Performance test method and device, storage medium and electronic equipment

Abstract

The invention discloses a performance test method and device, a storage medium and electronic equipment. The method comprises the steps of determining an initial node number of initial execution nodes used for executing a test task according to task description information matched with the test task; when it is detected that the resource use condition of the target server meets the resource adjustment condition, the initial node number is updated to the target node number according to the current resource use demand; under the condition that a reference server is determined from the candidate server cluster according to the resource occupation state, determining at least one reference execution node allocated to the reference server according to the number difference between the number of target nodes and the number of initial nodes; and sending the test script to the at least one reference execution node through the target communication port between the reference server and the at least one reference execution node. The technical problem of low testing efficiency caused by the fact that required resources cannot be dynamically expanded in performance testing in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of computer testing, and in particular to a performance testing method and device, a storage medium, and an electronic device. Background Art

[0002] Currently, in the performance testing process, it is necessary to first calculate all required resources based on the preliminary requirements, and then perform performance testing based on the calculated test resources during the testing process. However, during the testing process, there may be changes in requirements or other reasons that lead to too many or too few resources being requested. Too many resources will cause waste, and too few resources will cause inaccurate test results or even test delays.

[0003] That is to say, in the prior art, there is a problem that the server resources cannot be dynamically expanded during the performance testing process, resulting in low testing efficiency.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present application provide a performance testing method and device, a storage medium, and an electronic device to at least solve the technical problem in the current related technology that the performance test cannot dynamically expand the required resources, resulting in low testing efficiency.

[0006] According to one aspect of an embodiment of the present application, a performance testing method is provided, including: determining an initial node number of initial execution nodes used to execute a test task based on task description information matching a test task; in a process of executing the test task based on the initial execution nodes with the initial node number, when it is detected that the resource usage of the target server meets the resource adjustment condition, updating the initial node number to the target node number according to the current resource usage demand; when a reference server is determined from a candidate server cluster based on the resource occupancy status corresponding to each of a plurality of candidate servers included in the candidate server cluster, determining at least one reference execution node allocated to the reference server based on the difference in the number of target nodes and the initial node number; sending a test script to at least one reference execution node through a target communication port between the reference server and the at least one reference execution node, wherein the reference execution node is used to execute the test task according to the test script.

[0007] According to another aspect of an embodiment of the present application, a performance testing device is also provided, including: a first determination unit, determining the initial node number of initial execution nodes used to execute the test task according to task description information matching the test task; an updating unit, during the process of the initial execution nodes executing the test task according to the initial node number, when it is detected that the resource usage of the target server meets the resource adjustment condition, the updating unit updates the initial node number to the target node number according to the current resource usage demand; a second determination unit, when a reference server is determined from the candidate server cluster according to the resource occupancy status corresponding to each of a plurality of candidate servers included in the candidate server cluster, determining at least one reference execution node allocated to the reference server according to the difference in the number of target nodes and the initial node number; an execution unit, sending the test script to at least one reference execution node through the target communication port between the reference server and the at least one reference execution node, wherein the reference execution node is used to execute the test task according to the test script.

[0008] Optionally, the above-mentioned update unit includes: a third determination module, which is used for the initial execution node to execute the test task according to the test resources applied for by the target server; when it is detected that the current resource usage demand exceeds the maximum resource amount that can be applied for the target server, and the resource application trend in the historical time period is monitored to be an increasing trend, the expanded resource amount is determined according to the current resource usage demand, wherein the expanded resource amount is used to determine the number of target nodes.

[0009] Optionally, the above-mentioned third determination module includes: a fourth determination module, used to obtain the sum of the requested resource amounts of each initial execution node that executes the test task at the target moment, and the maximum amount of resources that can be applied indicated by the resource usage of the target server at the target moment; when the sum of the requested resource amounts is greater than the maximum amount of resources that can be applied, determine the resource application trend according to the historical resource usage demand amounts that match each monitoring moment in the historical time period; when the growth coefficient that matches the resource application trend is greater than the target growth coefficient, determine the product of the growth coefficient and the current resource usage demand amount as the expanded resource amount; determine the ratio of the maximum concurrency that matches the expanded resource amount to the standard concurrency that matches the reference execution node as the target node number.

[0010] Optionally, the third determination module includes: a fifth determination module, used to obtain the resource occupancy status of each candidate server in the candidate server cluster at the current moment; and determine at least one reference server from the candidate server cluster according to the resource occupancy status and the expanded resource amount.

[0011] Optionally, the fifth determination module further includes a release module, which is used to determine the completion of the reference execution node's task execution when the test task for which the reference execution node applies for test resources to execute meets the execution completion condition; and release the test resources and the reference execution node.

[0012] Optionally, the above-mentioned first determination unit includes: a sixth determination module, used to determine the maximum test concurrency number matching the test task, and the standard concurrency number matching each initial execution node; determine the initial node number of the initial task execution node based on the ratio of the maximum test concurrency number to the standard concurrency number.

[0013] Optionally, the above-mentioned second acquisition module includes: a third acquisition module, used to respectively obtain the duration of any two video streams and the number of key frames matching the video streams from multiple video streams; determine the time deviation between the two video streams based on the ratio of the difference in duration between the two video streams to the difference in the number of key frames; and adjust the duration of the multiple video streams based on the average value of multiple time deviations.

[0014] According to another aspect of the embodiments of the present application, a computer-readable storage medium is provided, in which a computer program is stored, wherein the computer program is configured to execute the above-mentioned performance testing method when running.

[0015] According to another aspect of the embodiments of the present application, there is further provided an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the performance testing method through the computer program.

[0016] In an embodiment of the present application, first, the initial node number of the initial execution nodes used to execute the test task is determined according to the task description information matching the test task; in the process of executing the test task according to the initial execution nodes with the initial node number, when it is detected that the resource usage of the target server meets the resource adjustment conditions, the initial node number is updated to the target node number according to the current resource usage demand, that is, the node number is dynamically adjusted during the test process; when a reference server is determined from the candidate server cluster according to the resource occupancy status corresponding to each of the multiple candidate servers included in the candidate server cluster, at least one reference execution node allocated to the reference server is determined according to the difference in the number of target nodes and the initial node number; the test script is sent to at least one reference execution node through the target communication port between the reference server and the at least one reference execution node, and the reference execution node is used to continue to complete the test task, thereby solving the technical problem in the current related technology that performance testing cannot dynamically expand the required resources, resulting in low testing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 is a schematic diagram of an application environment of an optional performance testing method according to an embodiment of the present application;

[0019] Figure 2 is a flow chart of an optional performance testing method according to an embodiment of the present application;

[0020] Figure 3 is a schematic diagram of an optional performance testing method according to an embodiment of the present application;

[0021] Figure 4 is a flowchart of another optional performance testing method according to an embodiment of the present application;

[0022] Figure 5 is a schematic diagram of another optional performance testing method according to an embodiment of the present application;

[0023] Figure 6 is a schematic structural diagram of an optional performance testing device according to an embodiment of the present application;

[0024] Figure 7 It is a schematic diagram of the structure of an optional electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0026] It should be noted that the terms "first", "second", etc. in the specification 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 the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] According to one aspect of the embodiments of the present application, a performance testing method is provided. Optionally, as an optional implementation, the performance testing method can be but is not limited to being applied to Figure 1 in the environment shown.

[0028] The server 112 includes a database 114 and a processing engine 116. The server 112 executes S102 to determine the initial node number of initial execution nodes for executing the test task according to the task description information matched with the test task;

[0029] S104, during the process of executing the test task according to the initial execution nodes of the initial node number, when it is detected that the resource usage of the target server meets the resource adjustment condition, the initial node number is updated to the target node number according to the current resource usage demand;

[0030] S106, when a reference server is determined from the candidate server cluster according to resource occupation states corresponding to each of the plurality of candidate servers included in the candidate server cluster, determining at least one reference execution node allocated to the reference server according to a difference between the number of target nodes and the number of initial nodes;

[0031] S108, sending the test script to at least one reference execution node through a target communication port between the reference server and at least one reference execution node, wherein the reference execution node is used to execute the test task according to the test script.

[0032] The server 112 executes S110 to the terminal device 102 via the network 110 to display the test information; the terminal device 102 includes a display 108 , a processor 106 , and a memory 104 .

[0033] Optionally, in this embodiment, the terminal device may be a terminal device configured with a target client, which may include but is not limited to at least one of the following: a mobile phone (such as an Android phone, an iOS phone, etc.), a laptop, a tablet computer, a PDA, a MID (Mobile Internet Devices), a PAD, a desktop computer, a smart TV, etc. The target client may be a video client, an instant messaging client, a browser client, an education client, etc. The network may include but is not limited to: a wired network, a wireless network, wherein the wired network includes: a local area network, a metropolitan area network and a wide area network, and the wireless network includes: Bluetooth, WIFI and other networks that realize wireless communication. The server may be a single server, or a server cluster consisting of multiple servers, or a cloud server. The above is only an example, and no limitation is made to this in this embodiment.

[0034] Optionally, as an optional implementation, as Figure 2 As shown, the above performance testing method includes:

[0035] S202, determining the initial number of initial execution nodes for executing the test task according to the task description information matching the test task;

[0036] S204, during the process of executing the test task according to the initial execution nodes of the initial node number, when it is detected that the resource usage of the target server meets the resource adjustment condition, the initial node number is updated to the target node number according to the current resource usage demand;

[0037] S206, when a reference server is determined from the candidate server cluster according to resource occupation states corresponding to each of the plurality of candidate servers included in the candidate server cluster, determining at least one reference execution node allocated to the reference server according to a difference between the number of target nodes and the number of initial nodes;

[0038] S208, sending the test script to at least one reference execution node through a target communication port between the reference server and at least one reference execution node, wherein the reference execution node is used to execute the test task according to the test script.

[0039] In step S202, the initial number of nodes for executing the test task is determined based on the task description information that matches the test task. Specifically, the task description information includes but is not limited to the task name, uploaded Locust files and parameter files, and the estimated concurrency of the test task, the server used by the task, the creator and other necessary information.

[0040] Optionally, determining the initial number of nodes based on the task description information may be by obtaining the expected concurrency number indicated by the task description information, determining the number of concurrent users that the initial node can support based on the configuration information of the initial node, and determining the initial number of nodes based on the ratio of the expected concurrency number to the number of concurrent users of a single node and the sum of redundant nodes, wherein the redundant nodes are protection nodes set up for load balancing to avoid overloading of a single node.

[0041] In the above step S204, during the process of executing the test task according to the initial execution node of the initial node number, when it is detected that the resource usage of the target server meets the resource adjustment condition, the initial node number is updated to the target node number according to the current resource usage demand. The above resource adjustment situation can be that the currently applied resources have exceeded the maximum amount of resources that can be applied, or it can be predicted that the amount of resources applied after a period of time will exceed the maximum amount of resources that can be applied.

[0042] Updating the initial number of nodes to the target number of nodes based on the current resource usage demand can be done by obtaining the estimated concurrency corresponding to the current resource usage demand, and determining the target number of nodes based on the ratio of the estimated concurrency to the concurrency that an initial execution node can support. It can also be done by analyzing and estimating the amount of resources that may increase over a period of time through machine learning historical behavior based on the current resource usage demand, determining the maximum amount of resources after the increase, and then determining the target number of nodes based on the maximum amount of resources.

[0043] Further in the above step S206, when a reference server is determined from the candidate server cluster according to the resource occupation status of each of the plurality of candidate servers included in the candidate server cluster, at least one reference execution node allocated to the reference server is determined according to the difference between the number of target nodes and the number of initial nodes, such as Figure 3 The diagram shows the master server expansion. The expanded reference server is on the right. That is, when multiple users perform stress testing concurrently, insufficient master resources can be achieved through expansion to quickly copy a set of stress testing environments. The arrows between the master and slave indicate which slave nodes belong to which master server for management.

[0044] Specifically, during the use of the server, the usage of server resources, mainly CPU and memory, will be monitored through scheduled tasks (for example, polling every 10 minutes), and can be viewed in the server management list;

[0045] When the CPU or memory usage reaches 80%, the system will send messages and resource usage information to the administrator through email and internal collaboration tools to prompt that resource usage is too high and the master server needs to be expanded. The master service can be manually expanded or automatically expanded through K8S. Manual expansion is completed by manually adding server-related information in the server management module. When automatically expanding, click the automatic expansion button in the server management module, enter the resource information to be applied for (for example: CPU 4 cores, memory 8G, disk 50G), and click OK to apply for the server with the specified resources from K8S. After the server is initialized, it is automatically added and displayed in the server management list.

[0046] When there are multiple master servers available in the server management list at the same time, each new task will first query the current resource usage of multiple master servers and give priority to servers with less resource usage.

[0047] In the above step S208, the test script is sent to at least one reference execution node through the target communication port between the reference server and the at least one reference execution node.

[0048] As an optional implementation, when multiple users conduct concurrent tests at the same time, you need to query the port number first when starting the test service, use the available port number (for example, the agreed port range for locust is: 8090-8150), and bind the port listened by the master (which can be used for communication between the master server and the slave node) and the port number used by the web ui (which can be used to monitor the running status of the slave executing the test task in the interface) when starting the service;

[0049] When multiple users are concurrent, locust will use the specified port and port number + 1 (need to occupy two ports), that is, concurrent user 1 uses 8094 and 8095, concurrent user 2 uses 8096 and 8097 (port numbers can be discontinuous), and so on. When the user finishes executing the task, the corresponding port number will be released. The specific port management allocation and recovery mechanism is as follows:

[0050] S1, according to the actual situation, for example, it is agreed that the master machine locust uses the port range: 8094-8150.

[0051] S2, in the server background, a scheduled task (e.g. 1 hour) will be used to check whether the port number in the specified range has been used, and mark it; in the server management list, you can click on the port usage of the corresponding server to view it;

[0052] S3, when the user starts the service concurrently, first get the two unused ports marked by the server and query them in real time. If the query result is unused, the current user uses the port number and marks the port number corresponding to the server as in use;

[0053] S4, if the query result is that all are in use, then mark the port number corresponding to the server as in use, and then continue to execute S3 to query the actual usage of the port number marked as unused; if it is partially in use, continue to find an unused port.

[0054] S5, when the user finishes executing the task, the port number used by the task is released and the port is marked as unused in the corresponding service.

[0055] Through the above implementation mode of the present application, first, according to the task description information matching the test task, the initial node number of the initial execution node used to execute the test task is determined; in the process of executing the test task according to the initial execution node with the initial node number, when it is detected that the resource usage of the target server meets the resource adjustment condition, the initial node number is updated to the target node number according to the current resource usage demand, that is, the node number is dynamically adjusted during the test process; when a reference server is determined from the candidate server cluster according to the resource occupancy status corresponding to each of the multiple candidate servers included in the candidate server cluster, at least one reference execution node allocated to the reference server is determined according to the difference in the number of target nodes and the initial node number; the test script is sent to at least one reference execution node through the target communication port between the reference server and at least one reference execution node, and the technical effect of continuing to complete the test task using the reference execution node is achieved. The above method can quickly respond to changes in test requirements without waiting for a long time for resource preparation or manually adjusting resource configuration, and can automatically expand master server resources to ensure the stability of the test environment and the smooth execution of test tasks, solving the current technical problem that performance testing cannot dynamically expand required resources, resulting in low test efficiency.

[0056] In an optional implementation, before updating the initial number of nodes to the target number of nodes according to the current resource usage demand, the method includes:

[0057] S1, the initial execution node executes the test task according to the test resources requested by the target server;

[0058] S2, when it is detected that the current resource usage demand exceeds the maximum resource amount that can be applied for the target server, and the resource application trend in the historical time period is monitored to be an increasing trend, the expanded resource amount is determined according to the current resource usage demand, wherein the expanded resource amount is used to determine the quantity stamp of the target node.

[0059] In the above steps S1-S2, the initial execution node executes the test task according to the test resources applied for by the target server; when it is detected that the current resource usage demand exceeds the maximum resource amount that can be applied for the target server, and the resource application trend in the historical time period is monitored to be an increasing trend, the expanded resource amount is determined according to the current resource usage demand.

[0060] As an optional implementation method, at the beginning of the performance test task, the system applies for a certain number of slave nodes (execution nodes) through K8S to carry the test task. These nodes will be initialized and configured according to the estimated resource requirements to perform the test task; during the test task, the system will continue to monitor the resource usage of the target server (master server) and the slave nodes. If the system detects that the resource usage demand (such as CPU usage, memory occupancy) exceeds the maximum pre-allocated resources in the target server or K8S cluster at the resource detection time point, that is, the current resource configuration may not be sufficient to maintain the stability and efficiency of the test, and according to machine learning, it is predicted that the resource demand will continue to increase over a period of time, the system will calculate the excess resource demand based on the current resource usage, that is, the above-mentioned expansion resource amount, and determine the number of CPU cores and memory size that need to be additionally applied for. The system sends a resource request to K8S based on the calculated expansion resource amount, automatically creates and configures a new slave node, ensures that the test task can continue, and optimizes resource utilization efficiency.

[0061] Through the above-mentioned implementation mode of the present application, the initial execution node executes the test task according to the test resources applied for by the target server; when it is detected that the current resource usage demand exceeds the maximum resource amount that can be applied for the target server, and the resource application trend in the historical time period is monitored to be an increasing trend, the amount of expanded resources is determined according to the current resource usage demand, and through dynamic management and optimization of resources in the performance testing environment, through real-time monitoring and historical data analysis, the system can intelligently adjust resource allocation to ensure efficient completion of the test task while avoiding waste of resources.

[0062] In an optional implementation, updating the initial number of nodes to the target number of nodes according to the current resource usage demand includes:

[0063] S1, obtaining the sum of the resource amounts requested by the initial execution nodes for each test task at the target time, and the maximum resource amount that can be requested indicated by the resource usage of the target server at the target time;

[0064] S2, when the sum of the resource applications is greater than the maximum resource application amount, the resource application trend is determined according to the historical resource usage demand that matches each monitoring moment in the historical time period;

[0065] S3, when the growth coefficient matching the resource application trend is greater than the target growth coefficient, the product of the growth coefficient and the current resource usage demand is determined as the expanded resource quantity;

[0066] S4, determining the ratio of the maximum concurrency matching the expanded resource amount to the standard concurrency matching the reference execution node as the target node number.

[0067] In the above steps S1-S4, first, the sum of the resource applications of the initial execution nodes that execute the test tasks at the target moment and the maximum resource application amount indicated by the resource usage of the target server at the target moment are obtained; then, when the sum of the resource applications is greater than the maximum resource application amount, the resource application trend is determined according to the historical resource usage demand that matches each monitoring moment in the historical time period; further, when the growth coefficient that matches the resource application trend is greater than the target growth coefficient, the product of the growth coefficient and the current resource usage demand is determined as the expanded resource amount; thereby, the ratio of the maximum concurrency that matches the expanded resource amount to the standard concurrency that matches the reference execution node is determined to be the target node number.

[0068] Optionally, the growth coefficient can be determined by exponential smoothing. Specifically, for example, the resource usage demand in the most recent week is obtained, and the resource usage at multiple monitoring moments is recorded, such as the concurrent user demand per hour. A target smoothing coefficient A is set to represent the weight ratio of historical data and the latest data in the calculation. For example, if A=30%, the weight of the latest data is 30%, and the weight of the historical data is 70%. The resource demand growth rate between the monitoring moments is further calculated, and the target smoothing coefficient A is used to weighted average the resource demand growth rate to obtain the growth coefficient.

[0069] The above process is described below with a specific implementation method. Assume that the system collects data on the number of concurrent users once an hour. The data for the past 4 hours are as follows (unit: number of concurrent users): time (t-3): 500, time (t-2): 600, time (t-1): 700, time (t): 800; set the smoothing coefficient to 0.3;

[0070] First, calculate the smoothed demand. The smoothed demand at time (t-2) is 0.3*600+(1-0.3)*500=530; the smoothed demand at time (t-1) is 0.3*700+(1-0.3)*600=630; the smoothed demand at time (t) is 0.3*800+(1-0.3)*700=730.

[0071] Further calculating the growth rate, the growth rate from time (t-2) to (t-1) = (700-600) / 600 = 16.67%, the growth rate from time (t-1) to (t) = (800-700) / 700 = 14.29%, so the average growth rate over a period of time can be used as the above growth coefficient.

[0072] After determining the growth coefficient (eg, 20%) and the current resource usage requirement (eg, 10G), the product of the growth coefficient and the current resource usage requirement is determined, ie, 10G*20%=2G, indicating that the additional expansion resource amount required to be applied for is 2G.

[0073] The ratio of the maximum concurrency matched by the expanded resource amount to the standard concurrency matched by the reference execution node is further determined as the target number of nodes that need to be expanded. For example, the specific resource application algorithm can be: Determine the number of slave nodes that need to be expanded = the expected maximum concurrency of the expansion tested / the maximum concurrency supported by a single node (for locusts, one CPU core can be regarded as one slave node). It can be understood that if the estimated maximum concurrency under the initial test conditions is 1000, and the maximum concurrency during the test is expected to reach 2000, then the estimated maximum concurrency of the expansion of the test is determined to be 2000-1000, which means that the expansion needs to increase the concurrency by 1000.

[0074] Through the implementation method of the present application, the sum of the requested resource amounts of the initial execution nodes that execute the test tasks at the target moment and the maximum amount of resources that can be requested as indicated by the resource usage of the target server at the target moment are obtained; when the sum of the requested resource amounts is greater than the maximum amount of resources that can be requested, the resource application trend is determined based on the historical resource usage demand amounts that match each monitoring moment in the historical time period; this helps to prepare resources in advance and avoid performance bottlenecks or test delays caused by insufficient resources during the peak testing period.

[0075] Furthermore, when the growth coefficient matching the resource application trend is greater than the target growth coefficient, the product of the growth coefficient and the current resource usage demand is determined as the expanded resource quantity; the ratio of the maximum concurrency matching the expanded resource quantity to the standard concurrency matching the reference execution node is determined as the target number of nodes. The resource dynamic expansion mechanism based on trend prediction predicts future resource requirements according to historical resource usage, and by comparing the growth coefficient with the target growth coefficient, the system can intelligently determine whether resources need to be expanded and how much resources to expand. In addition, the above steps realize the calculation of the number of automated nodes, avoid insufficient or excessive resources, and improve the predictability and accuracy of resource management.

[0076] In an optional implementation, before determining at least one reference execution node to be allocated to the reference server according to the difference between the number of target nodes and the number of initial nodes, the method includes:

[0077] S1, obtaining the resource occupancy status of each candidate server in the candidate server cluster at the current moment;

[0078] S2: Determine at least one reference server from the candidate server cluster according to the resource occupancy status and the amount of expanded resources.

[0079] In the above steps S1 to S2, the resource occupancy status of each candidate server in the candidate server cluster at the current moment is obtained; and at least one reference server is determined from the candidate server cluster according to the resource occupancy status and the amount of expanded resources.

[0080] As an optional implementation, when there are multiple master servers available in the server management list at the same time, each new task will first query the current resource usage of multiple master servers, and give priority to servers with less resource usage.

[0081] You can determine the server with less resource usage in the following ways: prioritize CPU usage. If the CPU usage differs by more than 5% (configurable), choose the server with lower CPU usage. If the CPU usage differs by less than 5% (configurable), query memory usage and give priority to the server with lower memory usage.

[0082] In an optional implementation, determining at least one reference server from a candidate server cluster according to a resource occupancy state and an expanded resource amount includes:

[0083] S1, obtaining the performance indicators and resource occupancy status matching each candidate server;

[0084] S2, determining the expansion priority of each candidate server according to the weighted average of the resource occupancy status and performance indicators matching each candidate server;

[0085] S3, determine the reference server according to the expansion priority and expansion resource amount.

[0086] As an optional implementation, in the above steps S1-S3, firstly, the performance indicators and resource occupancy status matching each candidate server are obtained; then, the expansion priority of each candidate server is determined according to the weighted average of the resource occupancy status and performance indicators matching each candidate server; thus, the reference server is determined according to the expansion priority and the expansion resource amount. The above performance indicators include but are not limited to CPU usage, memory usage, disk I / O rate, network bandwidth, etc.

[0087] The above process is described below in a specific implementation manner:

[0088] S1, first assign a weight to each performance indicator and resource occupancy status, which reflects the importance of the indicator in the resource expansion decision. For example, CPU usage: 0.4 Memory usage: 0.3 Disk remaining space: 0.2 Network latency: 0.1.

[0089] S2, multiplies the performance indicators and resource occupancy status of each candidate server by its corresponding weight, and then sums them up to get a comprehensive score. This score reflects the current health status and scalability of the server. The higher the score, the higher the priority of the server.

[0090] Specifically, for example, server A: CPU usage 30%, memory usage 40%, disk remaining space 500GB, network delay 10ms. Server B: CPU usage 60%, memory usage 50%, disk remaining space 200GB, network delay 20ms. Server C: CPU usage 20%, memory usage 30%, disk remaining space 300GB, network delay 5ms. The weighted calculation shows that server C has the highest comprehensive score, and server C is determined to have the highest priority level.

[0091] S3, the system selects the server with the highest comprehensive score from the candidate servers and whose resource capacity can meet or approach the required expansion resource amount as the reference server. That is, in the strategy of selecting the expansion server, the server C with the highest priority level is selected first. If the resource occupancy status of server C indicates that the test resources greater than the expansion resource amount can be allocated, server C is determined as the reference server, otherwise continue to judge.

[0092] The reference server determined in the above manner not only has good performance and low resource consumption currently, but also can efficiently support more concurrent users or test tasks after resource expansion.

[0093] Through the above implementation methods recorded in this application, the performance indicators and resource occupancy status that match each candidate server are obtained; the expansion priority of each candidate server is determined according to the weighted average of the resource occupancy status and performance indicators that match each candidate server; the reference server is determined according to the expansion priority and the amount of expansion resources. The optimal server for expansion is determined by comprehensively considering the performance indicators, resource occupancy status of the candidate servers and the degree of matching with the resource application trend and growth coefficient, and the selection of the server is dynamically adjusted according to the real-time resource demand and server status. That is, even if the test environment and resource demand change at any time, the system can respond quickly to ensure that resource expansion always maintains the best match with actual demand, thereby enhancing the adaptability and flexibility of the system.

[0094] In an optional implementation, after sending the test script to at least one reference execution node through the target communication port between the reference server and at least one reference execution node, the method further includes:

[0095] S1, when the test task executed by the reference execution node applying for test resources meets the execution end condition, determining that the reference execution node has finished executing the task;

[0096] S2, release the test resources and reference execution nodes.

[0097] In the above step S1, when the test task executed by the reference execution node applying for test resources meets the execution end condition, it is determined that the reference execution node has finished executing the task. The above execution end condition may be, but is not limited to, for example, recording tasks A, B, C, and D that need to be tested in the test task list, and after all tasks in the task list are executed, it is determined that the execution end condition is met, the end operation is triggered, and the task execution ends.

[0098] In step S2, the test resources and reference execution nodes are released. Specifically, when the slave node completes the test task, it sends a signal to the master node through the communication port to inform that the test task has been completed. After receiving the signal, the master node releases all slave nodes managed by the master server and the corresponding test resources. It should be noted that if no task is being executed, there is only the master server at this time, and there are no slave nodes.

[0099] After the slave node completes the test task, it actively releases resources, avoiding idleness and waste of resources, ensuring a clean and efficient test environment, and further, releasing resources immediately after the test is completed, increasing the availability of the resource pool and improving the dynamic allocation of resources. In concurrent test tasks, resources can be quickly reallocated to other tasks, reducing waiting time, improving the overall throughput of the test system, and improving test efficiency.

[0100] In an optional implementation, determining the initial number of initial execution nodes for executing the test task according to task description information matching the test task includes:

[0101] S1, determine the maximum concurrent number of tests that matches the test task, and the standard concurrent number that matches each initial execution node;

[0102] S2, determine the initial number of nodes for initial task execution based on the ratio of the maximum concurrency of the test to the standard concurrency.

[0103] As an optional implementation, the resource application algorithm can be: the number of slave nodes applied for = the maximum number of concurrent tests expected / the maximum number of concurrent tests supported by a single node (for locusts, one CPU core can be regarded as one slave node). For example, through multiple experiments, it was found that the maximum number of concurrent tests supported by a CPU core and 2G memory is 500. Therefore, when the maximum number of concurrent tests expected is 3000, the number of slave nodes required to be applied for is 3000 / 500=6, that is, 6-core CPU and 12G memory resources.

[0104] Through the above-mentioned implementation method recorded in the present application, the maximum test concurrency number that matches the test task and the standard concurrency number that matches each initial execution node are determined; the initial node number of the initial task execution node is determined according to the ratio of the maximum test concurrency number to the standard concurrency number, thereby improving the accuracy of the initial allocation of resources and nodes to the test task, thereby reducing resource allocation fluctuations during the test process, and the extension of the test time due to insufficient resources, thereby improving the efficiency of the test.

[0105] The following is a complete description of the performance test execution process using a specific implementation method, such as the flowchart Figure 4 As shown:

[0106] The user executes S402 to log in to the system, which is used to manage test tasks.

[0107] S404, create task / upload script. Specifically, the task management module in the system provides a task creation page. The created task needs to include the following information: task name, uploaded Locust file and parameter file, as well as the estimated concurrency of the test task, the server used by the task, the creator and other necessary information; and all created tasks can be displayed. Click the corresponding task name in the list page to enter the task details page, where you can edit the current task, delete the task (the running task cannot be deleted), upload and download the Locust and parameter files in the task, and start and end the task buttons.

[0108] S406, start the service. Specifically, the performance test is run in a master+slave mode, the performance test platform server is the master server by default and can be expanded, the slave machine is applied on demand and is recycled in time after use to reduce resource occupation.

[0109] S408, apply for resources; and execute S410, resource allocation. Specifically, apply for and allocate resources through K8S. The number of slave nodes applied for = the maximum number of concurrent tests expected / the maximum number of concurrent tests supported by a single node (for locusts, one CPU core can be regarded as one slave node). The schematic diagram of the above process is as follows Figure 5 As shown, after starting the service, K8S applies for resources on demand and allocates resources to complete the service startup.

[0110] S412, start the test. After starting the Locust service, the user performs multiple tests on the specified test page until all tests are completed;

[0111] As an optional implementation method, when the user clicks the "Start" button when starting the task, the background applies for the corresponding resources according to the resource application algorithm. After the resources are allocated, the Locust test script and master related information are pushed to the server and deployed, and then the service is started through commands. After the service is started, the front-end page gives a prompt message to let the user enter the specified page to run the test. The user enters the number of concurrent users and the number of users started per second on the specified test page to start the test. After the test is completed, the test results can be saved normally to the database.

[0112] When multiple users conduct concurrent testing at the same time, you need to query the port number first when starting the test service, use an available port number (for example, the agreed port range for locust is: 8090-8150), and bind the port listened by the master and the port number used by the web ui when starting the service.

[0113] S414, result display; specifically, this module displays the test results of the task. By clicking the name of the corresponding task in this page, all execution results of the task can be viewed. The test results can record necessary information such as the test task name, test time, number of concurrent users of the test, etc., and deletion operations are supported.

[0114] S416, test completed; and execute S418, resource recovery. After completing all tests, the user clicks the "End" button, and the system ends all processes of the task and releases the applied resources and used ports.

[0115] It should also be noted that the server management module in this application includes two parts: server addition and server management list; this module is used to expand the master server. When a large number of users conduct concurrent tests and the master resources are insufficient, the master is expanded by adding servers, and the basic usage of the master server resources can be displayed;

[0116] Server Addition: This page allows you to add nodes for expansion servers. When adding a server, you need to include the following information: server name, IP address, user name, password, number of server CPU cores, memory, and other necessary information.

[0117] Server Management List: The server management list supports viewing server information, including viewing server resource usage, specified port usage, server information editing, and server deletion (servers in use cannot be deleted).

[0118] Port usage list: Click the port usage button of a specified server in the server management list to jump to the port usage list of the server. The list can normally display the usage of ports 8090-8150 of the server and cannot be edited.

[0119] Service expansion management: During the use of the server, the usage of server resources, mainly CPU and memory, will be monitored through scheduled tasks (such as polling every 10 minutes), and can be viewed in the server management list; when the CPU or memory usage reaches 80%, the system will send messages and resource usage information to the administrator through email and internal collaboration tools to prompt that resource usage is too high and the master server needs to be expanded. The master service can be manually extended or automatically expanded through K8S.

[0120] Specifically, manual expansion is completed by manually adding server-related information in the server management module; for automatic expansion, click the automatic expansion button in the server management module, enter the resource information to be applied for (for example: CPU 4 cores, memory 8G, disk 50G), and click OK to apply for a server with specified resources like K8S. After the server is initialized, it is automatically added and displayed in the server management list.

[0121] It should be noted that when there are multiple master servers available in the server management list at the same time, each new task will first query the current resource usage of multiple master servers and give priority to servers with less resource usage.

[0122] Method for determining the server with less resource usage: prioritize the judgment based on CPU usage. If the CPU usage differs by more than 5% (configurable), choose the server with lower CPU usage. If the CPU usage differs by less than 5% (configurable), query the memory usage and give priority to the server with less memory usage.

[0123] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0124] According to another aspect of the embodiment of the present application, a performance testing device for implementing the above performance testing method is also provided. Figure 6 As shown, the device comprises:

[0125] A first determining unit 602 determines the initial number of initial execution nodes for executing the test task according to the task description information matched with the test task;

[0126] An updating unit 604 updates the initial node number to the target node number according to the current resource usage demand during the execution of the test task by the initial execution node according to the initial node number, if it is detected that the resource usage of the target server meets the resource adjustment condition;

[0127] The second determining unit 606 determines at least one reference execution node allocated to the reference server according to a difference between the number of target nodes and the number of initial nodes when the reference server is determined from the candidate server cluster according to the resource occupation status corresponding to each of the plurality of candidate servers included in the candidate server cluster;

[0128] The execution unit 608 sends the test script to at least one reference execution node through a target communication port between the reference server and the at least one reference execution node, wherein the reference execution node is used to execute the test task according to the test script.

[0129] Optionally, the above-mentioned update unit 604 includes: a third determination module, which is used for the initial execution node to execute the test task according to the test resources applied for by the target server; when it is detected that the current resource usage demand exceeds the maximum resource amount that can be applied for the target server, and the resource application trend in the historical time period is monitored to be an increasing trend, the expanded resource amount is determined according to the current resource usage demand, wherein the expanded resource amount is used to determine the number of target nodes.

[0130] Optionally, the above-mentioned third determination module includes: a fourth determination module, used to obtain the sum of the requested resource amounts of each initial execution node that executes the test task at the target moment, and the maximum amount of resources that can be applied indicated by the resource usage of the target server at the target moment; when the sum of the requested resource amounts is greater than the maximum amount of resources that can be applied, determine the resource application trend according to the historical resource usage demand amounts that match each monitoring moment in the historical time period; when the growth coefficient that matches the resource application trend is greater than the target growth coefficient, determine the product of the growth coefficient and the current resource usage demand amount as the expanded resource amount; determine the ratio of the maximum concurrency that matches the expanded resource amount to the standard concurrency that matches the reference execution node as the target node number.

[0131] Optionally, the third determination module includes: a fifth determination module, used to obtain the resource occupancy status of each candidate server in the candidate server cluster at the current moment; and determine at least one reference server from the candidate server cluster according to the resource occupancy status and the expanded resource amount.

[0132] Optionally, the fifth determination module further includes a release module, which is used to determine the completion of the reference execution node's task execution when the test task for which the reference execution node applies for test resources to execute meets the execution completion condition; and release the test resources and the reference execution node.

[0133] Optionally, the above-mentioned first determination unit 602 includes: a sixth determination module, used to determine the maximum test concurrency number matching the test task, and the standard concurrency number matching each initial execution node; determine the initial node number of the initial task execution node based on the ratio of the maximum test concurrency number to the standard concurrency number.

[0134] Optionally, the above-mentioned second acquisition module includes: a third acquisition module, used to respectively obtain the duration of any two video streams and the number of key frames matching the video streams from multiple video streams; determine the time deviation between the two video streams based on the ratio of the difference in duration between the two video streams to the difference in the number of key frames; and adjust the duration of the multiple video streams based on the average value of multiple time deviations.

[0135] According to another aspect of the embodiment of the present application, an electronic device for implementing the above performance testing method is also provided. The electronic device may be Figure 1 The terminal device or server shown in the figure. This embodiment is described by taking the electronic device as a mobile phone or a computer as an example. Figure 7 As shown, the electronic device includes a memory 702 and a processor 704. The memory 702 stores a computer program, and the processor 704 is configured to execute the steps in any of the above method embodiments through the computer program.

[0136] Optionally, in this embodiment, the electronic device may be located in at least one network device among a plurality of network devices of a computer network.

[0137] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0138] S1, determining the initial node number of initial execution nodes used to execute the test task according to the task description information matching the test task;

[0139] S2, during the process of executing the test task according to the initial execution nodes of the initial node number, when it is detected that the resource usage of the target server meets the resource adjustment condition, the initial node number is updated to the target node number according to the current resource usage demand;

[0140] S3, when a reference server is determined from the candidate server cluster according to resource occupation states corresponding to each of the plurality of candidate servers included in the candidate server cluster, determining at least one reference execution node allocated to the reference server according to a difference in the number of target nodes and the number of initial nodes;

[0141] S4, sending the test script to at least one reference execution node through a target communication port between the reference server and at least one reference execution node, wherein the reference execution node is used to execute the test task according to the test script.

[0142] Alternatively, a person skilled in the art may understand that: Figure 7 The structure shown is for illustration only, and the electronic device may also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, a mobile Internet device (Mobile Internet Devices, MID), a PAD, or other terminal devices. Figure 7 The structure of the electronic device is not limited. Figure 7 More or fewer components (such as network interfaces, etc.) as shown in, or with Figure 7 Different configurations shown.

[0143] Among them, the memory 702 can be used to store software programs and modules, such as the program instructions / modules corresponding to the performance testing method and device in the embodiments of the present application. The processor 704 executes various functional applications and data processing by running the software programs and modules stored in the memory 702, that is, to implement the above-mentioned performance testing method. The memory 702 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 702 may further include a memory remotely located relative to the processor 704, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. As an example, Figure 7 As shown, the memory 702 may include but is not limited to the first determination unit 602, the update unit 604, the second determination unit 606 and the execution unit 608 in the performance test device. In addition, it may also include but is not limited to other module units in the performance test device, which will not be repeated in this example.

[0144] Optionally, the transmission device 706 is used to receive or send data via a network. Specific examples of the network may include a wired network and a wireless network. In one example, the transmission device 706 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices and routers via a network cable so as to communicate with the Internet or a local area network. In one example, the transmission device 706 is a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0145] In addition, the electronic device mentioned above further includes: a display 708 and a connection bus 710, which is used to connect various module components in the electronic device mentioned above.

[0146] In other embodiments, the terminal device or server may be a node in a distributed system, wherein the distributed system may be a blockchain system, and the blockchain system may be a distributed system formed by connecting the multiple nodes through network communication. The nodes may form a point-to-point network, and any form of computing device, such as a server, terminal or other electronic device, may become a node in the blockchain system by joining the point-to-point network.

[0147] According to one aspect of the present application, a computer-readable storage medium is provided, and a processor of a computer device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the method provided in the above various optional implementations;

[0148] Optionally, in this embodiment, the computer-readable storage medium may be configured to store a computer program for performing the following steps:

[0149] S1, determining the initial node number of initial execution nodes used to execute the test task according to the task description information matching the test task;

[0150] S2, during the process of executing the test task according to the initial execution nodes of the initial node number, when it is detected that the resource usage of the target server meets the resource adjustment condition, the initial node number is updated to the target node number according to the current resource usage demand;

[0151] S3, when a reference server is determined from the candidate server cluster according to resource occupation states corresponding to each of the plurality of candidate servers included in the candidate server cluster, determining at least one reference execution node allocated to the reference server according to a difference in the number of target nodes and the number of initial nodes;

[0152] S4, sending the test script to at least one reference execution node through a target communication port between the reference server and at least one reference execution node, wherein the reference execution node is used to execute the test task according to the test script.

[0153] Optionally, in the embodiments of the present application, the term "module" or "unit" refers to a computer program or a part of a computer program with a predetermined function, and works together with other related parts to achieve a predetermined goal, and can be implemented in whole or in part by using software, hardware (such as processing circuits or memories), or a combination thereof. Similarly, a processor (or multiple processors or memories) can be used to implement one or more modules or units. In addition, each module or unit can be part of an overall module or unit that includes the function of the module or unit.

[0154] Optionally, in this embodiment, a person of ordinary skill in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing hardware related to the terminal device through a program, and the program may be stored in a computer-readable storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0155] If the integrated units in the above embodiments are implemented in the form of software functional units and sold or used as independent products, they can be stored in the above computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling one or more computer devices (which may be personal computers, servers, or network devices, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application.

[0156] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0157] In the several embodiments provided in the present application, it should be understood that the disclosed client can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0158] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0159] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0160] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A performance testing method, characterized in that: include: Determining the initial number of initial execution nodes for executing the test task according to the task description information matching the test task; During the process of executing the test task by the initial execution nodes according to the initial node quantity, when it is detected that the resource usage of the target server meets the resource adjustment condition, the initial node quantity is updated to the target node quantity according to the current resource usage demand; In a case where a reference server is determined from the candidate server cluster according to resource occupation states corresponding to each of a plurality of candidate servers included in the candidate server cluster, at least one reference execution node allocated to the reference server is determined according to a difference in the number of the target nodes and the number of the initial nodes; The test script is sent to at least one of the reference execution nodes through a target communication port between the reference server and at least one of the reference execution nodes, wherein the reference execution node is used to execute a test task according to the test script.

2. The method according to claim 1, characterized in that Before the initial number of nodes is updated to the target number of nodes according to the current resource usage demand, the method includes: The initial execution node executes the test task according to the test resources applied for by the target server; When it is detected that the current resource usage demand exceeds the maximum resource amount that can be applied for the target server, and the resource application trend in the historical time period is monitored to be an increasing trend, the expanded resource amount is determined based on the current resource usage demand, wherein the expanded resource amount is used to determine the number of target nodes.

3. The method according to claim 2, characterized in that The updating of the initial number of nodes to the target number of nodes according to the current resource usage demand includes: Obtaining the sum of the resource amounts applied for by the initial execution nodes that execute the test task at the target time, and the maximum resource amount that can be applied indicated by the resource usage of the target server at the target time; In the case where the sum of the applied resource amounts is greater than the maximum resource amount that can be applied, determining the resource application trend according to the historical resource usage demand amounts that match each monitoring moment in the historical time period; In the case where the growth coefficient matching the resource application trend is greater than the target growth coefficient, determining the product of the growth coefficient and the current resource usage demand as the expanded resource amount; The ratio of the maximum concurrency matching the extended resource amount to the standard concurrency matching the reference execution node is determined to be the target node number.

4. The method according to claim 2, characterized in that: Before determining at least one reference execution node allocated to the reference server according to the difference between the number of the target nodes and the number of the initial nodes, the method includes: Obtaining the resource occupancy status of each candidate server in the candidate server cluster at the current moment; At least one reference server is determined from the candidate server cluster according to the resource occupancy status and the expanded resource amount.

5. The method according to claim 4, characterized in that The step of determining at least one reference server from the candidate server cluster according to the resource occupancy status and the expanded resource amount includes: Acquire the performance indicators and resource occupancy status matching each of the candidate servers; Determining the expansion priority of each of the candidate servers according to the resource occupancy status and the weighted average value of the performance index matched with each of the candidate servers; The reference server is determined according to the expansion priority and the expansion resource amount.

6. The method according to claim 1, characterized in that After sending the test script to at least one of the reference execution nodes through the target communication port between the reference server and at least one of the reference execution nodes, the method further includes: When the test task for which the reference execution node applies for test resources to execute meets an execution end condition, determining that the reference execution node has finished executing the task; The test resource and the reference execution node are released.

7. The method according to claim 1, characterized in that The determining, according to the task description information matching the test task, the initial number of initial execution nodes for executing the test task comprises: Determine the maximum concurrent number of tests that matches the test task and the standard concurrent number that matches each initial execution node; The initial node number of the initial execution nodes is determined according to the ratio of the maximum concurrent number of the test to the standard concurrent number.

8. A performance testing device, characterized in that: include: A first determining unit, determining an initial node number of initial execution nodes for executing the test task according to task description information matching the test task; An updating unit, during the process of executing the test task by the initial execution nodes according to the initial node quantity, when detecting that the resource usage of the target server meets the resource adjustment condition, updates the initial node quantity to the target node quantity according to the current resource usage demand; A second determination unit, when determining a reference server from the candidate server cluster according to resource occupation states corresponding to each of a plurality of candidate servers included in the candidate server cluster, determines at least one reference execution node allocated to the reference server according to a difference in the number of target nodes and the number of initial nodes; An execution unit sends a test script to at least one of the reference execution nodes through a target communication port between the reference server and at least one of the reference execution nodes, wherein: The reference execution node is used to execute the test task according to the test script.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program is executed by a processor to perform the method described in any one of claims 1 to 7.

10. An electronic device, comprising: A memory and a processor, wherein the memory is used to store a computer program, and wherein the processor is used to execute the steps of the method according to any one of claims 1 to 7 when calling the computer program.

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