WO2024032100A1 - Micro service-based test system and method for industrial wireless network device accessing ipv6 - Google Patents

Abstract

The present invention belongs to the field of network device testing, and relates to a micro service-based test system and method for an industrial wireless network device accessing IPv6. The method comprises: a user logging in to a test management system, creating a test item, filling in a PICS form, and providing a device under test to a tester; the tester making the device under test access a network environment under test; the test management system generating a set of test cases, and performing priority ranking on the test cases in the set of test cases; the test management system executing the test cases one by one, and sending a test instruction to a test agent; the test agent sending, according to an operation instruction, a test flow to an environment for testing an industrial wireless network device accessing IPv6; a network device in the environment for testing the industrial wireless network device accessing IPv6 forwarding the test flow, and responding to the test agent; the test agent uploading a result to the test management system based on a micro-service architecture; and after all test cases are executed, the test management system analyzing the test result to generate a test report.

Description

Microservice-based industrial wireless network equipment access IPv6 test system and method Technical field

The invention belongs to the field of network equipment testing, and relates to a microservice-based industrial wireless network equipment access IPv6 testing system and method.

Background technique

In the field of industrial data collection, there are many types of industrial wireless network protocols. Currently, there are various industrial wireless protocol standards such as WIA-PA, WirelessHART, and 6LoWPAN. Each automation equipment manufacturer and integrator will also develop various private industrial protocols. The various protocol standards are not unified and incompatible with each other.

The emergence of IPv6 provides solutions to the above problems. As the next generation IP protocol, IPv6 provides necessary technical support and broad address resources for the seamless connection of IP networks and industrial networks. Applying IPv6 technology innovation to the field of industrial wireless networks can effectively solve the problem of massive terminal access, provide huge network space and data transmission channels for networked intelligent transformation and upgrading, and promote interconnection between heterogeneous networks.

Before industrial wireless network equipment is connected to IPv6, relevant tests should be carried out on the equipment. However, there are few research studies on the testing of industrial wireless network equipment connected to IPv6 networks, and there are various testing methods for various network protocols. Traditional single software Architectural testing methods are difficult to meet the integration and expansion needs of various industrial wireless network access IPv6 test services.

Contents of the invention

In view of this, the purpose of the present invention is to provide a microservice-based industrial wireless network device access IPv6 test system and method.

In order to achieve the above objects, the present invention provides the following technical solutions:

On the one hand, the present invention provides a microservice-based industrial wireless network device access IPv6 test system, including a test management system, a test agent, and a test environment based on a microservice architecture;

The test management system based on microservice architecture includes interaction layer, forwarding layer, service layer, data layer and governance layer:

Interaction layer: Web-based interactive interface, providing users with a human-computer interaction interface;

Forwarding layer: the service gateway, which is responsible for filtering and forwarding requests from the interaction layer, calling services of the service layer, and performing load balancing functions;

Service layer: Contains independent microservices divided into functional modules, including: test resource management service module, test implementation management service module, test project management service module, user management service module, and log management service module;

Data layer: saves all data required for the normal operation of the system;

Governance layer: Improve the reliability and fault tolerance of the microservice system, including: service registration and discovery module, which provides the function of managing each microservice instance; service circuit breaker module, which prevents fault spread through failover and system isolation; service chain Route tracking and monitoring collects performance data on microservice call links; the service configuration center centrally manages all configuration attribute files;

The test agent is used to analyze test instructions from the test management system based on microservice architecture, send data streams to the corresponding test environment, receive data streams from the test environment, process the data streams, and interact with the test environment The data flow processing results are uploaded to the test management system based on microservice architecture;

The test environment includes a gateway test environment, a router test environment, and a terminal test environment, which are respectively test environments built for gateways, routers, and terminals that want to access the IPv6 network; the test environment includes standard wireless routers, wireless terminals, and IPv6 wireless The border gateway, as well as the wireless router under test, the wireless terminal under test, and the IPv6 wireless border gateway under test provided by the user.

Further, the test agents include:

Communication interface: Provides communication functions with the test management system based on microservice architecture;

Protocol standard: Embedded with the same protocol module as the industrial wireless network under test, it can conduct protocol consistency testing with the industrial wireless network under test;

Test agent description: Contains useful information related to testing, including test agent definition information, driver test control information, and related parameter information;

Test driver: Responsible for the interactive test flow with industrial wireless network equipment connected to the IPv6 test environment.

Further, each microservice in the service layer specifically includes:

The test resource management service module includes test case management and test data management, and is used to manage IPv6 test cases for wireless network devices with different protocols, as well as test required data and test result data;

The test implementation management service module includes wireless access test management, test report management, and test case implementation management; the wireless access test management provides IPv6 test services for wireless network equipment access to various protocols; the test report management includes Add, delete and check operation functions for test reports; the test case implementation management includes test case set optimization and test case execution functions;

The test project management service module includes the functions of creating, deleting, viewing, and status maintenance of test projects;

The user management service module includes viewing, adding, deleting and assigning permissions to user information;

The log management service module includes recording system operation logs and test case execution logs.

On the other hand, the present invention provides a microservice-based industrial wireless network equipment access IPv6 testing method, which includes the following steps:

S1: The user logs in to the test management system based on microservice architecture, creates a test project, fills out the PICS form, and provides the tested device to the tester;

S2: The tester connects the device under test to the network environment under test according to the details in the test project;

S3: The test management system based on the microservice architecture calls the corresponding internal resources according to the test projects created by the user, calls the wireless access test service, generates a test case set, and calls the test case set optimization algorithm to analyze the test cases in the test case set. Prioritize;

S4: The test management system based on microservice architecture executes test cases one by one based on the test case set and sends test instructions to the test agent;

S5: The test agent sends a test stream to the IPv6 test environment where the industrial wireless network device accesses the device according to the operation instructions;

S6: The industrial wireless network equipment is connected to the network equipment in the IPv6 test environment to forward and respond to the test flow, and finally responds to the test flow to the test agent;

S7: The test agent simply processes the response test stream and uploads the results to the test management system based on microservice architecture;

S8: After executing all test cases, the test management system based on microservice architecture analyzes the test results and generates a test report.

Furthermore, when the test case set is first obtained, it is based on some entries of the PICS table filled in by the user, including

device_type_id field, protocol_type_id field, requirement_information field information; test case binding device_type_id field, protocol_type_id field, requirement_information field information;

If the test project is not executed for the first time, the access test service will send the test case historical execution record of the test project to the test case management service. The test case management service will retrieve the test case base from the database based on the test_case_id field information of the test case historical execution record. .

Furthermore, before optimizing the test case set, the test cases are renumbered to obtain the test case number sequence;

The input of the test case set optimization algorithm is the test case number x _ij and the test requirement coverage number of the corresponding test case Number of historical execution failures of test cases The output is the optimized test case number sequence; the test case set optimization algorithm includes the following steps:

S31: Define the test requirement coverage number and historical failure number of test cases;

S32: The number of test requirements coverage and the number of historical failures of initialization test cases;

S33: Determine whether it exists If it does not exist, use the ordinary sorting algorithm according to The optimized test case number sequence is obtained by sorting the size in descending order. If it exists, the improved multi-objective cuckoo search algorithm is called to obtain the optimized test case number sequence.

Further, the improved multi-objective cuckoo search algorithm includes the following steps:

A1: Define population size, discovery probability, and end conditions;

A bird's nest represents the number sequence of all test cases in a test case set, representing a possible solution. The bird's nest is defined as:

In the formula, n represents the number of all bird's nests, that is, the population size; m represents the number of test cases in a test case set, that is, the number of test case numbers; tMax represents the maximum number of iterations; x _ij represents the j-th test of the i-th bird's nest. Use case number; Represents the i-th bird's nest after t iterations;

A population is defined as:

When executing the random walk mechanism, part of the bird's nest is abandoned with a certain probability. The probability that the host of the bird's nest discovers the cuckoo egg is pa. The end condition is defined as whether the current number of iterations is the maximum number of iterations tMax;

A2: Initialize the population and determine the fitness function;

A3: Determine whether the end condition is met, that is, whether the maximum number of iterations tMax is reached. If it is met, the optimal bird's nest is output, otherwise the following loop steps are executed;

A4: Generate new bird nests and update the population through Levi’s flight mechanism;

A5: Generate new bird nests and update the population through the random walk mechanism;

A6: Determine whether the mutation decision-making condition is met. If it is met, update the number of iterations and return to step A4; if not, first use the mutation mechanism to generate a new bird's nest and update the population, then update the number of iterations and return to step A4.

The mutation decision condition is:

Among them, γ represents the threshold of the mutation mechanism; u represents the number of generations to be traced;

When the fitness value of the i-th bird's nest for consecutive u generations remains within a small range, the mutation mechanism is triggered and the population is updated with the current random walk mechanism. Treat it as the t+1 generation population for decision-making;

The mutation mechanism generates a new bird's nest formula as follows:

In the formula, represents the processed bird's nest; xθ represents the random mutation parameter;

The test case number of the new bird's nest is repaired by the asexual genetic mechanism; the population is calculated bird's nests fitness value non-dominated solution set Compare and Dominance relationship between solutions, update the non-dominated solution set to obtain

In the target space, according to find datum point pairwise comparison with reference point distance and with reference point distance; keep the nest with a smaller distance and get a new population

The bird's nest after comparison and retention operations is recorded as Update the best bird's nest and its fitness value Update the best bird's nest and its fitness value

Further, step A2 specifically includes the following steps:

Initialize each bird's nest in the population:

In the formula, randomPermutation(m) is the random permutation function of size m generated by the i-th initial bird nest, and the initial population is

The ranking objectives are to maximize test requirement coverage and maximize historical execution failure rate. Maximizing test requirement coverage means that test cases cover more test requirements as quickly as possible, and maximizing historical execution failure rate means that during the historical execution process , test cases that have discovered defects should have higher priority;

The objective function to maximize test requirement coverage is:

In the formula, m represents the number of test cases in a test case set; x _ij represents the j-th test case number of the i-th bird's nest; Indicates the number of test requirements covered by a test case; RCS indicates the number of test requirements covered by all test cases;

The objective function to maximize the historical execution failure rate is:

In the formula, Indicates the number of historical execution failures of a test case, and FCS indicates the number of historical execution failures of all test cases;

The Bird's Nest objective function f( _xi ) that comprehensively maximizes test requirement coverage and maximizes historical execution failure rate is expressed as:
f(x _i )=[f ₁ (x _i ), f ₂ (x _i )]

Taking the objective function as the fitness function and the value of the objective function as the fitness value, the non-dominated solution set NDS ⁽⁰⁾ of the initial population is obtained by the following formula:

Among them, x _a and x _b are two different bird's nests. Find the reference point (Max(f ₁ ), Max(f ₂ )) in NDS ⁽⁰⁾ , which is recorded as RP ⁽⁰⁾ . Calculate the non-dominated solution closest to the reference point as the optimal solution of the initial population P ⁽⁰⁾ its fitness value Calculate the solution farthest from the reference point as the worst solution of the initial population P ⁽⁰⁾ its fitness value

Further, the step A5 specifically includes the following steps:

Using Levi's flight mechanism to remove the optimal bird's nest The location and status of other bird's nests are updated. The initial update formula is:

In the formula, α represents the step control amount; Represents the i-th bird's nest after t iterations; expressed in The new bird's nest generated through Levi's flight mechanism is a temporarily updated version of the bird's nest, not the t+1 generation bird's nest; Represents point-to-point multiplication; Levy(β) represents a random search path, obeying Levy distribution;

Use the following formula to generate Levy random numbers:

In the formula, μ, ν obey the standard normal distribution;

Adaptation step size for:

In the formula, Represents the step size of the i-th bird's nest in the population after t iterations; It represents the fitness value of the i-th bird's nest in the population after t iterations; Indicates the optimal bird's nest fitness value in the population after t iterations; Represents the worst nest fitness value in the population after t iterations;

The improved Levi flight update formula is:

Round off the test case numbers of the new Bird's Nest, replace out-of-bounds test case numbers and duplicate numbers with irrelevant values, recorded as *; then the irrelevant values in the new Bird's Nest are removed from the old Bird's Nest Get in, follow the old bird's nest The values sequentially fill in the irrelevant values * of the new bird's nest; repair the new bird's nest through the asexual genetic mechanism and finally obtain the bird's nest.

Calculate the restored bird's nest fitness value Get the non-dominated solution set Compare and the dominance relationship of solutions in NDS ^(t) , update the non-dominated solution set to obtain In the target space, according to find datum point pairwise comparison with reference point distance and with reference point distance; keep the nest with a smaller distance and get a new population The bird's nest after comparison and retention operations is recorded as Update the best bird's nest and its fitness value Update the best bird's nest and its fitness value

Further, step A5 specifically includes the following steps:

The random walk mechanism is a process that simulates a bird's nest where the host may abandon the nest and generate a new bird's nest elsewhere after discovering a cuckoo egg with a certain probability. The random walk mechanism produces new bird's nests. The expression is as follows:

in, represents a population 3 different bird's nests in arbitrarily; ε represents a random number belonging to [0,1]; pa represents the discovery probability; H (ε-pa) Heaviside function, when (ε-pa) ≥ 0, the The function value is 1, otherwise the function value is 0;

Perform asexual genetic mechanism repair on the test case number of the new bird's nest to obtain the population

Calculate the population bird's nests fitness value non-dominated solution set Compare and Dominance relationship between solutions, update the non-dominated solution set to obtain

In the target space, according to find datum point pairwise comparison with reference point distance and with reference point distance; keep the nest with a smaller distance and get a new population

The bird's nest after comparison and retention operations is recorded as Update the best bird's nest and its fitness value Update the best bird's nest and its fitness value

The beneficial effects of the present invention are that: the present invention effectively solves the integration and expansion needs of various industrial wireless network access IPv6 test services through an IPv6 test system based on microservices. Each microservice only focuses on one task and can easily To complete the task well, each microservice can be deployed independently, the microservices are loosely coupled, and the services coordinate and cooperate with each other. The microservice architecture can provide great help for the deployment of test systems for industrial wireless network equipment to access IPv6.

Other advantages, objects, and features of the present invention will, to the extent that they are set forth in the description that follows, and to the extent that they will become apparent to those skilled in the art upon examination of the following, or may be derived from This invention is taught by practicing it. The objects and other advantages of the invention may be realized and obtained by the following description.

Description of drawings

In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be described in detail below in conjunction with the accompanying drawings, in which:

Figure 1 is a test topology diagram of IPv6 access to industrial wireless network equipment based on microservices;

Figure 2 shows the test framework diagram of microservice-based industrial wireless network equipment access to IPv6;

Figure 3 is the overall test workflow diagram;

Figure 4 is an organization chart of functional requirements of the test management system based on microservice architecture;

Figure 5 is the flow chart of test case acquisition;

Figure 6 is a flow chart of the test case set optimization service program;

Figure 7 is a flow chart based on the improved multi-objective cuckoo search algorithm;

Figure 8 is the target space diagram;

Figure 9 is a schematic diagram of the repair process of the asexual genetic mechanism;

Figure 10 is the test case execution flow chart.

Detailed ways

The following describes the embodiments of the present invention through specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner. The following embodiments and the features in the embodiments can be combined with each other as long as there is no conflict.

The drawings are only for illustrative purposes, and represent only schematic diagrams rather than actual drawings, which cannot be understood as limitations of the present invention. In order to better illustrate the embodiments of the present invention, some components of the drawings will be omitted. The enlargement or reduction does not represent the size of the actual product; it is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

In the drawings of the embodiments of the present invention, the same or similar numbers correspond to the same or similar components; in the description of the present invention, it should be understood that if there are terms "upper", "lower", "left" and "right" The orientation or positional relationship indicated by "front", "rear", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must be It has a specific orientation and is constructed and operated in a specific orientation. Therefore, the terms describing the positional relationships in the drawings are only for illustrative purposes and cannot be understood as limitations of the present invention. For those of ordinary skill in the art, they can determine the specific position according to the specific orientation. Understand the specific meaning of the above terms.

Figure 1 is a test topology diagram for IPv6 access to industrial wireless network equipment based on microservices. As shown in the figure, the test topology for IPv6 access to industrial wireless network equipment based on microservices mainly consists of two parts: the test service layer and the network layer under test. .

The test service layer consists of users and browsers, Internet routers, and test management systems based on microservice architecture:

(1) Users access the test management system based on microservice architecture through a browser, and the browser will display the user’s human-computer interaction Interface. Users can register, log in, select test services, query test results and other operations according to the human-computer interaction interface;

(2) The Internet router provides an Internet path between the user's browser device, the test management system based on microservice architecture and the network layer under test to achieve information interaction;

(3) The test management system based on microservice architecture deployed on the cloud server can call the internal database according to the test service submitted by the user, send test instructions to the network layer under test, and can analyze the test data and respond to the browser with the test results. device.

The network layer under test consists of test agent, gateway test environment, router test environment, terminal test environment, etc.:

(1) The test agent can analyze test instructions from the test management system based on microservice architecture, send data streams to the corresponding test environment, receive data streams from the test environment, and perform simple processing on the data streams. The test agent will upload the data flow processing results interacting with the test environment to the test management system based on microservice architecture;

(2) The gateway test environment, router test environment, and terminal test environment are test environments respectively built for gateways, routers, and terminals that want to access the IPv6 network. The test environment includes standard wireless routers, wireless terminals, IPv6 wireless border gateways and other equipment, as well as user-provided wireless routers under test, wireless terminals under test, IPv6 wireless border gateways under test and other equipment.

Figure 2 shows the test framework diagram of IPv6 access for industrial wireless network equipment based on microservices. The test management system based on microservices architecture includes interaction layer, forwarding layer, service layer, data layer and governance layer:

(1) The interaction layer is a Web-based interactive interface that provides users with a human-computer interaction interface;

(2) The forwarding layer, that is, the service gateway, is mainly responsible for filtering and forwarding requests from the interaction layer, calling services of the service layer, and performing load balancing and other functions;

(3) The service layer includes independent microservices divided into functional modules, including: test resource management service, test implementation management service, test project management service, user management service, and log management service modules;

(4) The data layer stores all data required for the normal operation of the system;

The governance layer mainly improves the reliability and fault tolerance of the microservice system, including: service registration and discovery module, which provides the function of managing each microservice instance; service circuit breaker module, which prevents avalanches caused by fault spread through failover, system isolation and other means. Effect; service link tracking and monitoring collects performance data on microservice call links; the service configuration center can centrally manage all configuration attribute files.

The test agent is a bridge between the test management system based on microservice architecture and the access of industrial wireless network equipment to the IPv6 test environment. It mainly includes:

(1) Communication interface, providing communication functions with the test management system based on microservice architecture;

(2) Protocol standard, embedded with the same protocol module as the industrial wireless network under test, can communicate with the industrial wireless network under test Protocol conformance testing;

(3) Test agent description, including some useful information related to testing, such as test agent definition information, driver test control information, and related parameter information;

The test driver is mainly responsible for interacting with the IPv6 test environment by connecting industrial wireless network equipment to the test flow.

The overall testing workflow is shown in Figure 3.

(1) The user needs to provide the device under test to the tester. After the user creates the test project, the tester will connect the device under test to the network environment under test according to the details in the test project;

(2) The user fills in the Protocol Implementation Conformance Statement (PICS) form on the browser and selects the device type, protocol type, test requirements, etc. to be tested based on the actual testing requirements of the wireless network device under test. The PICS table structure is shown in Table 1, and the test requirements table structure is shown in Table 2.

Table 1

Table 2

(3) The test management system based on the microservice architecture calls the corresponding internal resources according to the test projects created by the user, calls the wireless access test service, generates a test case set, and calls the test case set optimization algorithm to perform centralized testing of the test cases Prioritize use cases;

(4) The test management system based on microservice architecture executes test cases one by one based on the test case set and sends test instructions to the test agent;

(5) The test agent sends test streams to the IPv6 test environment where the industrial wireless network equipment accesses according to the operation instructions;

(6) The industrial wireless network equipment connected to the network equipment in the IPv6 test environment forwards and responds to the test flow, and ultimately responds to the test flow to the test agent;

(7) The test agent simply processes the response test stream and uploads the results to the test management system based on microservice architecture;

(8) After executing all test cases, the test management system based on microservice architecture will analyze the test results and generate testing report.

The functional requirements organization structure of the test management system based on microservice architecture is shown in Figure 4, including:

(1) Test resource management function

In order to facilitate the management of wireless network devices with different protocols accessing IPv6 test cases, as well as test required data and test result data, the test management system based on microservice architecture needs to have a test resource management function so that testers can increase the resources required for testing. Delete, modify and check.

(2) Test implementation management function

Since there are many wireless network protocols, the IPv6 test of wireless network devices with different protocols has different characteristics and different implementation processes, and the implementation operations related to test cases are an extremely important and cumbersome part of the entire test. Therefore, based on micro The test management system of the service architecture should have test implementation management functions.

Test implementation management functions include: wireless access test management, which includes wireless network device access IPv6 test services for various protocols, such as Wireless HART access test, WIA-PA access test, 6LoWPAN access test, etc.; test report Management includes operation functions such as adding, deleting and checking test reports; test case implementation management includes test case set optimization, test case execution and other functions.

(3) Test project management function

The user selects the test service by creating a test project. When the test service is executed, the user also needs to check the test status from the test project. At the same time, the test report generated when the test is completed needs to be obtained from the test project. Therefore, a test management system based on microservice architecture requires test project management functions. Test project management functions include test project creation, deletion, viewing, status maintenance and other functions.

(4)User management function

In the actual test environment, there are many people with permission to use the test management system based on microservice architecture, and the personnel are complex. It is necessary to design a login function to authenticate the accounts and passwords assigned to users to avoid irrelevant personnel or people with mismatched permissions. enter the system. By categorizing and grading user accounts, user permissions are assigned to avoid misoperation by ordinary users and ensure the security of the system to a certain extent. User management functions include viewing user information, adding and deleting users, and assigning user rights.

(5)Log management function

A test management system based on microservice architecture should have a log management function to record in detail the system users' operations and operation results, record the execution process of test cases, etc., to facilitate problem finding and accountability, and to solve problems in a timely manner.

The process of obtaining test cases is shown in Figure 5. The access test service calls test cases from the database by calling the test case management service to obtain the test case set. Access the test service and call the test case optimization service, through the optimization algorithm Prioritize the test case set, and then return the optimized test case set to the access test service.

When the test case set is first obtained, it is based on some entries in the PICS table filled in by the user, including the device_type_id field, protocol_type_id field, and requirement_information field information. When the test case is designed, the device_type_id field, protocol_type_id field, and requirement_information field information will be bound. The test case structure is shown in Table 3.

table 3

If the test project is not executed for the first time, the access test service will send the test case historical execution record of the test project to the test case management service. The test case historical execution record structure is shown in Table 4.

The test case management service retrieves test cases from the database based on the test_case_id field information in the test case history execution record.

Table 4

Before the test case set optimization service program is executed, the test management system based on the microservice architecture retrieves the test case set from the database and renumbers the test cases in it. Renumbering means that if the test case set has m test cases, then renumber each test case from 1 to m to obtain the test case number sequence.

The input of the test case set optimization service program is the test case number x _ij and the test requirement coverage number of the corresponding test case Number of historical execution failures of test cases As shown in Table 5. The output is the optimized test case number sequence.

table 5

The test case set optimization service program process is shown in Figure 6. The program will first determine whether the test project exists If it does not exist, use the ordinary sorting algorithm according to The optimized test case number sequence is obtained by sorting the size in descending order. If it exists, the improved multi-objective cuckoo search algorithm is called to obtain the optimized test case number sequence.

The process based on the improved multi-objective cuckoo search algorithm is shown in Figure 7. This algorithm is based on the ranking objectives of maximizing test requirement coverage and maximizing historical execution failure rate. First of all, it is necessary to construct the relationship between the test case and the test target to construct the fitness function, and ensure the quality of the optimization results through means such as Levi's flight mechanism global search, random walk mechanism local search, and mutation mechanism to prevent falling into local optimality. Specific steps are as follows:

Step 1: Define the population size, discovery probability, end conditions, etc.

A bird's nest represents the number sequence of all test cases in a test case set, representing a possible solution. The bird's nest is defined as:

In the formula, n represents the number of all bird nests, that is, the population size;

m represents the number of test cases in a test case set, that is, the number of test case numbers; tMax represents the maximum number of iterations; x _ij represents the j-th test case number of the i-th nest; Represents the i-th bird's nest after t iterations;

A population is defined as:

The algorithm abandons part of the bird's nest with a certain probability when executing the random walk mechanism. The probability that the host of the bird's nest discovers the cuckoo egg is pa. Define the end condition as whether the current number of iterations is the maximum number of iterations tMax.

Step 2: Initialize the population and determine the fitness function

Initialize each bird's nest in the population.

In the formula, randomPermutation(m) is a random arrangement function that generates a size m for the i-th initial bird's nest, then the initial population is

This algorithm is based on the ranking objectives of maximizing test requirement coverage and maximizing historical execution failure rate. Maximizing test requirement coverage means that test cases cover more test requirements as quickly as possible, and maximizing the historical execution failure rate means that test cases that have discovered defects during the historical execution process should have a higher priority.

(1) Maximize test requirement coverage

In the test case set, the greater the number of test requirements covered by a test case, the higher it should be ranked. The objective function to maximize test requirement coverage is shown in Expression 4.

In the formula, m represents the number of test cases in a test case set; x _ij represents the j-th test case number of the i-th bird's nest. Indicates the number of test requirements covered by a test case; RCS indicates the number of test requirements covered by all test cases.

In Expression 4, the number of coverage requirements of the test case is multiplied by the weight of the position of the test case, so that the nest with a larger number of test case coverage requirements and its position earlier in the sequence is more likely to be retained. .

(2) Maximize the historical execution failure rate

The greater the historical execution failure rate, the more times the test case failed in the execution history. It is generally believed that test cases that have failed many times in historical execution have a greater chance of detecting defects when executed on new version devices. Therefore, test cases with higher historical execution failure rates should be ranked higher. . The objective function that maximizes the historical execution failure rate is shown in Expression 5.

In the formula, m - represents the number of test cases in a test case set; x _ij represents the j-th test case number of the i-th bird's nest; Indicates the number of historical execution failures of a test case; FCS indicates the number of historical execution failures of all test cases.

The Bird's Nest objective function that comprehensively maximizes the test requirement coverage and maximizes the historical execution failure rate is expressed as f(xi ₎ .
f(x _i )=[f ₁ (x _i ), f ₂ (x _i )] (6)

(3) Pareto optimal concept

The concept of Pareto optimality is introduced here. If two different bird's nests x _a and x _b satisfy expression 7, then x _a is said to dominate x _b .

If there is no solution that can dominate x in the solution space, that is, all bird's nests, then x is said to be non-dominated, and such a solution is called a Pareto optimal solution. The solution of multi-objective optimization is usually not the only solution, but a set containing multiple Pareto optimal solutions, and this set is called the Pareto front. Since the objective functions of this test case set optimization algorithm are two, the Pareto front can be represented by two-dimensional coordinates, as shown in Figure 8.

This algorithm uses the objective function as the fitness function, and the value of the objective function is the fitness value. According to Expression 7, the non-dominated solution set NDS ⁽⁰⁾ of the initial population is obtained. Find the reference point (Max(f ₁ ), Max(f ₂ )) in NDS ⁽⁰⁾ and record it as RP ⁽⁰⁾ . Calculate the non-dominated solution closest to the reference point as the optimal solution of the initial population P ⁽⁰⁾ its fitness value Calculate the solution farthest from the reference point as the worst solution of the initial population P ⁽⁰⁾ its fitness value

Step 3: Whether the ending conditions are met

This test case set optimization algorithm must judge whether the end condition is met after each iteration, and the end condition is the maximum number of iterations tMax. If the current iteration number t reaches tMax, then jump out of the loop and output the optimal bird's nest. If t is less than tMax, then Execute loop content.

Step 4: Levi’s flight mechanism generates new nests and updates the population

(1) Levi’s flight mechanism generates a new bird’s nest

Using Levi's flight mechanism to remove the optimal bird's nest The position and status of other bird's nests are updated. The initial update formula of the algorithm is shown in Expression 8.

In the formula, α represents the step control amount; Represents the i-th bird's nest after t iterations; expressed in The new bird's nest generated through Levi's flight mechanism is a temporarily updated version of the bird's nest, not the t+1 generation bird's nest; Represents point-to-point multiplication; Levy(β) represents a random search path, obeying Levy distribution.

Levi's flight mechanism is a form of locomotion that alternates short-distance exploration with occasional longer-distance walking. Using Levi's flight mechanism can expand the search range, increase the diversity of the bird's nest, and make it easier to jump out of the local optimum. To facilitate calculation, expression 9 is used to generate Levy random numbers:

In the formula, μ, ν represent that they obey the standard normal distribution.

In order to move the possible solutions, that is, each bird's nest towards the current optimal solution The direction of the bird's nest is approaching, and expression 8 is improved to:

The value of the step control amount α in Expression 11 should be chosen carefully because it controls the global search. If the value of α is too small, then the possible solution will be close to the current optimal solution and will fall into the local optimal solution. If the value of α is too large, the result may be out of bounds. Improving α to a dynamic adaptive step size will expand the initial search range and reduce the step size of later iterations, thereby improving convergence efficiency. adaptive step size As shown in expression 12

In the formula, Represents the step size of the i-th bird's nest in the population after t iterations; Represents the fitness value of the i-th bird's nest in the population after t iterations; Indicates the optimal bird's nest fitness value in the population after t iterations; Indicates the worst nest fitness value in the population after t iterations.

Therefore, the improved Levy flight update formula is expression 13.

(2) Asexual genetic mechanism repairs new bird nests

New nests generated due to Levi's flight mechanism Invalid or out-of-bounds test case numbers will be generated, so the test case numbers of the new Bird's Nest need to be processed.

First, round the test case numbers of the new Bird's Nest, and replace the out-of-bounds test case numbers and duplicate numbers with irrelevant values, recorded as *. Then the irrelevant values in the new nest are removed from the old nest Get in, follow the old bird's nest The value order fills the new nest with irrelevant values*. Asexual genetic mechanism repairs new bird's nest and finally gets bird's nest The schematic diagram of the repair process is shown in Figure 9.

(3) Calculate the fitness value of the new nest and update the population

Calculate the repaired bird's nest fitness value Get the non-dominated solution set Compare and the dominance relationship of solutions in NDS ^(t) , update the non-dominated solution set to obtain

In the target space, according to find datum point pairwise comparison with reference point distance and with reference point distance. Keep the nest with a smaller distance to get a new population

The bird's nest after comparison and retention operations is recorded as Update the best bird's nest and its fitness value Update the best bird's nest and its fitness value

Step 5: Random walk mechanism generates new nests and updates the population

(1) Random walk mechanism generates new bird's nest

The random walk mechanism of the cuckoo algorithm simulates the process in which the host of a bird's nest may abandon the nest and generate a new bird's nest elsewhere after discovering a cuckoo egg with a certain probability. Random walk mechanism production line new bird's nest The expression of is shown in Expression 14:

in, represents a population 3 arbitrary different bird's nests in The value is 1, otherwise the function value is 0.

(2) Asexual genetic mechanism repairs new bird nests

Since the new bird's nest generated by the random walk mechanism will generate invalid or out-of-bounds test case numbers, the test case numbers of the new bird's nest need to be processed. The processing process is similar to step (2) in step 4. Obtained after all bird's nests are repaired population

(3) Calculate the fitness value of the new nest and update the population

Calculate the population bird's nests fitness value non-dominated solution set Compare and Dominance relationship between solutions, update the non-dominated solution set to obtain

In the target space, according to find datum point pairwise comparison with reference point distance and with reference point distance. Keep the nest with a smaller distance to get a new population

The bird's nest after comparison and retention operations is recorded as Update the best bird's nest and its fitness value Update the best bird's nest and its fitness value

Step 6: Determine whether the mutation decision-making conditions are met.

When the algorithm enters the later stage, the bird's nests generated by Levi's flight mechanism and random walk mechanism will be close to the old bird's nest. As the number of iterations increases, all bird's nests will be close to each other, and then the average fitness difference of the bird's nest will not change much. Indicates that the solution falls into a local optimum. This scheme uses the mutation mechanism to solve the local optimal problem in the later stages.

In order to prevent the mutation mechanism from generating new nests that are far from the old nests, resulting in missing high-quality nests. Therefore, mutation decision conditions are added.

Among them, γ represents the threshold of the mutation mechanism; u represents the number of generations to be traced.

When the fitness value of the i-th bird's nest in consecutive u generations remains within a small range, the mutation mechanism will be triggered. Note the population updated with the current random walk mechanism Treat it as the t+1 generation population for decision-making.

Step 7: The mutation mechanism generates new nests and updates the population

(1) The mutation mechanism generates a new bird's nest

The mutation mechanism produces a new bird's nest formula as shown in Expression 16.

In the formula, is the bird's nest processed in step five; xθ represents the random mutation parameter.

(2) Asexual genetic mechanism repairs new bird nests

Since the new nest generated by the mutation mechanism will produce invalid or out-of-bounds test case numbers, the test case numbers of the new nest need to be processed. The process of step (2) in step 4 of the processing process is similar. After all bird nests are repaired, the population will be obtained

(3) Calculate the fitness value of the new nest and update the population

Calculate the population bird's nests fitness value non-dominated solution set Compare and Dominance relationship between solutions, update the non-dominated solution set to obtain

In the target space, according to find datum point pairwise comparison with reference point distance and with reference point distance. Keep the nest with a smaller distance to get a new population

The bird's nest after comparison and retention operations is recorded as Update the best bird's nest and its fitness value Update the best bird's nest and its fitness value

Step 8: Update the number of iterations

If the mutation decision conditions are not met, the population in step five As the population P ^(t+1) that has been iterated t+1 times, if the mutation decision conditions are met, the population in step seven As the population P ^(t+1) that has been iterated t+1 times.

Step 9: Output the optimal bird's nest

When the number of iterations reaches tMax, the optimal bird's nest is output. The algorithm based on the improved multi-objective cuckoo search algorithm is over.

After accessing the test service to obtain the optimized test case set, each test case begins to be executed. The process is shown in Figure 10. The access test service parses the test cases in the test case set to obtain several test instructions, and forwards the test instructions to the test agent through the service gateway; after receiving the test instructions, the test agent sends a test stream to the industrial wireless network device access IPv6 test environment; test The stream is forwarded and processed by the device in the IPv6 test environment connected to the industrial wireless network device. The final response test stream will be received by the test agent; the test agent simply processes the response test stream and uploads the test instruction execution results to the access test through the service gateway. Serve. After all the test instructions of the current test case are executed, the next test case is parsed and executed until all test cases in the test case set are executed. Then access the test service to call the test report management service to generate a test report, and the test report will be saved to the database.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified. Modifications or equivalent substitutions without departing from the purpose and scope of the technical solution shall be included in the scope of the claims of the present invention.

Claims (10)

1. A microservice-based industrial wireless network equipment access IPv6 test system, which is characterized by: including a test management system, a test agent, and a test environment based on a microservice architecture;

   The test management system based on microservice architecture includes interaction layer, forwarding layer, service layer, data layer and governance layer:

   Interaction layer: Web-based interactive interface, providing users with a human-computer interaction interface;

   Forwarding layer: the service gateway, which is responsible for filtering and forwarding requests from the interaction layer, calling services of the service layer, and performing load balancing functions;

   Service layer: Contains independent microservices divided into functional modules, including: test resource management service module, test implementation management service module, test project management service module, user management service module, and log management service module;

   Data layer: saves all data required for the normal operation of the system;

   Governance layer: Improve the reliability and fault tolerance of the microservice system, including: service registration and discovery module, which provides the function of managing each microservice instance; service circuit breaker module, which prevents fault spread through failover and system isolation; service chain Route tracking and monitoring collects performance data on microservice call links; the service configuration center centrally manages all configuration attribute files;

   The test agent is used to analyze test instructions from the test management system based on microservice architecture, send data streams to the corresponding test environment, receive data streams from the test environment, process the data streams, and interact with the test environment The data flow processing results are uploaded to the test management system based on microservice architecture;

   The test environment includes a gateway test environment, a router test environment, and a terminal test environment, which are respectively test environments built for gateways, routers, and terminals that want to access the IPv6 network; the test environment includes standard wireless routers, wireless terminals, and IPv6 wireless The border gateway, as well as the wireless router under test, the wireless terminal under test, and the IPv6 wireless border gateway under test provided by the user.
2. The microservice-based industrial wireless network equipment access IPv6 test system according to claim 1, characterized in that: the test agent includes:

   Communication interface: Provides communication functions with the test management system based on microservice architecture;

   Protocol standard: Embedded with the same protocol module as the industrial wireless network under test, it can conduct protocol consistency testing with the industrial wireless network under test;

   Test agent description: Contains useful information related to testing, including test agent definition information, driver test control information, and related parameter information;

   Test driver: Responsible for the interactive test flow with industrial wireless network equipment connected to the IPv6 test environment.
3. The microservice-based industrial wireless network equipment access IPv6 test system according to claim 1, characterized in that: each microservice in the service layer specifically includes:

   The test resource management service module includes test case management and test data management, and is used to manage IPv6 test cases for wireless network devices with different protocols, as well as test required data and test result data;

   The test implementation management service module includes wireless access test management, test report management, and test case implementation management; the wireless access test management provides IPv6 test services for wireless network equipment access to various protocols; the test report management includes Add, delete and check operation functions for test reports; the test case implementation management includes test case set optimization and test case execution functions;

   The test project management service module includes the functions of creating, deleting, viewing, and status maintenance of test projects;

   The user management service module includes viewing, adding, deleting and assigning permissions to user information;

   The log management service module includes recording system operation logs and test case execution logs.
4. A microservice-based industrial wireless network equipment access IPv6 test method, which is characterized by: including the following steps:

   S1: The user logs in to the test management system based on microservice architecture, creates a test project, fills out the PICS form, and provides the tested device to the tester;

   S2: The tester connects the device under test to the network environment under test according to the details in the test project;

   S3: The test management system based on the microservice architecture calls the corresponding internal resources according to the test projects created by the user, calls the wireless access test service, generates a test case set, and calls the test case set optimization algorithm to analyze the test cases in the test case set. Prioritize;

   S4: The test management system based on microservice architecture executes test cases one by one based on the test case set and sends test instructions to the test agent;

   S5: The test agent sends a test stream to the IPv6 test environment where the industrial wireless network device accesses the device according to the operation instructions;

   S6: The industrial wireless network equipment is connected to the network equipment in the IPv6 test environment to forward and respond to the test flow, and finally responds to the test flow to the test agent;

   S7: The test agent simply processes the response test stream and uploads the results to the test management system based on microservice architecture;

   S8: After executing all test cases, the test management system based on microservice architecture analyzes the test results and generates a test report.
5. The microservice-based industrial wireless network equipment access IPv6 test method according to claim 4, characterized in that: when the test case set is first obtained, the basis is the partial entries of the PICS table filled in by the user, including the device_type_id field, the protocol_type_id field, requirement_information field information; test case binding device_type_id field, protocol_type_id field, requirement_information field information;

   If the test project is not executed for the first time, the access test service will send the test case historical execution record of the test project to the tester. The test case management service retrieves the test case base from the database based on the test_case_id field information of the test case historical execution record.
6. The microservice-based industrial wireless network equipment access IPv6 testing method according to claim 4, characterized in that: before optimizing the test case set, the test cases are renumbered to obtain the test case number sequence;

   The input of the test case set optimization algorithm is the test case number x _ij and the test requirement coverage number of the corresponding test case Number of historical execution failures of test cases The output is the optimized test case number sequence; the test case set optimization algorithm includes the following steps:

   S31: Define the test requirement coverage number and historical failure number of test cases;

   S32: The number of test requirements coverage and the number of historical failures of initialization test cases;

   S33: Determine whether it exists If it does not exist, use the ordinary sorting algorithm according to The optimized test case number sequence is obtained by sorting the size in descending order. If it exists, the improved multi-objective cuckoo search algorithm is called to obtain the optimized test case number sequence.
7. The microservice-based industrial wireless network equipment access IPv6 testing method according to claim 6, characterized in that: the improved multi-objective cuckoo search algorithm includes the following steps:

   A1: Define population size, discovery probability, and end conditions;

   A bird's nest represents the number sequence of all test cases in a test case set, representing a possible solution. The bird's nest is defined as:
   

   In the formula, n represents the number of all bird's nests, that is, the population size; m represents the number of test cases in a test case set, that is, the number of test case numbers; tMax represents the maximum number of iterations; x _ij represents the j-th test of the i-th bird's nest. Use case number; Represents the i-th bird's nest after t iterations;

   A population is defined as:
   

   When executing the random walk mechanism, part of the bird's nest is abandoned with a certain probability. The probability that the host of the bird's nest discovers the cuckoo egg is pa. The end condition is defined as whether the current number of iterations is the maximum number of iterations tMax;

   A2: Initialize the population and determine the fitness function;

   A3: Determine whether the end condition is met, that is, whether the maximum number of iterations tMax is reached. If it is met, the optimal bird's nest is output, otherwise the following loop steps are executed;

   A4: Generate new bird nests and update the population through Levi’s flight mechanism;

   A5: Generate new bird nests and update the population through the random walk mechanism;

   A6: Determine whether the mutation decision-making condition is met. If it is met, update the number of iterations and return to step A4; if not, first use the mutation mechanism to generate a new bird's nest and update the population, then update the number of iterations and return to step A4.

   The mutation decision condition is:
   

   Among them, γ represents the threshold of the mutation mechanism; u represents the number of generations to be traced;

   When the fitness value of the i-th bird's nest for consecutive u generations remains within a small range, the mutation mechanism is triggered and the population is updated with the current random walk mechanism. Treat it as the t+1 generation population for decision-making;

   The mutation mechanism generates a new bird's nest formula as follows:
   

   In the formula, represents the processed bird's nest; xθ represents the random mutation parameter;

   The test case number of the new bird's nest is repaired by the asexual genetic mechanism; the population is calculated bird's nests fitness value non-dominated solution set Compare and Dominance relationship between solutions, update the non-dominated solution set to obtain

   In the target space, according to find datum point pairwise comparison with reference point distance and with reference point distance; keep the nest with a smaller distance and get a new population

   The bird's nest after comparison and retention operations is recorded as Update the best bird's nest and its fitness value Update the best bird's nest and its fitness value
8. The microservice-based industrial wireless network equipment access IPv6 testing method according to claim 7, characterized in that step A2 specifically includes the following steps:

   Initialize each bird's nest in the population:
   

   In the formula, randomPermutation(m) is the random permutation function of size m generated by the i-th initial bird nest, and the initial population is

   The ranking objectives are to maximize test requirement coverage and maximize historical execution failure rate. Maximizing test requirement coverage means that test cases cover more test requirements as quickly as possible, and maximizing historical execution failure rate means that during the historical execution process , test cases that have discovered defects should have higher priority;

   The objective function to maximize test requirement coverage is:
   

   In the formula, m represents the number of test cases in a test case set; x _ij represents the j-th test case number of the i-th bird's nest; Indicates the number of test requirements covered by a test case; RCS indicates the number of test requirements covered by all test cases;

   The objective function to maximize the historical execution failure rate is:
   

   In the formula, Indicates the number of historical execution failures of a test case, and FCS indicates the number of historical execution failures of all test cases;

   The Bird's Nest objective function f( _xi ) that comprehensively maximizes test requirement coverage and maximizes historical execution failure rate is expressed as:
   f(x _i )=[f ₁ (x _i ), f ₂ (x _i )]

   Taking the objective function as the fitness function and the value of the objective function as the fitness value, the non-dominated solution set NDS ⁽⁰⁾ of the initial population is obtained by the following formula:
   

   Among them, x _a and x _b are two different bird's nests. Find the reference point (Max(f ₁ ), Max(f ₂ )) in NDS ⁽⁰⁾ , record it as RP ⁽⁰⁾ , and calculate the non-linear point closest to the reference point. Dominant solution, as the optimal solution of the initial population P ⁽⁰⁾ its fitness value Calculate the solution farthest from the reference point as the worst solution of the initial population P ⁽⁰⁾ its fitness value
9. The microservice-based industrial wireless network equipment access IPv6 testing method according to claim 8, characterized in that step A4 specifically includes the following steps:

   Using Levi's flight mechanism to remove the optimal bird's nest The location and status of other bird's nests are updated. The initial update formula is:
   

   In the formula, α represents the step control amount; Represents the i-th bird's nest after t iterations; expressed in The new bird's nest generated through Levi's flight mechanism is a temporarily updated version of the bird's nest, not the t+1 generation bird's nest; Represents point-to-point multiplication; Levy(β) represents a random search path, obeying Levy distribution;

   Use the following formula to generate Levy random numbers:
   

   In the formula, μ, v obey the standard normal distribution;
   

   Adaptation step size for:
   

   In the formula, Represents the step size of the i-th bird's nest in the population after t iterations; It represents the fitness value of the i-th bird's nest in the population after t iterations; Indicates the optimal bird's nest fitness value in the population after t iterations; Represents the worst nest fitness value in the population after t iterations;

   The improved Levi flight update formula is:
   

   Round off the test case numbers of the new Bird's Nest, replace out-of-bounds test case numbers and duplicate numbers with irrelevant values, recorded as *; then the irrelevant values in the new Bird's Nest are removed from the old Bird's Nest Get in, follow the old bird's nest The values sequentially fill in the irrelevant values * of the new bird's nest; repair the new bird's nest through the asexual genetic mechanism and finally obtain the bird's nest.

   Calculate the repaired bird's nest fitness value Get the non-dominated solution set Compare and the dominance relationship of solutions in NDS ^(t) , update the non-dominated solution set to obtain In the target space, according to find datum point pairwise comparison with reference point distance and with reference point distance; keep the nest with a smaller distance and get a new population The bird's nest after comparison and retention operations is recorded as Update the best bird's nest and its fitness value Update the best bird's nest and its fitness value
10. The microservice-based industrial wireless network equipment access IPv6 testing method according to claim 9, characterized in that step A5 specifically includes the following steps:

    The random walk mechanism is a process that simulates a bird's nest where the host may abandon the nest and generate a new bird's nest elsewhere after discovering a cuckoo egg with a certain probability. The random walk mechanism produces new bird's nests. The expression is as follows:
    

    in, represents a population 3 different bird's nests in arbitrarily; ε represents a random number belonging to [0,1]; pa represents the discovery probability; H (ε-pa) Heaviside function, when (ε-pa) ≥ 0, the The function value is 1, otherwise the function value is 0;

    Perform asexual genetic mechanism repair on the test case number of the new bird's nest to obtain the population

    Calculate the population bird's nests fitness value non-dominated solution set Compare and Dominance relationship between solutions, update the non-dominated solution set to obtain

    In the target space, according to find datum point pairwise comparison with reference point distance and with reference point distance; keep the nest with a smaller distance and get a new population

    The bird's nest after comparison and retention operations is recorded as Update the best bird's nest and its fitness value Update the best bird's nest and its fitness value