CN114091910A - 5G user quality difference complaint source tracing analysis method and device - Google Patents
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Abstract
Description
Technical Field
The embodiment of the application relates to the technical field of 5G big data application, in particular to a 5G user quality difference complaint traceability analysis method and device.
Background
With the development of 5G mobile internet services, the processing and supporting work of 5G complaint users is more and more important, and operators start from the perspective of users more, so that the perception and satisfaction of the users are improved.
The current complaint user analysis method mainly carries out correlation analysis based on KPI indexes, and the basic principle of the scheme is that network management data before and after the complaint time point of the complaint user, including relevant network element, base station and cell indexes, are manually inquired and extracted, and whether the quality of each link of a network in the internet surfing process of the user is normal or not is analyzed by combining the service understanding and the complaint processing experience, and finally root cause analysis of poor perception of the complaint user is formed. Firstly, because many KPI indexes which influence the service quality of a complaint user result in long analysis time and high requirement; secondly, the complaint source tracing analysis work is complex and difficult to quickly respond to the complaint problem of the client, the treatment work is complex, and the complaint treatment work efficiency is difficult to improve; the manual analysis data is mainly based on various KPI indexes after dimension reduction, and many details of user internet log details are lost, so that the problem of poor user quality caused by difficult accurate tracing is caused.
Disclosure of Invention
The embodiment of the application provides a 5G user quality complaint traceability analysis method and device, and aims to solve the problems that existing user quality complaint analysis cannot be automated, accuracy is low, batch processing cannot be achieved, and efficiency is low.
In a first aspect, an embodiment of the present application provides a method for analyzing 5G user quality complaints by tracing a source, where the method includes the following steps:
acquiring 5G internet log ticket information of a complaint user;
according to the 5G internet log ticket information, KPI indexes of the complaint users in each process are obtained, and whether the KPI indexes are poor or not is judged;
performing source tracing analysis on the quality difference KPI;
and outputting an analysis conclusion of the complaint user tracing delimitation.
Further, the 5G internet log ticket information comprises internet logs of the user at an N1 interface, an N2 interface and an N3 interface.
Further, the 5G internet log ticket information includes details of the user in an access process, a bearer establishment process, a moving process, a DNS query, a TCP link establishment, and an HTTP service.
Further, the step of obtaining KPI indexes of the complaint user in each process according to the 5G internet log ticket information and judging whether the KPI indexes are poor includes:
outputting KPI indexes of the complaint user in an access process, a bearing link establishment process, a moving process, a DNS analysis process, a TCP link establishment process and an HTTP service process according to the 5G internet log ticket information;
and comparing the KPI with a preset index threshold value, and judging whether the quality is poor.
Further, the KPI comprises success rate, time delay and HTTP rate.
Further, the performing source tracing analysis on the quality difference KPI indicators includes:
aiming at the quality difference KPI indexes, wireless delimitation, multi-dimensional common problem analysis, error code delimitation analysis and source tracing analysis of abnormal events are gradually carried out, and whether the user quality difference is caused by the abnormality of a wireless coverage network, a core network, a wireless base station, a cell, a user terminal and a server side is analyzed.
Further, the outputting of the analysis conclusion of the complaint user tracing definition includes:
and outputting the analysis conclusion of the source tracing and delimitation of the quality difference PI indexes existing in each process of the complaint user in the query time range.
In a second aspect, an embodiment of the present application further provides a source-tracing analysis apparatus for 5G user quality difference complaints, including:
the call ticket acquisition module is used for acquiring the call ticket information of the 5G internet log of the complaint user;
the quality difference judging module is used for acquiring KPI (Key performance indicator) of the complaint user in each process according to the 5G internet log ticket information and judging whether the KPI is poor or not;
the source tracing analysis module is used for carrying out source tracing analysis on the quality difference KPI;
and the conclusion analysis module is used for outputting an analysis conclusion of the source tracing delimitation of the complaint user.
In a third aspect, an embodiment of the present application further provides a computer device, including: a memory and one or more processors;
the memory to store one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a 5G user-quality complaint traceability analysis method as described above.
In a fourth aspect, embodiments of the present application further provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform a method for traceability analysis of 5G user-quality complaints as described above.
According to the embodiment of the application, 5G internet log ticket information of a complaint user is obtained; acquiring KPI (Key performance indicator) of the complaint user in each process according to the 5G internet log ticket information, and judging whether the KPI is poor or not; performing source tracing analysis on the quality difference KPI; outputting an analysis conclusion of the source tracing delimitation of the complaint user; the method and the device have the advantages that index quality difference analysis and quality difference reason traceability automation are achieved, traceability results of specific reasons of quality differences of complaint users are output, analysis dimensionality and accuracy are improved, and meanwhile analysis efficiency is high.
Drawings
Fig. 1 is a flowchart of a method for tracing and analyzing 5G user quality complaints provided in an embodiment of the present application;
fig. 2 is a flowchart of a method for analyzing 5G user quality complaints by tracing source according to an embodiment of the present application;
fig. 3 is a multi-dimensional commonality problem analysis diagram of a traceability analysis method for 5G user quality complaints provided in the embodiment of the present application;
fig. 4 is an error code delimiting algorithm diagram of a tracing analysis method for 5G user quality complaints provided in the embodiment of the present application;
fig. 5 is a schematic structural diagram of a 5G user quality complaint traceability analysis apparatus according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, specific embodiments of the present application will be described in detail with reference to the accompanying drawings. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some but not all of the relevant portions of the present application are shown in the drawings. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but could have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
At present, the traditional complaint user analysis has the following defects: firstly, because many KPI indicators affecting the service quality of a complaint user are provided, besides the success rate and the delay indicators of the processes of initial registration, mobility registration, PDU bearer establishment, handover performance, service request and the like of wireless network access, the success rate and the delay indicators also include the success rate of DNS resolution, the delay of DNS resolution, the success rate of TCP link establishment, the delay of TCP link establishment, the retransmission rate of TCP, the packet loss rate of TCP, the success rate of HTTP response, the delay of HTTP response, the rate of HTTP and the like, which are highly related to the perception of the user using the 5G network. Thus, the complaint handling staff needs a rich network experience to be competent for the complaint handling work. Secondly, the complaint source-tracing analysis work is complex and difficult to quickly respond to the complaint problem of the client, the complaint analysis firstly needs to manually extract diversified data from a plurality of platforms, then data fusion association analysis is carried out by using tools such as excel and the like, the processing work is complex, and the complaint processing work efficiency is difficult to improve. Secondly, complaint delimiting accuracy is to be improved. The manual analysis data is mainly based on various KPI indexes after dimension reduction, and many details of user internet log details are lost, so that the problem of poor user quality caused by difficult accurate tracing is caused. The embodiment of the application establishes a set of 5G user quality complaint traceability analysis method to solve the problems that the existing user quality complaint analysis can not be automated, has low accuracy, can not be processed in batches and has low efficiency.
The traceability analysis method for 5G user quality difference complaints provided in the embodiment can be executed by a traceability analysis device for 5G user quality difference complaints, and the traceability analysis device for 5G user quality difference complaints can be realized in a software and/or hardware manner and integrated in traceability analysis equipment for 5G user quality difference complaints. Wherein, the traceability analysis equipment for 5G user quality difference complaints can be equipment such as a computer.
Fig. 1 is a flowchart of a 5G user quality complaint traceability analysis method according to an embodiment of the present application. With reference to fig. 1 and 2, the method comprises the following steps:
specifically, the 5G internet log ticket information includes internet logs of the user at an N1 interface, an N2 interface, and an N3 interface; the 5G internet log ticket information comprises the detailed list of the user in the access process, the bearing establishment process, the moving process, the DNS inquiry, the TCP link establishment and the HTTP service.
specifically, KPI indexes of the complaint user in an access process, a bearing link establishment process, a moving process, a DNS analysis process, a TCP link establishment process and an HTTP service process are output according to the 5G internet log ticket information; and comparing the KPI with a preset index threshold value, and judging whether the quality is poor.
The KPI comprises a success rate, a time delay and an HTTP rate.
Illustratively, the success registration and registration delay KPI indexes of the access process, PDU establishment success rate of the bearer process, PDU establishment delay KPI indexes, switching success rate of the mobile process, switching delay KPI indexes, DNS analysis success rate and DNS analysis delay KPI indexes of the DNS process, TCP link establishment success rate and TCP link establishment delay KPI indexes of the TCP process, game, instant messaging, web browsing of HTTP service, HTTP response success rate of video, HTTP response delay and HTTP download rate KPI indexes of the HTTP service are calculated according to the interface data of N1, N2 and N3 according to the specification.
Illustratively, the registration success rate and quality difference judgment includes that firstly, the registration success rate of a complaint user is calculated according to a standard, then the registration success rate is compared with a preset index threshold (assumed to be 90%), if the registration success rate is lower than 90%, the registration success rate is judged to be quality difference, and tracing analysis is performed.
specifically, aiming at a quality difference KPI index, wireless delimitation, multi-dimensional common problem analysis, error code delimitation analysis and abnormal event clustering analysis are gradually carried out, and whether user quality difference is caused by abnormity of a wireless coverage network, a core network, a wireless base station, a cell, a user terminal and a server is analyzed.
The wireless delimitation algorithm is mainly used for analyzing the user signal difference and the service quality difference caused by the wireless environment problem, and the analysis method comprises the following steps:
1) and (3) data preprocessing, wherein three fields of the starting time, the ending time and the cell ID are extracted from the complaint user detailed list and are sorted according to the starting time (procedure starting time on Probe).
2) The sorted recordings were sliced at 15 second intervals by start time:
TS_NUM＝int((procedure end time onProbe-procedure start time on Probe)/1000/15)+1
3) calculating the switching times of each slice, and when the threshold value of the frequent switching event is met, switching the frequent switching event +1
For(i＝0；i++；i<TS_NUM)
{
Starting time is procedure start time on Probe + i 15000;
calculating the starting time +15000 as the ending time;
calculating the switching times of the first fragment;
if switching number > -3
Number of frequent handover events + +;
}
4) outputting a frequent switching result: slicing times, frequent switching event times, and frequent switching duty ratio.
Referring to fig. 3, the common problem of multiple dimensions is mainly used in the process of tracing the internet of a user, and which dimensions of objects, such as network elements, base stations, terminals, servers, IP, services, etc., cause poor user quality due to common poor quality problems, and the analysis process is as follows:
1) and after the user index is judged to be poor, comparing indexes of dimensionalities such as AMF/UPF/gNB/cell and the like with a threshold value one by one for analysis.
2) And (3) analyzing results of each dimension, entering the next cycle if the first user is normal, changing the dimension object quality to cause the user quality difference if the user quality difference and the dimension object quality difference exist, and analyzing whether the terminal of the user has a common problem if the user quality difference and each dimension object is normal.
3) And analyzing the terminal common problem, if the indexes of the user and the terminal of the same type of the whole network are poor, judging that the model quality of the terminal is poor to be the common problem, otherwise, judging that the problem is not positioned, and possibly being the personal reason of the user.
Referring to fig. 4, the error code delimitation algorithm mainly locates the specific reason of the failure for the error code returned in the failed communication process through the protocol specification, and classifies the reasons according to the core network side, the wireless side, the user side and the service side, and the flow is as follows:
1) aiming at the poor success rate index quality of the internet surfing process of the complaint user, the method can directly aim at the failure codes of the 5G complaint user in the service flow failure bill of registration, PDU establishment, authentication, service request, switching, DNS analysis, HTTP connection and the like.
2) And associating the failure ticket error codes with an error code rule table, and matching the error code analysis, the reason analysis and the problem delimitation of the protocol specification of each failure ticket error code. For example, the registration failure return error code is 1, meaning Illegal UE, indicating that the user terminal is Illegal to cause the core network to reject the registration request, and delimiting such problem as "user side cause".
3) Counting the reason classification of failure and the occupation ratio of problem definition, wherein the occupation ratio of failure larger than 50% is the main reason of poor user quality.
The abnormal event clustering mainly aims at performing source tracing analysis on abnormal events such as request failure, excessively high request response time delay, low downloading rate and the like, and the analysis method comprises the following steps:
1) and screening all the detailed lists of the index quality difference of the user aiming at the quality difference index, for example, the user registration success rate index quality difference, wherein all the detailed lists of the user registration request failure are screened.
2) And (3) carrying out centralized analysis on dimensionalities of the screened user detail lists, such as AMF, UPF, a base station, a cell, a terminal, a server IP and the like, for example, the user occupies 5 cells in the query period, wherein 1 cell quality difference detail list record is more than 50%, and then judging that the user is caused by the quality difference of the cell.
And after all dimension traceability analyses are completed, outputting abnormal objects discovered by the complaint user in a traceability mode.
In the above, the source tracing analysis of the complaint user is automated, the source tracing analysis of the complaint user quality difference problem is automated through algorithms such as wireless delimitation, multi-dimensional common problem analysis, error code delimitation and abnormal event cluster analysis, the reason delimitation results influencing user perception such as wireless coverage, core network elements, base stations, cells, terminals and server IP are output, and human intervention is not needed in the whole source tracing process.
The analysis dimensionality is wider and the accuracy is high, the traceability analysis data source comprises log data of each interface generated in the user internet surfing process, information comprises various poor quality problems of the user, such as poor quality of wireless access, bearing establishment, switching, DNS analysis, TCP link establishment, HTTP service and the like, through the large data analysis of the user internet surfing full flow, traceability delimitation comprises all links influencing user perception, such as AMF, UPF and the like of a core network side, a base station, a cell and a coverage condition of a wireless side, IP, service category and the like of a service side, compared with a traditional method, the traceability analysis method is more comprehensive and more accurate, and causes of the poor quality problems of the user perception are more effectively delimited.
And step 140, outputting an analysis conclusion of the source tracing delimitation of the complaint user.
Specifically, the analysis conclusion of tracing delimitation of the quality difference PI indexes existing in each process of the complaint user in the query time range is output, and the analysis conclusion is summarized by algorithms such as wireless delimitation, multi-dimensional common problem analysis, error code delimitation, abnormal event cluster analysis and the like.
The traceability analysis method for 5G user quality difference complaints provided by the embodiment of the application considers user quality difference evaluation from the complaint user accessing a 5G network to a full process using an internet service and key service process KPI quality difference traceability analysis, and the traceability comprises registration success rate and delay quality difference analysis of an access process, PDU establishment success rate and delay quality difference analysis of a bearing process, mobile process switching success rate and switching delay quality difference analysis of a mobile process, DNS process domain name resolution success rate and delay quality difference analysis of a TCP process, link establishment success rate and delay quality difference analysis of a HTTP process, and response success rate, response delay and download rate quality difference analysis of the HTTP service.
The traceability analysis method for 5G user poor quality complaints provided by the embodiment of the application analyzes multiple traceability algorithms simultaneously, for example, a wireless delimiting algorithm is used for analyzing whether user index poor quality is caused by frequent switching, a multi-dimension common problem traceability algorithm is used for analyzing whether common problems exist in dimensions such as a core network, a base station, a cell, a terminal and a server IP, delimitation analysis is carried out on radio access failure, bearing establishment failure, switching failure, DNS analysis failure, HTTP response failure and the like through error code definition, the root cause of the index poor quality is determined, various failure processes of complaint users are analyzed through abnormal event clustering, and concentrated analysis is carried out on core network equipment, wireless side equipment, a service side and the like at high delay and low rates.
And for the complaint user, performing traceability analysis by the multiple algorithms, realizing index quality difference analysis and reason traceability automation, and outputting a traceability result of the specific reason of the complaint user with poor quality.
According to the method, the processing efficiency of the batch complaint users is improved, specifically, the method can input a plurality of user labels and analysis time interval information through predefined tasks, automatic source tracing analysis of the batch complaint users is performed, and the complaint processing efficiency is greatly improved.
On the basis of the foregoing embodiment, fig. 5 is a schematic structural diagram of a 5G user quality complaint traceability analysis device provided in this embodiment of the present application. Referring to fig. 5, in the traceability analysis apparatus for 5G user quality difference complaints provided in this embodiment, the traceability analysis apparatus for 5G user quality difference complaints specifically includes: the system comprises aticket acquisition module 101, a qualitydifference judgment module 102, atraceability analysis module 103 and aconclusion analysis module 104.
The callticket acquiring module 101 is configured to acquire 5G internet log call ticket information of a complaint user; the qualitydifference judging module 102 is configured to obtain KPI indexes of the complaint user in each process according to the 5G internet log ticket information to judge whether the KPI indexes are poor or not; the source tracinganalysis module 103 is configured to perform source tracing analysis on the poor KPI indexes; theconclusion analysis module 104 is configured to output an analysis conclusion of the complaint user tracing delimitation.
The method comprises the steps of obtaining 5G internet log ticket information of a complaint user; acquiring KPI (Key performance indicator) of the complaint user in each process according to the 5G internet log ticket information, and judging whether the KPI is poor or not; performing source tracing analysis on the quality difference KPI; outputting an analysis conclusion of the source tracing delimitation of the complaint user; the method and the device realize index quality difference analysis and quality difference reason traceability automation, output the traceability result of the specific quality difference reason of the complaint user, improve analysis dimension and accuracy, and have high analysis efficiency.
The traceability analysis device for 5G user quality difference complaints provided by the embodiment of the application can be used for executing the traceability analysis method for 5G user quality difference complaints provided by the embodiment, and has corresponding functions and beneficial effects.
The embodiment of the application also provides computer equipment which can be integrated with the 5G source tracing analysis device for the user quality difference complaints provided by the embodiment of the application. Fig. 6 is a schematic structural diagram of a computer device according to an embodiment of the present application. Referring to fig. 6, the computer apparatus includes: aninput device 43, anoutput device 44, amemory 42, and one ormore processors 41; thememory 42 for storing one or more programs; when the one or more programs are executed by the one ormore processors 41, the one ormore processors 41 implement the tracing analysis method for 5G user quality complaints provided in the above embodiment. Theinput device 43, theoutput device 44, thememory 42 and theprocessor 41 may be connected by a bus or other means, and fig. 6 illustrates the connection by the bus as an example.
Theprocessor 41 executes various functional applications and data processing of the device by running software programs, instructions and modules stored in thememory 41, that is, the source tracing analysis method for 5G user quality complaints is realized.
The computer equipment provided by the embodiment can be used for executing the 5G user quality complaint traceability analysis method provided by the embodiment, and has corresponding functions and beneficial effects.
The embodiment of the present application further provides a storage medium containing computer-executable instructions, where the computer-executable instructions are executed by a computer processor to perform a traceability analysis method for 5G user quality complaints, where the traceability analysis method for 5G user quality complaints includes: by acquiring the 5G internet log ticket information of the complaint user; acquiring KPI (Key performance indicator) of the complaint user in each process according to the 5G internet log ticket information, and judging whether the KPI is poor or not; performing source tracing analysis on the quality difference KPI; and outputting an analysis conclusion of the complaint user tracing delimitation.
Storage medium-any of various types of memory devices or storage devices. The term "storage medium" is intended to include: mounting media such as CD-ROM, floppy disk, or tape devices; computer device memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Lanbas (Rambus) RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. The storage medium may also include other types of memory or combinations thereof. In addition, the storage medium may be located in a first computer apparatus in which the program is executed, or may be located in a different second computer apparatus connected to the first computer apparatus through a network (such as the internet). The second computer device may provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media that may reside in different locations, such as in different computer devices that are connected by a network. The storage medium may store program instructions (e.g., embodied as a computer program) that are executable by one or more processors.
Of course, the storage medium provided in the embodiments of the present application and containing computer-executable instructions is not limited to the above-mentioned tracing analysis method for 5G user quality difference complaints, and may also perform related operations in the tracing analysis method for 5G user quality difference complaints provided in any embodiments of the present application.
The traceability analysis apparatus, the storage medium, and the computer device for 5G user quality difference complaints provided in the embodiments above may execute the traceability analysis method for 5G user quality difference complaints provided in any embodiments of the present application, and refer to the traceability analysis method for 5G user quality difference complaints provided in any embodiments of the present application without detailed technical details described in the embodiments above.
The foregoing is considered as illustrative only of the preferred embodiments of the invention and the principles of the technology employed. The present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the claims.
Claims (10)
1. A tracing analysis method for 5G user quality complaints is characterized by comprising the following steps:
acquiring 5G internet log ticket information of a complaint user;
acquiring KPI (Key performance indicator) of the complaint user in each process according to the 5G internet log ticket information, and judging whether the KPI is poor or not;
performing source tracing analysis on the quality difference KPI;
and outputting an analysis conclusion of the complaint user tracing delimitation.
2. The source-tracing analysis method for 5G user quality complaints of claim 1, wherein the 5G internet log ticket information includes internet logs of users at an N1 interface, an N2 interface, and an N3 interface.
3. The source-tracing analysis method for 5G user quality difference complaints according to claim 1, wherein the 5G internet log ticket information comprises detailed lists of user in an access process, a bearer establishment process, a mobile process, DNS query, TCP link establishment and HTTP service.
4. The source tracing analysis method for 5G user complaint of poor quality according to claim 1, wherein the step of obtaining KPI (Key performance indicator) of the complaint user in each process according to the 5G internet log ticket information and judging whether the KPI is poor in quality comprises the steps of:
outputting KPI indexes of the complaint user in an access process, a bearing link establishment process, a moving process, a DNS analysis process, a TCP link establishment process and an HTTP service process according to the 5G internet log ticket information;
and comparing the KPI with a preset index threshold value, and judging whether the quality is poor.
5. The traceability analysis method of 5G user quality-difference complaints of claim 1, wherein the KPI indicators comprise success rate, latency and HTTP rate.
6. The traceability analysis method for 5G user quality-difference complaints according to claim 1, wherein the traceability analysis of the quality-difference KPI indexes comprises:
aiming at the quality difference KPI indexes, wireless delimitation, multi-dimensional common problem analysis, error code delimitation analysis and abnormal event clustering analysis are gradually carried out, and whether the user quality difference is caused by the abnormality of a wireless coverage network, a core network, a wireless base station, a cell, a user terminal and a server side is analyzed.
7. The method of claim 1, wherein the outputting the analysis result of the complaint user source-tracing definition comprises:
and outputting the analysis conclusion of the source tracing and delimitation of the quality difference PI indexes existing in each process of the complaint user in the query time range.
8. A traceability analysis device for 5G user quality difference complaints is characterized by comprising:
the call ticket acquisition module is used for acquiring the call ticket information of the 5G internet log of the complaint user;
the quality difference judging module is used for acquiring KPI (Key performance indicator) of the complaint user in each process according to the 5G internet log ticket information and judging whether the KPI is poor or not;
the source tracing analysis module is used for carrying out source tracing analysis on the quality difference KPI;
and the conclusion analysis module is used for outputting an analysis conclusion of the source tracing delimitation of the complaint user.
9. A computer device, comprising: a memory and one or more processors;
the memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a 5G user-quality complaint traceability analysis method of any of claims 1-7.
10. A storage medium containing computer-executable instructions for performing a 5G user-quality complaint traceability analysis method as claimed in any one of claims 1-7 when executed by a computer processor.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN117692948A (en)* | 2023-11-10 | 2024-03-12 | 广州丰石科技有限公司 | Quality difference IP identification method and device |
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