program stored in the memory to implement the steps of the information adjustment method described in any one of the above.

In a third aspect, a storage medium stores an information adjustment program, and when the information adjustment program is executed by a processor, the steps of the information adjustment method described in any one of the foregoing are implemented.

In this embodiment of the application, after determining at least one first data transmission interface that is currently in the current limiting mode, determine the first current limiting threshold corresponding to the current limiting parameter of each first data transmission interface, and obtain at least one first current limiting threshold. flow threshold, and analyze the CPU occupancy rate of at least one first current current limiting threshold to determine the corresponding current limiting threshold of each data transmission interface to be adjusted, so as to adjust the current limiting parameter value of each first data transmission interface In order to adjust the current limit threshold, it solves the problem of low flexibility in the current limit configuration process, and implements an intelligent automatic adjustment current limit threshold implementation method, through the real-time transmission of all data transmission interfaces. The current limit parameter value is dynamically adjusted, which effectively improves the flexibility and adjustment efficiency of the current limit configuration process.

Description of drawings

FIG. 1 is a schematic flow diagram of an information adjustment method provided in an embodiment of the present application;

FIG. 2 is a schematic flowchart of another information adjustment method provided by the embodiment of the present application;

FIG. 3 is a schematic flowchart of another information adjustment method provided by the embodiment of the present application;

FIG. 4 is a schematic flowchart of an information adjustment method provided by another embodiment of the present application;

FIG. 5 is a schematic flowchart of another information adjustment method provided by another embodiment of the present application;

FIG. 6 is a schematic diagram of a system architecture for implementing an information adjustment method provided by an embodiment of the present application;

FIG. 7 is a schematic structural diagram of an information adjustment device provided by an embodiment of the present application.

Detailed ways

In order to make the purpose, technical solutions and advantages of the application clearer, the application will be further described in detail below in conjunction with the accompanying drawings. All other embodiments obtained under the premise of creative labor belong to the scope of protection of this application.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application, and are not intended to limit the present application.

An embodiment of the present application provides an information adjustment method. Referring to FIG. 1, the method is applied to an information adjustment device, and the method includes the following steps:

Step 101. Determine at least one first data transmission interface that is currently in a current limiting mode.

In this embodiment of the present application, the first data transmission interface generally refers to an interface provided by the information adjustment device for communicating with an external Internet system, and is used for receiving request information sent by an external application. The current limiting mode refers to a way to limit the data transmission interface when the current number of requests of the data transmission interface exceeds the upper threshold of the data transmission interface processing requests. Post-processing, or sending requests exceeding the upper threshold to other interfaces of the same type for processing. In this way, it is possible to prevent the service system provided by the information adjustment device from collapsing due to too many requests, and effectively ensure that the information adjustment device can provide services normally, continuously and stably. The information adjustment device can usually be a server device, which can be used to run a service system that provides services, or it can be an electronic device that runs some application systems with a large amount of information interaction.

Step 102: Determine a first current current limiting threshold corresponding to the current limiting parameter of each first data transmission interface, to obtain at least one first current current limiting threshold.

In this embodiment of the present application, the first current current limiting threshold corresponding to the current limiting parameter of each first data transmission interface may be a preset current limiting upper limit value.

Step 103 , analyzing the CPU usage of at least one first current current limiting threshold, and determining the corresponding current limiting threshold of each first data transmission interface to be adjusted.

In this embodiment of the present application, a preset analysis method is used to analyze the CPU occupancy rate of each first current limit value, and the corresponding current limit threshold to be adjusted for each data transmission interface is determined, wherein the preset analysis method The method can be a trained target neural network model, or some linear algorithm with determined weight coefficients, such as a matrix operation algorithm with determined weight coefficients, a polynomial regression algorithm, or a ridge regression algorithm.

Step 104, adjusting the value of the current limiting parameter of each first data transmission interface to the corresponding current limiting threshold to be adjusted.

In this embodiment of the application, since each first data transmission interface is currently in the current limiting mode, the corresponding dynamic adjustment is made to the value of the current limiting parameter of each first data transmission interface, wherein the adjusted to-be-adjusted The current limiting threshold can make the CPU usage rate of the information adjustment device not exceed the preset CPU usage rate, thereby ensuring the operation efficiency of the information adjustment device.

Based on the foregoing embodiments, the embodiments of the present application provide an information adjustment method, as shown in FIG. 2 , the method is applied to an information adjustment device, and the method includes the following steps:

Step 201. Determine at least one second data transmission interface that is in a data transmission mode at the current moment.

In the embodiment of the present application, the information adjustment device may be a bank server device that provides various bank business services, and the data transmission mode refers to a mode in which the interface survives and the interface can normally transmit data information. The at least one second data transmission interface refers to all surviving data transmission interfaces currently used by the information adjustment device to provide services. Exemplarily, it is assumed that the information adjustment device determines that the at least one second data transmission interface in the data transmission mode at the current moment is interface 1, interface 2, interface 3, interface 4, and interface 5.

Step 202. Determine a first current current limiting threshold corresponding to a current limiting parameter of each second data transmission interface.

In this embodiment of the present application, the information adjustment device determines the first current current limiting threshold set by each second data transmission interface for its current limiting parameter. Exemplarily, it is determined that the first current limit threshold of interface 1 is a1, the first current limit threshold of interface 2 is a2, the first current limit threshold of interface 3 is a3, and the first current limit threshold of interface 4 is The threshold is a4 and the first current current limiting threshold of interface 5 is a5.

Step 203. Determine the current request quantity value of each second data transmission interface.

In this embodiment of the present application, the information adjustment device determines the current request quantity value of each second data transmission interface included in the at least one second data transmission interface, and obtains at least one current request quantity value. Exemplarily, it is determined that the current request quantity value of interface 1 is q1, the current request quantity value of interface 2 is q2, the current request quantity value of interface 3 is q3, the current request quantity value of interface 4 is q4, and the current request quantity value of interface 5 is The requested quantity value is q5.

Step 204: From the at least one second data transmission interface, determine the second data transmission interface whose current request quantity value is greater than the corresponding first current current limiting threshold, and obtain at least one first data transmission interface.

In this embodiment of the application, the current request quantity value of each second data transmission interface is compared with its corresponding first current current limiting threshold to obtain the second data whose current request quantity value is greater than the corresponding first current current limiting threshold transmission interface, and determine the second data transmission interface whose current request quantity value is greater than the corresponding first current limiting threshold as at least one first data transmission interface. Wherein, at least one first data transmission interface includes one first data transmission interface and at least two first data transmission interfaces.

It should be noted that, for at least one second data transmission interface, there is a situation where each current request quantity value is smaller than the corresponding first current current limiting threshold, that is, a first data transmission interface cannot be determined, that is to say, there is no need to A current limiting operation is performed on at least one second data transmission interface.

Step 205: Determine the first current current limiting threshold corresponding to the current limiting parameter of each first data transmission interface, and obtain at least one first current current limiting threshold.

In this embodiment of the present application, the first current current limiting threshold corresponding to each first data transmission interface may be directly obtained from the determined first current current limiting threshold corresponding to at least one second data transmission interface. Exemplarily, it is assumed that the determined at least one first data transmission interface is at least one second data transmission interface, that is, interface 2, interface 4, and interface 5 among interface 1, interface 2, interface 3, interface 4, and interface 5, and the corresponding It can be determined that the first current limit thresholds corresponding to the current limit parameters of each first data transmission interface included in the at least one first data transmission interface are in turn: the first current limit threshold corresponding to interface 2 is a2, and the first current limit threshold corresponding to interface 4 is a2. The first current limiting threshold is a4 and the first current limiting threshold corresponding to the interface 5 is a5.

Step 206: Analyze the CPU usage of at least one first current current limiting threshold, and determine the corresponding current limiting threshold of each first data transmission interface to be adjusted.

In this embodiment of the application, the first current limiting threshold corresponding to interface 2 is a2, the first current limiting threshold corresponding to interface 4 is a4, and the first current limiting threshold corresponding to interface 5 is a5. The current limiting threshold to be adjusted corresponding to interface 2, the current limiting threshold to be adjusted corresponding to interface 4, and the current limiting threshold to be adjusted corresponding to interface 5 are obtained. When determining the to-be-adjusted current limiting threshold of each first data transmission interface, it may be obtained by independently analyzing and determining the first current current limiting threshold of each corresponding first data transmission interface. However, in some application scenarios, since the adjustment of the current limiting threshold of each data transmission interface will have a greater impact on the CPU usage of the information adjustment device, therefore, when adjusting the current limiting parameter of each first data transmission interface When the value is , it may be necessary to conduct a global analysis on the current limiting parameter values of all data transmission interfaces of the information adjustment device to determine the current limiting threshold to be adjusted for each first data transmission interface.

Step 207, adjusting the value of the current limiting parameter of each first data transmission interface to the corresponding current limiting threshold to be adjusted.

In this embodiment of the application, after the information adjustment device determines the current limiting threshold to be adjusted for each first data transmission interface, it adjusts the value of the current limiting parameter of each first data transmission interface to the corresponding current limiting threshold to be adjusted, However, the values of the current limiting parameters of the at least one second data transmission interface other than the at least one first data transmission interface are not adjusted.

It should be noted that, for descriptions of the same steps and content in this embodiment as in other embodiments, reference may be made to the descriptions in other embodiments, and details are not repeated here.

An embodiment of the present application provides an information adjustment method, as shown in FIG. 3 , the method is applied to an information adjustment device, and the method includes the following steps:

Step 301. Determine at least one second data transmission interface that is in a data transmission mode at the current moment.

Step 302. Determine a first current current limiting threshold corresponding to a current limiting parameter of each second data transmission interface.

Step 303. Determine the current request quantity value of each second data transmission interface.

Step 304: From the at least one second data transmission interface, determine the second data transmission interface whose current request quantity value is greater than the corresponding first current limiting threshold, and obtain at least one first data transmission interface.

Step 305: Determine a first current current limiting threshold corresponding to the current limiting parameter of each first data transmission interface, to obtain at least one first current current limiting threshold.

Step 306, acquiring a trained target neural network model.

In the embodiment of the present application, the trained target neural network model may be obtained by performing model training on a back propagation (Back Propagation, BP) neural network using a large amount of historical data. Wherein, the historical data includes the current limiting threshold of each data transmission interface, and on the premise of the current limiting threshold of each data transmission interface, the corresponding information adjusts the CPU usage of the device.

Among them, step 306 can be realized by the following steps: obtaining historical sample data; cleaning historical sample data, eliminating error data, and obtaining target sample data; using target sample data to perform model training on the initialized neural network model to obtain the target neural network model .

Step 307. Determine a preset step value of each first data transmission interface.

In the embodiment of the present application, the preset step value of each first data transmission interface may be preset, or may be calculated according to actual conditions.

Step 308: Based on the first current limit threshold of at least one first data transmission interface and the corresponding preset step value of each first data transmission interface, use the target neural network model to perform CPU usage prediction processing, and determine the corresponding The current limiting threshold to be adjusted for each first data transmission interface.

In this embodiment of the application, after adjusting the first current limit threshold of each first data transmission interface by using the preset step value of each first data transmission interface, the input to the target neural network model Layer, so that the target neural network model predicts the knowledge after adjusting the first current limit threshold of the corresponding first data transmission interface based on the preset step value of each first data transmission interface, and then according to the prediction result, to Determine the current limit threshold to be adjusted corresponding to each first data transmission interface.

Step 309 , adjusting the value of the current limiting parameter of each first data transmission interface to the corresponding current limiting threshold to be adjusted.

Based on the foregoing embodiments, in other embodiments of the present application, step 307 may be implemented by steps 307a or 307b-307c; wherein, when the number of at least one first data transmission interface is 1, choose to execute step 307a, and at least one When the number of the first data transmission interface is greater than or equal to 2, choose to perform steps 307b-307c:

Step 307a, if at least one first data transmission interface includes one first data transmission interface, determine a preset step value corresponding to the first data transmission interface as a unit step value.

In the embodiment of the present application, the unit step value may be a preset positive integer value, for example, the unit step value may be 1.

Step 307b. If at least one first data transmission interface includes at least two first data transmission interfaces, determine a proportional relationship between first current limiting thresholds of the at least two first data transmission interfaces.

In the embodiment of the present application, when the number of at least one first data transmission interface is greater than or equal to 2, a proportional calculation is performed on the first current limiting threshold of the at least one first data transmission interface to obtain a corresponding proportional relationship. Exemplarily, when at least one first data transmission interface is interface 2, interface 4, and interface 5, since the first current limit threshold corresponding to interface 2 is a2, and the first current limit threshold corresponding to interface 4 is a4 and The first current limiting threshold corresponding to interface 5 is a5, therefore, it can be determined that the proportional relationship between the first current limiting thresholds of at least one first data transmission interface can be recorded as interface 2:interface 4:interface 5=a2 :a4:a5, assuming a2:a4:a5=1:2:1.

Step 307c, based on the proportional relationship and the unit step value, determine a preset step value corresponding to each first data transmission interface.

In this embodiment of the application, assuming that the unit step value is 1, the corresponding proportional relationship a2:a4:a5=1:2:1 and the unit step value of 1 determine the preset step value of interface 2 1. The preset step value of port 4 is 2, and the default step value of port 5 is 1.

Based on the foregoing embodiments, in other embodiments of the present application, step 308 can be implemented by steps 308a-308h, or steps 308a and 308i-308p; The number of second interfaces of the second data transmission interface is the same, choose to execute steps 308a-308h, if the number of second interfaces is greater than the number of first interfaces, steps 308a and 308i-308p:

Step 308a. Determine the sum of the first current current limiting threshold and the corresponding preset step value of each first data transmission interface to obtain at least one first reference current limiting threshold.

In this embodiment of the application, when the number of at least one first data transmission interface is equal to 1, the first reference current limiting threshold of the first data transmission interface=the first current current limiting threshold of the first data transmission interface+preset Step value, where the preset step value is a unit step value. Exemplarily, the first reference current limiting threshold of the first data transmission interface is the first current current limiting threshold+1.

When the number of at least one first data transmission interface is greater than or equal to 2, the calculation formula of the first reference current limiting threshold can be written as: first reference current limiting threshold=first current current limiting threshold+preset step value, so , the first reference current limiting threshold a21 corresponding to interface 2 is a2+1, the first reference current limiting threshold a41 corresponding to interface 4 is a4+2, and the first reference current limiting threshold a51 corresponding to interface 5 is a5+1.

Step 308b, if the number of the first interface of the at least one first data transmission interface is the same as the number of the second interface of the at least one second data transmission interface, through the target neural network model, perform the central processing unit on at least one first reference current limiting threshold (Central Processing Unit, CPU) occupancy rate prediction to obtain the first predicted occupancy rate.

In this embodiment of the application, the number of first interfaces of at least one first data transmission interface is the same as the number of second interfaces of at least one second data transmission interface, indicating that the current request quantity values of all data transmission interfaces of the information adjustment device exceed If the corresponding first current current limiting threshold is determined, the current limiting parameters of all data transmission interfaces need to be adjusted. At this time, if the first interface number of at least one first data transmission interface is 1, the second number of at least one second data transmission interface is also 1. Input at least one first reference current-limiting threshold corresponding to at least one first data transmission interface to the input layer of the target neural network model, and use the target neural network model to predict that in the case of at least one first reference current-limiting threshold, information adjustment The occupancy rate of the central processing unit (Central Processing Unit, CPU) corresponding to the device is used to obtain the first predicted occupancy rate.

Step 308c, acquiring the current CPU usage at the current moment.

In this embodiment of the present application, when the current occupancy rate of the CPU at the current moment and the current limiting parameter of each second data transmission interface included in at least one second data transmission interface are the first current current limiting threshold, the information adjustment device corresponds to The actual CPU usage.

Step 308d. Determine a first difference between the first predicted occupancy rate and the current occupancy rate.

In this embodiment of the present application, the first difference=the first predicted occupancy rate−the current occupancy rate.

Wherein, after the information adjustment device executes step 308d, it can choose to execute step 308e, or choose to execute steps 308f-308h; where, if the first difference is greater than or equal to the target error, choose to execute step 308e, if the first difference is smaller than the target error , choose to execute steps 308f to 308h:

Step 308e, if the first difference is greater than or equal to the target error, determine the current-limiting threshold to be adjusted for each first data transmission interface as the corresponding first reference current-limiting threshold.

In the embodiment of this application, the target error is an error experience value obtained from a large number of experiments, or an error experience value set by the user according to actual needs. In the actual use process, the target error can be continuously corrected and adjusted. When the first difference is greater than or equal to the target error, it is determined that the adjusted first reference current limit threshold meets the requirements, therefore, it is determined that the adjusted current limit threshold of each first data transmission interface is the corresponding first reference limit flow threshold.

Exemplarily, when the first interface number of at least one first data transmission interface is the same as the second interface number of at least one second data transmission interface, that is, interface 1, interface 2, interface 3, interface 4, and interface 5 are all within the limit In streaming mode, it is assumed that the first current limit threshold corresponding to at least one first data transmission interface is: the first current limit threshold of interface 1 is a1, the first current limit threshold of interface 2 is a2, and the first current limit threshold of interface 3 is The first current limiting threshold is a3, the first current limiting threshold of interface 4 is a4, and the first current limiting threshold of interface 5 is a5. Correspondingly, the determined preset step value of interface 1 is b1, interface The preset step value of 2 is b2, the default step value of interface 3 is b3, the preset step value of interface 4 is b4, and the preset step value of interface 5 is b5. Therefore, the determined interface 1 The first reference current limit threshold of interface 2 is a11=a1+b1, the first reference current limit threshold of interface 2 is a21=a2+b2, the first reference current limit threshold of interface 3 is a31=a3+b3, and the first reference current limit threshold of interface 4 is a31=a3+b3. A reference current limiting threshold is a41=a4+b4 and the first reference current limiting threshold of interface 5 is a51=a5+b5. At this time, if a11, a21, a31, a41 and a51 are predicted by the target neural network model , when the obtained first difference between the first predicted occupancy rate and the current occupancy rate is greater than or equal to the target error, determine that the current limiting threshold to be adjusted for interface 1 is a11, the current limiting threshold for interface 2 is a21, and the current limiting threshold for interface 3 is determined to be a11. The current limiting threshold to be adjusted is a31, the current limiting threshold to be adjusted of interface 4 is a41, and the current limiting threshold to be adjusted of interface 5 is a51.

Step 308f, if the first difference is smaller than the target error, determine the sum of each first reference current-limiting threshold and the corresponding preset step value to obtain at least one second reference current-limiting threshold.

In the embodiment of the present application, if the first difference is smaller than the target error, continue to sum each first reference current-limiting threshold and the corresponding preset step value to obtain at least one second reference current-limiting threshold. Exemplarily, correspondingly, it can be determined that the second reference current limiting threshold of interface 1 is a12=a11+b1=a1+2b1, the second reference current limiting threshold of interface 2 is a22=a21+b2=a2+2b2, and the interface The second reference current limit threshold of 3 is a32=a31+b3=a3+2b3, the second reference current limit threshold of interface 4 is a42=a41+b4=a4+2b4, and the second reference current limit threshold of interface 5 is a52=a51+b5=a5+2b5.

Step 308g, updating at least one first reference current limiting threshold to at least one second reference current limiting threshold.

In this embodiment of the application, the calculated second reference current limit threshold a12=a1+2b1 of interface 1 is assigned to the first reference current limit threshold a11 of interface 1 and the second reference current limit threshold a22=a2 of interface 2 +2b2 is assigned to the first reference current limit threshold a21 of interface 2 and the second reference current limit threshold of interface 3 a32=a3+2b3 is assigned to the first reference current limit threshold a31 of interface 3 and the second reference current limit of interface 4 The threshold a42=a4+2b4 is assigned to the first reference current limiting threshold a41 of interface 4, and the second reference current limiting threshold a52=a5+2b5 of interface 5 is assigned to the first reference current limiting threshold a51 of interface 5.

Step 308h, return to execute "predict the CPU occupancy rate of at least one first reference current limiting threshold through the target neural network model to obtain the first predicted occupancy rate", until after n times of looping, when the first difference is greater than or equal to the target In the case of an error, or in the case of n being greater than or equal to the first preset number of times, determine that the current-limiting threshold to be adjusted for each first data transmission interface is the corresponding updated first reference current-limiting threshold.

Wherein, the updated first reference current limiting threshold is the sum of n times the preset step value corresponding to the corresponding first data transmission interface and the corresponding first current limiting threshold, and n is a positive value greater than or equal to 1. integer.

In the embodiment of this application, the target neural network model is used to predict the updated a11 of interface 1, a21 of interface 2, a31 of interface 3, a41 of interface 4, and a51 of interface 5 to obtain the corresponding first prediction occupancy, and then determine a first reference difference between the first predicted occupancy and the current occupancy.

If the first reference difference is greater than or equal to the target error, determine that the current-limiting threshold to be adjusted for each first data transmission interface is the corresponding updated first reference current-limiting threshold, that is, if the first reference difference is greater than or equal to the target Error, determine that the current limiting threshold to be adjusted for interface 1 is a11=a1+2b1, the current limiting threshold for interface 2 is a21=a2+2b2, and the current limiting threshold for interface 3 is a31=a3+2b3. The current limiting threshold to be adjusted for 4 is a41=a4+2b4 and the current limiting threshold for interface 5 is a51=a5+2b5.

If the first reference difference is smaller than the target error, calculate the sum of the updated a11, a21, a31, a41, and a51 and their corresponding preset step values again, and obtain the second reference current-limiting threshold of interface 1 as a12= a1+3b1, the second reference current limit threshold of interface 2 is a22=a2+3b2, the second reference current limit threshold of interface 3 is a32=a3+3b3, and the second reference current limit threshold of interface 4 is a42=a4+ 3b4, and the second reference current limiting threshold of interface 5 is a52=a5+3b5, then assign a12=a1+3b1 to a11, a22=a2+3b2 to a21, a32=a3+3b3 to a31, a42= After a4+3b4 is assigned to a41, and a52=a5+3b5 is assigned to a51, continue to use the target neural network model to perform CPU occupancy prediction processing on the updated a11, a21, a31, a41, and a51, and obtain the corresponding predicted occupancy and The difference between the current occupancy rate, if the difference between the corresponding predicted occupancy rate and the current occupancy rate is greater than or equal to the target difference, determine the current limit thresholds to be adjusted corresponding to each interface as the updated a11, a21, a31, a41, and a51 , otherwise, continue to repeat the preceding steps until the difference between the predicted occupancy rate obtained by the target neural network model and the current occupancy rate corresponding to the same time is greater than or equal to the target error, Or when the number of iterations of the updated a11, a21, a31, a41 and a51 exceeds the first preset number, the operation ends.

Wherein, the first preset number of times is an experience value of times obtained from a large number of experiments, or may be an experience value of times set by the user according to actual needs.

Step 308i. If the second interface number is greater than the first interface number, determine a first current current limiting threshold of at least one third data transmission interface.

Wherein, the at least one third data transmission interface is a data transmission interface in the at least one second data transmission interface except the at least one first data transmission interface.

In this embodiment of the present application, the number of second interfaces is greater than the number of first interfaces, indicating that at least one first data transmission interface is a part of the data transmission interface included in at least one second data transmission interface, that is, only some transmission interfaces are in the current limiting mode , determine at least one third data transmission interface that is not in the current limiting mode in the information adjustment device, and determine the first current current limiting threshold of the at least one third data transmission interface. Wherein, at least one second data transmission interface is composed of at least one first data transmission interface and at least one third data transmission interface.

Step 308j: Using the target neural network model, perform CPU occupancy prediction on at least one first reference current limiting threshold and the first current current limiting threshold of at least one third data transmission interface to obtain a second preset occupancy.

In this embodiment of the application, since at least one second data transmission interface is currently transmitting data, the request traffic of at least one second data transmission interface has an impact on the CPU occupancy rate of the information adjustment device. Therefore, when using the target When the neural network model predicts the CPU usage, at least one current limiting parameter of the second data transmission interface needs to be considered. Therefore, when determining the current limiting parameter of at least one first data transmission interface through the target neural network model, it is also necessary to input the first current limiting threshold of at least one third data transmission interface to obtain an accurate at least one first The current limit threshold to be adjusted for the data transmission interface.

Step 308k, acquiring the current CPU usage at the current moment.

Step 308l. Determine a second difference between the second preset occupancy rate and the current occupancy rate.

Wherein, after the information adjustment device executes step 308l, it can choose to execute step 308m, or choose to execute steps 308n-308p; where, if the second difference is greater than or equal to the target error, choose to execute step 308m, if the second difference is less than or equal to Target error, choose to execute steps 308n-308p:

Step 308m, if the second difference is greater than or equal to the target error, determine the current-limiting threshold to be adjusted for each first data transmission interface as the corresponding first reference current-limiting threshold.

Step 308n, if the second difference is smaller than the target error, determine the sum of each first reference current-limiting threshold and the corresponding preset step value to obtain at least one second reference current-limiting threshold.

Step 308o, updating at least one first reference current limiting threshold to at least one second reference current limiting threshold.

Step 308p, return to execute step 308j, until after looping m times, if the second difference is greater than or equal to the target error, or m is greater than or equal to the second preset number of times, determine each first data transmission interface The current limiting threshold to be adjusted is the corresponding updated first reference current limiting threshold.

Wherein, the updated first reference current limiting threshold is the sum of m times the preset step value corresponding to the corresponding first data transmission interface and the corresponding first current limiting threshold, and m is a positive value greater than or equal to 1. integer.

Based on the foregoing embodiments, in other embodiments of the present application, after performing step 308, the information adjustment device is further configured to perform the following steps: If it detects that there is an interface in current-limiting mode among at least one second data transmission interface, return to execute " Determine at least one first data transmission interface that is currently in the current-limiting mode, until the number of interfaces in the current-limiting mode in the at least one second data transmission interface is zero, or the updated data included in the at least one second data transmission interface When the current limiting parameter corresponding to the at least one first data transmission interface is adjusted to the corresponding first to-be-adjusted current limiting threshold, the determined first actual CPU occupancy rate is greater than or equal to the preset occupancy rate.

In the embodiment of the present application, the working mode of each data transmission interface is constantly checked, that is, whether it is in the current limiting mode. Once it is detected that there is an interface in the current limiting mode in at least one second data transmission interface, then from the step 301 starts to be executed repeatedly, and adjusts the current limiting parameters of the data transmission interface in the current limiting mode to ensure the efficiency of data transmission.

Based on the foregoing embodiments, in other embodiments of the present application, as shown in FIG. 4 , after performing step 309, the information adjustment device may also be used to perform steps 310-312:

Step 310, acquiring the first actual CPU usage rate corresponding to the value of the current limiting parameter of each first data transmission interface when the current limiting threshold is to be adjusted.

In this embodiment of the application, after the information adjustment device adjusts the value of the current limiting parameter of at least one first data transmission interface to the corresponding current limiting threshold to be adjusted, since the data transmission interface of the information adjustment device is still receiving service requests, the The corresponding service is provided. Therefore, the information adjustment device can collect the first value of the CPU of the corresponding information adjustment device when the value of the current limit parameter of each first data transmission interface is adjusted to the corresponding current limit threshold to be adjusted. actual occupancy.

Step 311 , determining the corresponding target predicted occupancy rate obtained through the prediction of the target neural network model when the value of the current limiting parameter of each first data transmission interface is the current limiting threshold to be adjusted.

In this embodiment of the application, when the value of the current limiting parameter of each first data transmission interface is the current limiting threshold to be adjusted, the corresponding target predicted occupancy rate can be determined according to the aforementioned implementation process, if the first difference is greater than or is equal to the target error, the target predicted occupancy rate can be determined as the first predicted occupancy rate; if the second difference is greater than or equal to the target error, the target predicted occupancy rate can be determined as the second predicted occupancy rate.

Step 312: Update the target neural network model based on the target predicted occupancy rate and the first actual occupancy rate.

In the embodiment of the present application, the information adjustment device performs feedback processing according to the first actual occupancy rate obtained after adjusting at least one first data transmission interface, and updates and adjusts the target neural network model to make the target neural network model more realistic The application scenario ensures the accuracy of the target neural network model and effectively ensures the reliability of the prediction process.

Based on the foregoing embodiments, in other embodiments of the present application, as shown in FIG. 5 , after performing step 303, the information adjustment device is also used to perform steps 313-314:

Step 313: If it is detected that in at least one second data transmission interface, the current request quantity value of each second data transmission interface is less than the corresponding first current limiting threshold, determine the ratio of each first current limiting threshold to a preset value The product of , get the corresponding feedback current limit threshold.

Wherein, the feedback current limiting threshold is smaller than the first current current limiting threshold.

In the embodiment of the present application, the preset ratio is an empirical ratio value obtained from a large number of experiments, and may also be an empirical ratio value set by the user according to actual needs. If the at least one second data transmission interface included in the information adjustment device does not need to perform current limiting processing, determine the product of each first current current limiting threshold and the preset ratio to obtain the corresponding feedback current limiting threshold. Exemplarily, the at least one first current limit threshold corresponding to at least one second data transmission interface is sequentially: the first current limit threshold of interface 1 is a1, the first current limit threshold of interface 2 is a2, and the first current limit threshold of interface 2 is a2. The first current limiting threshold of interface 3 is a3, the first current limiting threshold of interface 4 is a4, and the first current limiting threshold of interface 5 is a5. Correspondingly, when the preset ratio is γ, the corresponding interface 1 The feedback current-limiting threshold of interface 2 is recorded as γ*a1, the feedback current-limiting threshold of interface 2 is recorded as γ*a2, the feedback current-limiting threshold of interface 3 is recorded as γ*a3, the feedback current-limiting threshold of interface 4 is recorded as γ*a4 and The feedback current limiting threshold of interface 5 is denoted as γ*a5.

Step 314, if it is detected that among at least one second data transmission interface, the current request quantity value of each second data transmission interface is less than the corresponding feedback current limiting threshold, adjust the value of the current limiting parameter of each second data transmission interface To initialize the current limit threshold.

In this embodiment of the application, the initial current limit threshold is the default current limit threshold set by the information adjustment device for each second data transmission interface. The system of the device is set by default. Exemplarily, since the current request quantity value of interface 1 is q1, the current request quantity value of interface 2 is q2, the current request quantity value of interface 3 is q3, the current request quantity value of interface 4 is q4, and the current request quantity value of interface 5 is The quantity value is q5, therefore, when q1<γ*a1, q2<γ*a2, q3<γ*a3, q4<γ*a4 and q5<γ*a5, adjust the current limit of each second data transmission interface The value of the parameter is the initial current limit threshold.

Based on the foregoing embodiments, the embodiment of the present application provides a system architecture diagram for implementing an information adjustment method, as shown in FIG. Dictionary service (Remote Dictionary Server, Redis) 46 and application server agent (Agent) 47; Wherein:

The configuration module 41 is used to provide service operation and maintenance personnel (referred to as operation and maintenance personnel) with an interface for filling in the configuration information of each data transmission interface and the adjustable flag bit. The configuration information includes at least the aforementioned initialized current limiting threshold. Suppose there are three second data transmission interfaces A, B, and C. After the configuration information for the three second data transmission interfaces A, B, and C is submitted, the configuration information for the three second data transmission interfaces A, B, and C will be Write the configuration table rate_config preset in the database 45 for recording the configuration information of each second data transmission interface, and write the initial current limiting thresholds for the three second data transmission interfaces A, B and C into the database 45 In the preset agent_upload_data_log table for recording the initial current limit threshold of each second data transmission interface, the naming method of the initial current limit threshold of each second data transmission interface can be recorded as "interface name_limit".

It should be noted that the information adjustment method provided by this application is executed only when the adjustable flag is marked as adjustable, and the information adjustment method provided by this application is not executed when the adjustable flag is marked as non-adjustable.

In the database 45, it also includes the number of requests received for each time slice of each second data transmission interface, and the naming method of the number of requests received by each time slice of each second data transmission interface is record It is "interface name_request_cnt"; an agent_upload_data_cal table used to record the current limit threshold of each second data transmission interface in each time slice, the number of requests for each second data transmission interface, and the CPU usage rate.

The acquisition module 42 is used to receive the data of each time slice returned by the application server agent 47, which may be JavaScript object notation (JavaScript Object Notation, JSON) data. Exemplarily, the JSON data format received by the acquisition module 42 may be as follows:

After the acquisition module 42 receives the above data, it analyzes it and writes the analyzed data into the agent_upload_data_log data table in the database 45 . Acquisition module 42 writes the data that analysis obtains in the agent_upload_data_log data table in the database 45 and comprises: create asynchronous task one, and asynchronous task one query records the number of requests of each second data request interface in the Redis 46 of this time slice, i.e. the aforementioned When creating an asynchronous task, ensure that there is no corresponding time slice task in the task table; create asynchronous task 2, first, asynchronous task 2 calculates the current limit value A_limit_sum of the time slice for A data transmission interface, and B data transmission The current-limited value B_limit_sum of the interface and the current-limited value C_limit_sum of the C data transmission interface. It should be noted that, taking the A data transmission interface as an example, the current-limited value A_limit_sum of the A data transmission interface is based on the The number of requests for this time slice is determined by the current limit threshold of A data transmission interface in this time slice. The number of requests for A data transmission interface in this time slice is less than or equal to the limit of A data transmission interface in this time slice. When the flow threshold is set, A_limit_sum is determined to be 0. When the number of requests of A data transmission interface in this time slice is greater than the current limit threshold of A data transmission interface in this time slice, A_limit_sum is determined to be the request of A data transmission interface in this time slice The difference between the number minus the current limit threshold of the A data transmission interface in this time slice; secondly, calculate the average cpu_avg of the CPU usage rate of the time slice; then, query the data transmission interface in Redis 46 of the time slice The number of requests is A_request_cnt, B_request_cnt, C_request_cnt; finally, time_stamp, A_limit_sum, B_limit_sum, C_limit_sum, cpu_avg, A_request_cnt, B_request_cnt, C_request_cnt are written into the preset agent_upload_data_cal table in the database 45.

The training module 43 is used to perform model training on the BP initialization neural network model to obtain the target neural network model, and continuously update the model of the target neural network model.

The training module 43 is driven by a timed task, for example, it may train once an hour. The specific implementation process of the training module 43 is as follows:

(1) Data selection and cleaning

Obtain all the data in the time slice in the agent_upload_data_cal table included in the database 45 within a period of time, for example, within two days from the current moment, to obtain the first data set. If the duration of the data included in the agent_upload_data_cal table is less than two days, stop this training.

According to the above description, A_limit_sum is the current limit value corresponding to the A data transmission interface in a certain time slice, B_limit_sum is the current limit value corresponding to the B data transmission interface in a certain time slice, and C_limit_sum is the C data transmission interface in a certain time slice. The current-limited value corresponding to the time slice. If the current-limited value of a data transmission interface is greater than 0, it means that the data transmission interface has a current-limited value during this time slice. Current limiting is to reject requests at the bottom of the application. At this time, the application consumes almost no resources, so this part of the data needs to be removed, otherwise the calculation accuracy will be affected. In this way, the first data set is traversed to determine whether at least one current-limited value in each group of A_limit_sum, B_limit_sum, and C_limit_sum is greater than 0. If there is at least one data transmission interface whose current-limited value is greater than 0, determine the judgment condition If it is established, each group of A_limit_sum, B_limit_sum and C_limit_sum including the judgment condition is established is eliminated from the first data set, and finally the second data set is obtained.

In the actual operating environment, the specifications of the server devices in the same operating system are consistent, and the number of online requests processed is almost equal, so the difference in CPU utilization does not exceed 5%. Traversing the second data set, using the time slice time_stamp as an index, query the corresponding time slice in agent_upload_data_log whether there is a difference between the CPU usage of a certain server in the time slice and the average CPU usage cpu_avg of all servers in the time slice exceeds 0.05. If the CPU usage rate of a certain server exceeds the average CPU usage rate cpu_avg, the data of the server in the time slice is removed from the second data set to obtain the third data set. Select A_request_cnt, B_request_cnt, C_request_cnt, and cpu_avg from the third data set, that is, the aforementioned first actual CPU usage field, to form a new fourth data set.

(2) BP neural network model training

The number of input variables of the BP neural network model is the number of data transmission interfaces included in the configuration table rate_config; the number of hidden layers is at least 2, and the number of output variables is 1. Exemplarily, as shown in the aforementioned JSON data format, there are three interfaces in total, so the number of input variables of the BP neural network model is 3, and the number of hidden layers is assumed to be 3.

The weight coefficient and bias coefficient initialization process of the BP neural network model: input each group of A_request_cnt, B_request_cnt and C_request_cnt in the fourth data set to the input layer of the BP neural network model; expected output: and each group in the fourth data set The cpu_avg corresponding to A_request_cnt, B_request_cnt and C_request_cnt; the training output is input A_request_cnt, B_request_cnt, C_request_cnt to the input layer of the BP neural network model, and the output layer of the BP neural network model outputs the predicted CPU usage rate Y_cpu_avg; calculation error Err=cpu_avg-Y_cpu_avg, Update the weight coefficient and bias coefficient of the BP neural network model according to the error Err, until the error between the predicted CPU usage calculated by the updated BP neural network model and the corresponding cpu_avg is less than or equal to 5%, determine at this time The corresponding updated BP neural network model is the aforementioned target neural network model.

The adjustment module 44 is configured to automatically adjust the current limiting threshold configuration of each data transmission interface in gray scale based on the principle of negative feedback.

(1) The adjustment module 44 checks the data reported by the agent_upload_data_cal latest server agent 46, and checks whether the current-limited value of each data transmission interface is greater than 0, that is, whether the data request quantity of each data transmission interface is greater than the current-limited threshold of each data transmission interface . If the current limit value of the data transmission interface is greater than 0, the current limit threshold adjustment task is started, and the target neural network model is obtained as the operation model for this adjustment. For the current limit situation of different data transmission interfaces, it can be divided into single interface occurrence The following two adjustment methods are adopted for current limiting and multi-interface current limiting:

For the situation where a single interface is limited: Assuming that the B data transmission interface has a current limit, first, the current limit threshold of the current limited B data transmission interface is increased by a unit step value such as 1 to update B_request_cnt, A The data transmission interface A_request_cnt is the original configuration current limiting threshold, and the C data transmission interface C_request_cnt is the original configuration current limiting threshold. Input A_request_cnt, updated B_request_cnt and C_request_cnt into the target neural network model to obtain the first predicted CPU usage, At the same time, calculate the difference between the first predicted CPU usage rate and the cpu_avg of the current time slice. If the difference is greater than or equal to 0.05, end; otherwise, repeat the above steps and continuously adjust the B_request_cnt of the B data transmission interface until it passes the target neural network. If the difference between the third predicted CPU usage obtained by the model prediction and cpu_avg is greater than 0.05, the loop is terminated, and the updated B_request_cnt is determined as the latest current limit threshold of the B data transmission interface, and then the latest limit of the updated B_request_cnt is set to The configuration of the flow threshold is delivered to each application; finally, the adjusted configuration and the corresponding predicted CPU usage are stored in the database 45 .

For the situation where multiple interfaces are limited in current: Assume that data transmission interface A and data transmission interface B have current limitation at the same time, first, calculate the ratio of the initial current limiting threshold of data transmission interface A and data transmission interface B, assuming A:B = 1:3, the cycle starts, and the current-limited data transmission interface increases the preset step value proportionally in each cycle. Assuming that the unit step value is 1, the original configuration current-limiting threshold of the A data transmission interface is increased by 1 as A_request_cnt, then the current limiting threshold of the original configuration of the B data transmission interface is increased by 3 as B_request_cnt, and C_request_cnt of the C data transmission interface is the original configuration of the current limiting threshold. In this way, the updated A_request_cnt, B_request_cnt and C_request_cnt are input into the target neural network model , get the first predicted CPU occupancy rate, and calculate the cpu_avg difference between the predicted CPU occupancy rate and the current time slice at the same time, so that the preset step value of the A data transmission interface and the preset step value of the B data transmission interface are continuously used Make adjustments and perform loop processing until the difference between the predicted third predicted CPU usage and cpu_avg is greater than or equal to 0.05, or the number of iterations reaches a preset number of times, such as 10000, and the loop is terminated, so that the latest A data transmission can be obtained The current limit threshold corresponding to the interface and the current limit threshold corresponding to the B data transmission interface. Then send and configure the latest current limiting threshold corresponding to the A data transmission interface and the current limiting threshold corresponding to the B data transmission interface to each application, and finally, store the adjusted configuration and the corresponding third predicted CPU usage rate in the database 45 .

(2) After the adjustment module 44 sends the updated configuration to each application, it collects the latest data reported by the application server agent 47 in the next time period, such as 5 seconds from the current period, to obtain the updated configuration correspondence The first actual CPU occupancy rate of , and calculate the error between the first actual CPU occupancy rate and the corresponding third predicted CPU occupancy rate, and negatively feed back the error to the target neural network model, and perform model training on the target neural network model Update to get the updated target neural network model.

(3) The adjustment module 44 checks the data reported to the agent_upload_data_cal table by the application server agent 47 in (2), and checks whether the current-limited value of each data transmission interface is greater than 0. If there is still a current-limited value of the data transmission interface greater than 0, the current limit still exists, and (1) and (2) can be repeated until the latest actual CPU usage collected in (2) exceeds 75% or there is no current limit. If the current-limited data transmission interface is used, the adjustment module 44 terminates the adjustment task and initializes the monitoring task.

(4) When the adjustment module 44 is also used to detect the data reported by the agent_upload_data_cal latest application server agent 47, if it detects that the request quantity values of each data transmission interface, such as A_request_cnt, B_request_cnt and C_request_cnt, are less than the corresponding current current limit thresholds When half of the aforementioned preset ratio is 50%, the current limiting thresholds of each data transmission interface are restored to the initial current limiting thresholds in the configuration table rate_config.

In this way, negative feedback current limiting threshold adjustment can be realized, and 25% to 30% of CPU resources that are idle in production can be temporarily used when current limiting occurs, effectively reducing the impact of current limiting and gaining time for capacity expansion. In some application scenarios, in order to ensure stable operation and meet the disaster recovery requirements of business systems, the actual CPU usage is usually controlled at about 45%. If the current limit threshold of each data transmission interface is increased due to the existence of current limit, the actual CPU usage will increase. When the volume increases rapidly, some requests may be processed too slowly. In order to avoid such risks, this application also proposes to restore the value of the current limiting parameter of each data transmission interface to the configured The initial rate limit threshold in the table rate_config.

In this embodiment of the application, after determining at least one first data transmission interface that is currently in the current limiting mode, determine the first current limiting threshold corresponding to the current limiting parameter of each first data transmission interface, and obtain at least one first current limiting threshold. flow threshold, and analyze the CPU occupancy rate of at least one first current current limit threshold to determine the current limit threshold to be adjusted corresponding to each first data transmission interface, so that the current limit parameters of each first data transmission interface The value is adjusted to the current limit threshold to be adjusted, which solves the problem of low flexibility in the current limit configuration process, and realizes an intelligent automatic adjustment of the current limit threshold. The current limit parameter value of the interface is dynamically adjusted, which effectively improves the flexibility and adjustment efficiency of the current limit configuration process.

Based on the foregoing embodiments, the embodiments of the present application provide an information adjustment device, which can be applied to the information adjustment method provided in the embodiments corresponding to Figures 1 to 5, as shown in Figure 7, the information adjustment device 5 May include: processor 51, memory 52 and communication bus 53, wherein:

Memory 52, used to store executable instructions;

Communication bus 53, for realizing the communication connection between processor 51 and memory 52;

The processor 51 is configured to execute the information adjustment program stored in the memory 52, so as to realize the following steps:

Determining the first current current limiting threshold corresponding to the current limiting parameter of each first data transmission interface to obtain at least one first current current limiting threshold;

Analyzing the CPU occupancy rate of the central processing unit for at least one first current limiting threshold, and determining the corresponding current limiting threshold for each first data transmission interface to be adjusted;

The value of the current limiting parameter of each first data transmission interface is adjusted to a corresponding to-be-adjusted current limiting threshold.

In other embodiments of the present application, when the processor executes the step of determining at least one first data transmission interface that is currently in the current limiting mode, it may be implemented through the following steps:

Determine at least one second data transmission interface that is in data transmission mode at the current moment;

Determine the first current current limiting threshold corresponding to the current limiting parameter of each second data transmission interface;

determining the current request quantity value of each second data transmission interface;

From the at least one second data transmission interface, determine the second data transmission interface whose current request quantity value is greater than the corresponding first current current limiting threshold, to obtain at least one first data transmission interface.

In other embodiments of the present application, the processor executes the step of analyzing the CPU occupancy rate of the central processing unit for at least one first current limiting threshold, and when determining the corresponding current limiting threshold of each first data transmission interface to be adjusted, it can be determined by Follow these steps to achieve:

Obtain the trained target neural network model;

determining a preset step value for each first data transmission interface;

Based on the first current limiting threshold of at least one first data transmission interface and the corresponding preset step value of each first data transmission interface, the target neural network model is used to perform CPU occupancy rate prediction processing, and each corresponding first data transmission interface is determined. A current limiting threshold to be adjusted for a data transmission interface.

In other embodiments of the present application, when the processor executes the step of determining the preset step value corresponding to each first data transmission interface, it may be implemented through the following steps:

If at least one first data transmission interface includes a first data transmission interface, determine that the preset step value corresponding to the first data transmission interface is a unit step value;

If at least one first data transmission interface includes at least two first data transmission interfaces, determining a proportional relationship between the first current limiting thresholds of the at least two first data transmission interfaces;

Based on the proportional relationship and the unit step value, a preset step value corresponding to each first data transmission interface is determined.

In other embodiments of the present application, the processor executes the step based on the first current limit threshold of at least one first data transmission interface and the corresponding preset step value of each first data transmission interface, using the target neural network model to perform CPU usage prediction processing, when determining the current limiting threshold to be adjusted for each corresponding first data transmission interface, can be achieved through the following steps:

Determining the sum of the first current current limiting threshold and the corresponding preset step value of each first data transmission interface to obtain at least one first reference current limiting threshold;

If the number of the first interface of the at least one first data transmission interface is the same as the number of the second interface of the at least one second data transmission interface, the target neural network model is used to predict the CPU usage of the at least one first reference current limiting threshold, and obtain a first predicted occupancy rate;

Obtain the current CPU usage at the current moment;

determining a first difference between a first predicted occupancy and a current occupancy;

If the first difference is greater than or equal to the target error, determine that the current-limiting threshold to be adjusted for each first data transmission interface is a corresponding first reference current-limiting threshold.

In other embodiments of the present application, the processor is further configured to perform the following steps:

If the first difference is smaller than the target error, determine the sum of each first reference current-limiting threshold and the corresponding preset step value to obtain at least one second reference current-limiting threshold;

Updating at least one first reference current limiting threshold to at least one second reference current limiting threshold;

Return to execute "predict the CPU occupancy rate of at least one first reference current limiting threshold through the target neural network model to obtain the first predicted occupancy rate" until the loop n times, when the first difference is greater than or equal to the target error , or when n is greater than or equal to the first preset number of times, determine that the current-limiting threshold to be adjusted for each first data transmission interface is the corresponding updated first reference current-limiting threshold; wherein, the updated first The reference current limiting threshold is the sum of n times the preset step value corresponding to the corresponding first data transmission interface and the corresponding first current limiting threshold, where n is a positive integer greater than or equal to 1.

If the number of second interfaces is greater than the number of first interfaces, determine the first current limit threshold of at least one third data transmission interface; wherein, at least one third data transmission interface is at least one second data transmission interface divided by at least one first A data transfer interface other than a data transfer interface;

Predicting the CPU occupancy rate of at least one first reference current limiting threshold and the first current current limiting threshold of at least one third data transmission interface through the target neural network model to obtain a second preset occupancy rate;

Obtain the current CPU usage at the current moment;

determining a second difference between a second preset occupancy rate and the current occupancy rate;

If the second difference is greater than or equal to the target error, determine that the current-limiting threshold to be adjusted for each first data transmission interface is the corresponding first reference current-limiting threshold.

If the second difference is smaller than the target error, determine the sum of each first reference current-limiting threshold and the corresponding preset step value to obtain at least one second reference current-limiting threshold;

Return to execute "predict the CPU occupancy of at least one first reference current limiting threshold and the first current current limiting threshold of at least one third data transmission interface through the target neural network model to obtain the second predicted occupancy" until loop m After the number of times, when the second difference is greater than or equal to the target error, or m is greater than or equal to the second preset number of times, it is determined that the current limiting threshold to be adjusted for each first data transmission interface is the corresponding updated The first reference current limiting threshold; wherein, the updated first reference current limiting threshold is the sum of m times the preset step value corresponding to the corresponding first data transmission interface and the corresponding first current limiting threshold, m is a positive integer greater than or equal to 1.

In other embodiments of the present application, after the processor executes the step of adjusting the value of the current limiting parameter of each first data transmission interface to the corresponding current limiting threshold to be adjusted, it is further used to perform the following steps:

If it is detected that there is an interface in the current-limiting mode in at least one second data transmission interface, return to the execution of "determining at least one first data transmission interface currently in the current-limiting mode" until at least one second data transmission interface is in the current-limiting mode The number of interfaces in the mode is zero, or the current limiting parameter corresponding to the updated at least one first data transmission interface included in the at least one second data transmission interface is adjusted to the corresponding first current limiting threshold to be adjusted, determined The first actual usage rate of the CPU is greater than or equal to the preset usage rate.

Obtaining the value of the current limiting parameter of each first data transmission interface is the first actual occupancy rate of the corresponding CPU when the current limiting threshold is to be adjusted;

When the value of the current limiting parameter of each first data transmission interface is determined to be the current limiting threshold to be adjusted, the corresponding target predicted occupancy rate obtained through the prediction of the target neural network model;

The target neural network model is updated based on the target predicted occupancy rate and the first actual occupancy rate.

In other embodiments of the present application, after the processor performs the step of determining the current request quantity value of each second data transmission interface, it is further used to perform the following steps:

If it is detected that in at least one second data transmission interface, the current request quantity value of each second data transmission interface is less than the corresponding first current limiting threshold, determine the product of each first current limiting threshold and the preset ratio, Obtaining a corresponding feedback current limiting threshold; wherein, the feedback current limiting threshold is smaller than the first current current limiting threshold;

If it is detected that in at least one second data transmission interface, the current request quantity value of each second data transmission interface is less than the corresponding feedback current limit threshold, adjust the value of the current limit parameter of each second data transmission interface to the initialization limit flow threshold.

It should be noted that one or more programs in the embodiments of the present application may be explained by the steps of one or more processors, and the implementation process may refer to the methods provided in the corresponding embodiments of 1 to 5, which will not be repeated here.

Based on the foregoing embodiments, the embodiments of the present application provide a computer-readable storage medium, referred to as a storage medium for short, where one or more programs are stored in the computer-readable storage medium, and the one or more programs can be used by one or more The processor executes to implement the implementation process of the information adjustment method provided in the embodiments corresponding to FIGS. 1 to 5 , which will not be repeated here.

The above are only examples of the present application, and are not intended to limit the scope of protection of the present application. Any modifications, equivalent replacements and improvements made within the spirit and scope of the present application are included in the protection scope of the present application.

Industrial Applicability

An embodiment of the present application provides an information adjustment method, device, and storage medium. The method includes: determining at least one first data transmission interface that is currently in the current limiting mode; determining the current limiting parameter corresponding to each of the first data transmission interfaces The first current limiting threshold value of the first current limiting threshold value, at least one first current limiting threshold value is obtained; CPU utilization rate analysis of the central processing unit is performed on at least one of the first current limiting threshold value, and each corresponding first data transmission interface is determined the current limiting threshold to be adjusted; adjust the value of the current limiting parameter of each of the first data transmission interfaces to the corresponding current limiting threshold to be adjusted, thus solving the problem of low flexibility in the current limiting configuration process Problem, a realization method of intelligent automatic adjustment of the current limit threshold has been implemented. Through the real-time transmission of all data transmission interfaces, the current limit parameter value of the data transmission interface is dynamically adjusted, which effectively improves the flexibility and flexibility of the current limit configuration process. Regulatory efficiency.

Claims

An information regulation method, the method comprising:

Determine at least one first data transmission interface that is currently in a current-limiting mode;

determining a first current current limiting threshold corresponding to the current limiting parameter of each of the first data transmission interfaces, to obtain at least one first current current limiting threshold;

Analyzing the CPU occupancy rate of the central processing unit for at least one of the first current limiting thresholds, and determining the corresponding current limiting thresholds to be adjusted for each of the first data transmission interfaces;

The value of the current limiting parameter of each of the first data transmission interfaces is adjusted to the corresponding value of the current limiting threshold to be adjusted.
The method according to claim 1, wherein said determining at least one first data transmission interface currently in a current limiting mode comprises:

Determine at least one second data transmission interface that is in data transmission mode at the current moment;

determining a first current current limiting threshold corresponding to a current limiting parameter of each second data transmission interface;

determining a current request quantity value for each of said second data transmission interfaces;

From the at least one second data transmission interface, determine the second data transmission interface whose current request quantity value is greater than the corresponding first current limit threshold, to obtain at least one first data transmission interface.
The method according to claim 2, wherein said at least one said first current limiting threshold is analyzed for the CPU usage of the central processing unit to determine the current limiting to be adjusted corresponding to each of said first data transmission interfaces Thresholds, including:

Obtain the trained target neural network model;

determining a preset step value for each of the first data transmission interfaces;

Based on the first current limiting threshold of at least one of the first data transmission interfaces and the corresponding preset step value of each of the first data transmission interfaces, the target neural network model is used to perform CPU occupation Rate prediction processing, determining the current limit threshold to be adjusted corresponding to each of the first data transmission interfaces.
The method according to claim 3, wherein said determining the preset step value corresponding to each said first data transmission interface comprises:

If at least one of the first data transmission interfaces includes one of the first data transmission interfaces, determine that the preset step value corresponding to the first data transmission interface is a unit step value;

If at least one of the first data transmission interfaces includes at least two of the first data transmission interfaces, determining a proportional relationship between the first current limiting thresholds of at least two of the first data transmission interfaces;

Based on the proportional relationship and the unit step value, the preset step value corresponding to each of the first data transmission interfaces is determined.
The method according to claim 3 or 4, wherein the preset threshold value of each of the corresponding first data transmission interfaces is based on the first current current limiting threshold of at least one of the first data transmission interfaces. Setting a step value, using the target neural network model to perform CPU occupancy rate prediction processing, and determining the current-limiting threshold to be adjusted corresponding to each of the first data transmission interfaces, including:

determining the sum of the first current current limiting threshold and the corresponding preset step value of each of the first data transmission interfaces to obtain at least one first reference current limiting threshold;

If the number of the first interface of at least one of the first data transmission interfaces is the same as the number of the second interface of at least one of the second data transmission interfaces, through the target neural network model, limit the current of at least one of the first reference The threshold is used to predict the CPU occupancy rate to obtain the first predicted occupancy rate;

Obtain the current occupancy rate of the CPU at the current moment;

determining a first difference between the first predicted occupancy and the current occupancy;

If the first difference is greater than or equal to a target error, determine that the current-limiting threshold to be adjusted for each of the first data transmission interfaces is the corresponding first reference current-limiting threshold.
The method according to claim 5, wherein the method further comprises:

If the first difference is smaller than the target error, determine the sum of each of the first reference current-limiting thresholds and the corresponding preset step value to obtain at least one second reference current-limiting threshold;

updating the at least one first reference current limiting threshold to the at least one second reference current limiting threshold;

Go back and execute the "predict the CPU occupancy rate of at least one of the first reference current-limiting thresholds through the target neural network model to obtain the first predicted occupancy rate" until after looping n times, after the first difference When the value is greater than or equal to the target error, or when n is greater than or equal to the first preset number of times, determine that the current limiting threshold to be adjusted for each of the first data transmission interfaces is the corresponding updated The first reference current limit threshold; wherein, the updated first reference current limit threshold is n times the preset step value corresponding to the corresponding first data transmission interface and the corresponding first current limit value The sum of thresholds, n is a positive integer greater than or equal to 1.
The method according to claim 5, wherein the method further comprises:

If the number of the second interfaces is greater than the number of the first interfaces, determine the first current limit threshold of at least one third data transmission interface; where at least one of the third data transmission interfaces is at least one of the second data transmission interfaces A data transmission interface other than at least one of the first data transmission interfaces among the transmission interfaces;

Using the target neural network model, performing CPU occupancy prediction on at least one of the first reference current limiting threshold and at least one first current limiting threshold of the third data transmission interface to obtain a second predicted occupancy;

Obtain the current occupancy rate of the CPU at the current moment;

determining a second difference between the second preset occupancy rate and the current occupancy rate;

If the second difference is greater than or equal to the target error, determine the to-be-adjusted current-limiting threshold of each of the first data transmission interfaces as the corresponding first reference current-limiting threshold.
The method according to claim 7, wherein the method further comprises:

If the second difference is smaller than the target error, determine the sum of each of the first reference current-limiting thresholds and the corresponding preset step value to obtain at least one second reference current-limiting threshold;

updating the at least one first reference current limiting threshold to the at least one second reference current limiting threshold;

Returning to the execution of the "using the target neural network model, perform CPU occupancy prediction on at least one of the first reference current limiting threshold and at least one first current limiting threshold of the third data transmission interface, and obtain the second Predicted occupancy rate", until after looping m times, if the second difference is greater than or equal to the target error, or m is greater than or equal to the second preset number of times, determine each of the first The current-limiting threshold to be adjusted of the data transmission interface is a corresponding updated first reference current-limiting threshold; wherein, the updated first reference current-limiting threshold is the corresponding preset value corresponding to the first data transmission interface. Assuming a sum of m times the step value and the corresponding first current limiting threshold, m is a positive integer greater than or equal to 1.
The method according to claim 3, wherein, after adjusting the value of the current limiting parameter of each of the first data transmission interfaces to the corresponding current limiting threshold to be adjusted, the method further comprises:

If it is detected that there is an interface in the current-limiting mode among at least one of the second data transmission interfaces, return to "determining at least one first data transmission interface currently in the current-limiting mode" until at least one of the second data transmission interfaces The number of interfaces in the current limiting mode is zero, or the current limiting parameter corresponding to the updated at least one first data transmission interface included in the at least one second data transmission interface is adjusted to the corresponding limit to be adjusted After the flow threshold, the determined first actual CPU usage rate is greater than or equal to the preset usage rate.
The method according to claim 3, wherein, after adjusting the value of the current limiting parameter of each of the first data transmission interfaces to the corresponding current limiting threshold to be adjusted, the method further comprises:

Obtaining the first actual occupancy rate of the corresponding CPU when the value of the current limiting parameter of each of the first data transmission interfaces is the current limiting threshold to be adjusted;

When determining that the value of the current limiting parameter of each of the first data transmission interfaces is the current limiting threshold to be adjusted, the corresponding target predicted occupancy rate obtained through the prediction of the target neural network model;

The target neural network model is updated based on the target predicted occupancy rate and the first actual occupancy rate.
The method according to claim 2, wherein, after the determination of the current request quantity value of each of the second data transmission interfaces, the method further comprises:

If it is detected that in at least one of the second data transmission interfaces, the current request quantity value of each of the second data transmission interfaces is less than the corresponding first current current limit threshold, determine each of the first current current limit The product of the threshold and the preset ratio to obtain a corresponding feedback current limiting threshold; wherein, the feedback current limiting threshold is smaller than the first current current limiting threshold;

If it is detected that among at least one of the second data transmission interfaces, the current request quantity value of each of the second data transmission interfaces is less than the corresponding feedback current limiting threshold, adjust the current request quantity value of each of the second data transmission interfaces. The value of the current limiting parameter is an initial current limiting threshold.
An information conditioning device, the device comprising: a memory, a processor, and a communication bus; wherein:

The memory is used to store executable instructions;

The communication bus is used to realize the communication connection between the processor and the memory;

The processor is configured to execute the information adjustment program stored in the memory to realize the steps of the information adjustment method according to any one of claims 1 to 11.
A storage medium, on which an information adjustment program is stored, and when the information adjustment program is executed by a processor, the steps of the information adjustment method according to any one of claims 1 to 11 are realized.