Network quality evaluation method and device, electronic equipment and computer program product
By subdividing the network request scenarios and replenishing the missing data using the quantile values and tail mean of historical data, the data missing problem caused by network request failure is solved, and the accuracy of network quality evaluation is improved.
Patent Information
- Application Number
- CN202510933653.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-07
- Publication Date
- 2025-08-15
AI Technical Summary
In the scenario where network request fails, since the data does not arrive at the server, some indicators cannot be collected, which affects the accuracy of network quality evaluation.
By subdividing the scene types of network requests, obtain preset network quality evaluation indicators for missing data, and use indicators in historical network requests to supplement data, including supplementing missing data using preset quantile values and tail data mean.
It improves the accuracy of network quality evaluation, solves the problem of data missing due to access failure, and ensures that the relevant data of the failed requests are reflected in the evaluation.
Smart Images
Figure CN120499043A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the field of Internet technology, and in particular to a network quality assessment method, a network quality assessment device, an electronic device, and a computer program product. Background Art
[0002] During client development, evaluating network quality is a common requirement. This involves collecting network-related metrics and combining them to generate network quality assessment results.
[0003] However, in the scenario of network request failure, since the network request data may not reach the server, some indicators may not be collected and many indicators cannot be calculated, which will affect the accuracy of network quality assessment.
[0004] In view of this, there is an urgent need in this field for a network quality assessment method that can solve the problem of inaccurate network quality assessment caused by data missing after access failure.
[0005] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute prior art known to ordinary technicians in the field. Summary of the Invention
[0006] The purpose of the present disclosure is to provide a network quality assessment method, a network quality assessment device, an electronic device and a computer program product, thereby at least to a certain extent being able to solve the problem of inaccurate network quality assessment caused by missing data after access failure.
[0007] According to a first aspect of the present disclosure, a network quality assessment method is provided, comprising:
[0008] Get the scenario type where the network request access fails;
[0009] According to the scenario type, obtaining missing data corresponding to a preset network quality assessment indicator in the scenario type;
[0010] The missing data is supplemented according to the network quality evaluation index in the historical network request, and the network quality evaluation is performed according to the supplemented network quality evaluation index.
[0011] In an exemplary embodiment of the present disclosure, obtaining the scenario type of network request access failure includes:
[0012] The network request is divided into multiple network request stages, and the scenario type of network request access failure is determined according to the multiple network request stages.
[0013] In an exemplary embodiment of the present disclosure, the network request phase includes a connection establishment phase, a response phase, and a response body data transmission phase, and the scenario types of network request access failure include a connection establishment failure scenario, a response failure scenario, and a response body data transmission failure scenario.
[0014] In an exemplary embodiment of the present disclosure, the network quality evaluation indicators include first packet response time, download speed and packet loss rate.
[0015] In an exemplary embodiment of the present disclosure, supplementing the missing data according to the network quality evaluation indicator in the historical network request includes:
[0016] Determining, based on the evaluation requirements of the missing data in the scenario type, a corresponding preset percentile value in the network quality evaluation indicator of the historical network request;
[0017] The missing data is supplemented according to the indicator data corresponding to the preset quantile value.
[0018] In an exemplary embodiment of the present disclosure, supplementing the missing data according to the network quality evaluation indicator in the historical network request includes:
[0019] Determining, based on the evaluation requirements of the missing data in the scenario type, a corresponding tail data ratio in the network quality evaluation index of the historical network requests;
[0020] A tail data mean of the network quality evaluation index of the historical network requests is obtained according to the tail data ratio, and the missing data is supplemented according to the tail data mean.
[0021] In an exemplary embodiment of the present disclosure, supplementing the missing data according to the network quality evaluation indicator in the historical network request includes:
[0022] Determine the reference time period corresponding to the current time period according to the preset period;
[0023] The missing data of the current time period is supplemented according to the network quality evaluation index in the historical network requests within the reference time period.
[0024] According to a second aspect of the present disclosure, there is provided a network quality assessment device, comprising:
[0025] A scene type acquisition module is configured to execute acquisition of the scene type for which the network request access fails;
[0026] A missing data acquisition module is configured to execute, according to the scenario type, acquiring missing data corresponding to a preset network quality assessment indicator in the scenario type;
[0027] The network quality evaluation module is configured to supplement the missing data according to the network quality evaluation index in the historical network request, and perform network quality evaluation according to the supplemented network quality evaluation index.
[0028] In an exemplary embodiment of the present disclosure, the scene type acquisition module includes:
[0029] The network request stage division unit is configured to execute the division of the network request into multiple network request stages, and determine the scenario type of network request access failure according to the multiple network request stages.
[0030] In an exemplary embodiment of the present disclosure, the network quality assessment module includes:
[0031] a preset percentile value determining unit configured to determine a corresponding preset percentile value in the network quality evaluation indicator of the historical network request according to the evaluation requirement of the missing data in the scenario type;
[0032] The preset percentile value supplement unit is configured to supplement the missing data according to the indicator data corresponding to the preset percentile value.
[0033] In an exemplary embodiment of the present disclosure, the network quality assessment module further includes:
[0034] a tail data ratio determining unit configured to determine a tail data ratio corresponding to a network quality evaluation indicator of the historical network request according to an evaluation requirement of the missing data in the scenario type;
[0035] The tail data mean value supplement unit is configured to obtain the tail data mean value of the network quality evaluation index of the historical network requests according to the tail data ratio, and supplement the missing data according to the tail data mean value.
[0036] In an exemplary embodiment of the present disclosure, the network quality assessment module further includes:
[0037] A reference time period determining unit, configured to determine a reference time period corresponding to a current time period according to a preset period;
[0038] The reference time period data supplement unit is configured to supplement the missing data of the current time period according to the network quality evaluation index in the historical network request within the reference time period.
[0039] According to a third aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement any one of the above-mentioned network quality assessment methods.
[0040] According to a fourth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any one of the above-mentioned network quality assessment methods.
[0041] The exemplary embodiments of the present disclosure may have the following beneficial effects:
[0042] In the network quality assessment method of the example implementation method of the present disclosure, by obtaining the scenario type of network request access failure, obtaining the missing data corresponding to the preset network quality assessment indicator in the scenario type according to the scenario type, then supplementing the missing data according to the network quality assessment indicator in the historical network request, and performing network quality assessment based on the supplemented network quality assessment indicator. The network quality assessment method of the example implementation method of the present disclosure, by subdividing different network request failure scenarios, evaluates the data missing situation of each indicator in different scenarios, and supplements these missing data, ensures that when a network request fails, the relevant data of the failed request can be reflected in the network quality assessment, solves the problem of inaccurate network quality assessment caused by missing data after access failure, and further improves the accuracy of the final network quality assessment.
[0043] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS
[0044] The accompanying drawings are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification, are used to explain the principles of the present disclosure. Obviously, the drawings described below are only some embodiments of the present disclosure, and those skilled in the art can derive other drawings based on these drawings without inventive effort.
[0045] Figure 1 A schematic diagram showing a flow chart of a network quality assessment method according to an exemplary embodiment of the present disclosure;
[0046] Figure 2 A schematic diagram of a process for supplementing missing data using preset quantile values in historical data according to an exemplary embodiment of the present disclosure is shown;
[0047] Figure 3 A schematic diagram of a process for supplementing missing data by using the tail mean in historical data according to an exemplary embodiment of the present disclosure is shown;
[0048] Figure 4 A block diagram showing a network quality assessment apparatus according to an exemplary embodiment of the present disclosure is provided;
[0049] Figure 5 A schematic structural diagram of a computer system suitable for implementing the electronic device according to the embodiment of the present disclosure is shown. DETAILED DESCRIPTION
[0050] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.
[0051] It should be noted that the terms "first," "second," and the like in the specification and claims of the present disclosure and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, such that the embodiments of the present disclosure described herein can be implemented in an order other than that illustrated or described herein.
[0052] The following example embodiments can be implemented in a variety of forms and should not be construed as being limited to the examples set forth herein; rather, these embodiments are provided so that the present disclosure will be more comprehensive and complete and will fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or that other methods, components, devices, steps, etc. may be employed. In other cases, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present disclosure.
[0053] In addition, the accompanying drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.
[0054] In some related embodiments, a single indicator can be used to evaluate network quality, such as request success or request failure. In this way, the single indicator can directly include information about request failure, without having to consider the problem of not being able to collect data indicators when the request fails, and without the need for further indicator optimization.
[0055] However, directly using indicators that can include network request failure information to evaluate network quality will have certain limitations and low accuracy. For example, the request success rate can indeed be included, but to more accurately evaluate network quality, it is necessary to combine other indicators that may be missing data when network request access fails.
[0056] In other related embodiments, in the event of a network request access failure, the current network quality assessment result can be directly reduced by a percentage. For example, if the missing indicator data caused by the network request access failure is not considered, the network quality assessment result is 80. When a network request access failure occurs, the current network quality assessment result is multiplied by 80%, that is, 80 * 80% = 64, to reduce the overall assessment result, thereby reflecting the impact of the request failure data on the result.
[0057] However, this approach can only roughly solve the problem of missing indicator data caused by failed network request access. It does not break down the causes of failure based on the failure scenario, nor does it analyze the data missing situation from the perspective of different indicators. The resulting accuracy improvement is very limited and may even lead to a decrease in accuracy.
[0058] Based on the above problems, this exemplary embodiment first provides a network quality assessment method. Figure 1 As shown, the above network quality assessment method may include the following steps:
[0059] Step S110: Obtain the scenario type in which the network request access fails.
[0060] Step S120: According to the scenario type, obtain missing data corresponding to the preset network quality assessment indicator in the scenario type.
[0061] Step S130: Supplement the missing data according to the network quality evaluation indicators in the historical network requests, and perform network quality evaluation according to the supplemented network quality evaluation indicators.
[0062] In the network quality assessment method of the example implementation method of the present disclosure, by obtaining the scenario type of network request access failure, obtaining the missing data corresponding to the preset network quality assessment indicator in the scenario type according to the scenario type, then supplementing the missing data according to the network quality assessment indicator in the historical network request, and performing network quality assessment based on the supplemented network quality assessment indicator. The network quality assessment method of the example implementation method of the present disclosure, by subdividing different network request failure scenarios, evaluates the data missing situation of each indicator in different scenarios, and supplements these missing data, ensures that when a network request fails, the relevant data of the failed request can be reflected in the network quality assessment, solves the problem of inaccurate network quality assessment caused by missing data after access failure, and further improves the accuracy of the final network quality assessment.
[0063] Next, combine Figures 2 to 3 The above steps of this exemplary embodiment are described in more detail.
[0064] In step S110 , the scenario type of the network access request failure is obtained.
[0065] In this example implementation, scenarios where network request access failure occurs can be divided into multiple types. By subdividing the scenarios where network request access failure occurs, the data missing status of each indicator in different scenarios can be further evaluated.
[0066] In this example implementation, a network request may be divided into multiple network request stages, and the scenario type of network request access failure may be determined based on the multiple network request stages.
[0067] For example, a network request can be divided into three phases: connection establishment, response, and response body data transfer. The performance of each phase directly impacts overall latency and user experience. The connection establishment phase establishes the network connection between the client and server; the response phase generates the response header after the server receives the request and returns it to the client; and the response body data transfer phase transmits the response body content.
[0068] The scenarios of network request access failure can be subdivided based on these three stages. For example, the types of network request access failure scenarios can include connection failure scenarios, response failure scenarios, and response body data transmission failure scenarios.
[0069] In step S120, according to the scenario type, missing data corresponding to the preset network quality assessment indicator in the scenario type is obtained.
[0070] In this example implementation, the preset network quality assessment indicators may include first packet response time, download speed, and packet loss rate. First packet response time refers to the time from when the client initiates a request to when the first data packet is received back from the server. Download speed refers to the amount of data transmitted from the server to the client per unit time. Packet loss rate refers to the ratio of data packets lost during transmission to the total number of packets sent.
[0071] In this example implementation, the missing conditions of the adopted network quality evaluation indicators in the above scenarios can be analyzed. For example, the missing conditions of data in the scenarios of connection failure, response failure, and response body data transmission failure are shown in Table 1:
[0072] Connection Failure Scenarios Response failure scenarios Response body data transmission failure scenario First packet response time Missing Missing Normal acquisition Download speed Missing Missing Missing Packet loss rate Missing Normal acquisition Normal acquisition
[0073] Table 1
[0074] By analyzing the missing data of network quality assessment indicators in different scenarios, we can analyze the missing data from the perspective of different indicators based on the specific failure scenario, making the network quality assessment more comprehensive.
[0075] In step S130, the missing data is supplemented according to the network quality evaluation index in the historical network request, and the network quality evaluation is performed according to the supplemented network quality evaluation index.
[0076] After determining the missing conditions of network quality assessment indicators in different scenarios, the relevant missing data can be supplemented, and network quality assessment can be performed based on the supplemented network quality assessment indicators.
[0077] In this example implementation, missing data can be supplemented by preset quantile values in historical data, such as Figure 2 As shown in the figure, the missing data can be supplemented based on the network quality evaluation indicators in the historical network requests. Specifically, the following steps can be included:
[0078] Step S210: Determine the corresponding preset percentile value in the network quality evaluation index of the historical network requests according to the evaluation requirements of the missing data in the scenario type.
[0079] Based on the evaluation requirements for missing data in the scenario type, different quantiles can be selected from the network quality evaluation indicators of historical network requests to supplement missing data. For example, if the evaluation requirements are strict, the p1, p5, and p10 quantiles of the large-scale network requests can be used to supplement missing values for the connection failure scenario, response failure scenario, and response body data transmission failure scenario, respectively. If the evaluation requirements are more relaxed, the p5, p10, and p15 quantiles of the large-scale network requests can be used to supplement missing values for the connection failure scenario, response failure scenario, and response body data transmission failure scenario, respectively.
[0080] Step S220: Supplement the missing data according to the indicator data corresponding to the preset percentile value.
[0081] To address the problem of missing data in different scenarios, we use data from different percentiles of the market and, in combination with different scenarios, use actual data from different percentiles to supplement the missing data.
[0082] After determining the preset percentile value in the historical data, you can obtain the specific indicator data corresponding to the preset percentile value to supplement the missing data. For example, if the p1 percentile value of the first packet response time in a large-scale network request is 2000ms, 2000ms can be used as the first packet response time indicator corresponding to the connection failure scenario.
[0083] In this example implementation, the missing data can also be supplemented by the tail mean of the historical data, such as Figure 3 As shown in the figure, the missing data can be supplemented based on the network quality evaluation indicators in the historical network requests. Specifically, the following steps can be included:
[0084] Step S310: Determine the corresponding tail data ratio in the network quality evaluation index of the historical network requests according to the evaluation requirements of the missing data in the scenario type.
[0085] Step S320: Obtain the tail data mean of the network quality evaluation index of the historical network requests according to the tail data ratio, and supplement the missing data according to the tail data mean.
[0086] Depending on the evaluation requirements for missing data in the scenario type, the network quality evaluation indicators of historical network requests can be supplemented with different tail data means. For example, if the evaluation requirements are strict, the tail data means of 1%, 5%, and 10% of the large-scale network requests can be used to supplement missing values for the connection failure scenario, response failure scenario, and response body data transmission failure scenario, respectively. If the evaluation requirements are more relaxed, the tail data means of 5%, 10%, and 15% of the large-scale network requests can be used to supplement missing values for the connection failure scenario, response failure scenario, and response body data transmission failure scenario, respectively.
[0087] In this example implementation, a reference time period corresponding to the current time period may be determined according to a preset period, and missing data of the current time period may be supplemented based on network quality evaluation indicators in historical network requests within the reference time period.
[0088] Since the percentile values or the mean of the tail data are not fixed values but will be affected by weekends, the end of the month, holidays, etc., they can be dynamically updated according to the preset cycle. For example, with a daily cycle, historical data of the same time period within a day is obtained to supplement the missing data, so as to avoid the impact of periodic data on the evaluation results and further improve the accuracy of network quality assessment.
[0089] The supplemented network quality evaluation indicators are shown in Table 2:
[0090] Connection Failure Scenarios Response failure scenarios Response body data transmission failure scenario First packet response time 2000ms 2000ms Normal acquisition Download speed 0KB / s 5KB / s 10KB / s Packet loss rate 100％ Normal acquisition Normal acquisition
[0091] Table 2
[0092] In actual applications, the accuracy of network quality assessment of two groups of online users can be compared. One group uses the network quality assessment method in this example implementation as the experimental group, and the other group does not use the network quality assessment method in this example implementation as the control group. The final verification result shows that the accuracy of the experimental group is improved by about 2% relative to the control group.
[0093] It should be noted that although the steps of the method of the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all steps must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.
[0094] Furthermore, the present disclosure also provides a network quality assessment device. Figure 4 As shown, the network quality assessment device may include a scene type acquisition module 410, a missing data acquisition module 420, and a network quality assessment module 430.
[0095] The scenario type acquisition module 410 is configured to acquire the scenario type of the network access request failure;
[0096] The missing data acquisition module 420 is configured to acquire missing data corresponding to a preset network quality assessment indicator in a scenario type according to the scenario type;
[0097] The network quality evaluation module 430 is configured to supplement the missing data according to the network quality evaluation indicators in the historical network requests, and perform network quality evaluation according to the supplemented network quality evaluation indicators.
[0098] In some exemplary embodiments of the present disclosure, the scenario type acquisition module 410 may include a network request stage division unit configured to split the network request into multiple network request stages and determine the scenario type of the network request access failure based on the multiple network request stages.
[0099] In some exemplary embodiments of the present disclosure, the network quality assessment module 430 may include a preset percentile value determination unit and a preset percentile value supplementation unit.
[0100] a preset quantile value determining unit configured to determine a corresponding preset quantile value in a network quality evaluation indicator of historical network requests according to an evaluation requirement of missing data in a scenario type;
[0101] The preset percentile value supplement unit is configured to supplement the missing data according to the indicator data corresponding to the preset percentile value.
[0102] In some exemplary embodiments of the present disclosure, the network quality assessment module 430 may further include a tail data ratio determination unit and a tail data mean value supplementation unit.
[0103] a tail data ratio determination unit configured to determine a tail data ratio corresponding to a network quality evaluation indicator of a historical network request based on an evaluation requirement of missing data in a scenario type;
[0104] The tail data mean value supplement unit is configured to obtain the tail data mean value of the network quality evaluation index of the historical network requests according to the tail data ratio, and supplement the missing data according to the tail data mean value.
[0105] In some exemplary embodiments of the present disclosure, the network quality assessment module 430 may further include a reference time period determination unit and a reference time period data supplementation unit.
[0106] A reference time period determining unit, configured to determine a reference time period corresponding to a current time period according to a preset period;
[0107] The reference time period data supplement unit is configured to supplement the missing data of the current time period according to the network quality evaluation index in the historical network requests within the reference time period.
[0108] The specific details of each module / unit in the above network quality assessment device have been described in detail in the corresponding method embodiment part and will not be repeated here.
[0109] Figure 5 A schematic diagram of the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present disclosure is shown.
[0110] It should be noted that Figure 5 The computer system 500 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.
[0111] like Figure 5 As shown, computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage unit 508 into a random access memory (RAM) 503. Various programs and data required for system operation are also stored in RAM 503. CPU 501, ROM 502, and RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to bus 504.
[0112] The following components are connected to the I / O interface 505: an input section 506 including a keyboard, a mouse, and the like; an output section 507 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 508 including a hard disk; and a communication section 509 including a network interface card such as a LAN card or a modem. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 510 as needed, so that computer programs read therefrom can be installed into the storage section 508 as needed.
[0113] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 509, and / or installed from a removable medium 511. When the computer program is executed by the central processing unit (CPU) 501, various functions defined in the system of the present disclosure are performed.
[0114] The exemplary embodiments of the present disclosure further provide a computer program product, which includes a computer program, and when the computer program is executed by a processor, implements the above-mentioned network quality assessment method.
[0115] In one embodiment, a computer program product may be a tangible product containing a computer program, such as a computer-readable storage medium storing the computer program. The computer-readable storage medium may be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, including but not limited to random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory (Flash), mechanical hard disk drive (HDD), solid-state drive (SSD), and the like. Exemplarily, the computer program product may be implemented as a non-volatile storage medium storing the computer program, such as a read-only memory, NAND flash memory, and the like.
[0116] In one embodiment, the computer program product may be an intangible product containing a computer program. For example, the computer program product may be implemented as a virtual digital product, such as a digital file such as an executable file or installation package storing the computer program.
[0117] The code of the computer program can be written in one or more programming languages. Programming languages include C, Java, C++, etc. The program code can be executed entirely on the user computing device, partially on the user computing device, or as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device via any type of network, such as a local area network (LAN), a wide area network (WAN), etc., or can be connected to an external computing device (e.g., via an Internet connection provided by a carrier).
[0118] Computer programs can be carried or transmitted via electrical, magnetic, optical, electromagnetic, infrared, or other signals. Electronic devices can convert signals carrying computer programs into digital signals to run the computer programs. When the computer program runs on an electronic device, its code causes the electronic device to execute (more specifically, the processor of the electronic device to execute) the method steps of various exemplary embodiments of the present disclosure, such as the network quality assessment method described above.
[0119] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.
[0120] It should be noted that although several modules of the device for action execution are mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules described above can be embodied in one module. Conversely, the features and functions of one module described above can be further divided into multiple modules to be embodied.
[0121] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein.
[0122] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims
1. A network quality assessment method, characterized in that: include: Get the scenario type where the network request access fails; According to the scenario type, obtaining missing data corresponding to a preset network quality assessment indicator in the scenario type; The missing data is supplemented according to the network quality evaluation index in the historical network request, and the network quality evaluation is performed according to the supplemented network quality evaluation index.
2. The network quality assessment method according to claim 1, wherein: The scenario types for obtaining network request access failure include: The network request is divided into multiple network request stages, and the scenario type of network request access failure is determined according to the multiple network request stages.
3. The network quality assessment method according to claim 2, wherein: The network request phase includes a connection establishment phase, a response phase, and a response body data transmission phase. The scenario types of network request access failure include a connection establishment failure scenario, a response failure scenario, and a response body data transmission failure scenario.
4. The network quality assessment method according to claim 1, wherein: The network quality evaluation indicators include first packet response time, download speed and packet loss rate.
5. The network quality assessment method according to claim 1, wherein: The supplementing of the missing data according to the network quality evaluation index in the historical network request includes: Determining, based on the evaluation requirements of the missing data in the scenario type, a corresponding preset percentile value in the network quality evaluation indicator of the historical network request; The missing data is supplemented according to the indicator data corresponding to the preset quantile value.
6. The network quality assessment method according to claim 1, wherein: The supplementing of the missing data according to the network quality evaluation index in the historical network request includes: Determining, based on the evaluation requirements of the missing data in the scenario type, a corresponding tail data ratio in the network quality evaluation index of the historical network requests; A tail data mean of the network quality evaluation index of the historical network requests is obtained according to the tail data ratio, and the missing data is supplemented according to the tail data mean.
7. The network quality assessment method according to claim 1, wherein: The supplementing of the missing data according to the network quality evaluation index in the historical network request includes: Determine the reference time period corresponding to the current time period according to the preset period; The missing data of the current time period is supplemented according to the network quality evaluation index in the historical network requests within the reference time period.
8. A network quality assessment device, characterized in that: include: A scene type acquisition module is configured to execute acquisition of the scene type for which the network request access fails; A missing data acquisition module is configured to execute, according to the scenario type, acquiring missing data corresponding to a preset network quality assessment indicator in the scenario type; The network quality evaluation module is configured to supplement the missing data according to the network quality evaluation index in the historical network request, and perform network quality evaluation according to the supplemented network quality evaluation index.
9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the network quality assessment method according to any one of claims 1 to 7.
10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the network quality assessment method according to any one of claims 1 to 7 is implemented.