CN114579442A - Capacity estimation parameter control method and system - Google Patents

Abstract

The application provides a method and a system for controlling capacity evaluation parameters. The method comprises the following steps: the capacity evaluation parameter control device may acquire at least one system parameter of each device under test and a parameter value of each system parameter by interacting with the device under test. The capacity estimation parameter control device may input a parameter value of at least one system parameter of one device under test into a preset tuning algorithm. The capacity evaluation parameter control device can obtain a parameter value of at least one evaluation parameter of the tested device through the preset tuning algorithm. The capacity evaluation parameter control equipment can generate a capacity evaluation case of the tested equipment according to a parameter value combination predicted by a preset tuning algorithm. The method improves the generation efficiency of the evaluation parameter and improves the evaluation accuracy and the evaluation efficiency of the tested equipment.

Description

Capacity evaluation parameter control method and system

technical field

The present application relates to the field of computers, and in particular, to a method and system for controlling capacity evaluation parameters.

Background technique

Capacity evaluation is a branch of performance testing. Capacity evaluation usually evaluates the highest load capacity of the software and hardware systems under test through Benchmark. The parameter combination of Benchmark will determine the evaluation effect of this capacity evaluation. Inappropriate parameter combinations may cause Benchmark to fail to generate enough pressure data to evaluate the true capacity capability of the hardware and software systems.

In order to improve the efficiency of capacity evaluation, in the prior art, technicians are usually required to determine the parameter combination of the benchmark according to manual experience, so as to realize the capacity evaluation of the software and hardware systems under test. Moreover, for different models of tested software and hardware systems, the parameters of its CPU, memory, IO, network, etc. are usually different. Technicians need to determine different parameter combinations according to the tested software and hardware systems of different models to achieve the optimal capacity evaluation effect.

However, using the parameter combination for capacity evaluation formulated by human experience, there is a problem of low parameter formulation efficiency.

SUMMARY OF THE INVENTION

The present application provides a capacity evaluation parameter control method and system to solve the problem of low parameter formulation efficiency existing in the prior art.

In a first aspect, the present application provides a capacity evaluation parameter control method, including:

Obtain the parameter value of at least one system parameter of the device under test;

determining a parameter value of at least one evaluation parameter of the device under test according to the parameter value of the at least one system parameter of the device under test and a preset tuning algorithm;

According to the parameter value of the at least one evaluation parameter, a capacity evaluation case of the device under test is generated, and the capacity evaluation case is used to evaluate the capacity of the device under test.

Optionally, determining the parameter value of at least one evaluation parameter of the device under test according to the parameter value of at least one system parameter of the device under test and a preset tuning algorithm, specifically including:

Determine the parameter adjustment range of each evaluation parameter of the device under test according to the parameter value of at least one system parameter of the device under test;

A parameter value of each evaluation parameter of the device under test is determined according to the parameter adjustment range of each evaluation parameter and a preset optimization algorithm.

Optionally, according to the parameter value of at least one system parameter of the device under test, the parameter adjustment range of each evaluation parameter of the device under test is determined, specifically including:

For each evaluation parameter, a calculation model corresponding to the evaluation parameter is obtained, the parameter value of the system parameter is input into the calculation model corresponding to the evaluation parameter, and the parameter adjustment range of the evaluation parameter is obtained by calculation.

Optionally, according to the parameter adjustment range of each evaluation parameter and a preset optimization algorithm, determine the parameter value of each evaluation parameter of the device under test, specifically including:

Generate a parameter matrix according to the parameter adjustment range of each of the evaluation parameters;

The parameter matrix is input into the preset tuning algorithm to obtain a parameter value of each of the evaluation parameters.

Optionally, the method further includes:

Evaluate the device under test using the capacity evaluation use case corresponding to the device under test to obtain an evaluation result;

According to the evaluation result, an evaluation index of the device under test is determined, and the evaluation index is used to indicate the real capacity of the device under test.

Optionally, the at least one system parameter includes at least one of a CPU parameter, a memory parameter, an IO parameter, and a network parameter.

In a second aspect, the present application provides a capacity evaluation parameter control system, including:

an acquisition module for acquiring the parameter value of at least one system parameter of the device under test;

a control module, configured to determine a parameter value of at least one evaluation parameter of the device under test according to a parameter value of at least one system parameter of the device under test and a preset tuning algorithm; according to the parameter value of the at least one evaluation parameter value to generate a capacity evaluation use case of the device under test, where the capacity evaluation use case is used to evaluate the capacity of the device under test.

Optionally, the control module is specifically used for:

Determine the parameter adjustment range of each evaluation parameter of the device under test according to the parameter value of at least one system parameter of the device under test;

A parameter value of each evaluation parameter of the device under test is determined according to the parameter adjustment range of each evaluation parameter and a preset optimization algorithm.

Optionally, the control module is specifically used for:

For each evaluation parameter, a calculation model corresponding to the evaluation parameter is obtained, the parameter value of the system parameter is input into the calculation model corresponding to the evaluation parameter, and the parameter adjustment range of the evaluation parameter is obtained by calculation.

Optionally, the control module is specifically used for:

Generate a parameter matrix according to the parameter adjustment range of each of the evaluation parameters;

The parameter matrix is input into the preset tuning algorithm to obtain a parameter value of each of the evaluation parameters.

Optionally, the system further includes:

an evaluation module, configured to evaluate the device under test by using the capacity evaluation case corresponding to the device under test to obtain an evaluation result; according to the evaluation result, determine the evaluation index of the device under test, the evaluation Metrics are used to indicate the true capacity of the device under test.

Optionally, the at least one system parameter includes at least one of a CPU parameter, a memory parameter, an IO parameter, and a network parameter.

In a third aspect, the present application provides a capacity evaluation parameter control device, including: a memory, a processor, and the like;

The memory is used for storing a computer program; the processor is used for executing the first aspect and the capacity evaluation parameter control method in any possible design of the first aspect according to the computer program stored in the memory.

In a fourth aspect, the present application provides a readable storage medium in which a computer program is stored, and when at least one processor of the capacity evaluation parameter control device executes the computer program, the capacity evaluation parameter control device executes the first aspect and a capacity evaluation parameter control method in any possible design of the first aspect.

In a fifth aspect, the present application provides a computer program product, the computer program product comprising a computer program, when at least one processor of the capacity evaluation parameter control device executes the computer program, the capacity evaluation parameter control device executes the first aspect and the first aspect. On the one hand the capacity evaluation parameter control method in any possible design.

In the capacity evaluation parameter control method provided by the present application, at least one system parameter of each device under test and the parameter value of each system parameter are obtained by interacting with the device under test; the parameter value of at least one system parameter of one device under test is Input a preset tuning algorithm; obtain a parameter value of at least one evaluation parameter of the device under test through the preset tuning algorithm; generate a capacity evaluation case for the device under test according to the combination of parameter values predicted by the preset tuning algorithm It realizes the generation of personalized evaluation parameters of the device under test, improves the generation efficiency of the evaluation parameters, avoids the redundancy of capacity evaluation use cases caused by multiple sets of evaluation parameters, and improves the evaluation accuracy of the device under test. Evaluate the effect of efficiency.

Description of drawings

In order to illustrate the technical solutions in the present application or the prior art more clearly, the following briefly introduces the accompanying drawings required in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are the For some embodiments of the application, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without any creative effort.

FIG. 1 is a schematic diagram of a scenario of manually formulating a capacity evaluation use case provided by the prior art;

FIG. 2 is a schematic diagram of a scenario of capacity evaluation parameter control provided by an embodiment of the present application;

3 is a flowchart of a method for controlling a capacity evaluation parameter provided by an embodiment of the present application;

4 is a flowchart of a method for controlling a capacity evaluation parameter provided by an embodiment of the present application;

FIG. 5 is a schematic structural diagram of a capacity evaluation parameter control system provided by an embodiment of the present application;

FIG. 6 is a schematic diagram of a hardware structure of a capacity evaluation parameter control device according to an embodiment of the present application.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below with reference to the accompanying drawings in the present application. Obviously, the described embodiments are part of the embodiments of the present application. , not all examples. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

The terms "first", "second", "third", "fourth", etc. in the description and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that data so used may be interchanged under appropriate circumstances. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of this document.

Depending on the context, the word "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determining."

Also, as used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context dictates otherwise.

It should be further understood that the terms "comprising" and "comprising" indicate the presence of features, steps, operations, elements, components, items, kinds, and/or groups, but do not exclude one or more other features, steps, operations, elements, The existence, appearance or addition of components, items, categories, and/or groups.

The terms "or" and "and/or" as used herein are to be construed to be inclusive or to mean any one or any combination. Thus, "A, B or C" or "A, B and/or C" means "any of the following: A; B; C; A and B; A and C; B and C; A, B and C" . Exceptions to this definition arise only when combinations of elements, functions, steps, or operations are inherently mutually exclusive in some way.

Capacity evaluation is a branch of performance testing. Capacity evaluation usually evaluates the highest load capacity of the software and hardware systems under test through Benchmark. Specifically, capacity evaluation is a method of testing and evaluating the maximum processing capacity of requests when the system is in a maximum load state or when a certain indicator reaches an acceptable maximum threshold through Benchmark. Among them, Benchmark is the benchmark program. The benchmark is an evaluation program used to estimate the performance of a tuned application and give a performance score. After completing the evaluation, users can use the evaluation results obtained from the evaluation to assist in completing the verification and comparison of new models, machine procurement, and solutions. For example, the evaluation result can be used to determine whether the service carrying capacity of the current cluster/data center meets the requirements. For another example, information such as the type and quantity of purchased machines may be determined according to the evaluation result.

In the prior art, different devices under test usually have different system parameters. The system parameter may be a configuration item that can be dynamically set in the operating system and affects application performance, such as kernel configuration parameters and application configuration parameters. When the user sets different system parameters in the device under test, the score of the device under test on a certain benchmark program will change. For example, the system parameters may include CPU, memory, IO, network, and the like. Technicians can specify several sets of Benchmark parameter combinations based on the system parameters of the device under test and human experience. The capacity evaluation parameter control device can realize the capacity evaluation of the tested software and hardware system according to the parameter combination of these benchmarks. In the process of capacity evaluation, the parameter combination of Benchmark will determine the evaluation effect of this capacity evaluation. Inappropriate parameter combinations may cause Benchmark to fail to generate enough pressure data to evaluate the true capacity capability of the hardware and software systems. For example, on different models, a fixed parameter combination may not allow Benchmark to generate enough pressure data, which will make it impossible to evaluate the real capacity capability of software and hardware. Therefore, technicians need to determine different parameter combinations according to the tested software and hardware systems of different models to achieve the optimal capacity evaluation effect.

However, when technicians formulate the parameter combinations for capacity evaluation based on experience, as shown in Figure 1, in order to evaluate the capacity of different environments as accurately as possible, multiple sets of parameter combinations are often set. However, the setting of the multiple sets of parameter combinations may easily lead to redundancy of test cases and increase the time-consuming of tests, resulting in the problem of low evaluation efficiency. Moreover, the multiple sets of parameter combinations still cannot adapt to the problems of all devices. For example, when used on a device under test with a small size, the combination of multiple sets of parameters is likely to have too much pressure, causing the machine to hang up. Moreover, when used on a large-scale device under test, the multiple sets of parameter combinations are prone to insufficient pressure, resulting in an inability to effectively evaluate the true capacity of the device under test. In addition, once a new model or new software becomes the device under test, technicians are often required to manually adapt the use case or write a new use case, which has the problem of high maintenance costs.

In view of the above problems, the present application proposes a capacity evaluation parameter control method. This application proposes a benchmark evaluation parameter control method based on a hyperparameter tuning algorithm. The parameter tuning algorithm based on hyperparameter tuning can continuously provide a better combination of evaluation parameters through a certain algorithm strategy, so as to find a parameter configuration with better evaluation effect. In addition, the present application also realizes an intelligent control method of evaluation parameters for different devices under test by detecting the system parameters of the device under test. The present application can obtain system parameters of hardware resources such as CPU parameters, memory parameters, IO parameters, and network parameters by detecting the device under test. These system parameters can provide parameter adjustment ranges for Benchmark's evaluation parameters. In the present application, different evaluation parameter combinations can be formed by selecting appropriate parameter values from the parameter adjustment range of the evaluation parameters of Benchmark through the hyperparameter tuning algorithm. The application can generate a capacity evaluation case of the device under test according to the combination of evaluation parameters. The capacity evaluation case is a customized test case generated by the capacity evaluation parameter control device for different software and hardware environments, which can effectively detect the real capacity of different devices under test.

The present application realizes the generation of customized parameter combinations in different software and hardware environments and the generation of customized capacity evaluation use cases through the above solutions. The capacity evaluation use case can generate enough pressure to evaluate the real capacity of the environment, which greatly improves the efficiency of parameter formulation. In addition, the present application generates capacity evaluation use cases through customization, which reduces the redundancy problem caused by using the same set of evaluation use cases in different environments, effectively reduces the cost of manual maintenance, and greatly improves the evaluation efficiency.

The technical solutions of the present application will be described in detail below with specific examples. The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

FIG. 2 shows a schematic diagram of a scenario of capacity evaluation parameter control provided by an embodiment of the present application. As shown in Fig. 2, one capacity evaluation parameter control device may correspond to a plurality of devices under test. The capacity evaluation parameter control device can acquire the software and hardware system parameters of the device under test from each device under test. The capacity evaluation parameter control device may be preset with calculation models for multiple evaluation parameters. The capacity evaluation parameter control device may determine the parameter adjustment range of the evaluation parameters of each device under test according to the system parameters of each device under test. The capacity evaluation parameter control device may also input the system parameters of each device under test and a plurality of evaluation parameters preset in the capacity evaluation parameter control device into the preset tuning algorithm. The capacity evaluation parameter control device may determine the parameter value of at least one evaluation parameter of each device under test through the preset tuning algorithm. The capacity evaluation parameter control device may generate a capacity evaluation case for the device under test according to the parameter value of at least one evaluation parameter of each device under test. The capacity assessment parameter control device can use the capacity assessment use case to assess the capacity of the device under test. For example, as shown in FIG. 2 , after the capacity evaluation parameter control device acquires the system parameters of the device under test 1 , the corresponding generated capacity evaluation case can be used to evaluate the capacity of the device under test 1 .

In the present application, the capacity assessment parameter control device is used as the execution body to execute the capacity assessment parameter control method of the following embodiments. Specifically, the executive body may be a hardware device of a capacity evaluation parameter control device, or a software application implementing the following embodiments in the capacity evaluation parameter control device, or a computer-readable computer readable with a software application implementing the following embodiments installed. A storage medium, or a code for implementing the software application of the following embodiments.

Fig. 3 shows a flow chart of a capacity evaluation parameter control method provided by an embodiment of the present application. On the basis of the embodiment shown in Fig. 2, as shown in Fig. 3, a capacity evaluation parameter control device is used as the execution subject, The method of this embodiment may include the following steps:

S101. Acquire a parameter value of at least one system parameter of the device under test.

In this embodiment, one capacity evaluation parameter control device may communicate with multiple devices under test. The capacity evaluation parameter control device can acquire at least one system parameter of each device under test and a parameter value of each system parameter by interacting with the device under test. The system parameters may be CPU parameters, memory parameters, IO parameters, network parameters, and the like.

S102: Determine a parameter value of at least one evaluation parameter of the device under test according to a parameter value of at least one system parameter of the device under test and a preset tuning algorithm.

In this embodiment, the capacity evaluation parameter control device may input a parameter value of at least one system parameter of a device under test into a preset tuning algorithm. The capacity evaluation parameter control device may obtain a parameter value of at least one evaluation parameter of the device under test through the preset tuning algorithm. When the capacity evaluation parameter control device corresponds to a plurality of devices under test, the capacity evaluation parameter control device may input the parameter value of at least one system parameter of each device under test into the preset tuning algorithm one by one, so as to calculate each device under test. A parameter value of at least one evaluation parameter of a device under test. The preset tuning algorithm may be a hyperparameter tuning algorithm.

In an example, the specific process of calculating the parameter value of at least one evaluation parameter by the capacity evaluation parameter control device may include the following steps:

Step 1. Determine the parameter adjustment range of each evaluation parameter of the device under test according to the parameter value of at least one system parameter of the device under test.

In this step, the capacity evaluation parameter control device may store an evaluation parameter set. The evaluation parameter set may include at least one evaluation parameter and a calculation model for each evaluation. The capacity evaluation parameter control device may, after acquiring the parameter value of at least one system parameter of a device under test, calculate the value of the device under test according to the parameter value of at least one system parameter of the device under test and a preset calculation model of evaluation parameters. The parameter adjustment range of the evaluation parameters of the device. For example, the system parameter is a CPU parameter, and the parameter value of the CPU parameter is used to indicate the number of CPUs/processors in the device under test. The process parameter in the evaluation parameter can be calculated according to the CPU parameter. The capacity evaluation parameter control device can determine, according to a preset calculation model, that the lower limit of the process parameter is 0.5*the number of cpus, and the upper limit is 10*the number of cpus. For example, when there are 4 CPU parameters in the device under test, the lower limit of the process parameter is 2, and the upper limit is 40. That is, the parameter adjustment range of the process parameter of the device under test is [2, 40].

Step 2: Determine the parameter value of each evaluation parameter of the device under test according to the parameter adjustment range of each evaluation parameter and the preset optimization algorithm.

In this step, after determining the parameter adjustment range of at least one evaluation parameter, the capacity evaluation parameter control device may input the parameter adjustment range of these evaluation parameters into the preset tuning algorithm. The capacity evaluation parameter control device may determine the optimal parameter value combination of the evaluation parameter through the preset tuning algorithm. The test efficiency will be optimal when the capacity assessment parameter control device uses the combination of these parameter values to generate capacity assessment cases.

In an implementation manner, the capacity evaluation parameter control device may generate a parameter matrix according to the parameter adjustment range of these evaluation parameters. where each evaluation parameter can be represented by a row in the parameter matrix. For example, the vector at the row corresponding to the process parameter can be represented as [2, 40]. The capacity evaluation parameter control device may input the parameter matrix into a preset tuning algorithm, and obtain a parameter value of each evaluation parameter in the evaluation parameters by default. A combination of parameter values consisting of the parameter values of these evaluation parameters.

S103. Generate a capacity evaluation case of the device under test according to the parameter value of at least one evaluation parameter, where the capacity evaluation case is used to evaluate the capacity of the device under test.

In this embodiment, the capacity evaluation parameter control device may generate a capacity evaluation use case of the device under test according to a combination of parameter values predicted by a preset tuning algorithm. For example, when the parameter value of the process parameter is 10, the number of concurrent processes corresponding to the generated capacity evaluation test case may be 10. The capacity evaluation parameter control device can use the capacity evaluation use case to evaluate the capacity of the device under test, thereby determining the real capacity of the device under test.

In the capacity evaluation parameter control method provided by the present application, the capacity evaluation parameter control device can acquire at least one system parameter of each device under test and the parameter value of each system parameter by interacting with the device under test. The capacity evaluation parameter control device may input the parameter value of at least one system parameter of a device under test into a preset tuning algorithm. The capacity evaluation parameter control device may obtain a parameter value of at least one evaluation parameter of the device under test through the preset tuning algorithm. The capacity evaluation parameter control device can generate the capacity evaluation use case of the device under test according to the combination of parameter values predicted by the preset tuning algorithm. In the present application, by obtaining the system parameters of the device under test, the generation of the personalized evaluation parameters of the device under test is realized, the generation efficiency of the evaluation parameters is improved, and the redundancy of the capacity evaluation case caused by multiple sets of evaluation parameters is avoided, The evaluation accuracy and evaluation efficiency of the device under test are improved.

FIG. 4 shows a flowchart of a method for controlling a capacity evaluation parameter provided by an embodiment of the present application. On the basis of the embodiments shown in FIG. 2 and FIG. 3 , as shown in FIG. 4 , with the capacity evaluation parameter control device as the execution subject, the method of this embodiment may include the following steps:

S201. Obtain a parameter value of at least one system parameter of the device under test.

S202. Determine a parameter value of at least one evaluation parameter of the device under test according to a parameter value of at least one system parameter of the device under test and a preset tuning algorithm.

S203. Generate a capacity evaluation case of the device under test according to the parameter value of at least one evaluation parameter, where the capacity evaluation case is used to evaluate the capacity of the device under test.

The implementation manner of steps S201 to S203 is similar to that of steps S101 to S103 in the embodiment of FIG. 2 , and details are not described herein again in this embodiment.

S204 , evaluating the device under test by using a capacity evaluation case corresponding to the device under test to obtain an evaluation result.

In this embodiment, the capacity evaluation parameter control device may generate a test request according to the capacity evaluation case after completing the generation of the capacity evaluation case. The capacity evaluation parameter control device can send these test requests to the device under test, so as to realize the processing capability of the device under test when it is in a state of maximum load or when a certain indicator reaches an acceptable maximum threshold. The capacity evaluation parameter control device can obtain the processing result of the measured feedback. The capacity evaluation parameter control device can obtain the evaluation result by statistics according to the processing result. For example, the evaluation result may include information such as the number of completed requests, the average waiting time, and the like.

S205. Determine an evaluation index of the device under test according to the evaluation result, where the evaluation index is used to indicate the real capacity of the device under test.

In this embodiment, the capacity evaluation parameter control device may calculate and obtain the real capacity of the device under test according to the evaluation result obtained by statistics. The real capacity is the estimated number of requests that the device under test can handle when the maximum load state or a certain indicator reaches the acceptable maximum threshold. The capacity evaluation parameter control device can generate an evaluation index for the real capacity of the device under test. The capacity evaluation parameter control device can also display the evaluation index, so that the technician can make subsequent judgments based on the evaluation index.

In the capacity evaluation parameter control method provided by the present application, the capacity evaluation parameter control device can acquire the parameter value of at least one system parameter of the device under test. The capacity evaluation parameter control device may determine the parameter value of the at least one evaluation parameter of the device under test according to the parameter value of the at least one system parameter of the device under test and the preset tuning algorithm. The capacity evaluation parameter control device may generate a capacity evaluation case of the device under test according to the parameter value of at least one evaluation parameter, and the capacity evaluation case is used to evaluate the capacity of the device under test. The capacity evaluation parameter control device can generate a test request according to the capacity evaluation case. The capacity evaluation parameter control device can send these test requests to the device under test to obtain evaluation results. The capacity evaluation parameter control device can calculate the real capacity of the device under test according to the evaluation result obtained by statistics. In the present application, by acquiring the system parameters of the device under test, the generation of the personalized evaluation parameters of the device under test is realized, and the generation efficiency of the evaluation parameters is improved. In addition, the present application can also generate capacity evaluation use cases according to the evaluation parameters, which avoids redundancy of capacity evaluation use cases caused by multiple sets of evaluation parameters, and improves the evaluation accuracy and evaluation efficiency of the device under test.

FIG. 5 shows a schematic structural diagram of a capacity evaluation parameter control system provided by an embodiment of the present application. As shown in FIG. 5 , the capacity evaluation parameter control system 10 of this embodiment is used to implement the corresponding method in any of the above method embodiments. For the operation of the capacity evaluation parameter control device, the capacity evaluation parameter control system 10 of this embodiment includes:

The obtaining module 11 is configured to obtain a parameter value of at least one system parameter of the device under test.

The control module 12 is configured to determine a parameter value of at least one evaluation parameter of the device under test according to a parameter value of at least one system parameter of the device under test and a preset tuning algorithm. According to the parameter value of at least one evaluation parameter, a capacity evaluation case of the device under test is generated, and the capacity evaluation case is used to evaluate the capacity of the device under test.

In an example, the control module 12 is specifically used for:

The parameter adjustment range of each evaluation parameter of the device under test is determined according to the parameter value of at least one system parameter of the device under test.

According to the parameter adjustment range of each evaluation parameter and the preset optimization algorithm, the parameter value of each evaluation parameter of the device under test is determined.

In an example, the control module 12 is specifically used for:

For each evaluation parameter, a calculation model corresponding to the evaluation parameter is obtained, and the parameter value of the system parameter is input into the calculation model corresponding to the evaluation parameter, and the parameter adjustment range of the evaluation parameter is obtained by calculation.

In an example, the control module 12 is specifically used for:

According to the parameter adjustment range of each evaluation parameter, a parameter matrix is generated.

The parameter matrix is input into the preset tuning algorithm, and the parameter value of each evaluation parameter in the evaluation parameters is obtained.

In one example, the capacity evaluation parameter control system 10 further includes:

The evaluation module 13 is used for evaluating the device under test by using a capacity evaluation case corresponding to the device under test to obtain an evaluation result. According to the evaluation result, the evaluation index of the device under test is determined, and the evaluation index is used to indicate the real capacity of the device under test.

In an example, the at least one system parameter includes at least one of a CPU parameter, a memory parameter, an IO parameter, and a network parameter.

The capacity evaluation parameter control system 10 provided in this embodiment of the present application can execute the foregoing method embodiments, and the specific implementation principles and technical effects thereof may refer to the foregoing method embodiments, which will not be repeated here.

FIG. 6 shows a schematic diagram of the hardware structure of a capacity evaluation parameter control device provided by an embodiment of the present application. As shown in FIG. 6 , the capacity evaluation parameter control device 20 is used to implement operations corresponding to the capacity evaluation parameter control device in any of the above method embodiments. The capacity evaluation parameter control device 20 in this embodiment may include: a memory 21, Processor 22 and communication interface 24 .

The memory 21 is used to store computer programs. The memory 21 may include a high-speed random access memory (Random Access Memory, RAM), and may also include a non-volatile memory (Non-Volatile Memory, NVM), such as at least one disk memory, and may also be a U disk, a removable hard disk , read-only memory, magnetic disk or optical disk, etc.

The processor 22 is configured to execute the computer program stored in the memory, so as to realize the capacity evaluation parameter control method in the above embodiment. For details, refer to the relevant descriptions in the foregoing method embodiments. The processor 22 may be a central processing unit (Central Processing Unit, CPU), or other general-purpose processors, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in conjunction with the invention can be directly embodied as executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

Optionally, the memory 21 may be independent or integrated with the processor 22 .

When the memory 21 is a separate device from the processor 22 , the capacity evaluation parameter control device 20 may also include a bus 23 . The bus 23 is used to connect the memory 21 and the processor 22 . The bus 23 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus can be divided into address bus, data bus, control bus and so on. For convenience of representation, the buses in the drawings of the present application are not limited to only one bus or one type of bus.

The communication interface 24 can be connected to the processor 21 through the bus 23 . The communication interface 24 can communicate with the device under test, and obtain a parameter value of at least one system parameter of the device under test from the device under test. The communication interface can also send an evaluation signal to the device under test according to the capacity evaluation use case, so as to realize the evaluation of the device under test.

The capacity evaluation parameter control device provided in this embodiment can be used to execute the above-mentioned capacity evaluation parameter control method, and its implementation manner and technical effects are similar, and details are not described herein again in this embodiment.

The present application further provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, is used to implement the methods provided by the above-mentioned various embodiments.

The computer-readable storage medium may be a computer storage medium or a communication medium. Communication media includes any medium that facilitates transfer of a computer program from one place to another. Computer storage media can be any available media that can be accessed by a general purpose or special purpose computer. For example, a computer-readable storage medium is coupled to the processor such that the processor can read information from, and write information to, the computer-readable storage medium. Of course, the computer-readable storage medium can also be an integral part of the processor. The processor and the computer-readable storage medium may reside in Application Specific Integrated Circuits (ASIC). Alternatively, the ASIC may be located in the user equipment. Of course, the processor and computer-readable storage medium may also exist in the communication device as discrete components.

Specifically, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random-Access Memory (SRAM), electrically erasable Except Programmable Read-Only Memory (Electrically-Erasable Programmable Read-Only Memory, EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM) ), read-only memory (Read-Only Memory, ROM), magnetic memory, flash memory, magnetic disk or optical disk. A storage medium can be any available medium that can be accessed by a general purpose or special purpose computer.

The present application also provides a computer program product comprising a computer program stored in a computer-readable storage medium. At least one processor of the device can read the computer program from a computer-readable storage medium, and the at least one processor executes the computer program to cause the device to implement the methods provided by the various embodiments described above.

An embodiment of the present application further provides a chip, the chip includes a memory and a processor, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the device installed with the chip can perform various possible implementations as above method in method.

In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are only illustrative. For example, the division of modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another A system, or some feature, can be ignored, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or modules, and may be in electrical, mechanical or other forms.

Wherein, each module may be physically separated, for example, installed in different positions of one device, or installed on different devices, or distributed to multiple network units, or distributed to multiple processors. The individual modules can also be integrated, eg, installed in the same device, or integrated in a set of codes. Each module can exist in the form of hardware, or can also exist in the form of software, or can also be implemented in the form of software plus hardware. The present application may select some or all of the modules according to actual needs to achieve the purpose of the solution of this embodiment.

When each module is implemented as an integrated module in the form of a software function module, it can be stored in a computer-readable storage medium. The above-mentioned software function modules are stored in a storage medium, and include several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor to execute some steps of the methods of various embodiments of the present application.

It should be understood that, although the steps in the flow charts in the above embodiments are sequentially displayed according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, the execution of these steps is not strictly limited to the order and may be performed in other orders. Moreover, at least a part of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but may be executed at different times, and the execution order is not necessarily sequential. Instead, it may be performed in turn or alternately with other steps or at least a portion of sub-steps or stages of other steps.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that the technical solutions described in the foregoing embodiments can still be modified, or some or all of the technical features thereof can be equivalently replaced. . However, these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims (11)

1. A capacity estimation parameter control method, characterized in that the method comprises:

acquiring a parameter value of at least one system parameter of the tested equipment;

determining a parameter value of at least one evaluation parameter of the tested equipment according to the parameter value of at least one system parameter of the tested equipment and a preset tuning algorithm;

and generating a capacity evaluation use case of the tested device according to the parameter value of the at least one evaluation parameter, wherein the capacity evaluation use case is used for evaluating the capacity of the tested device.

2. The method according to claim 1, wherein the determining a parameter value of at least one evaluation parameter of the device under test according to the parameter value of the at least one system parameter of the device under test and a preset tuning algorithm specifically comprises:

determining a parameter adjustment range of each evaluation parameter of the tested device according to a parameter value of at least one system parameter of the tested device;

and determining the parameter value of each evaluation parameter of the tested equipment according to the parameter adjustment range of each evaluation parameter and a preset tuning algorithm.

3. The method according to claim 2, wherein the determining a parameter adjustment range for each evaluation parameter of the device under test according to the parameter value of the at least one system parameter of the device under test specifically comprises:

and aiming at each evaluation parameter, obtaining a calculation model corresponding to the evaluation parameter, inputting the parameter value of the system parameter into the calculation model corresponding to the evaluation parameter, and calculating to obtain the parameter adjustment range of the evaluation parameter.

4. The method according to claim 2, wherein the determining the parameter value of each evaluation parameter of the device under test according to the parameter adjustment range of each evaluation parameter and a preset tuning algorithm specifically comprises:

generating a parameter matrix according to the parameter adjustment range of each evaluation parameter;

and inputting the parameter matrix into the preset tuning algorithm to obtain the parameter value of each evaluation parameter in the evaluation parameters.

5. The method according to any one of claims 1-4, further comprising:

evaluating the tested equipment by using the capacity evaluation use case corresponding to the tested equipment to obtain an evaluation result;

and determining an evaluation index of the tested device according to the evaluation result, wherein the evaluation index is used for indicating the real capacity of the tested device.

6. The method according to any of claims 1-4, wherein the at least one system parameter comprises at least one of a CPU parameter, a memory parameter, an IO parameter, and a network parameter.

7. A capacity estimation parameter control system, the system comprising:

the acquisition module is used for acquiring a parameter value of at least one system parameter of the tested equipment;

the control module is used for determining the parameter value of at least one evaluation parameter of the tested equipment according to the parameter value of at least one system parameter of the tested equipment and a preset tuning algorithm; and generating a capacity evaluation use case of the tested device according to the parameter value of the at least one evaluation parameter, wherein the capacity evaluation use case is used for evaluating the capacity of the tested device.

8. The system of claim 7, further comprising:

the evaluation module is used for evaluating the tested equipment by using the capacity evaluation use case corresponding to the tested equipment to obtain an evaluation result; and determining an evaluation index of the tested device according to the evaluation result, wherein the evaluation index is used for indicating the real capacity of the tested device.

9. A capacity estimation parameter control apparatus, characterized in that the apparatus comprises: a memory, a processor;

the memory is used for storing a computer program; the processor is configured to implement the capacity estimation parameter control method according to the computer program stored in the memory, according to any one of claims 1 to 6.

10. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, is configured to implement the capacity estimation parameter control method according to any one of claims 1 to 6.

11. A computer program product, characterized in that the computer program product comprises a computer program which, when being executed by a processor, implements the capacity estimation parameter control method of any one of claims 1 to 6.

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