CN109672548A - A kind of VoLTE network fault detecting method, device and server - Google Patents
A kind of VoLTE network fault detecting method, device and server Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0823—Errors, e.g. transmission errors
- H04L43/0829—Packet loss
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
- H04L41/0636—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis based on a decision tree analysis
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0677—Localisation of faults
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Abstract
本发明提供一种VoLTE网络故障检测方法、装置及服务器。该方法包括：获取每一监测网点的丢包统计数据；根据所述丢包统计数据，统计出现丢包的用户相对应的用户标签和丢包信息之间的对应关系；根据所述对应关系，确定大概率丢包用户的用户标签。采用该方法，通过将用户标签与丢包信息进行关联，能够确定大概率丢包用户的用户标签，从而为发生VoLTE网络故障的链路进行故障原因界定提供精确依据。
The present invention provides a VoLTE network fault detection method, device and server. The method includes: acquiring the packet loss statistics data of each monitoring network point; according to the packet loss statistics data, statistics the correspondence relationship between the user labels corresponding to the users with packet loss and the packet loss information; according to the correspondence relationship, Determine the user labels of users with high probability of packet loss. Using this method, by associating user labels with packet loss information, the user labels of users with a high probability of packet loss can be determined, thereby providing an accurate basis for defining the failure cause of a link in which VoLTE network failure occurs.
Description
Technical field
The present invention relates to wireless technical field, a kind of VoLTE network fault detecting method, device and service are referred in particular to
Device.
Background technique
With long term evolution (Long Term Evolution, referred to as LTE) voice (Voice over LTE, abbreviation
Volte) technical application is more and more extensive, and promoting network performance seems most important, and the critically important task of one of them is exactly net
Network positioning problems.And network element that Volte problem is related to is numerous, scene is complicated, or even since trans-departmental, cross operator can also produce
The phenomenon that raw responsibility is shifted responsibility onto others, therefore how accurately to carry out problem and delimit the key points and difficulties for becoming Volte increased quality.
Currently, industry, which has had, counts real-time transport protocol (Real-time Transport using monitoring point
Protocol, referred to as RTP) it carries in number of dropped packets and RTP Control Protocol (RTP Control Protocol, referred to as RTCP)
RTP number of dropped packets, carry out Volte or network protocol voice (Voice over Internet Protocol, referred to as VoIP)
The problems such as the method delimited.For example, network segment each between source to opposite end can be set up to the mode of monitoring point, pass through monitoring
Each network segment whether there is packet loss, which section that failure appears in whole link checked, carry out VoLTE Network Fault Detection.
However, can only be coarsely defined network problem using RTP number of dropped packets is to occur in which section, but using aforesaid way
The concrete reason of Volte network failure cannot be defined, it is therefore necessary to which Volte network failure can accurately be detected by providing one kind
Method.
Summary of the invention
The purpose of technical solution of the present invention is to provide a kind of VoLTE network fault detecting method, device and server, is used for
The VoLTE Network Fault Detection mode using the prior art is solved, can only determine the link that VoLTE network failure occurs, it cannot
The problem of defining specific failure cause.
The specific embodiment of the invention provides a kind of long term evolution voice Volte network fault detecting method, wherein includes:
Obtain the packet loss statistical data of each monitoring network；
According to the packet loss statistical data, statistics occurs between the corresponding user tag of user of packet loss and packet loss information
Corresponding relationship；
According to the corresponding relationship, the user tag of maximum probability packet loss user is determined.
Preferably, the Volte network fault detecting method, wherein the method also includes:
According to the user tag of identified maximum probability packet loss user, Analysis of Network Malfunction is carried out.
Preferably, the Volte network fault detecting method, wherein the packet loss system for obtaining each monitoring network
After the step of counting, the method also includes:
According to the packet loss statistical data, the total packet number for extracting transmitted data in each monitoring network is more than or equal to
First numerical value, packet loss are more than or equal to the specific user of second value；
Wherein, described according to the packet loss statistical data, there is the corresponding user tag of user of packet loss and loses in statistics
In the step of corresponding relationship between package informatin:
According to the packet loss statistical data, count between the corresponding user tag of the specific user and packet loss information
Corresponding relationship.
Preferably, the Volte network fault detecting method, wherein described according to the packet loss statistical data, statistics
Occur packet loss the corresponding user tag of user and packet loss information between corresponding relationship the step of include:
There is the user tag corresponding relationship between packet loss information respectively of the different dimensions of the user of packet loss in statistics；
According to the corresponding relationship, Hash Hash tree is established.
Preferably, the Volte network fault detecting method, wherein it is described according to the corresponding relationship, it determines general
The step of user tag of rate packet loss user includes:
The user tag that corresponding packet loss information in the Hash tree does not meet the first preset condition is deleted, beta pruning is obtained
Hash tree afterwards；
Determine that the packet loss information of Xiang Diying meets the user tag of the second preset condition, is after the beta pruning in Hash tree
The user tag of maximum probability packet loss user.
Preferably, the Volte network fault detecting method, wherein corresponding in the deletion Hash tree
In the step of packet loss information does not meet the user tag of the first preset condition, obtains Hash tree after beta pruning, the packet loss packet
The total packet number and packet loss for counting transmission data are included, wherein first preset condition is that total packet number is less than third number
Value, the packet loss is less than the 4th numerical value.
Preferably, the Volte network fault detecting method, wherein after the determination beta pruning in Hash tree, phase
The step of packet loss information that ground is answered meets the user tag of the second default value, is the user tag of maximum probability packet loss user wraps
It includes:
According in Hash tree after the beta pruning, the sequence of number of dropped packets recorded in packet loss information from high to low, to corresponding
User tag be ranked up；
The top n user tag in user tag after extracting sequence；
Analyzing in top n user tag has inclusion relation with the presence or absence of at least two, and between corresponding packet loss number
Difference be less than default value user tag group；
The user tag group if it exists, then retain the wherein user tag in the user tag group, described in deletion
Other labels in user tag group；
According to the user tag after sequence, the user tag being deleted in top n user tag is supplemented, determines supplement user
N number of user tag after label is the user tag of maximum probability packet loss user.
The specific embodiment of the invention also provides a kind of long term evolution voice Volte Network Fault Detection device, wherein packet
It includes:
Module is obtained, for obtaining the packet loss statistical data of each monitoring network；
First analysis module, for according to the packet loss statistical data, the corresponding user of user of packet loss to occur in statistics
Corresponding relationship between label and packet loss information；
Second analysis module, for determining the user tag of maximum probability packet loss user according to the corresponding relationship.
On the other hand the embodiment of the present invention also provides a kind of server, wherein including memory, processor and be stored in institute
State the computer program that can be run on memory and on the processor；The processor is realized as above when executing described program
Described in any item Volte network fault detecting methods.
Another further aspect of the embodiment of the present invention also provides a kind of computer readable storage medium, is stored thereon with computer journey
Sequence, wherein as above described in any item Volte network fault detecting methods are realized when the program is executed by processor.
One or more embodiments of the invention at least has the advantages that
Volte network fault detecting method of the present invention, by the way that user tag and packet loss information are associated, energy
The user tag of maximum probability packet loss user is enough determined, to define for the link of VoLTE network failure progress failure cause occurs
Accurate foundation is provided.
Detailed description of the invention
Fig. 1 is the flow diagram of Volte network fault detecting method described in a wherein embodiment of the invention；
Fig. 2 is the flow diagram of Volte network fault detecting method described in another embodiment of the present invention；
Fig. 3 is flow diagram when step S120 is executed；
Fig. 4 is using Volte network fault detecting method described in the embodiment of the present invention, the structural representation of established Hash tree
Figure；
Fig. 5 is flow diagram when step S130 is executed；
Fig. 6 is flow diagram when step S132 is executed；
Fig. 7 is the structural schematic diagram of Volte Network Fault Detection device described in the embodiment of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are some of the embodiments of the present invention, instead of all the embodiments.Based on this hair
Embodiment in bright, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall within the protection scope of the present invention.
Long term evolution voice Volte network fault detecting method described in the specific embodiment of the invention, as shown in Figure 1, comprising:
S110 obtains the packet loss statistical data of each monitoring network；
S120, according to the packet loss statistical data, there is the corresponding user tag of user of packet loss and packet loss letter in statistics
Corresponding relationship between breath；
S130 determines the user tag of maximum probability packet loss user according to the corresponding relationship.
Volte network fault detecting method of the present invention, by the way that user tag and packet loss information are associated, energy
The user tag of maximum probability packet loss user is enough determined, to define for the link of VoLTE network failure progress failure cause occurs
Accurate foundation is provided.
According to fig. 2, preferably, using Volte network fault detecting method described in the specific embodiment of the invention, in step
After S130, further includes:
S140 carries out Analysis of Network Malfunction according to the user tag of identified maximum probability packet loss user.
In addition, the another aspect of the specific embodiment of the invention, preferably, after step S110, the method also includes:
According to the packet loss statistical data, the total packet number for extracting transmitted data in each monitoring network is more than or equal to
First numerical value, packet loss are more than or equal to the specific user of second value；
Wherein, step S120, according to the packet loss statistical data, there is the corresponding user tag of user of packet loss in statistics
In the step of corresponding relationship between packet loss information:
According to the packet loss statistical data, count between the corresponding user tag of the specific user and packet loss information
Corresponding relationship.
Using above-mentioned steps, to avoid randomness, total packet of the transmitted data of user of each monitoring network is preset
Number thresholding (the first numerical value) and packet loss thresholding (second value), the packet loss statistical data that will only be obtained from each monitoring network
In, total packet number of transmitted data is more than or equal to the first numerical value, and (for example m), and packet loss is more than or equal to second value (for example
N% statistical data), the data foundation as the user tag for calculating maximum probability packet loss user.
In addition, specifically, in step s 110, by setting up monitoring point between the network element in certain region, such as in two sessions
Monitoring point is set up between boarder controller (Session Border Controller, referred to as SBC), obtains packet loss statistical number
According to packet loss statistics can be carried out.Wherein, the data transmitted between network element, can be No. Sequence according to the sequence carried in RTP
The continuity of code is to determine whether be packet loss statistical data.
In the step s 120, by the way that the packet loss information in packet loss statistical data to be associated with user tag, to unite
It counts out which user, cell and/or network element and packet loss occurs, and establish the corresponding user tag of user and packet loss for packet loss occur
Corresponding relationship between information.
Preferably, the packet loss information may include transmitted data in preset time in the specific embodiment of the invention
Total packet number, number of dropped packets and/or packet loss etc..
In addition, the user tag may include multiple dimensions in the specific embodiment of the invention, it is illustrated below, uses
Multiple dimensions included by the label of family can be with are as follows:
Transmission direction: upstream or downstream；
Conversation type: voice or video
Network element: center Cell, base station, public data network gateway PGW, SBC
Time: 0 point~24 points
Site attribute: grid
Equipment manufacturer: in emerging, Huawei or Nokia etc. (if necessary, also may include version number)
User: IMSI, cell-phone number etc.；
Terminal models: apple, millet, Samsung (if necessary, also may include os release number)
Network type: 4G-4G, 4G-2G, 2G-4G
According to the user tag of above-mentioned various dimensions, occur between the corresponding user tag of user of packet loss and packet loss information
It can establish association as shown in table 1 below:
Table 1
| User | Terminal models | Cell | …… | Total packet number | Number of dropped packets | Packet loss |
| A | Apple | Cell1 | …… | 1000 | 10 | 1% |
| B | Millet | Cell2 | …… | 2000 | 1 | < 1% |
| C | Samsung | Cell1 | …… | 3000 | 15 | 0.5% |
Volte network fault detecting method described in the specific embodiment of the invention, it is corresponding according to the user for packet loss occur
User tag and packet loss information between association, carry out the corresponding relationship statistics between user tag and packet loss information, preferably
Ground, step S120, according to the packet loss statistical data, there is the corresponding user tag of user and packet loss information of packet loss in statistics
Between corresponding relationship the step of it is as shown in Figure 3, comprising:
S121, statistics occur packet loss user different dimensions user tag respectively between packet loss information it is corresponding close
System；
S122 establishes Hash Hash tree according to the corresponding relationship.
For example, respectively the user tag of the single dimension such as counting user, network element and conversation type and packet loss information it
Between corresponding relationship, further counting user and cell are combined the corresponding pass between the user tag of dimension and packet loss information
System and user, cell and conversation type are that voice is combined the corresponding relationship between the user tag of dimension and packet loss information
Deng establishing for defining pair occurred between the different dimensions user tag of the user of packet loss and packet loss information using which
It should be related to, constitute Hash tree as shown in Figure 4, with the determination of the user tag for subsequent maximum probability packet loss user.
Preferably, Volte network fault detecting method described in the specific embodiment of the invention, in step S130, described
According to the corresponding relationship, the step of determining the user tag of maximum probability packet loss user, as shown in Figure 5, comprising:
S131 deletes the user tag that corresponding packet loss information in the Hash tree does not meet the first preset condition, obtains
Hash tree after beta pruning；
S132 determines after the beta pruning in Hash tree that the packet loss information of Xiang Diying meets user's mark of the second preset condition
Label are the user tag of maximum probability packet loss user.
Specifically, step S131 deletes corresponding packet loss information in the Hash tree and does not meet the first preset condition
User tag, obtain beta pruning after Hash tree the step of in, the packet loss information include count transmit data total packet number with lose
Packet rate, wherein first preset condition is that total packet number is less than third value, the packet loss is less than the 4th numerical value.
By step S131, respectively preset time counts total packet number of transmission data and packet loss sets thresholding, with
Set thresholding is foundation, carries out beta pruning to Hash tree, removes non-key user tag, thus reduce calculation amount, so that
The result of Volte network fault detecting method described in the specific embodiment of the invention obtains more quick.
In the specific embodiment of the invention, preferably, for the user tag of single dimension, the use according to every dimension respectively
Family label sets the thresholding being retained in Hash tree, preferably, the user tag of the single dimension retained includes: user, net
Member, site attribute, setting producer and terminal models.Confirm whether a certain user tag appears in the user tag of single dimension
Decision rule is that judging whether may be by " beta pruning ".Label is applied generally for quantity is more, for example " equipment " may
There are thousands of, " beta pruning " occurs because portfolio is insufficient then necessarily having some equipment；Conversely, for " up/down
This kind of user tag of row ", since certain time period uplink and downlink portfolio is about the same, be generally not in uplink or
The case where downlink is by " beta pruning ", therefore it is not recommended that appear in the user tag of single dimension.
By taking the one day data statistics amount in a certain region as an example, the thresholding of the user tag of each single dimension can be according to such as
Shown in the following table 2:
Table 2
In addition, can use for the method for determination of various dimensions user tag thresholding: the thresholding of single dimension user tag removes
It is determined with statistical magnitude corresponding to other dimension user tags.
Using aforesaid way, total packet number that only reservation counts transmission data in Hash tree is more than or equal to third data,
Packet loss is more than or equal to the user tag of the 4th numerical value, and other users label is then deleted.
Preferably, step S132, determine that the packet loss information of Xiang Diying meets the second present count after the beta pruning in Hash tree
The user tag of value, be maximum probability packet loss user user tag the step of, include: as shown in Figure 6
S1321, according in Hash tree after the beta pruning, the sequence of number of dropped packets recorded in packet loss information from high to low,
Corresponding user tag is ranked up；
S1322, the top n user tag in user tag after extracting sequence；
S1323, analyzing in top n user tag has inclusion relation, and corresponding number of dropped packets with the presence or absence of at least two
Difference between mesh is less than the user tag group of default value；
S1324, the user tag group, then retain the wherein user tag in the user tag group, delete if it exists
Except other labels in the user tag group；
S1325 supplements the user tag being deleted in top n user tag according to the user tag after sequence, determines and mends
N number of user tag after filling user tag is the user tag of maximum probability packet loss user.
It adopts in manner just described, by step S1321 and step S1322, obtains number of dropped packets recorded in packet loss information
Higher top n user tag；By step S1323 and S1324, extracted top n user tag is analyzed, is screened
The user tag of inclusion relation is provided, the difference between the user tag and corresponding packet loss number with inclusion relation is retained
Less than the wherein user tag in the user tag group of default value, other users label is deleted, and passes through step S1325,
Polishing other users label is into extracted top n user tag, so that it is determined that N number of after final acquisition supplement user tag
User tag is the user tag of maximum probability packet loss user.
For example, user tag A2, B1 when various dimensions is completely contained in the user tag A2 of single dimension, and institute is right
The difference between packet loss number answered is less than preset value, it is believed that when about the same, it may be considered that the user of low-level marks
Label are completely contained in the user tag of high-level, one of user tag can be deleted.
The user tag of the N number of maximum probability packet loss user determined through the above way, it is more accurate, avoid the presence of repetition,
Accurate data is provided for subsequent network accident analysis.
Volte network fault detecting method described in the specific embodiment of the invention, in step S140, according to identified big
The user tag of probability packet loss user, when carrying out Analysis of Network Malfunction, preferably, the concrete mode for carrying out Analysis of Network Malfunction can
With are as follows:
For identified N number of user tag, priority division is carried out to each user tag, can be substantially divided into
" tag types for needing addressing network problems " (such as network element) and " tag types without addressing network problems " (such as user,
Terminal type)；
For each user tag, if corresponding user tag includes the " tag class without addressing network problems
Investigation can then be focused on user, period, the even factors such as version number by type "；
For each user tag, if corresponding user tag only includes " to need the tag class of addressing network problems
Type " is then handled according to the property of tag types.
It is understood that using Volte network fault detecting method described in the specific embodiment of the invention, it is N number of obtaining
After the user tag of maximum probability packet loss user, the data foundation of multiple network accident analysis can be used as, for heterogeneous networks event
Barrier, the mode for carrying out Analysis of Network Malfunction is different, specifically can require to determine according to analysis.
Specifically, one of embodiment of Analysis of Network Malfunction is carried out to the user tag of N number of maximum probability packet loss user
Process after start-up, can be made whether respectively include time tag, whether belong to busy or particular time, whether include
User/terminal type, whether comprising cell/grid, whether comprising upstream or downstream field, whether comprising equipment and whether wrapping
Judgement containing equipment manufacturer etc. executes different processing according to different judging results respectively.For example, when judge comprising cell/
When grid, then suggest the investigation for carrying out respective cell/grid wireless issue；When judging comprising upstream or downstream field,
It is recommended that investigation one way link whether there is failure；When judging comprising equipment manufacturer, it is proposed that check the software version of vendor equipment
This, is confirmed whether bug occur, and optionally upgraded；When judgement is comprising multiple equipment, it is proposed that the chain between investigation equipment
Road whether there is failure；When judgement only includes an equipment, it is proposed that investigation equipment itself whether there is failure etc..
Volte network fault detecting method described in the specific embodiment of the invention, by by user tag and packet loss information
It is associated, can determine the user tag of maximum probability packet loss user, so as to define the link that VoLTE network failure occurs
Failure cause.
On the other hand the specific embodiment of the invention also provides a kind of long term evolution voice Volte Network Fault Detection device,
As shown in fig. 7, described device includes:
Module is obtained, for obtaining the packet loss statistical data of each monitoring network；
First analysis module, for according to the packet loss statistical data, the corresponding user of user of packet loss to occur in statistics
Corresponding relationship between label and packet loss information；
Second analysis module, for determining the user tag of maximum probability packet loss user according to the corresponding relationship.
Volte Network Fault Detection device of the present invention, by the way that user tag and packet loss information are associated, energy
The user tag of maximum probability packet loss user is enough determined, to define for the link of VoLTE network failure progress failure cause occurs
Accurate foundation is provided.
Preferably, as shown in fig. 7, the Volte Network Fault Detection device further include:
Third analysis module carries out network failure point for the user tag according to identified maximum probability packet loss user
Analysis.
In addition, described device further include:
Data extraction module, for extracting transmitted number in each monitoring network according to the packet loss statistical data
According to total packet number be more than or equal to the first numerical value, packet loss be more than or equal to second value specific user；
Wherein, first analysis module counts the corresponding use of the specific user according to the packet loss statistical data
Corresponding relationship between family label and packet loss information.
Using above-mentioned module, to avoid randomness, total packet of the transmitted data of user of each monitoring network is preset
Number thresholding (the first numerical value) and packet loss thresholding (second value), the packet loss statistical data that will only be obtained from each monitoring network
In, total packet number of transmitted data is more than or equal to the first numerical value, and (for example m), and packet loss is more than or equal to second value (for example
N% statistical data), the data foundation as the user tag for calculating maximum probability packet loss user.
Specifically, first analysis module includes:
There is the user tags of the different dimensions of user of packet loss respectively between packet loss information for counting in statistic unit
Corresponding relationship；
Hash tree establishes unit, for establishing Hash Hash tree according to the corresponding relationship.
In addition, second analysis module includes:
Unit is deleted, the user of the first preset condition is not met for deleting corresponding packet loss information in the Hash tree
Label obtains Hash tree after beta pruning；
Analytical unit, for determining that the packet loss information of Xiang Diying meets the second preset condition after the beta pruning in Hash tree
User tag, be maximum probability packet loss user user tag.
Specifically, the packet loss information includes the total packet number and packet loss for counting transmission data, wherein described first is pre-
If condition is that total packet number is less than third value, the packet loss is less than the 4th numerical value.
Preferably, the analytical unit includes:
Sorting subunit, for according in Hash tree after the beta pruning, number of dropped packets recorded in packet loss information to be by up to
Low sequence is ranked up corresponding user tag；
Subelement is extracted, for extracting the top n user tag in the user tag after sorting；
Subelement is analyzed, there is inclusion relation with the presence or absence of at least two for analyzing in top n user tag, and institute is right
The difference between packet loss number is answered to be less than the user tag group of default value；
Subelement is deleted, for the user tag group if it exists, then retains wherein one using in the user tag group
Family label deletes other labels in the user tag group；
Subelement is supplemented, for according to the user tag after sequence, supplementing the user's mark being deleted in top n user tag
Label, N number of user tag after determining supplement user tag are the user tag of maximum probability packet loss user.
On the other hand the specific embodiment of the invention also provides a kind of server, wherein including memory, processor and storage
On the memory and the computer program that can run on the processor；It is characterized in that, the processor executes institute
As above described in any item Volte network fault detecting methods are realized when stating program.
The present invention also provides a kind of computer readable storage mediums, are stored thereon with computer program, wherein the program quilt
As above described in any item Volte network fault detecting methods are realized when processor executes.
Based on above detailed description, those skilled in the art should be able to understand using described in the specific embodiment of the invention
Volte network fault detecting method server and computer readable storage medium specific embodiment, it is no longer superfluous herein
It states.Volte network fault detecting method and device described in the specific embodiment of the invention, utilize the calculation of big data association analysis
Method, the reason of Volte network failure can be more accurately located, and can be greatly reduced due to environment, user behavior etc. with
The problem of machine factor causes network failure to be judged by accident, and take this to provide correctly investigation according to the result that network problem positions and build
View.
Above-described is the preferred embodiment of the present invention, it should be pointed out that the ordinary person of the art is come
It says, can also make several improvements and retouch under the premise of not departing from principle of the present invention, these improvements and modifications also exist
In protection scope of the present invention.
Claims (10)
1. a kind of long term evolution voice Volte network fault detecting method characterized by comprising
Obtain the packet loss statistical data of each monitoring network；
According to the packet loss statistical data, there is pair between the corresponding user tag of user of packet loss and packet loss information in statistics
It should be related to；
According to the corresponding relationship, the user tag of maximum probability packet loss user is determined.
2. Volte network fault detecting method according to claim 1, which is characterized in that the method also includes:
According to the user tag of identified maximum probability packet loss user, Analysis of Network Malfunction is carried out.
3. Volte network fault detecting method according to claim 1, which is characterized in that described to obtain each monitoring net
After the step of packet loss statistical data of point, the method also includes:
According to the packet loss statistical data, the total packet number for extracting transmitted data in each monitoring network is more than or equal to first
Numerical value, packet loss are more than or equal to the specific user of second value；
Wherein, described according to the packet loss statistical data, there is the corresponding user tag of user of packet loss and packet loss letter in statistics
In the step of corresponding relationship between breath:
According to the packet loss statistical data, the correspondence between the corresponding user tag of the specific user and packet loss information is counted
Relationship.
4. Volte network fault detecting method according to claim 1, which is characterized in that described to be united according to the packet loss
It counts, counting the step of corresponding relationship between the corresponding user tag of user of packet loss and packet loss information occur includes:
There is the user tag corresponding relationship between packet loss information respectively of the different dimensions of the user of packet loss in statistics；
According to the corresponding relationship, Hash Hash tree is established.
5. Volte network fault detecting method according to claim 4, which is characterized in that described according to the corresponding pass
System, the step of determining the user tag of maximum probability packet loss user include:
The user tag that corresponding packet loss information in the Hash tree does not meet the first preset condition is deleted, after obtaining beta pruning
Hash tree；
Determine that the packet loss information of Xiang Diying meets the user tag of the second preset condition, is general after the beta pruning in Hash tree
The user tag of rate packet loss user.
6. Volte network fault detecting method according to claim 5, which is characterized in that described to delete the Hash tree
In in corresponding packet loss information the step of not meeting the user tag of the first preset condition, obtaining Hash tree after beta pruning, it is described
Packet loss information includes the total packet number and packet loss for counting transmission data, wherein first preset condition is that total packet number is small
In third value, the packet loss is less than the 4th numerical value.
7. Volte network fault detecting method according to claim 5, which is characterized in that after the determination beta pruning
In Hash tree, the packet loss information of Xiang Diying meets the user tag of the second default value, is that the user of maximum probability packet loss user marks
The step of label includes:
According in Hash tree after the beta pruning, the sequence of number of dropped packets recorded in packet loss information from high to low is used corresponding
Family label is ranked up；
The top n user tag in user tag after extracting sequence；
Analyzing in top n user tag has inclusion relation, and the difference between corresponding packet loss number with the presence or absence of at least two
Value is less than the user tag group of default value；
The user tag group if it exists then retains the wherein user tag in the user tag group, deletes the user
Other labels in set of tags；
According to the user tag after sequence, the user tag being deleted in top n user tag is supplemented, determines supplement user tag
N number of user tag afterwards is the user tag of maximum probability packet loss user.
8. a kind of long term evolution voice Volte Network Fault Detection device characterized by comprising
Module is obtained, for obtaining the packet loss statistical data of each monitoring network；
First analysis module, for according to the packet loss statistical data, the corresponding user tag of user of packet loss to occur in statistics
Corresponding relationship between packet loss information；
Second analysis module, for determining the user tag of maximum probability packet loss user according to the corresponding relationship.
9. a kind of server, which is characterized in that including memory, processor and be stored on the memory and can be at the place
The computer program run on reason device；The processor is realized as described in any one of claim 1 to 7 when executing described program
Volte network fault detecting method.
10. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is by processor
Volte network fault detecting method as described in any one of claim 1 to 7 is realized when execution.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2006136900A1 (en) * | 2005-06-15 | 2006-12-28 | Nortel Networks Limited | Method and apparatus for non-intrusive single-ended voice quality assessment in voip |
| US7209472B2 (en) * | 2001-05-18 | 2007-04-24 | Fujitsu Limited | Method of controlling change-over of connection route between media gateway apparatuses, and call agent apparatus |
| CN101877659A (en) * | 2010-06-30 | 2010-11-03 | 中兴通讯股份有限公司 | Method, device and system for monitoring packet loss |
| US8014273B1 (en) * | 2005-08-22 | 2011-09-06 | Avaya Inc. | Dynamic feedback from an internet service provider about network occupancy/availability |
| CN105007612A (en) * | 2014-04-25 | 2015-10-28 | 中兴通讯股份有限公司 | Method for obtaining data in wireless body area network and central device |
| US20170054619A1 (en) * | 2015-08-21 | 2017-02-23 | Barefoot Networks, Inc. | Fast detection and identification of lost packets |
| CN106713063A (en) * | 2015-11-18 | 2017-05-24 | 德科仕通信(上海)有限公司 | VoIP network packet loss fault detection method |
| US20170294991A1 (en) * | 2016-04-11 | 2017-10-12 | Enyx Sa | Low latency packet recovery |
-
2017
- 2017-10-17 CN CN201710966390.1A patent/CN109672548B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7209472B2 (en) * | 2001-05-18 | 2007-04-24 | Fujitsu Limited | Method of controlling change-over of connection route between media gateway apparatuses, and call agent apparatus |
| WO2006136900A1 (en) * | 2005-06-15 | 2006-12-28 | Nortel Networks Limited | Method and apparatus for non-intrusive single-ended voice quality assessment in voip |
| US8014273B1 (en) * | 2005-08-22 | 2011-09-06 | Avaya Inc. | Dynamic feedback from an internet service provider about network occupancy/availability |
| CN101877659A (en) * | 2010-06-30 | 2010-11-03 | 中兴通讯股份有限公司 | Method, device and system for monitoring packet loss |
| CN105007612A (en) * | 2014-04-25 | 2015-10-28 | 中兴通讯股份有限公司 | Method for obtaining data in wireless body area network and central device |
| US20170054619A1 (en) * | 2015-08-21 | 2017-02-23 | Barefoot Networks, Inc. | Fast detection and identification of lost packets |
| CN106713063A (en) * | 2015-11-18 | 2017-05-24 | 德科仕通信(上海)有限公司 | VoIP network packet loss fault detection method |
| US20170294991A1 (en) * | 2016-04-11 | 2017-10-12 | Enyx Sa | Low latency packet recovery |
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