Cloud host network performance testing method and device, computer equipment and storage medium

Abstract

This application relates to a method, apparatus, computer device, and storage medium for testing the network performance of a cloud server. The method includes: creating a cloud server based on configuration information; wherein the configuration information includes instance specifications and network settings; determining complex network traffic based on multiple sets of test data packets; performing network performance testing on the cloud server based on the complex network traffic to obtain performance data; and generating and displaying a performance test report based on the performance data. This application performs network performance testing on a cloud server based on complex network data determined by multiple sets of test data packets, which can better simulate the network performance of the cloud server under real load conditions. Simultaneously, it can automatically generate a visual performance test report, making the test results more intuitive and improving overall testing efficiency.

Description

Technical Field

[0001] This application relates to the field of cloud server performance testing technology, and in particular to a cloud server network performance testing method, apparatus, computer equipment, and storage medium. Background Technology

[0002] With the development of cloud computing technology, cloud hosting technology has emerged. A cloud server is an internet-based computing method that provides computing resources (such as CPU, memory, and hard drive) to users via the network. These resources are integrated on a cloud computing platform, forming a resource pool from which users can obtain the resources they need. Cloud servers maximize resource utilization and enable flexible management by dividing a physical server into multiple virtual servers, each with its own operating system, applications, and user permissions. Because cloud servers are provided to users over the network, their network performance is particularly important.

[0003] Traditional technologies for network performance testing of cloud servers typically target performance under simple background traffic conditions, which cannot fully simulate network performance under real load environments. Summary of the Invention

[0004] Therefore, it is necessary to provide a cloud host network performance testing method, apparatus, computer equipment, and storage medium that can fully simulate network performance under real load conditions to address the above-mentioned technical problems.

[0005] Firstly, this application provides a method for testing the network performance of a cloud server. The method includes: creating a cloud server based on configuration information; wherein the configuration information includes instance specifications and network settings; determining complex network traffic based on multiple sets of test data packets; performing network performance testing on the cloud server based on the complex network traffic to obtain performance data; and generating and displaying a performance test report based on the performance data.

[0006] In one embodiment, the step of creating a cloud host based on configuration information includes: responding to identity information and authorization information, and obtaining the configuration information if verification is successful; dynamically allocating resources of the cloud host based on the configuration information; and determining the operating system and applications of the cloud host based on the configuration information.

[0007] In one embodiment, the step of determining complex network traffic based on multiple sets of test data packets includes: normalizing the multiple sets of test data packets to obtain normalized data; performing chaotic mapping on the normalized data to obtain mapped data; and inputting the mapped data into a Gaussian mixture model to obtain the complex network traffic.

[0008] In one embodiment, prior to the step of determining complex network traffic based on multiple sets of test data packets, the method further includes: acquiring multiple sets of raw data packets; filtering out data packets with valid protocol fields from the multiple sets of raw data packets, and using them as test data packets.

[0009] In one embodiment, the step of performing network performance testing on the cloud host based on the complex network traffic includes: configuring a weight for each data packet in the complex network traffic; and sending the data packets to the cloud host based on the total packet sending time and the weight of each data packet to perform network performance testing on the cloud host.

[0010] In one embodiment, the step of sending the data packet to the cloud host based on the total packet sending time and the weight of each data packet includes: calculating the interval time for sending each data packet based on the total packet sending time and the weight of each data packet; determining whether the current data packet's sending time has reached its interval time within each scheduling cycle; if the interval time has not been reached, continuing to send the current data packet; if the interval time has been reached, sending the next data packet.

[0011] In one embodiment, the step of generating and displaying a performance test report based on the performance data includes: responding to a performance indicator selection instruction; wherein the performance indicator selection instruction is used to indicate the performance indicator to be evaluated; and processing the performance data according to the performance indicator selection instruction to generate and display the performance test report.

[0012] Secondly, this application also provides a cloud server network performance testing device. The device includes: a cloud server creation module for creating a cloud server based on configuration information; wherein the configuration information includes instance specifications and network settings; a network traffic generation module for determining complex network traffic based on multiple sets of test data packets; a network performance testing module for performing network performance tests on the cloud server based on the complex network traffic to obtain performance data; and a test report generation module for generating and displaying a performance test report based on the performance data.

[0013] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the above-described method.

[0014] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the above-described method.

[0015] The aforementioned cloud server network performance testing method, apparatus, computer equipment, and storage medium, after creating the cloud server based on configuration information, perform network performance testing on the cloud server using complex network traffic determined by multiple sets of test data packets, thereby obtaining corresponding performance data. Finally, a performance test report is generated and displayed based on the performance data. This application, by using complex network data determined by multiple sets of test data packets when testing the network performance of the cloud server, can better simulate the network performance of the cloud server under real load conditions. Simultaneously, it can automatically generate a visual performance test report, making the test results more intuitive and improving overall testing efficiency. Attached Figure Description

[0016] Figure 1 This is an application environment diagram of a cloud host network performance testing method in one embodiment;

[0017] Figure 2 This is a flowchart illustrating a cloud host network performance testing method in one embodiment;

[0018] Figure 3 This is a schematic diagram of the process for creating a cloud host in one embodiment;

[0019] Figure 4 This is a flowchart illustrating the process of determining complex network traffic in one embodiment;

[0020] Figure 5 This is a flowchart illustrating the process of determining complex network traffic in another embodiment;

[0021] Figure 6 This is a flowchart illustrating the network performance testing process in one embodiment.

[0022] Figure 7 This is a flowchart illustrating the network performance testing process in another embodiment;

[0023] Figure 8 This is a schematic diagram of the process for generating and displaying a performance test report in one embodiment;

[0024] Figure 9 This is a schematic diagram of a cloud host network performance testing device in one embodiment;

[0025] Figure 10 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0027] The cloud server network performance testing method provided in this application embodiment can be applied to, for example, Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or placed in the cloud or on other network servers. Server 104 creates a cloud host based on configuration information, determines complex network traffic based on multiple sets of test data packets, performs network performance testing on the cloud host based on the complex network traffic, obtains performance data, and finally generates and displays a performance test report based on the performance data. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. Portable wearable devices can include smartwatches, smart bracelets, head-mounted devices, etc. Server 104 can be implemented using a standalone server or a server cluster composed of multiple servers.

[0028] In one embodiment, such as Figure 2 As shown, a method for testing the network performance of a cloud server is provided, and this method is applied to... Figure 1 Taking server 104 as an example, the following steps are included:

[0029] Step S110: Create a cloud host based on the configuration information.

[0030] Specifically, when creating a cloud host, server 104 first obtains the configuration information input by the user from terminal 102. After obtaining the configuration information, server 104 creates a cloud host of the corresponding type based on the data in the configuration information. The configuration information includes instance specifications and network settings. Instance specifications include the cloud host's hardware resources such as CPU, memory, and hard disk, while network settings include network resources such as network bandwidth, IP address, and network protocols. Cloud hosts with different configurations have different performance characteristics.

[0031] Step S120: Determine complex network traffic based on multiple sets of test data packets.

[0032] Specifically, during network testing, Server 104 determines complex network traffic based on multiple sets of test data packets to simulate various complex network traffic scenarios. The data packets in complex network traffic can include traffic of different sizes, types (such as TCP, UDP, ICMP, etc.), and directions to comprehensively test the performance of the cloud server under various network conditions. Furthermore, by adjusting parameters such as the sending rate, interval, and duration of data packets in complex network traffic, complex traffic conditions in a real network environment can be further simulated.

[0033] Step S130: Perform network performance testing on the cloud host based on complex network traffic to obtain performance data.

[0034] Specifically, after Server 104 determines the cloud server to be tested, it will conduct actual network performance tests on the cloud server through complex network traffic. Network performance tests can include throughput tests (measuring the cloud server's ability to process data), latency tests (measuring the round-trip time of data packets), jitter tests (assessing changes in network latency), etc. Through network performance tests, performance data of the cloud server under different network traffic conditions can be obtained. Performance data includes key indicators such as throughput, latency, data transmission speed, and packet loss rate.

[0035] Step S140: Generate and display a performance test report based on the performance data.

[0036] Specifically, Server 104 generates and displays performance test reports by processing, analyzing, and designing visualization charts based on the performance data obtained from network performance tests. This allows users to more intuitively understand the network performance of the cloud server. Understandably, the performance test report includes information such as: test objective, test environment, test steps, test data, and test result analysis.

[0037] The aforementioned cloud server network performance testing method, after creating the cloud server based on configuration information, performs network performance testing on the cloud server using complex network traffic determined by multiple sets of test data packets, thereby obtaining corresponding performance data. Finally, a performance test report is generated and displayed based on the performance data. This application uses complex network data determined by multiple sets of test data packets when testing the network performance of the cloud server, which can better simulate the network performance of the cloud server under real load conditions. Furthermore, compared to using multiple different testing tools and settings to test different performance indicators, this application can obtain multiple performance indicators at once, thereby comprehensively evaluating the performance of the cloud server and avoiding the need to switch between different testing tools multiple times, thus improving testing efficiency. In addition, the automatic generation of a visual performance test report makes the test results more intuitive.

[0038] In one embodiment, such as Figure 3 As shown, step S110, the step of creating a cloud host based on configuration information, includes:

[0039] Step S111: Respond to identity information and authorization information, and obtain configuration information if verification is successful.

[0040] Specifically, during the cloud host creation process, server 104 first obtains the user's submitted identity and authorization information. Identity information may include username, password, or other authentication information (such as fingerprint or facial recognition). After successful identity verification, the user's submitted authorization information also needs to be verified. Only authorized users can create and manage cloud hosts; unauthorized users have no permission to log in. Authorization information may include specific authorization codes, API keys, or other forms of permission proof. Once both identity and authorization information are successfully verified, server 104 can obtain the user-input configuration information to create the appropriate type of cloud host based on that configuration.

[0041] Step S112: Dynamically allocate resources for the cloud host based on the configuration information.

[0042] Specifically, after obtaining the configuration information, server 104 dynamically allocates resources to the created cloud host based on the user request in the configuration information and the current resource status of the cloud platform. This dynamic allocation process includes the allocation of computing, storage, and network resources. For example, server 104 can select suitable computing nodes, storage devices, and network devices from the resource pool and configure corresponding network settings (such as IP address, subnet mask, etc.) for the cloud host.

[0043] Step S113: Determine the operating system and applications of the cloud host based on the configuration information.

[0044] Specifically, after obtaining the configuration information, server 104 will select the corresponding operating system and applications from the image library based on that information. The image library contains images of multiple operating system versions, such as Ubuntu, CentOS, and Windows Server, allowing users to choose and configure according to their needs. The image library also contains images of various applications, such as web servers and databases, facilitating rapid application deployment and startup, and reducing the time spent on manual installation and configuration. Once the operating system and applications for the cloud host are determined, the corresponding operating system and application images will be deployed to the cloud host with allocated resources, thus completing the creation of the cloud host.

[0045] In one embodiment, such as Figure 4 As shown, step S120, the step of determining complex network traffic based on multiple sets of test data packets, includes:

[0046] Step S121: Normalize multiple sets of test data packets to obtain normalized data.

[0047] Specifically, when determining complex network traffic, server 104 first obtains multiple sets of test data packets from the live network. These data packets have different network traffic characteristics, such as protocol type, packet size, and transmission rate. These multiple sets of test data packets can be denoted as set P. Each element in set P represents a complete test data packet. To make the tested network traffic more consistent with real-world network conditions, multiple sets of test data packets are normalized, that is, set P is normalized, to obtain normalized data. , Normalization can be achieved through min-max normalization or Z-score normalization. Normalized data will fall within a uniform numerical range after normalization, which facilitates subsequent data processing.

[0048] Step S122: Perform chaotic mapping on the normalized data to obtain mapped data.

[0049] Specifically, after obtaining the normalized data, server 104 performs chaotic mapping on the normalized data to extract the nonlinear features, thereby obtaining the mapped data. Chaotic mapping can employ Cubic mapping, Logistic mapping, Henon mapping, etc. In some embodiments, Cubic mapping is used, and the mapped data is denoted as P. i+1 , .

[0050] Step S123: Input the mapping data into the Gaussian mixture model to obtain the complex network traffic.

[0051] Specifically, after obtaining the mapping data, server 104 inputs the mapping data into the Gaussian Mixture Model (GMM) to ultimately obtain the complex network traffic. The Gaussian Mixture Model (GMM) is a statistical model used to represent a mixture of probability distributions composed of multiple Gaussian distributions. In the complex network traffic generation of this application, the GMM can be used to fit the distribution characteristics of network traffic. Through the probability distribution output by the model, the dynamic changes and potential characteristics of the network traffic can be determined.

[0052] A concrete example of generating complex network traffic using a Gaussian mixture model is shown below: Given K Gaussian distributions, each data packet in the mapped data is represented by a multivariate Gaussian distribution with a mean of [value missing]. covariance matrix Its weight is ϕ k For the i-th data packet, select a component k from K Gaussian distributions, and then take the data x from the multivariate Gaussian distribution of the selected Gaussian component k.

[0053]

[0054] The multivariate Gaussian distribution can be represented as:

[0055]

[0056] in, This represents the probability density of the generated i-th data packet. is the feature vector of the data packet, and D is the feature dimension of the data packet.

[0057] In one embodiment, such as Figure 5 As shown, before the step of determining complex network traffic based on multiple sets of test data packets in step S120, the cloud host network performance testing method also includes:

[0058] Step S124: Obtain multiple sets of raw data packets;

[0059] Step S125: Select data packets with valid protocol fields from multiple sets of raw data packets and use them as test data packets.

[0060] Specifically, in this embodiment, when filtering test data packets, multiple sets of raw data packets are first captured or collected from the network environment. These raw data packets may come from different network nodes, different time periods, or be based on different network protocols. After obtaining multiple sets of raw data packets, the protocol fields of these data packets need to be checked to ensure that they conform to preset protocol specifications. When checking the validity of protocol fields, each field of the data packet is checked for validity according to specific protocol specifications (such as IP, TCP, UDP, etc.). For example, checking whether the IP address is valid, whether the port number is within a reasonable range, and whether the verification is correct. When the protocol fields of the data packet are valid, it is used as a test data packet to generate complex network traffic. When the protocol fields of the data packet are invalid, the corresponding data packet is discarded.

[0061] In one embodiment, such as Figure 6 As shown, step S130, which involves performing network performance testing on the cloud host based on complex network traffic, includes:

[0062] Step S131: Configure a weight for each data packet in the complex network traffic.

[0063] Specifically, in this embodiment, when scheduling the transmission of complex network traffic, a weight is first configured for each data packet in the complex network traffic. When configuring the weight, the weight allocation standard for each data packet can be determined based on the characteristics of the network traffic (such as the importance of the protocol, the priority of the data packet, etc.). For example, data packets for critical services can be assigned a higher weight; while data packets for non-critical services or low priority can be assigned a lower weight.

[0064] Step S132: Send data packets to the cloud host based on the total packet sending time and the weight of each data packet to perform network performance testing on the cloud host.

[0065] Specifically, server 104 determines the total packet transmission time based on test requirements and network conditions. This total transmission time should be sufficiently long to fully reflect the network performance of the cloud host. Then, a packet transmission plan is formulated based on the weight of each packet and the total transmission time. Within the total transmission time, packets are sent to the cloud host according to the plan, ensuring that the transmission order, intervals, and quantity of packets meet the test requirements. During packet transmission, monitoring tools are used to record the cloud host's network performance data in real time, thus completing the network performance test of the cloud host.

[0066] In one embodiment, such as Figure 7 As shown, step S132, which involves sending data packets to the cloud host based on the total packet sending time and the weight of each data packet, includes:

[0067] Step S133: Calculate the interval for sending each data packet based on the total packet sending time and the weight of each data packet.

[0068] Specifically, during the process of sending data packets to the cloud host, the interval for sending each data packet is first calculated based on the total packet sending time and the weight of each data packet. For example, suppose there are m data packets, and each data packet i has a weight. At this point, the sum of the weights of all data packets is W:

[0069]

[0070] Based on the weighted sum W and the total packet sending time T 总 The interval t between the transmission of each data packet can then be calculated. i :

[0071]

[0072] The greater the weight of a data packet, the longer the interval between data packet transmissions. This means that data packets with higher weights will have more opportunities to be transmitted within the total transmission time, thus reflecting their importance in the test.

[0073] Step S134: Within each scheduling cycle, determine whether the current data packet transmission time has reached its interval.

[0074] Specifically, the scheduler is configured to maintain a task list Q for sending current data packets and a counter for each data packet. During each scheduling cycle, the scheduler checks the current tasks. counter Has the interval for sending packets been reached? .

[0075] In step S135, if the interval time has not been reached, continue sending the current data packet; if the interval time has been reached, send the next data packet.

[0076] Specifically, if Less than This indicates that the current data packet has not been sent within its interval, therefore the data packet will continue to be sent. Greater than or equal to If the current data packet's transmission time has reached its interval, then the next data packet is sent. By repeating the above steps, all data packets in complex network traffic can be sent according to plan. This method ensures that more important data packets receive more frequent transmission opportunities, while also guaranteeing that all data packets are reasonably allocated to the network within the specified total transmission time. This method of sending network traffic is particularly suitable for scenarios requiring balanced resource allocation and priority management. It is frequently used in task scheduling in cloud computing environments and is more in line with the actual usage scenarios of cloud host network traffic.

[0077] In one embodiment, such as Figure 8 As shown, step S140, which involves generating and displaying a performance test report based on performance data, includes:

[0078] Step S141, in response to the performance metric selection instruction.

[0079] Specifically, the user can send a performance metric selection command to the server 104 through the terminal 102. The performance metric selection command is used to indicate the performance metrics that need to be evaluated, and the user can select to evaluate one or more performance metrics. After receiving the performance metric selection command, the server 104 can determine the performance metrics that the user needs to generate and display.

[0080] Step S142: Process the performance data according to the performance index selection instruction to generate and display a performance test report.

[0081] Specifically, after receiving the performance metric selection instruction, server 104 processes the collected performance data according to the required performance metrics to be evaluated, thereby generating and displaying the final performance test report to the user. It is understandable that when performing network performance tests on cloud hosts based on complex network traffic, the performance metric selection instruction will also determine the type of network test to be performed, and a performance test report will be generated and displayed based on the obtained performance data.

[0082] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0083] Based on the same inventive concept, this application also provides a cloud server network performance testing device for implementing the cloud server network performance testing method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more embodiments of the cloud server network performance testing device provided below can be found in the limitations of the cloud server network performance testing method described above, and will not be repeated here.

[0084] In one embodiment, such as Figure 9 As shown, a cloud server network performance testing device is provided, including: a cloud server creation module 210, a network traffic generation module 220, a network performance testing module 230, and a test report generation module 240, wherein:

[0085] The cloud server creation module 210 is used to create cloud servers based on configuration information; the configuration information includes: instance specifications and network settings;

[0086] The network traffic generation module 220 is used to determine complex network traffic based on multiple sets of test data packets;

[0087] The network performance testing module 230 is used to perform network performance testing on cloud hosts based on complex network traffic and obtain performance data.

[0088] Test report generation module 240 is used to generate and display performance test reports based on performance data.

[0089] In one embodiment, the cloud host creation module 210 is further configured to respond to identity information and authorization information, and obtain the configuration information upon successful verification; dynamically allocate the resources of the cloud host based on the configuration information; and determine the operating system and applications of the cloud host based on the configuration information.

[0090] In one embodiment, the network traffic generation module 220 is further configured to normalize multiple sets of test data packets to obtain normalized data; perform chaotic mapping on the normalized data to obtain mapped data; and input the mapped data into a Gaussian mixture model to obtain the complex network traffic.

[0091] In one embodiment, the network traffic generation module 220 is further configured to acquire multiple sets of raw data packets; filter out data packets with valid protocol fields from the multiple sets of raw data packets, and use them as test data packets.

[0092] In one embodiment, the network performance testing module 230 is further configured to configure a weight for each data packet in the complex network traffic; and send the data packets to the cloud host based on the total packet sending time and the weight of each data packet to perform network performance testing on the cloud host.

[0093] In one embodiment, the network performance testing module 230 is further configured to calculate the interval time for sending each data packet based on the total packet sending time and the weight of each data packet; within each scheduling period, determine whether the sending time of the current data packet has reached its interval time; if it has not reached its interval time, continue sending the current data packet; if it has reached its interval time, send the next data packet.

[0094] In one embodiment, the test report generation module 240 is further configured to respond to a performance indicator selection instruction; wherein the performance indicator selection instruction is used to indicate the performance indicator to be evaluated; and to process the performance data according to the performance indicator selection instruction to generate and display the performance test report.

[0095] Each module in the aforementioned cloud server network performance testing device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0096] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 10As shown, this computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a cloud host network performance testing method.

[0097] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0098] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0099] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-described method embodiments.

[0100] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0101] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0102] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for testing the network performance of a cloud server, characterized in that, The method includes: A cloud server is created based on configuration information; wherein, the configuration information includes: instance specifications and network settings; Determining complex network traffic based on multiple sets of test data packets includes: normalizing the multiple sets of test data packets to obtain normalized data; performing chaotic mapping on the normalized data to obtain mapped data; and inputting the mapped data into a Gaussian mixture model to obtain the complex network traffic. The cloud host is subjected to network performance testing based on the complex network traffic to obtain performance data, including: configuring a weight for each data packet in the complex network traffic; calculating the transmission interval for each data packet based on the total transmission time and the weight of each data packet; within each scheduling cycle, determining whether the transmission time of the current data packet has reached its interval; if it has not reached its interval, continuing to transmit the current data packet; if it has reached its interval, transmitting the next data packet; wherein, the transmission interval for each data packet is... , , Let T be the weight of packet i, W be the sum of the weights of all packets, and T be the weight of packet i. 总 The total packet transmission time is m, where m is the number of data packets. A performance test report is generated and displayed based on the performance data.

2. The cloud server network performance testing method according to claim 1, characterized in that, The steps for creating a cloud host based on configuration information include: In response to identity and authorization information, and upon successful verification, the configuration information is obtained. The cloud host's resources are dynamically allocated based on the configuration information. The operating system and applications of the cloud host are determined based on the configuration information.

3. The cloud server network performance testing method according to claim 1, characterized in that, Before the step of determining complex network traffic based on multiple sets of test data packets, the method further includes: Obtain multiple sets of raw data packets; Select data packets with valid protocol fields from multiple sets of raw data packets and use them as test data packets.

4. The cloud server network performance testing method according to claim 1, characterized in that, The step of generating and displaying a performance test report based on the performance data includes: Responding to a performance metric selection instruction; wherein the performance metric selection instruction is used to indicate the performance metric that needs to be evaluated; The performance data is processed according to the performance indicator selection instructions to generate and display the performance test report.

5. A cloud server network performance testing device, characterized in that, The device includes: The cloud server creation module is used to create cloud servers based on configuration information; wherein, the configuration information includes: instance specifications and network settings; A network traffic generation module is used to determine complex network traffic based on multiple sets of test data packets, including: normalizing the multiple sets of test data packets to obtain normalized data; performing chaotic mapping on the normalized data to obtain mapped data; and inputting the mapped data into a Gaussian mixture model to obtain the complex network traffic. The network performance testing module is used to perform network performance testing on the cloud host based on the complex network traffic to obtain performance data. This includes: configuring a weight for each data packet in the complex network traffic; calculating the transmission interval for each data packet based on the total transmission time and the weight of each data packet; determining whether the transmission time of the current data packet has reached its interval within each scheduling cycle; if not, continuing to transmit the current data packet; if the interval has been reached, transmitting the next data packet; wherein the transmission interval for each data packet is... , , Let T be the weight of packet i, W be the sum of the weights of all packets, and T be the weight of packet i. 总 The total packet transmission time is m, where m is the number of data packets. The test report generation module is used to generate and display a performance test report based on the performance data.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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