Cloud-based voice service full-link pressure measurement method and related equipment

Abstract

The invention discloses a cloud-based voice service full-link pressure measurement method and related equipment, and relates to the field of cloud testing, and the method comprises the steps: obtaining actual vehicle historical voice service use rule statistical information associated with a target cloud, the historical voice service use rule statistical information comprises statistical time period information, voice service calling vehicle number information and voice service calling average frequency information of each vehicle; controlling the simulation vehicle to establish connection with the target cloud; and controlling the simulation vehicle to perform voice service full-link pressure measurement on the target cloud based on the historical voice service use rule statistical information, and obtaining a test result.

Description

Technical Field

[0001] This specification relates to the field of cloud testing, and more specifically, to a cloud-based full-link stress testing method for voice services and related equipment. Background Art

[0002] With the popularity of smart cockpits, users are increasingly accustomed to calling vehicle services through voice interaction. At present, the voice services provided to smart cockpits include the implementation of voice commands in the car. However, the entire full-link test lacks a stress testing method. The stress testing of voice services on the market can often only support voice recognition and understanding, while the full-link test based on real vehicles lacks a stress testing link due to its high cost.

[0003] Based on this, it is necessary to propose a full-link stress testing method for cloud-based voice services. Summary of the invention

[0004] A series of simplified concepts are introduced in the Summary of the Invention section, which will be further described in detail in the Detailed Description of the Invention section. The Summary of the Invention section of this application does not mean to attempt to define the key features and essential technical features of the claimed technical solution, nor does it mean to attempt to determine the scope of protection of the claimed technical solution.

[0005] In the first aspect, the present application proposes a full-link stress testing method for a cloud-based voice service, comprising:

[0006] Obtaining historical voice service usage rule statistics of actual vehicles associated with the target cloud, wherein the historical voice service usage rule statistics include statistical time period information, number of vehicles calling voice services, and average number of times each vehicle calls voice services;

[0007] Control the simulated vehicle to establish a connection with the above-mentioned target cloud;

[0008] Control the above-mentioned simulated vehicle to perform full-link stress testing of the voice service on the above-mentioned target cloud based on the above-mentioned historical voice service usage rule statistics information, and obtain the test results.

[0009] In a feasible implementation, it also includes:

[0010] Collect all historical voice service usage information of the above target cloud;

[0011] Excluding the simulated vehicle voice service usage information from all the historical voice service usage information according to the identity information of the simulated vehicle, so as to obtain the historical voice service usage information of the actual vehicle;

[0012] Obtaining the time period of sporadic phenomena, wherein the time period of sporadic phenomena includes the time period of severe weather and the time period of major events;

[0013] The voice service usage information corresponding to the above-mentioned occasional phenomenon time period is removed from the above-mentioned actual vehicle historical voice service usage information, and regular statistics are performed to obtain the above-mentioned actual vehicle historical voice service usage regularity statistical information.

[0014] In a feasible implementation manner, the statistical time period information is determined based on traffic congestion time period information, and the time period lengths corresponding to the statistical time period end information are different.

[0015] In a feasible implementation, it also includes

[0016] Based on the above-mentioned vehicle historical voice service usage regularity statistics, determine the operating pressure and time regularity information of the target cloud;

[0017] Based on the above operation pressure and time rule information and the above historical voice service usage rule statistics, the voice service full-link stress test is performed on the above target cloud to reduce the impact of the above full-link stress test on the actual operation of the target cloud.

[0018] In a feasible implementation manner, the above-mentioned historical voice service usage pattern statistical information also includes vehicle model calling pattern information, network connection condition information and abnormal behavior information. The network connection condition information includes 4G connection conditions, 5G connection conditions and weak signal connection conditions. The above-mentioned abnormal behavior information includes a large number of service request behaviors, network jitter behaviors and disconnection and reconnection behaviors.

[0019] In a feasible implementation, it also includes:

[0020] Generate a voice service request based on the vehicle model calling rule information;

[0021] Randomly assign network conditions based on the above network connection conditions;

[0022] A large number of service request behaviors are introduced during peak hours, and network jitter and disconnection and reconnection behaviors are randomly inserted to perform additional stress testing on the entire link of voice services and obtain test results under additional conditions.

[0023] In a feasible implementation manner, the above test results include one or more of QPS, TPS, response time, memory and CPU usage.

[0024] In a second aspect, the present application proposes a cloud-based voice service full-link stress testing device, including:

[0025] An acquisition unit, used to acquire the historical voice service usage regularity statistics information of the actual vehicles associated with the target cloud, wherein the historical voice service usage regularity statistics information includes statistical time period information, number of vehicles calling the voice service information, and average number of times each vehicle calls the voice service information;

[0026] A control unit, used for controlling the simulated vehicle to establish a connection with the target cloud;

[0027] The test unit is used to control the above-mentioned simulated vehicle to perform full-link stress testing of the voice service on the above-mentioned target cloud based on the above-mentioned historical voice service usage rule statistical information, and obtain the test results.

[0028] In a third aspect, an electronic device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is used to implement the steps of the cloud-based voice service full-link stress testing method as described in any one of the first aspects above when executing the computer program stored in the memory.

[0029] In a fourth aspect, the present application further proposes a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the cloud-based full-link stress testing method for voice services according to any one of the first aspects is implemented.

[0030] In summary, the full-link stress testing method for voice services based on the cloud in the embodiment of the present application includes: obtaining the historical voice service usage regularity statistics of the actual vehicles associated with the target cloud, wherein the historical voice service usage regularity statistics include statistical time period information, the number of vehicles calling the voice service, and the average number of times each vehicle calls the voice service; controlling the simulated vehicle to establish a connection with the above-mentioned target cloud; controlling the above-mentioned simulated vehicle to perform full-link stress testing of the voice service on the above-mentioned target cloud based on the above-mentioned historical voice service usage regularity statistics, and obtaining the test results. The full-link stress testing method for voice services based on the cloud proposed in the embodiment of the present application makes the test closer to the actual usage by simulating the voice service request of the vehicle based on the historical usage regularity. This method covers the usage of different time periods, simulates a variety of network conditions and abnormal behaviors, and comprehensively evaluates the performance and stability of cloud services. Through automated simulation and real-time monitoring, test results can be quickly obtained to identify system bottlenecks and potential problems. By monitoring key performance indicators such as QPS, TPS, response time, memory and CPU usage, the performance and stability of cloud services can be comprehensively evaluated.

[0031] The cloud-based voice service full-link stress testing method proposed in this application, and other advantages, objectives and features of this application will be partially reflected in the following description, and will also be partially understood by technical personnel in this field through research and practice of this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present specification. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0033] Figure 1 A schematic diagram of the process of a full-link stress testing method for a cloud-based voice service provided in an embodiment of the present application;

[0034] Figure 2 A schematic diagram of the structure of a cloud-based voice service full-link stress testing device provided in an embodiment of the present application;

[0035] Figure 3 A schematic diagram of the structure of a cloud-based voice service full-link stress testing electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0036] The terms "first", "second", "third", "fourth", etc. (if any) 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 described herein can be implemented in an order other than that 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 that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The technical solutions 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, rather than all of the embodiments.

[0037] See also Figure 1 , which is a process diagram of a full-link stress testing method for a cloud-based voice service provided in an embodiment of the present application, which may specifically include:

[0038] S110, obtaining historical voice service usage rule statistics information of actual vehicles associated with the target cloud, wherein the historical voice service usage rule statistics information includes statistical time period information, number of vehicles calling voice service information, and average number of times each vehicle calls voice service information;

[0039] For example, statistics are collected on the use of voice services by actual vehicles in different time periods to simulate real usage scenarios. Historical data is collected and analyzed to determine the patterns of how vehicles use voice services in different time periods (such as hours, days, weeks, and months). For example, the frequency of use and number of requests in a certain time period. Statistics are collected on how many vehicles have called the voice service in each time period. Calculate the average number of times each vehicle calls the voice service in a certain time period.

[0040] For example, if the statistical time period is hours, 500 vehicles use the voice service every day, and each vehicle calls the voice service an average of 20 times a day.

[0041] S120, controlling the simulated vehicle to establish a connection with the target cloud;

[0042] For example, simulate the connection between real vehicles and cloud services to conduct comprehensive stress testing. Create virtual vehicles by writing scripts or using simulation tools. These vehicles can simulate the behavior of real vehicles and establish connections with the target cloud. Set connection parameters based on historical statistical data, such as connection frequency, number of concurrent connections, etc.

[0043] For example, when accessing the interface provided by the cloud service of the vehicle simulation environment through websocket, the parameter information required by the cloud service to establish a new simulated vehicle will be transmitted after the first link is established. The cloud service will construct an initial state cloud simulated vehicle based on the transmitted information and return a designated unique identification code for the vehicle to the local. At this point, a vehicle is simulated and constructed, and audio files can be transmitted through the link later to simulate voice interaction scenarios such as wake-up and recognition in the car.

[0044] S130. Control the simulated vehicle to perform full-link stress testing of the voice service on the target cloud based on the historical voice service usage rule statistics, and obtain the test results.

[0045] Exemplarily, the simulated vehicle is controlled to send voice service requests according to historical usage patterns. The wake-up scenario is implemented by passing in the wake-up audio, and the scenario in which the user enters a voice command after waking up is implemented by passing in a specific voice command such as "open the window". The number of requests for each vehicle during the test and the time interval between each request will be added with a small random offset based on the average value. These requests should simulate actual usage, including but not limited to request frequency, request content, and network conditions. During the stress test, the response time, success rate, resource usage (such as CPU, memory, bandwidth), etc. of the cloud are monitored and recorded in real time.

[0046] In summary, the cloud-based full-link stress testing method for voice services proposed in the embodiment of the present application simulates the vehicle's voice service requests based on historical usage patterns, making the test closer to actual usage. This method covers usage in different time periods, simulates a variety of network conditions and abnormal behaviors, and comprehensively evaluates the performance and stability of cloud services. Through automated simulation and real-time monitoring, test results can be quickly obtained to identify system bottlenecks and potential problems. By monitoring key performance indicators such as QPS, TPS, response time, memory, and CPU usage, the performance and stability of cloud services can be comprehensively evaluated.

[0047] In some examples, this also includes:

[0048] Collect all historical voice service usage information of the above target cloud;

[0049] Excluding the simulated vehicle voice service usage information from all the historical voice service usage information according to the identity information of the simulated vehicle, so as to obtain the historical voice service usage information of the actual vehicle;

[0050] Obtaining the time period of sporadic phenomena, wherein the time period of sporadic phenomena includes the time period of severe weather and the time period of major events;

[0051] The voice service usage information corresponding to the above-mentioned occasional phenomenon time period is removed from the above-mentioned actual vehicle historical voice service usage information, and regular statistics are performed to obtain the above-mentioned actual vehicle historical voice service usage regularity statistical information.

[0052] For example, extract all historical voice service usage records from the cloud logs and databases. These records should contain detailed information for each request, such as the timestamp of the request, the vehicle ID that issued the request, the type of request, and other relevant information. Ensure that all possible usage data is obtained to provide a comprehensive data foundation for subsequent analysis and simulation.

[0053] After obtaining all historical voice service usage information, it is necessary to identify and exclude the usage records of simulated vehicles based on the vehicle ID. This ensures that the dataset only contains usage information of actual vehicles, thereby preventing the data of simulated vehicles from interfering with the statistical results. By filtering out the records of simulated vehicles, we can obtain a more accurate historical usage dataset of actual vehicles.

[0054] Use the weather service API to query weather records from the past year to identify time periods when severe weather occurred. Also, use news data or specific event logs to record time periods of significant events. These time periods are marked as anomalies and may have a significant impact on the use of voice services.

[0055] In the above steps, the abnormal time periods have been marked. By comparing the timestamps, the voice service usage records in these time periods are removed from the data set. For example, if the timestamp of a request falls within a marked bad weather period, the record will be deleted.

[0056] After cleaning the data, regularity statistics are collected. For example, the average number of requests per hour, the average number of requests per vehicle, etc. Through these statistics, a model that reflects normal usage patterns can be generated. For example, the analysis results may show peak usage periods (such as 8 to 10 a.m. every day) and low usage periods (such as late at night).

[0057] In some examples, the statistical time period information is determined based on traffic congestion time period information, and the time period lengths corresponding to the statistical time period end information are different.

[0058] For example, the time period is not fixed. The time period information can be determined according to the traffic congestion time period. The more congested the time period, the shorter the time span. Instead, it is set according to the time occupied by the peak and valley values ​​of usage. For example, if the vehicle usage is the same from 11 pm to 5 am, then this is a time period. From 7 am to 9 am, there is a peak time period. This can lead to a test scenario similar to the following:

[0059]

[0060]

[0061] In some examples, this also includes:

[0062] Based on the above-mentioned vehicle historical voice service usage regularity statistics, determine the operating pressure and time regularity information of the target cloud;

[0063] Based on the above operation pressure and time rule information and the above historical voice service usage rule statistics, the voice service full-link stress test is performed on the above target cloud to reduce the impact of the above full-link stress test on the actual operation of the target cloud.

[0064] Exemplarily, the number of voice service requests in each time period (such as every hour) is extracted from the historical data, and the average number of requests R(t) and the peak number of requests Rmax(t) in each time period are calculated.

[0065] A time regularity model P(t) is established to describe the operating pressure of the target cloud in each time period. This model can be used to predict the operating pressure in any time period.

[0066] For example: P(t) = α*R(t) + β*Rmax(t)

[0067] Among them, α and β are weight parameters used to adjust the impact of average and peak requests.

[0068] According to the time law model P(t), the stress test load for each time period is determined. For example, in high-load time periods (such as peak hours), the stress test load is reduced to avoid interference with actual services; in low-load time periods, the stress test load can be appropriately increased.

[0069] Evenly distribute the requests of simulated vehicles in multiple time periods to avoid sending a large number of requests in a certain period. For example, if the model shows that 8 pm to 10 pm is a high-load period, the stress test requests during this period can be evenly distributed to the time periods before and after.

[0070] Extract the number of requests per hour from historical data. Assume that the average number of requests during a certain period of time (such as 8 to 9 a.m. every day) is 1,000 and the peak number of requests is 1,500.

[0071] Establish a time regularity model: P(t) = 0.7*R(t) + 0.3*Rmax(t); for 8 to 9 in the morning: P(8-9) = 0.7*1000 + 0.3*1500 = 1150

[0072] Perform full-link stress testing:

[0073] During the high load period (such as 8 to 9 in the morning), the stress test load is reduced, for example, reduced to 70% of the total load, that is, the stress test load is: Ltest(8-9)=0.7*1150=805.

[0074] During the low load period (such as 2pm to 4pm), increase the stress test load, for example, to 130% of the total load, that is, the stress test load is: Ltest(14-16)=1.3*Paverage

[0075] Among them, Paverage is the average operating pressure throughout the day.

[0076] In some examples, the above-mentioned historical voice service usage pattern statistical information also includes vehicle model calling pattern information, network connection condition information and abnormal behavior information. The network connection condition information includes 4G connection conditions, 5G connection conditions and weak signal connection conditions. The above-mentioned abnormal behavior information includes a large number of service request behaviors, network jitter behaviors and disconnection and reconnection behaviors.

[0077] For example, the voice service call frequency of different models in different time periods is counted. For example, statistics show that the average number of calls for model A from 8 to 9 a.m. every day is 20, while the average number of calls for model B from 6 to 7 p.m. is 15.

[0078] Network connection conditions for recording voice service requests, including 4G, 5G, and weak signal connection conditions. Statistics on request success rates and delays under different network conditions. For example, the request success rate for 4G networks is 95% and the delay is 50ms; the success rate for 5G networks is 99% and the delay is 10ms; the success rate under weak signal conditions is 70% and the delay is 200ms.

[0079] Record the occurrence of abnormal behaviors, including large numbers of service requests, network jitter, and disconnection and reconnection. Count the frequency and impact of abnormal behaviors. For example, network jitters occur randomly 5 times a day, each lasting 30 seconds; a large number of service requests occur once a week, lasting 10 minutes. Based on the statistical results, establish an abnormal behavior model.

[0080] Comprehensively analyze vehicle call patterns, network connection conditions and abnormal behavior information to establish an operating pressure and time pattern model. The model can be expressed as:

[0081]

[0082] in:

[0083] R i (t) is the average number of calls for vehicle type i in time period t.

[0084] N j (t) is the influencing factor of network condition j in time period t (such as request success rate, delay).

[0085] E k (t) is the occurrence of abnormal behavior k in time period t.

[0086] α i , β j and γ k is the corresponding weight parameter.

[0087] In some examples, this also includes:

[0088] Generate a voice service request based on the vehicle model calling rule information;

[0089] Randomly assign network conditions based on the above network connection conditions;

[0090] A large number of service request behaviors are introduced during peak hours, and network jitter and disconnection and reconnection behaviors are randomly inserted to perform additional stress testing on the entire link of voice services and obtain test results under additional conditions.

[0091] Exemplarily, all voice service usage records are extracted from the database, and a comprehensive statistical analysis is performed to obtain vehicle model calling patterns, network connection conditions, and abnormal behavior information.

[0092] Generate voice service requests that match actual usage every hour based on the vehicle model’s call pattern model. Randomly assign network conditions for each request based on the network connection condition model. Introduce abnormal behaviors for additional stress testing. For example, during the peak hours of 8 to 9 a.m., generate a large number of service requests every minute to test the processing capacity of cloud services. Insert network jitter and disconnection and reconnection behaviors in random time periods to test the stability of cloud services. Record the response time, success rate, and resource usage of cloud services during stress testing. Analyze test results to evaluate the performance and stability of cloud services.

[0093] The embodiments of this application cover various factors such as vehicle type, network, and abnormal behavior to ensure the comprehensiveness of simulation and testing. Through detailed data analysis and modeling, the simulation process is made as close to actual usage as possible to improve the accuracy of the test. By reasonably arranging the stress test load and time, it is ensured that the test process does not interfere with the actual service, thereby improving the effectiveness of the test.

[0094] In some examples, the test results include one or more of QPS, TPS, response time, memory, and CPU usage.

[0095] For example, during the stress test, the response time, success rate, resource usage (such as CPU, memory, bandwidth), etc. of the cloud service are recorded in real time. Based on the analysis of the test results, the performance of the cloud service under different conditions is evaluated. QPS (Queries Per Second) is the number of queries processed per second, which measures the processing capacity of the system under high load. TPS (Transactions Per Second) is the number of transactions processed per second. Evaluate the performance of the system when processing complex transactions. The response time is the time required from sending a request to receiving a response, reflecting the response speed of the system and user experience. Memory usage is the proportion of memory resources used by the system during operation. Evaluate the resource consumption and memory management efficiency of the system. CPU usage is the proportion of CPU resources used by the system during operation. Evaluate the processing capacity of the system and the utilization of CPU resources.

[0096] It is understood that the final result output can be displayed according to the time period and overall time of the test plan.

[0097] like Figure 2 As shown, this application proposes a cloud-based voice service full-link stress testing device, including:

[0098] The acquisition unit 21 is used to acquire the historical voice service usage regularity statistics information of the actual vehicles associated with the target cloud, wherein the historical voice service usage regularity statistics information includes the statistical time period information, the number of vehicles calling the voice service and the average number of times each vehicle calls the voice service;

[0099] A control unit 22, used to control the simulated vehicle to establish a connection with the target cloud;

[0100] The testing unit 23 is used to control the above-mentioned simulated vehicle to perform a full-link stress test of the voice service on the above-mentioned target cloud based on the above-mentioned historical voice service usage rule statistical information, and obtain the test results.

[0101] A cloud-based voice service full-link stress testing device can also perform the following method:

[0102] Collect all historical voice service usage information of the above target cloud;

[0103] Excluding the simulated vehicle voice service usage information from all the historical voice service usage information according to the identity information of the simulated vehicle, so as to obtain the historical voice service usage information of the actual vehicle;

[0104] Obtaining the time period of sporadic phenomena, wherein the time period of sporadic phenomena includes the time period of severe weather and the time period of major events;

[0105] The voice service usage information corresponding to the above-mentioned occasional phenomenon time period is removed from the above-mentioned actual vehicle historical voice service usage information, and regular statistics are performed to obtain the above-mentioned actual vehicle historical voice service usage regularity statistical information.

[0106] In some examples, the statistical time period information is determined based on traffic congestion time period information, and the time period lengths corresponding to the statistical time period end information are different.

[0107] In some examples, this also includes

[0108] Based on the above-mentioned vehicle historical voice service usage regularity statistics, determine the operating pressure and time regularity information of the target cloud;

[0109] Based on the above operation pressure and time rule information and the above historical voice service usage rule statistics, the voice service full-link stress test is performed on the above target cloud to reduce the impact of the above full-link stress test on the actual operation of the target cloud.

[0110] In some examples, the above-mentioned historical voice service usage pattern statistical information also includes vehicle model calling pattern information, network connection condition information and abnormal behavior information. The network connection condition information includes 4G connection conditions, 5G connection conditions and weak signal connection conditions. The above-mentioned abnormal behavior information includes a large number of service request behaviors, network jitter behaviors and disconnection and reconnection behaviors.

[0111] In some examples, this also includes:

[0112] Generate a voice service request based on the vehicle model calling rule information;

[0113] Randomly assign network conditions based on the above network connection conditions;

[0114] A large number of service request behaviors are introduced during peak hours, and network jitter and disconnection and reconnection behaviors are randomly inserted to perform additional stress testing on the entire link of voice services and obtain test results under additional conditions.

[0115] In some examples, the test results include one or more of QPS, TPS, response time, memory, and CPU usage.

[0116] like Figure 3 As shown, an embodiment of the present application also provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor. When the processor 320 executes the computer program 311, the steps of any method of the above-mentioned cloud-based voice service full-link stress testing are implemented.

[0117] Since the electronic device introduced in this embodiment is a device used to implement a cloud-based voice service full-link stress testing device in the embodiment of the present application, based on the method introduced in the embodiment of the present application, technical personnel in this field can understand the specific implementation mode of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of the present application is not introduced in detail here. As long as the equipment used by technical personnel in this field to implement the method in the embodiment of the present application is within the scope of protection of this application.

[0118] In the specific implementation process, when the computer program 311 is executed by the processor, it can achieve Figure 1 Any implementation manner in the corresponding embodiments.

[0119] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0120] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0121] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0122] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0123] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0124] An embodiment of the present application also provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device executes the process of full-link stress testing of cloud-based voice services in the corresponding embodiment.

[0125] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server or a data center that includes one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state drive (SSD)), etc.

[0126] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0127] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of 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 an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0128] 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.

[0129] 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.

[0130] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially 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, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0131] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A full-link stress testing method for voice services based on the cloud. It is characterized in that include: Obtaining historical voice service usage rule statistics of actual vehicles associated with the target cloud, wherein the historical voice service usage rule statistics include statistical time period information, number of vehicles calling voice services, and average number of times each vehicle calls voice services; Controlling the simulated vehicle to establish a connection with the target cloud; The simulated vehicle is controlled to perform a full-link stress test of the voice service on the target cloud based on the historical voice service usage rule statistical information, and a test result is obtained.

2. According to claim 1, the full-link stress testing method for cloud-based voice services, It is characterized in that Also includes: Collect all historical voice service usage information of the target cloud; Excluding the simulated vehicle voice service usage information from the entire historical voice service usage information according to the identity information of the simulated vehicle, so as to obtain the actual vehicle historical voice service usage information; Obtaining a time period for sporadic phenomena, wherein the time period for sporadic phenomena includes a time period for severe weather and a time period for major events; The voice service usage information corresponding to the occasional phenomenon time period is removed from the actual vehicle historical voice service usage information, and regular statistics are performed to obtain the actual vehicle historical voice service usage regularity statistical information.

3. According to claim 1, the full-link stress testing method for cloud-based voice services, It is characterized in that The statistical time period information is determined based on the traffic congestion time period information, and the time period lengths corresponding to the statistical time period end information are different.

4. The full-link stress testing method for cloud-based voice services according to claim 1, It is characterized in that Also includes: Based on the vehicle's historical voice service usage regularity statistics, determine the target cloud's operating pressure and time regularity information; Based on the operation pressure and time regularity information and the historical voice service usage regularity statistical information, a full-link stress test of the voice service is performed on the target cloud to reduce the impact of the full-link stress test on the actual operation of the target cloud.

5. The full-link stress testing method for cloud-based voice services according to claim 1, It is characterized in that The historical voice service usage pattern statistical information also includes vehicle model calling pattern information, network connection condition information and abnormal behavior information. The network connection condition information includes 4G connection conditions, 5G connection conditions and weak signal connection conditions. The abnormal behavior information includes a large number of service request behaviors, network jitter behaviors and disconnection and reconnection behaviors.

6. The full-link stress testing method for cloud-based voice services according to claim 5, It is characterized in that Also includes: Generate a voice service request based on the vehicle model calling rule information; Randomly assigning network conditions based on the network connection conditions; A large number of service request behaviors are introduced during peak hours, and network jitter and disconnection and reconnection behaviors are randomly inserted to perform additional stress testing on the entire link of voice services and obtain test results under additional conditions.

7. The full-link stress testing method for voice service based on cloud according to any one of claims 1 to 6, It is characterized in that The test results include one or more of QPS, TPS, response time, memory and CPU usage.

8. A full-link stress testing device for voice services based on the cloud. It is characterized in that include: An acquisition unit, used to acquire the historical voice service usage regularity statistics information of the actual vehicles associated with the target cloud, wherein the historical voice service usage regularity statistics information includes statistical time period information, number of vehicles calling the voice service information, and average number of times each vehicle calls the voice service information; A control unit, used for controlling the simulated vehicle to establish a connection with the target cloud; The testing unit is used to control the simulated vehicle to perform a full-link stress test of the voice service on the target cloud based on the historical voice service usage rule statistical information, and obtain the test results.

9. An electronic device, include: A memory and a processor, wherein the processor is used to implement the steps of the cloud-based voice service full-link stress testing method as described in any one of claims 1 to 7 when executing the computer program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by the processor, the steps of the cloud-based voice service full-link stress testing method as described in any one of claims 1 to 7 are implemented.

Images