Webpage probing-based network quality assessment method, system and apparatus, and medium

Abstract

The present application discloses a webpage probing-based network quality assessment method, system and apparatus, and a medium. The method comprises: using a multi-layer regression and correlation analysis method to obtain a first correlation analysis function and a second correlation analysis function on the basis of a network quality index data set, network experience perception data and network quality comprehensive assessment data in each fiber-optic broadband network environment; and on the basis of a network quality index data set to be assessed, determining first network experience perception assessment data and second network experience perception assessment data by means of a first association analysis function and a second association analysis function. According to the present application, network quality index data and the network experience perception data corresponding to a user are subjected to association analysis, thereby improving the accuracy of user experience perception assessment, user experience perception is continuously monitored to optimize the fiber-optic broadband network environment, thereby improving the quality of service of a fiber-optic broadband service, and satisfying the requirements of the user, and the present application is widely applied to the technical field of data communications.

Description

Network quality assessment method, system, device and medium based on web page dialing test Technical Field

[0001] The present application relates to the field of data communication technology, and in particular to a network quality assessment method, system, device and medium based on web page dialing test. Background Art

[0002] Optical broadband services are the competitive anchor for all operators. Accurately assessing users' experience perception of optical broadband services and improving users' experience perception evaluation of optical broadband services have been the focus of major operators in recent years.

[0003] Traditional user experience perception is mostly evaluated based on KPI indicators such as optical attenuation of optical path equipment, on / off and power-off status of network element equipment, download rate of accessed web pages, and homepage latency. This lacks analysis of users' subjective experience perception, making it impossible to accurately obtain user experience perception evaluation through KPI indicators. It is also impossible to continuously monitor user experience perception to optimize the optical broadband network environment, reducing the service quality of optical broadband services and failing to meet user needs. Summary of the Invention

[0004] In order to solve at least one technical problem existing in the above-mentioned related technologies, the embodiments of the present application propose a network quality assessment method, system, device and medium based on web dialing, aiming to improve the accuracy of evaluating user experience perception, continuously monitor user experience perception to optimize the optical broadband network environment, improve the service quality of optical broadband services, and meet user needs.

[0005] On the one hand, an embodiment of the present application proposes a network quality assessment method based on web page dialing test, the method comprising the following steps:

[0006] Obtain network quality indicator datasets under different optical bandwidth network environments;

[0007] For each of the optical broadband network environments, obtaining a user's eye movement heat map and trajectory map through an eye tracker to determine network experience perception data under each of the optical broadband network environments;

[0008] Determining corresponding first network quality comprehensive evaluation data according to the network quality indicator data sets under each of the optical broadband network environments;

[0009] A multi-layer regression correlation analysis method is used to obtain a first correlation analysis function and a second correlation analysis function based on the network quality indicator data set, the network experience perception data, and the network quality comprehensive evaluation data under each of the optical broadband network environments;

[0010] Obtain a dataset of network quality indicators to be evaluated;

[0011] Determining corresponding first network experience perception evaluation data according to the network quality indicator dataset to be evaluated by using the first correlation analysis function;

[0012] Determining second network quality comprehensive evaluation data based on the network experience perception evaluation data;

[0013] According to the second network quality comprehensive evaluation data, corresponding second network experience perception evaluation data is determined through the second association analysis function.

[0014] In some embodiments, the method further comprises the following steps:

[0015] According to the first network experience perception evaluation data and the second network experience perception evaluation data, data analysis is performed, an optical broadband network environment early warning function is executed, and optical broadband network environment parameters are adjusted.

[0016] In some embodiments, the network quality indicator data set includes multiple network quality indicator data, and the step of determining the corresponding first network quality comprehensive evaluation data according to each network quality indicator data set under the optical broadband network environment specifically includes:

[0017] Obtaining the value-taking method and weight coefficient corresponding to each of the network quality indicator data;

[0018] Using the value obtaining method corresponding to each of the network quality indicator data, obtaining a value for each of the network quality indicator data, and determining the network quality indicator data value corresponding to each of the network quality indicator data;

[0019] The first network quality comprehensive evaluation data is calculated according to the weight coefficient corresponding to each of the network quality indicator data and the value of the network quality indicator data.

[0020] In some embodiments, the step of obtaining the first correlation analysis function and the second correlation analysis function using a multi-layer regression correlation analysis method based on the network quality indicator data, network experience perception data, and network quality comprehensive evaluation data in each of the optical broadband network environments specifically includes:

[0021] Adopting the multi-layer regression association analysis method, constructing the first association analysis function according to the network experience perception data under each of the optical broadband network environments, and the network quality indicator data value and the weight coefficient corresponding to each of the network quality indicator data;

[0022] The multi-layer regression correlation analysis method is adopted to construct the second correlation analysis function according to the network experience perception data and the network quality comprehensive evaluation data under each of the optical broadband network environments.

[0023] In some embodiments, the first network quality comprehensive evaluation data is calculated using the following formula:

[0024] Among them, KQI is the first network quality comprehensive evaluation data, KPI i is the network quality indicator data value corresponding to the i-th network quality indicator data, P i is the weight coefficient of the i-th network quality indicator data.

[0025] In some embodiments, the network quality indicator data set to be evaluated includes a plurality of network quality indicator data to be evaluated, and the corresponding first network experience perception evaluation data is determined by the first correlation analysis function according to the network quality indicator data set to be evaluated, which is specifically expressed by the following formula: MOS1=F1(KPI i , P i );

[0026] Among them, MOS1 is the first network experience perception evaluation data, F1() is the first correlation analysis function, KPI k is the network quality indicator data value corresponding to the kth network quality indicator data to be evaluated, P k is the weight coefficient corresponding to the kth network quality indicator data to be evaluated, the network quality indicator data to be evaluated is delay indicator data or rate indicator data, NNNN is the number of delay indicator data in the network quality indicator data set to be evaluated, M is the number of rate indicator data in the network quality indicator data set to be evaluated, P 1i is the first weight coefficient of the i-th delay indicator data, P 2f is the second weight coefficient of the i-th delay indicator data, KPI i is the network quality indicator data value corresponding to the i-th delay indicator data, P j is the weight coefficient of the j-th rate indicator data, KPI j is the network quality indicator data value corresponding to the j-th rate-type indicator data.

[0027] In some embodiments, the second network quality comprehensive evaluation data is used to determine the corresponding second network experience perception evaluation data through the second correlation analysis function, which is specifically expressed by the following formula: MOS2 = F2 (KQI); F2 (KQI) = a k KQI+b k , Q kmin <=KQI<=Q kmax ;

[0028] Among them, MOS2 is the second network experience perception evaluation data, F2() is the second correlation analysis function, KQI is the second network quality comprehensive evaluation data, Q kmin is the minimum value of the kth preset data value interval corresponding to the second network quality comprehensive evaluation data, Q kmax is the maximum value of the kth preset data value interval corresponding to the second network quality comprehensive evaluation data, a k is the first line parameter of the kth preset data value interval, b k The second line type parameter of the kth preset data value interval.

[0029] On the other hand, an embodiment of the present application proposes a network quality assessment system based on web page dialing test, the system comprising:

[0030] The first module is used to obtain network quality indicator data sets under different optical bandwidth network environments;

[0031] The second module is used to obtain the user's eye movement heat map and trajectory map through an eye tracker for each of the optical broadband network environments, and determine the network experience perception data under each of the optical broadband network environments;

[0032] A third module is used to determine corresponding first network quality comprehensive evaluation data according to the network quality indicator data set under each of the optical broadband network environments;

[0033] A fourth module is configured to obtain a first correlation analysis function and a second correlation analysis function using a multi-layer regression correlation analysis method based on the network quality indicator dataset, the network experience perception data, and the network quality comprehensive evaluation data under each of the optical broadband network environments;

[0034] The fifth module is used to obtain the network quality evaluation indicator data set;

[0035] A sixth module is configured to determine corresponding first network experience perception evaluation data based on the network quality indicator dataset to be evaluated by using the first correlation analysis function;

[0036] A seventh module is configured to determine second network quality comprehensive evaluation data based on the network experience perception evaluation data;

[0037] An eighth module is configured to determine corresponding second network experience perception evaluation data based on the second network quality comprehensive evaluation data through the second association analysis function.

[0038] On the other hand, an embodiment of the present application proposes a network quality assessment device based on web page dialing, which includes a memory and a processor. The memory stores a computer program, and the processor implements the network quality assessment method described above when executing the memory.

[0039] In another aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the network quality assessment method described above is implemented.

[0040] The present application provides a network quality assessment method, system, device and medium based on web dialing test, which obtains network quality indicator data sets and network experience perception data under different optical broadband network environments, determines first network quality comprehensive assessment data under each optical broadband network environment based on the network quality indicator data sets, adopts a multi-layer regression correlation analysis method based on the network quality indicator data sets, network experience perception data and network quality comprehensive assessment data under each optical broadband network environment, obtains a first correlation analysis function and a second correlation analysis function, obtains a network quality indicator data set to be assessed, and determines first network experience perception assessment data and second network experience perception assessment data based on the network quality indicator data set to be assessed using the first correlation analysis function and the second correlation analysis function. The present application performs correlation analysis on the network quality indicator data and the network experience perception data corresponding to the user, improves the accuracy of the user experience perception assessment, continuously monitors the user experience perception to optimize the optical broadband network environment, improve the service quality of the optical broadband service, and meet the needs of users. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] FIG1 is a flow chart of a network quality assessment method based on web page dialing test provided by an embodiment of the present application;

[0042] FIG2 is a schematic diagram of obtaining a network quality indicator data set under different optical broadband network environments in an embodiment of the present application;

[0043] FIG3 is a flow chart of step S103 in an embodiment of the present application;

[0044] FIG4 is a schematic diagram of determining a network quality indicator data value corresponding to network quality indicator data in an embodiment of the present application;

[0045] FIG5 is a schematic diagram of determining comprehensive network quality evaluation data in an embodiment of the present application;

[0046] FIG6 is a flow chart of step S104 in an embodiment of the present application;

[0047] 7 is another flow chart of a network quality assessment method based on web page dialing test provided in an embodiment of the present application;

[0048] FIG8 is a schematic diagram of an embodiment of the present application to implement the optical broadband network environment warning function;

[0049] 9 is a schematic structural diagram of a network quality assessment system based on web page dialing test provided in an embodiment of the present application;

[0050] FIG10 is a schematic diagram of the hardware structure of a network quality assessment device based on web page dialing provided in an embodiment of the present application. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0052] It should be noted that although the device schematics illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the device or the sequence in the flowcharts. The terms "first," "second," and so on, in the specification, claims, and drawings, are used to distinguish similar items and are not necessarily used to describe a specific sequence or precedence.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0054] First, let’s analyze some of the terms used in this application:

[0055] KQI (Key Quality Index): A service quality parameter close to customer experience proposed by different services, which is a key indicator at the business level.

[0056] KPI (Key Performance Index): A basic indicator for detecting and evaluating the end-to-end infrastructure network and service quality.

[0057] MOS (mean opinion score): In voice communications, particularly Internet telephony, it provides a measure of the quality of human communication at the destination end of a circuit. The program uses a mathematical average of subjective tests (subjective ratings) to derive a quantitative indicator of system performance.

[0058] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.

[0059] Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0060] It should be noted that in each specific embodiment of the present application, when it comes to the need to perform relevant processing based on data related to the user's identity or characteristics, such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of such data will comply with relevant laws, regulations, and standards. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.

[0061] Optical broadband services are the competitive anchor for all operators. Accurately assessing users' experience perception of optical broadband services and improving users' experience perception evaluation of optical broadband services have been the focus of major operators in recent years.

[0062] Traditional user experience perception is mostly evaluated based on KPI indicators such as optical attenuation of optical path equipment, on / off and power-off status of network element equipment, download rate of accessed web pages, and homepage latency. This lacks analysis of users' subjective experience perception, making it impossible to accurately obtain user experience perception evaluation through KPI indicators. It is also impossible to continuously monitor user experience perception to optimize the optical broadband network environment, reducing the service quality of optical broadband services and failing to meet user needs.

[0063] Based on this, the embodiments of the present application propose a network quality assessment method, system, device and medium based on web dialing, aiming to improve the accuracy of evaluating user experience perception, continuously monitor user experience perception to optimize the optical broadband network environment, improve the service quality of optical broadband services, and meet user needs.

[0064] 1 , which is an optional flowchart of a network quality assessment method based on web page dialing provided by an embodiment of the present application, the method may include but is not limited to steps S101 to S108:

[0065] Step S101, obtaining a network quality indicator dataset under different optical broadband network environments;

[0066] Step S102: For each optical broadband network environment, obtain a user's eye movement heat map and trajectory map through an eye tracker to determine network experience perception data in each optical broadband network environment;

[0067] Step S103, determining corresponding first network quality comprehensive evaluation data according to the network quality indicator data set under each optical broadband network environment;

[0068] Step S104, using a multi-layer regression correlation analysis method based on the network quality indicator dataset, network experience perception data, and network quality comprehensive evaluation data under each optical broadband network environment to obtain a first correlation analysis function and a second correlation analysis function;

[0069] Step S105, obtaining a data set of network quality indicators to be evaluated;

[0070] Step S106, determining corresponding first network experience perception evaluation data through a first correlation analysis function according to the network quality indicator dataset to be evaluated;

[0071] Step S107, determining second network quality comprehensive evaluation data based on the network experience perception evaluation data;

[0072] Step S108: Determine corresponding second network experience perception evaluation data according to the second network quality comprehensive evaluation data through a second correlation analysis function.

[0073] In some embodiments, the above-mentioned network quality assessment method based on web page dialing simulates different optical broadband network environments, builds a user experience perception verification platform, and uses probes deployed on the optical broadband line gateway to actively dial Internet web pages at the same time, extracting network quality indicator data such as latency, rate, and success rate during web page access, obtaining a network quality indicator data set, and preliminarily constructing a first correlation analysis function between KQI (first network quality comprehensive assessment data) and network quality indicator data. Based on an eye tracker, the user's real experience perception during the access process under different optical broadband network environments is recorded to obtain the user's network experience perception data; the KQI (first network quality comprehensive assessment data) is correlated and analyzed with the user's network experience perception data to provide a related second correlation analysis function. The first correlation analysis function and the second correlation analysis function are used to correlate and analyze the network quality indicator data set to be evaluated obtained by web page dialing in the real optical broadband network environment to obtain corresponding network experience perception assessment data and second network quality comprehensive assessment data. Based on the network experience perception assessment data and the second network quality comprehensive assessment data, the network quality is analyzed and the optical broadband network parameters are optimized.

[0074] In step S102 of some embodiments, specifically, the subjective MOS values ​​(network experience perception data) of users accessing web pages, as calculated and evaluated by the user eye movement heat map and trajectory map on the eye tracker during the same period under various optical broadband network environments, are recorded.

[0075] Refer to Figure 2, which is an optional schematic diagram of obtaining network quality indicator data sets under different optical broadband network environments in an embodiment of the present application, wherein multiple optical broadband network environments 1 to N are simulated, and network quality indicator data sets under each optical broadband network environment are obtained to obtain network quality indicator data sets 1 to N.

[0076] In some embodiments, the network quality indicator data set may include but is not limited to multiple network quality indicator data including DNS delay, TCP connection delay, first packet delay, home page access delay, access success rate, web page download rate, etc.

[0077] Referring to FIG. 3 , FIG. 3 is an optional flowchart of step S103 in an embodiment of the present application. Step S103 may include but is not limited to steps S201 to S203:

[0078] Step S201, obtaining the value selection method and weight coefficient corresponding to each network quality indicator data;

[0079] Step S202: using the value obtaining method corresponding to each network quality indicator data, obtaining a value for each network quality indicator data, and determining the network quality indicator data value corresponding to each network quality indicator data;

[0080] Step S203: Calculate first network quality comprehensive evaluation data according to the weight coefficient corresponding to each network quality indicator data and the network quality indicator data value.

[0081] In steps S201 to S202 of some embodiments, specifically, a score value (network quality indicator data value) corresponding to the network quality indicator data is determined according to a method for obtaining a value of the network quality indicator data.

[0082] For example, referring to FIG4, FIG4 is an optional schematic diagram of determining the network quality indicator data value corresponding to the network quality indicator data in an embodiment of the present application. The DNS delay (network quality indicator data) corresponds to multiple value intervals, including value interval 1: (0ms, 5ms], value interval 2: (5ms, 10ms], value interval 3: (10ms, 20ms], value interval 4: (20ms, 50ms] and value interval 5: (50ms, 100ms], each value interval corresponds to a KPI value range, and the KPI value range 1 corresponding to value interval 1 is (80, 1 00], the KPI value range corresponding to value interval 2 is (60, 80], the KPI value range corresponding to value interval 3 is (40, 60], the KPI value range corresponding to value interval 4 is (20, 40], and the KPI value range corresponding to value interval 5 is (0, 20]). When the obtained DNS latency is 4 ms, the DNS latency is in value interval 1, and the corresponding KPI value range is (80, 100]. Based on the corresponding value relationship, the KPI value (network quality indicator data value) of DNS latency is determined to be 100-20*(4ms / 5ms)=84.

[0083] In step S203 of some embodiments, specifically, the first network quality comprehensive evaluation data is calculated by the following formula:

[0084] Among them, KQI is the first network quality comprehensive evaluation data, KPI i is the network quality indicator data value corresponding to the i-th network quality indicator data, P i is the weight coefficient of the i-th network quality indicator data, and N is the number of network quality indicator data.

[0085] In some embodiments, referring to FIG5 , FIG5 is an optional schematic diagram of determining network quality comprehensive evaluation data in an embodiment of the present application, and the corresponding network quality comprehensive evaluation data is calculated based on multiple network quality indicator data in the network quality indicator data set through the AI ​​big data analysis platform.

[0086] For example, Table 1 is a table of KPI value ranges and weight coefficients for network quality indicator data. The details of Table 1 are as follows:

[0087] Table 1 KPI value range and weight coefficient table of network quality indicator data

[0088] In some embodiments, referring to FIG. 6 , FIG. 6 is an optional flowchart of step S104 in an embodiment of the present application. Step S104 may include but is not limited to steps S301 to S302:

[0089] Step S301: Using a multi-layer regression correlation analysis method, a first correlation analysis function is constructed based on the network experience perception data under each optical broadband network environment, and the network quality indicator data value and weight coefficient corresponding to each network quality indicator data;

[0090] Step S302 : A multi-layer regression correlation analysis method is used to construct a second correlation analysis function based on the network experience perception data and the network quality comprehensive evaluation data under each optical broadband network environment.

[0091] In step S301 of some embodiments, the first correlation analysis function is specifically as follows:

[0092] Among them, F1() is the first correlation analysis function, It is the calculation sub-item related to the latency indicator data, P 1i is the first weight coefficient of the i-th delay indicator data, P 2i is the second weight coefficient of the i-th delay indicator data, P 1i With P 2i The sum of the two equals the weight coefficient P of the delay indicator data. i , KPI i is the network quality indicator data value corresponding to the i-th delay indicator data, P j KPI j It is the related calculation item of rate index data, P j is the weight coefficient of the j-th rate indicator data, KPI j is the network quality indicator data value corresponding to the j-th rate-type indicator data.

[0093] In step S302 of some embodiments, the second correlation analysis function is specifically as follows: F2(KQI)=a k KQI+b k , Q kmin <=KQI<=Q kmax ;

[0094] Among them, F2() is the second correlation analysis function, KQI is the second network quality comprehensive evaluation data, Q kmin is the minimum value of the kth preset data value interval corresponding to the second network quality comprehensive evaluation data, Q kmax is the maximum value of the kth preset data value interval corresponding to the second network quality comprehensive evaluation data, a k is the first line parameter of the kth preset data value interval, b k The second line type parameter of the kth preset data value interval.

[0095] In some embodiments, illustratively, there are five KQI value intervals preset, including value interval 1: [98, 100], value interval 2: [90, 98], value interval 3: [80, 90], value interval 4: [60, 80], and value interval 5: [0, 60]. The second correlation analysis function can be expressed as:

[0096] Among them, a1 is the first line type parameter of data value interval 1, b1 is the second line type parameter of data value interval 1, a2 is the first line type parameter of data value interval 2, b2 is the second line type parameter of data value interval 2, a3 is the first line type parameter of data value interval 3, b3 is the second line type parameter of data value interval 3, a4 is the first line type parameter of data value interval 4, b4 is the second line type parameter of data value interval 4, a5 is the first line type parameter of data value interval 5, and b5 is the second line type parameter of data value interval 5.

[0097] In some embodiments, referring to Table 2, Table 2 is an optional correlation analysis comparison table of MOS and KQI, which is shown as follows:

[0098] Table 2 Correlation analysis comparison table of MOS and KQI

[0099] In step S106 of some embodiments, it is specifically expressed by the following formula: MOS1=F1(KPI k , P k );

[0100] Among them, MOS1 is the first network experience perception evaluation data, F1() is the first correlation analysis function, KPI k is the network quality indicator data value corresponding to the kth network quality indicator data to be evaluated, P k is the weight coefficient corresponding to the kth network quality indicator data to be evaluated. When the network quality indicator data to be evaluated is the delay indicator data, P k Can be split into P 1k and P 2k Perform relevant calculations.

[0101] In step S108 of some embodiments, it is specifically expressed by the following formula: MOS2=F2(KQI);

[0102] Among them, MOS2 is the second network experience perception evaluation data, F2() is the above-mentioned second correlation analysis function, and KQI is the second network quality comprehensive evaluation data.

[0103] In step S105 of some embodiments, optionally, a data set of network quality indicators to be evaluated is collected based on web dialing tests of massive home gateway probes, and the second network quality comprehensive evaluation data is calculated using an AI big data analysis platform.

[0104] In some embodiments, the network quality assessment method based on web page dialing test may further include step S109:

[0105] Step S109: Perform data analysis based on the first network experience perception evaluation data and the second network experience perception evaluation data, execute the optical broadband network environment early warning function, and adjust the optical broadband network environment parameters to optimize the optical broadband network environment and improve the specific value of the network experience perception evaluation data.

[0106] In some embodiments, the network experience perception MOS value evaluated by the eye tracker under simulated different optical bandwidth network environments is correlated with the comprehensive evaluation value of service quality perception (network quality comprehensive evaluation data) calculated by the probe test data (network quality indicator data) deployed on massive home gateways through the AI ​​big data platform, and a service perception evaluation indicator system that can be collected, monitored, and improved is constructed to achieve the purpose of continuously monitoring and optimizing the quality of Internet web services and improving users' network experience perception.

[0107] In some embodiments, referring to FIG. 7 , FIG. 7 is another optional flow chart of a network quality assessment method based on web page dialing provided by an embodiment of the present application, which includes the following steps 01 to 0:

[0108] Step 01: Simulate various optical broadband network environments and obtain network quality indicator datasets and network experience perception data under each optical broadband network environment;

[0109] Step 02: Determine comprehensive network quality evaluation data for each optical broadband network environment based on the network quality indicator dataset using the AI ​​big data analysis platform;

[0110] Step 03: Perform correlation analysis through the AI ​​big data analysis platform to obtain a first correlation analysis function and a second correlation analysis function;

[0111] Step 04: Perform web dial-up testing based on probes deployed on a large number of home gateways to obtain a data set of network quality indicators to be evaluated;

[0112] Step 05: Using the AI ​​big data analysis platform, based on the network quality indicator dataset to be evaluated, the first and second correlation analysis functions are used to determine first and second network experience perception evaluation data.

[0113] Step 06: Based on the first network experience perception evaluation data and the second network experience perception evaluation data, data analysis is performed through the AI ​​big data analysis platform to execute the optical broadband network environment early warning function.

[0114] In step S109 of some embodiments, specifically, referring to Figure 8, Figure 8 is an optional schematic diagram of executing the optical broadband network environment warning function in an embodiment of the present application, wherein a warning threshold of the network experience perception evaluation data is set, and when the first network experience perception evaluation data exceeds the warning threshold or the second network experience perception evaluation data exceeds the warning threshold, the optical broadband network environment warning function is executed, and the warning information is output, and the warning information is pushed to the relevant monitoring platform or relevant maintenance personnel, and relevant adjustments are made in a timely manner to adjust the optical broadband network environment parameters to optimize the optical broadband network environment and improve user experience perception.

[0115] 9 , which is a schematic diagram of an optional structure of a network quality assessment system based on web page dialing provided by an embodiment of the present application, the system may include but is not limited to:

[0116] The first module is used to obtain network quality indicator data sets under different optical bandwidth network environments;

[0117] The second module is used to obtain user eye movement heat map and trajectory map for each optical broadband network environment through an eye tracker to determine the network experience perception data in each optical broadband network environment;

[0118] The third module is used to determine the corresponding first network quality comprehensive evaluation data according to the network quality indicator data set under each optical broadband network environment;

[0119] The fourth module is used to obtain a first correlation analysis function and a second correlation analysis function using a multi-layer regression correlation analysis method based on the network quality indicator data set, network experience perception data, and network quality comprehensive evaluation data under each optical broadband network environment;

[0120] The fifth module is used to obtain the network quality evaluation indicator data set;

[0121] A sixth module is configured to determine corresponding first network experience perception evaluation data based on the network quality indicator dataset to be evaluated by using a first correlation analysis function;

[0122] A seventh module is configured to determine second network quality comprehensive evaluation data based on the network experience perception evaluation data;

[0123] The eighth module is used to determine the corresponding second network experience perception evaluation data according to the second network quality comprehensive evaluation data through a second correlation analysis function.

[0124] The specific implementation of the network quality assessment system based on web page dialing test is basically the same as the specific embodiment of the network quality assessment method based on web page dialing test mentioned above, and will not be repeated here.

[0125] An embodiment of the present application also provides a network quality assessment device based on web page dialing test, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the above-mentioned network quality assessment method based on web page dialing test is implemented.

[0126] Please refer to FIG10 , which illustrates the hardware structure of a network quality assessment device based on web page dialing test according to another embodiment. The network quality assessment device based on web page dialing test includes:

[0127] The processor 901 can be implemented as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0128] The memory 902 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program codes are stored in the memory 902 and are called by the processor 901 to execute the network quality assessment method based on web page dialing test in the embodiments of this application.

[0129] Input / output interface 903, used to implement information input and output;

[0130] Communication interface 904, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.);

[0131] Bus 905 , which transmits information between various components of the device (e.g., processor 901 , memory 902 , input / output interface 903 , and communication interface 904 );

[0132] The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0133] An embodiment of the present application further provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned network quality assessment method based on web page dialing.

[0134] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0135] The embodiments of the present application provide a network quality assessment method, system, device, and medium based on web dialing, which obtains network quality indicator data sets and network experience perception data under different optical broadband network environments, determines first network quality comprehensive assessment data under each optical broadband network environment based on the network quality indicator data sets, and adopts a multi-layer regression correlation analysis method based on the network quality indicator data sets, network experience perception data, and network quality comprehensive assessment data under each optical broadband network environment to obtain a first correlation analysis function and a second correlation analysis function, obtains a network quality indicator data set to be assessed, and determines first network experience perception assessment data and second network experience perception assessment data based on the network quality indicator data set to be assessed using the first correlation analysis function and the second correlation analysis function. The present application performs correlation analysis on the network quality indicator data and the network experience perception data corresponding to the user, improves the accuracy of the user experience perception assessment, continuously monitors the user experience perception to optimize the optical broadband network environment, improve the service quality of the optical broadband service, and meet the needs of the user.

[0136] The embodiments described in the embodiments of this application are intended to more clearly illustrate the technical solutions of the embodiments of this application and do not constitute a limitation on the technical solutions provided by the embodiments of this application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0137] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0138] The system embodiment described above is merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0139] Those skilled in the art will appreciate that all or some of the steps in the methods, systems, and functional modules / units in the devices disclosed above may be implemented as software, firmware, hardware, or appropriate combinations thereof.

[0140] The terms "first", "second", "third", "fourth", etc. (if any) in the specification 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 sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof 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 clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0141] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0142] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of the above units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

[0143] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0144] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0145] 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, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes multiple instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: various media that can store programs, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0146] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and essence of the present invention should be within the scope of the present invention.

Claims

1. A network quality assessment method based on web page dialing test, characterized in that: The method comprises the following steps: Obtain network quality indicator data sets under different optical bandwidth network environments; For each of the optical broadband network environments, an eye tracker is used to obtain a user's eye movement heat map and trajectory map, and network experience perception data under each of the optical broadband network environments is determined; Determine the corresponding first network quality comprehensive evaluation data according to the network quality indicator data set under each of the optical broadband network environments; According to the network quality indicator data set, network experience perception data and network quality comprehensive evaluation data under each of the optical broadband network environments, a multi-layer regression correlation analysis method is used to obtain a first correlation analysis function and a second correlation analysis function; Obtain a data set of network quality indicators to be evaluated; According to the network quality indicator data set to be evaluated, determining corresponding first network experience perception evaluation data through the first association analysis function; Determining second network quality comprehensive evaluation data according to the network experience perception evaluation data; According to the second network quality comprehensive evaluation data, the corresponding second network experience perception evaluation data is determined through the second association analysis function.

2. The network quality assessment method according to claim 1, characterized in that: The method further comprises the following steps: According to the first network experience perception evaluation data and the second network experience perception evaluation data, data analysis is performed, an optical broadband network environment early warning function is executed, and optical broadband network environment parameters are adjusted.

3. The network quality assessment method according to claim 1, characterized in that: The network quality indicator data set includes a plurality of network quality indicator data, and the step of determining the corresponding first network quality comprehensive evaluation data according to each of the network quality indicator data sets under the optical broadband network environment specifically includes: Obtaining the value-taking method and weight coefficient corresponding to each of the network quality indicator data; Using the value-taking method corresponding to each of the network quality indicator data, taking a value for each of the network quality indicator data, and determining the network quality indicator data value corresponding to each of the network quality indicator data; The first network quality comprehensive evaluation data is calculated according to the weight coefficient corresponding to each of the network quality indicator data and the value of the network quality indicator data.

4. The network quality assessment method according to claim 3, characterized in that: The step of obtaining the first correlation analysis function and the second correlation analysis function by using a multi-layer regression correlation analysis method according to the network quality indicator data, the network experience perception data and the network quality comprehensive evaluation data under each of the optical broadband network environments specifically includes: Adopting the multi-layer regression association analysis method, constructing the first association analysis function according to the network experience perception data under each of the optical broadband network environments, and the network quality indicator data value and the weight coefficient corresponding to each of the network quality indicator data; The multi-layer regression association analysis method is adopted to construct the second association analysis function according to the network experience perception data and the network quality comprehensive evaluation data in each of the optical broadband network environments.

5. The network quality assessment method according to claim 3, characterized in that: The first network quality comprehensive evaluation data is calculated by the following formula: Among them, KQI is the first network quality comprehensive evaluation data, KPI i is the network quality indicator data value corresponding to the i-th network quality indicator data, P i is the weight coefficient of the ith network quality indicator data, and N is the number of network quality indicator data.

6. The network quality assessment method according to claim 4, characterized in that: The network quality indicator data set to be evaluated includes a plurality of network quality indicator data to be evaluated, and the corresponding first network experience perception evaluation data is determined according to the network quality indicator data set to be evaluated by the first association analysis function, which is specifically expressed by the following formula: MOS1=F1(KPI k , P k ): Among them, MOS1 is the first network experience perception evaluation data, F1() is the first correlation analysis function, KPI k is the network quality indicator data value corresponding to the kth network quality indicator data to be evaluated, P k is the weight coefficient corresponding to the kth network quality indicator data to be evaluated, the network quality indicator data to be evaluated is delay indicator data or rate indicator data, N is the number of delay indicator data in the network quality indicator data to be evaluated, M is the number of rate indicator data in the network quality indicator data to be evaluated, P 1i is the first weight coefficient of the i-th delay indicator data, P 2i is the second weight coefficient of the i-th delay indicator data, KPI i is the network quality indicator data value corresponding to the i-th delay indicator data, P j is the weight coefficient of the j-th rate indicator data, KPI j is the network quality indicator data value corresponding to the j-th rate-type indicator data.

7. The network quality assessment method according to claim 4, characterized in that: According to the second network quality comprehensive evaluation data, the corresponding second network experience perception evaluation data is determined by the second association analysis function, which is specifically expressed by the following formula: MOS2 = F2 (KQI); F2 (KQI) = a k KQI+b k , Q kmin <=KQI<=Q kmax ; Among them, MOS2 is the second network experience perception evaluation data, F2() is the second correlation analysis function, KQI is the second network quality comprehensive evaluation data, Q kmin is the minimum value of the kth preset data value interval corresponding to the second network quality comprehensive evaluation data, Q kmax is the maximum value of the kth preset data value interval corresponding to the second network quality comprehensive evaluation data, a k is the first line parameter of the kth preset data value interval, b k It is the second line type parameter of the kth preset data value interval.

8. A network quality assessment system based on web page dialing test, characterized in that: The system comprises: The first module is used to obtain network quality indicator data sets under different optical bandwidth network environments; The second module is used to obtain the user's eye movement heat map and trajectory map through an eye tracker for each of the optical broadband network environments, and determine the network experience perception data under each of the optical broadband network environments; A third module is used to determine the corresponding first network quality comprehensive evaluation data according to the network quality indicator data set under each of the optical broadband network environments; The fourth module is used to obtain a first correlation analysis function and a second correlation analysis function by using a multi-layer regression correlation analysis method according to the network quality indicator data set, the network experience perception data and the network quality comprehensive evaluation data under each of the optical broadband network environments; The fifth module is used to obtain the data set of network quality indicators to be evaluated; A sixth module is used to determine corresponding first network experience perception evaluation data according to the network quality indicator data set to be evaluated through the first association analysis function; A seventh module is used to determine second network quality comprehensive evaluation data based on the network experience perception evaluation data; An eighth module is used to determine corresponding second network experience perception evaluation data according to the second network quality comprehensive evaluation data through the second association analysis function.

9. A network quality assessment device based on web page dialing test, characterized in that: The network quality assessment device comprises a memory and a processor, the memory stores a computer program, and the processor implements the network quality assessment method according to any one of claims 1 to 7 when executing the memory.

10. A computer-readable storage medium storing 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.

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