CN108289031B - Home broadband network fault diagnosis method and device - Google Patents
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Abstract
The embodiment of the application discloses a method and a device for diagnosing faults of a home broadband network. The method comprises the following steps: for a user in a home broadband network, performing a reverse diagnosis from a lowest level associated device of the user, wherein the reverse diagnosis comprises: confirming whether the target associated equipment is abnormal or not according to the index data of the target associated equipment; determining adjacent users of the user, wherein the target associated equipment and the same-level associated equipment of the adjacent users have the same upper-level associated equipment; according to the index data of the same-level associated equipment of the adjacent users, whether the same-level associated equipment of the adjacent users is abnormal is confirmed; and under the condition that the indication data of the same-level associated equipment of the adjacent users are abnormal, taking the upper-level associated equipment as target associated equipment, and performing reverse diagnosis aiming at the target associated equipment. The embodiment of the application has the advantages that the traditional forward fault diagnosis is supplemented beneficially, the invalid complaints of users are reduced, and the fault delimiting efficiency is improved.
Description
Technical Field
The present invention relates to the field of fault diagnosis technologies, and in particular, to a fault diagnosis method and apparatus for a wired home broadband network.
Background
The fault diagnosis device of the wired home broadband is used as a core module for complaint preprocessing, and is directly used by a front-line user, so that the fault diagnosis device has great practical significance for shortening fault location, responding to customer complaints and improving brand value.
In the prior art, home Broadband fault diagnosis is based on positive fault determination of an account, that is, a resource tree "account-Optical Network Unit (ONU) -Optical splitter-Optical Line Terminal (OLT) -Broadband remote Access Server (BAS)" based on the account is first carded, then alarm data and account data of a user are analyzed layer by layer, and finally a decision is made on complaints of the user according to states of nodes to guide the user to remove faults or forward related nodes to remove faults. The current fault diagnosis is based on the logic judgment diagnosis of a single user and a single node, the association degree is lacked, the group fault function is actively reported based on the equipment alarm, the method is single, and no effective verification mechanism exists; cannot give the complaint users macroscopic feedback based on population effects.
Disclosure of Invention
The embodiment of the application provides a home broadband network fault diagnosis method and device, and aims to at least solve the problem that a fault area is inaccurate to judge due to single diagnosis means.
An embodiment of the present application provides a home broadband network fault diagnosis method, including: for a user in the home broadband network, performing reverse diagnosis starting from the lowest level associated device of the user, taking the lowest level associated device of the user as a target associated device, wherein each user has multiple levels of associated devices,
wherein the reverse diagnosis comprises:
according to the index data of the target associated equipment, whether the target associated equipment is abnormal or not is confirmed;
under the condition that the target associated equipment is determined to be abnormal, determining an adjacent user of the user, wherein the target associated equipment and the same-level associated equipment of the adjacent user have the same upper-level associated equipment;
according to the index data of the same-level associated equipment of the adjacent user, confirming whether the same-level associated equipment of the adjacent user is abnormal or not;
and when the indication data of the same-level associated equipment of the adjacent user is abnormal, taking the upper-level associated equipment as target associated equipment, and executing the reverse diagnosis aiming at the target associated equipment.
Further, before the reverse diagnosis, the method further comprises:
and establishing an index library based on the multi-stage association equipment of each user.
Further, the creating an index library based on the multi-level association device of each user includes:
inquiring a set of index data of the multilevel associated equipment of each user, abstracting three dimensional indexes of alarm, performance and flow based on the set of index data, establishing an index document library, and storing the index document library in the index library.
Further, after the index library is established based on the multi-level association device of each user, the method further includes: and when the index data of the multilevel associated equipment of the user is updated, synchronously updating the index document library in the index library based on the updated index data.
Further, the creating an index library based on the multi-level association device of each user includes:
querying structured data in the set of metric data of the multilevel associated device of each user;
establishing a mapping relation between fields in the index data set and corresponding values to obtain mapping fields;
forming a preset matching condition according to the corresponding value of the mapping field, and matching the input character string with the entries of the machine dictionary according to the preset matching condition;
and sequencing the entries of the machine dictionary, sequencing the entries according to the sequence of the occurrence frequency from high to low, generating an index document library, and storing the index document library into the index library.
Further, the synchronously updating the index document library in the index library includes:
obtaining increment alarm data according to the alarm reporting message of each user, and updating the increment alarm data into the index data set;
storing the increment alarm data into a change table;
and acquiring the increment alarm data, establishing an increment index document library according to the increment alarm data, and storing the increment index document library in the index library.
Further, the reverse diagnosis comprises: performing a reverse diagnosis based on a search mechanism, the search mechanism comprising:
inputting a query character string;
searching the index document library in the index library according to the query character string to find the index document library corresponding to the query character string;
and according to at least one of the dimension indexes, performing classified statistics on the index document library corresponding to the query character string, and outputting a classified statistical result.
An embodiment of the present invention further provides a home broadband network fault diagnosis apparatus, where the apparatus is configured to perform, for fault diagnosis of a user in a home broadband network, reverse diagnosis from a lowest-level associated device of the user, and use the lowest-level associated device of the user as a target associated device, where each user has multiple levels of associated devices, and the apparatus includes:
the target associated equipment abnormity confirming module is used for confirming whether the target associated equipment is abnormal or not according to the index data of the target associated equipment;
the system comprises an adjacent user confirmation module, a target association device and an adjacent user confirmation module, wherein the adjacent user confirmation module is used for confirming an adjacent user of a user under the condition that the target association device is determined to be abnormal, and the target association device and the same-level association device of the adjacent user have the same upper-level association device;
the same-level associated equipment abnormity confirming module is used for confirming whether the same-level associated equipment of the adjacent user is abnormal or not according to the index data of the same-level associated equipment of the adjacent user;
and the upper-level associated equipment abnormity confirmation module is used for taking the upper-level associated equipment as target associated equipment and returning the target associated equipment to the abnormity confirmation module under the condition that the indication data of the same-level associated equipment of the adjacent users is abnormal.
Further, the apparatus further comprises:
and the index base establishing module is used for establishing an index base based on the multi-stage associated equipment of each user.
Further, the index base establishing module includes:
the query unit is used for querying the index data set of the multilevel associated equipment of each user;
the establishing unit is used for abstracting three dimensional indexes of alarm, performance and flow based on the set of index data and establishing an index document library;
and the storage unit is used for storing the index document library into the index library.
Further, the apparatus further includes an index repository updating module, configured to update the index document repository in the index repository synchronously based on the updated index data when the index data of the multi-level associated device of the user is updated.
Further, the index repository establishing module further includes:
the structure extraction unit is used for inquiring the structured data in the set of the index data of the multi-level associated equipment of each user;
the field mapping unit is used for establishing a mapping relation between the fields in the index data set and the corresponding values to obtain mapping fields;
the matching unit is used for forming a preset matching condition according to the corresponding value of the mapping field and matching the input character string with the entry of the machine dictionary according to the preset matching condition;
and the index library generating unit is used for sequencing the entries of the machine dictionary, arranging the entries according to the sequence of the occurrence frequency from high to low, generating an index document library and storing the index document library into the index library.
Further, the index repository updating module comprises:
the data updating unit is used for obtaining increment alarm data according to the alarm reporting message of each user and updating the increment alarm data into the index data set;
the database trigger is used for storing the increment alarm data into a change table;
and the index base updating unit is used for acquiring the increment alarm data, establishing an increment index document base according to the increment alarm data and storing the increment index document base in the index base.
Further, the apparatus further includes an index search module, where the index search module includes:
an input unit for inputting a query string;
the search unit is used for searching the index document library in the index library according to the query character string and finding the index document library corresponding to the query character string;
and the output unit is used for carrying out classified statistics on the index document library corresponding to the query character string according to at least one of the dimension indexes and outputting a classified statistical result.
According to the technical scheme provided by the embodiment of the application, the broadband state of the adjacent user is diagnosed through single-user single-node complaint or fault association, a single means of reporting and troubleshooting by simply depending on equipment alarm is avoided, and the group effect is shown in a point-to-area mode, so that the node or the area of the network fault is deduced more accurately, the traditional positive fault diagnosis is supplemented beneficially, the invalid complaint of the user is reduced, and the fault definition efficiency is improved; and the method for intelligently inquiring a large amount of data with Lucene high performance and a real-time index synchronization mechanism are utilized to realize efficient instant intelligent diagnosis.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort.
Fig. 1 is a schematic diagram illustrating a home broadband network structure according to an embodiment of the present application;
fig. 2 is a schematic reverse diagnostic flow chart in a home broadband network fault diagnosis method according to an embodiment of the present application;
fig. 3 is a schematic partial flowchart of a home broadband network fault diagnosis method according to an embodiment of the present application;
fig. 4 is a schematic diagram illustrating the establishment of an index library in the home broadband network fault diagnosis method according to an embodiment of the present application;
fig. 5 is a schematic diagram of an updated index database in the home broadband network fault diagnosis method according to an embodiment of the present application;
fig. 6 is a schematic diagram of a search mechanism in a home broadband network fault diagnosis method according to an embodiment of the present application;
fig. 7 is a schematic diagram of a home broadband network fault diagnosis device according to a second embodiment of the present application.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The first embodiment is as follows:
multiple users access the whole network through a logic structure as shown in fig. 1, and each user does not exist singly and is intercommunicated. For example: a user of one floor belongs to a secondary optical splitter; a user of one building belongs to one primary optical splitter; subscribers of one cell belong to one OLT. Therefore, in the process of fault judgment, the data information of the adjacent users has definite guiding significance for a single user.
The embodiment of the invention provides a home broadband network fault diagnosis method, which is used for carrying out reverse diagnosis from the lowest-level associated equipment of a user in a home broadband network and taking the lowest-level associated equipment of the user as target associated equipment, wherein each user has a plurality of levels of associated equipment,
as shown in fig. 2, the reverse diagnosis may include the following steps S1-S4:
and S1, confirming whether the target related equipment has abnormity according to the index data of the target related equipment. If yes, go to S2. If not, the reverse diagnosis may be ended.
And S2, determining the adjacent user of the user, wherein the target associated device and the same upper-level associated device of the adjacent user have the same upper-level associated device.
And S3, confirming whether the same-level related equipment of the adjacent user is abnormal or not according to the index data of the same-level related equipment of the adjacent user. If yes, go to S4. If not, the reverse diagnosis may be ended.
S4, regarding the upper level association device as a target association device, executing S1 aiming at the target association device.
According to the logic of the method, the maximum of seven iterations are sequentially completed, namely, secondary light splitting, primary light splitting, a Passive Optical Network (PON) port of the OLT, a Private Virtual Local Area Network (SVLAN) of the OLT, the OLT equipment 500, the BAS port 600 and the BAS equipment 700. In S1, if the target associated device is normal, the iteration is ended, and at this time, if the target associated device is the lowest-level associated device of the user, it is determined that the user side has a single fault, and if the target associated device is not the lowest-level associated device of the user, it is determined that the next-level associated device of the target associated device has a fault. In S3, if the associated devices at the same level are normal, the iteration is ended, and it may be determined that the target associated device in S1 in the current iteration process has a fault.
Specifically, when the target associated device in S1 is the lowest-level associated device of user 1 in which any one of the users has a fault, the same-level associated device is the lowest-level associated device of user 1 that is in the same level as the target associated device, and the target associated device is associated with the same-level associated device through a previous-level associated device, for example, the previous-level associated device of the lowest-level target associated device is a second-level splitter, the previous-level associated device of the second-level splitter is a first-level splitter, the previous-level associated device of the first-level splitter is a PON port 300 of the OLT, the previous-level associated device of the PON port 300 of the OLT is an SVLAN400 of the OLT, the previous-level associated device of the SVLAN400 of the OLT is an OLT device 500 of the OLT, the previous-level associated device of the OLT device 500 is a BAS port 600, and the previous-level associated device of the BAS port. And circularly executing the steps from S1 to S4 until the BRAS equipment or the current target associated equipment is normal, and ending.
For example, when the iteration is sequentially performed from the second-level light splitting to the SVLAN400 of which the target associated device is located at the OLT, when S1 is performed, the target associated device is abnormal, and S2, S3 are continuously performed, and the same-level associated device of the target associated device in S3 is normal, it may be determined that the fault occurs at the PON port 300 of the OLT at this time, and the SVLAN400 of the OLT and its upper layer are normal, and the iteration may be stopped.
By inquiring service quality information reported by adjacent users of access equipment (ONU100 or MDU200, OLT, BRAS) associated with users, whether the same optical splitter, PON port, PON plate and BRAS have normal reported service quality indexes is judged in an auxiliary way, whether the optical splitter, PON port, PON plate and BRAS are normal or not is judged, whether a fault in a bound office or a fault at a user side is defined, and whether the fault specifically appears in a certain area range is confirmed. If the single fault at the user side is judged, the user can be guided to carry out local repair and non-common network problem, and the maintenance personnel is not required to carry out home processing. According to the method and the device, the broadband state of the adjacent user is diagnosed through the complaint or fault association of the single user and the single node, the single means of reporting the alarm and troubleshooting by simply relying on the equipment is avoided, the group effect is shown in a point-to-area mode, the node or the area of the network fault is deduced more accurately, the traditional forward fault diagnosis is supplemented beneficially, the invalid complaint of the user is reduced, and the fault delimiting efficiency is improved.
The method needs to establish a model for judging the target associated equipment; the model needs to store and retrieve over 100 types of resource information, alarm information, performance data and the like for a long time, and the total amount of data is huge for the provinces of million-level user quantity. If the performance of directly operating the data indexes is very low, an information model is established for a single node through a Lucene search engine in the calculation process, the big data retrieval capability is assisted to be improved, and the performance is effectively improved by the method.
Therefore, as shown in fig. 3, S1 also includes S101 and S102 before:
s101: and establishing an index library based on the multi-stage association equipment of each user.
S101 includes: inquiring a set of index data of the multi-level associated equipment, abstracting three dimensional indexes of alarm, performance and flow based on the set of index data, establishing an index, and storing the index in an index database. Although the index data in the database is structured data, the index data is not subjected to word segmentation, the relation between the character string and the document needs to be established, and an index needs to be created and stored in the index database in order to establish the relation.
S102: and when the index data of the multi-level associated equipment of the user is updated, synchronously updating the index document library in the index library based on the updated index data.
As shown in fig. 4, the step S101 specifically includes:
opening the connection: a free connection is obtained from a connection pool of the set of metric data.
And (3) inquiring data: querying structured data in the set of index data through SQL; in order to reduce the load and I/O pressure of a database server, a paging query mode is adopted to obtain data.
And (3) field mapping: and establishing a mapping relation between the fields in the index data set and the corresponding values to obtain mapping fields.
Lexical analysis: forming a preset matching condition according to the corresponding value of the mapping field, and matching the input character string with the entries of the machine dictionary according to the preset matching condition; if the current character string is found in the machine dictionary entry, the recognized entry is successfully output.
Semantic analysis: and analyzing corresponding values of the mapping fields according to entries, syntax and semantics in parallel, and processing ambiguity of word segmentation by using syntax and semantic information.
Word frequency statistics: combining all the corresponding values of the mapping fields, and carrying out word frequency statistics; the more frequently adjacent word matches occur, the more likely it is that a fixed word is formed. And performing weight calculation on the fixed entries for sequencing, wherein the fixed entries are ranked in front according to the ranking with high occurrence frequency, and the fixed entries are ranked in back according to the ranking with low occurrence frequency.
Creating an index: and generating an index document library and saving the index document library into the index library.
The full synchronization of the alarm data is realized by generating the index database for the first time, the incremental data synchronization needs to be completed by a database trigger, and the incremental data synchronization is realized by storing the incremental data, generating a change notification and the like. As shown in fig. 5, S102 includes:
updating data: updating the set of index data through an alarm report message;
the trigger stores incremental data: storing the increment alarm data into a change table by a database trigger;
and sending a change notice: acquiring incremental alarm data by adopting a Lucenu server;
returning incremental data: inquiring and returning changed data;
lexical analysis: forming a preset matching condition according to the corresponding value of the mapping field, and matching the input character string with the entries of the machine dictionary according to the preset matching condition;
semantic analysis: analyzing corresponding values of the mapping fields in parallel according to entries, syntax and semantics, and processing ambiguity of word segmentation by using syntax and semantic information;
word frequency statistics: combining all the corresponding values of the mapping fields, and carrying out word frequency statistics;
updating the index: and updating the index document library of the original index library.
As shown in fig. 6, preferably, the reverse diagnosis in the home broadband network fault diagnosis method in the present embodiment includes: and carrying out reverse diagnosis according to a search mechanism, wherein the search mechanism comprises:
a query string is entered.
Searching the index: the index is searched based on the query string.
The search index includes: performing lexical analysis on the query string to identify fixed terms and keywords, forming a syntax tree according to syntax rules of the query sentence, and finding at least one of the documents through merging and difference operations.
Hit indexing: searching the index, and finding out the document corresponding to the query character string;
outputting a statistical classification search result: and counting the query conditions of the input single entry according to the full field of the alarm, and outputting a classification counting result.
And (3) displaying data: and displaying the classification statistical result.
And viewing the classified search results.
Classifying the search request: and triggering a secondary search request according to the classification result. Searching the index: and triggering a secondary search request according to the classified search result.
Searching the index: and performing secondary lexical and semantic analysis according to the classification statistical result.
And (3) secondary hit indexing: and searching the index and finding the document corresponding to the index.
And outputting a result: and outputting the search result hit by the classified entry vocabulary entry to a display window to display data.
Example two:
as shown in fig. 7, an embodiment of the present invention further provides a home broadband network fault diagnosis apparatus 10, where the apparatus 10 is configured to perform, for fault diagnosis of a user in a home broadband network, reverse diagnosis from a lowest-level associated device of the user, and use the lowest-level associated device of the user as a target associated device, where each user has multiple-level associated devices, and the apparatus 10 includes: the device comprises a target associated device abnormity confirmation module 11, an adjacent user confirmation module 12, a same-level associated device abnormity confirmation module 13 and a previous-level associated device abnormity confirmation module 14. The working principle of the device 10 is the same as that of the first embodiment, and therefore, the description thereof is not repeated herein.
And the target associated device abnormality confirmation module 11 is configured to confirm whether the target associated device is abnormal according to the index data of the target associated device.
The adjacent user confirmation module 12 is configured to determine an adjacent user of the user when it is determined that the target associated device is abnormal, where the target associated device and a same-level associated device of the adjacent user have a same upper-level associated device.
And the same-level associated equipment abnormality confirmation module 13 is configured to confirm whether there is an abnormality in the same-level associated equipment of the adjacent user according to the index data of the same-level associated equipment of the adjacent user.
And the previous-level associated device abnormality confirmation module 14 is configured to, when the indication data of the same-level associated device of the adjacent user is abnormal, take the previous-level associated device as a target associated device, and return the target associated device to the abnormality confirmation module 11.
Preferably, the device 10 further comprises: the index database updating module is used for updating the index database and searching the index.
The index base establishing module is used for establishing an index base based on the multi-stage associated equipment of each user. The index base building module comprises: the query unit is used for querying the index data set of the multi-level associated equipment of each user; the establishing unit is used for abstracting three dimensional indexes of alarm, performance and flow based on the set of index data and establishing an index document library; and the storage unit is used for storing the index document library into the index library. Further comprising: the structure extraction unit is used for inquiring the structured data in the index data set of the multi-level associated equipment of each user; the field mapping unit is used for establishing a mapping relation between the fields in the index data set and the corresponding values to obtain mapping fields; the matching unit is used for forming a preset matching condition according to the corresponding value of the mapping field and matching the input character string with the entry of the machine dictionary according to the preset matching condition; and the index library generating unit is used for sequencing the entries of the machine dictionary, arranging the entries according to the sequence from high to low of the occurrence frequency, generating an index document library and storing the index document library into the index library.
The index database updating module is used for updating the index document database in the index database synchronously based on the updated index data when the index data of the multi-level associated equipment of the user is updated. The index base updating module comprises: the data updating unit is used for obtaining increment alarm data according to the alarm reporting message of each user and updating the increment alarm data into the index data set; the database trigger is used for storing the increment alarm data into the change table; and the index base updating unit is used for acquiring the increment alarm data, establishing an increment index document base according to the increment alarm data and storing the increment index document base in the index base.
The index search module comprises: an input unit for inputting a query string; the search unit is used for searching the index document library in the index library according to the query character string and finding the index document library corresponding to the query character string; and the output unit is used for carrying out classified statistics on the index document library corresponding to the query character string according to at least one of the dimension indexes and outputting a classified statistical result.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (14)
1. A home broadband network fault diagnosis method is characterized by comprising the following steps: for a user in the home broadband network, performing reverse diagnosis starting from the lowest level associated device of the user, taking the lowest level associated device of the user as a target associated device, wherein each user has multiple levels of associated devices,
wherein the reverse diagnosis comprises:
according to the index data of the target associated equipment, whether the target associated equipment is abnormal or not is confirmed;
under the condition that the target associated equipment is determined to be abnormal, determining an adjacent user of the user, wherein the target associated equipment and the same-level associated equipment of the adjacent user have the same upper-level associated equipment;
according to the index data of the same-level associated equipment of the adjacent user, confirming whether the same-level associated equipment of the adjacent user is abnormal or not;
and when the indication data of the same-level associated equipment of the adjacent user is abnormal, taking the upper-level associated equipment as target associated equipment, and executing the reverse diagnosis aiming at the target associated equipment.
2. The home broadband network fault diagnosis method according to claim 1, wherein the reverse diagnosis further comprises, before:
and establishing an index library based on the multi-stage association equipment of each user.
3. The home broadband network fault diagnosis method according to claim 2, wherein the building of the index library based on the multi-level association device of each of the subscribers comprises:
inquiring a set of index data of the multilevel associated equipment of each user, abstracting three dimensional indexes of alarm, performance and flow based on the set of index data, establishing an index document library, and storing the index document library in the index library.
4. The home broadband network fault diagnosis method according to claim 3, wherein after the building of the index library based on the multi-level association device of each of the users, further comprising: and when the index data of the multilevel associated equipment of the user is updated, synchronously updating the index document library in the index library based on the updated index data.
5. The home broadband network fault diagnosis method according to claim 4, wherein the building of the index base based on the multi-level association device of each of the subscribers comprises:
querying structured data in the set of metric data of the multilevel associated device of each user;
establishing a mapping relation between fields in the index data set and corresponding values to obtain mapping fields;
forming a preset matching condition according to the corresponding value of the mapping field, and matching the input character string with the entries of the machine dictionary according to the preset matching condition;
and sequencing the entries of the machine dictionary, sequencing the entries according to the sequence of the occurrence frequency from high to low, generating an index document library, and storing the index document library into the index library.
6. The home broadband network fault diagnosis method according to claim 5, wherein the synchronously updating the index document library in the index library comprises:
obtaining increment alarm data according to the alarm reporting message of each user, and updating the increment alarm data into the index data set;
storing the increment alarm data into a change table;
and acquiring the increment alarm data, establishing an increment index document library according to the increment alarm data, and storing the increment index document library in the index library.
7. The home broadband network fault diagnosis method of claim 6, wherein the reverse diagnosis comprises: performing a reverse diagnosis based on a search mechanism, the search mechanism comprising:
inputting a query character string;
searching the index document library in the index library according to the query character string to find the index document library corresponding to the query character string;
and according to at least one of the dimension indexes, performing classified statistics on the index document library corresponding to the query character string, and outputting a classified statistical result.
8. A home broadband network fault diagnosis apparatus, configured to perform, for a user in a home broadband network, a reverse diagnosis starting from a lowest-level associated device of the user, with the lowest-level associated device of the user as a target associated device, where each user has multiple levels of associated devices, the apparatus comprising:
the target associated equipment abnormity confirming module is used for confirming whether the target associated equipment is abnormal or not according to the index data of the target associated equipment;
the system comprises an adjacent user confirmation module, a target association device and an adjacent user confirmation module, wherein the adjacent user confirmation module is used for confirming an adjacent user of a user under the condition that the target association device is determined to be abnormal, and the target association device and the same-level association device of the adjacent user have the same upper-level association device;
the same-level associated equipment abnormity confirming module is used for confirming whether the same-level associated equipment of the adjacent user is abnormal or not according to the index data of the same-level associated equipment of the adjacent user;
and the upper-level associated equipment abnormity confirmation module is used for taking the upper-level associated equipment as target associated equipment and returning the target associated equipment to the abnormity confirmation module under the condition that the indication data of the same-level associated equipment of the adjacent users is abnormal.
9. The home broadband network failure diagnosis apparatus according to claim 8, wherein the apparatus further comprises:
and the index base establishing module is used for establishing an index base based on the multi-stage associated equipment of each user.
10. The home broadband network failure diagnosis device according to claim 9, wherein the index repository establishing module includes:
the query unit is used for querying the index data set of the multilevel associated equipment of each user;
the establishing unit is used for abstracting three dimensional indexes of alarm, performance and flow based on the set of index data and establishing an index document library;
and the storage unit is used for storing the index document library into the index library.
11. The home broadband network fault diagnosis device according to claim 10, wherein the device further comprises an index repository updating module, configured to update the index document repository in the index repository synchronously based on the updated index data when the index data of the multi-level associated device of the user is updated.
12. The home broadband network failure diagnosis device according to claim 11, wherein the index repository establishing module further comprises:
the structure extraction unit is used for inquiring the structured data in the set of the index data of the multi-level associated equipment of each user;
the field mapping unit is used for establishing a mapping relation between the fields in the index data set and the corresponding values to obtain mapping fields;
the matching unit is used for forming a preset matching condition according to the corresponding value of the mapping field and matching the input character string with the entry of the machine dictionary according to the preset matching condition;
and the index library generating unit is used for sequencing the entries of the machine dictionary, arranging the entries according to the sequence of the occurrence frequency from high to low, generating an index document library and storing the index document library into the index library.
13. The home broadband network failure diagnosis device according to claim 12, wherein the index repository updating module includes:
the data updating unit is used for obtaining increment alarm data according to the alarm reporting message of each user and updating the increment alarm data into the index data set;
the database trigger is used for storing the increment alarm data into a change table;
and the index base updating unit is used for acquiring the increment alarm data, establishing an increment index document base according to the increment alarm data and storing the increment index document base in the index base.
14. The home broadband network failure diagnosis apparatus of claim 13, wherein the apparatus further comprises an index search module, the index search module comprising:
an input unit for inputting a query string;
the search unit is used for searching the index document library in the index library according to the query character string and finding the index document library corresponding to the query character string;
and the output unit is used for carrying out classified statistics on the index document library corresponding to the query character string according to at least one of the dimension indexes and outputting a classified statistical result.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH07245609A (en) * | 1994-03-07 | 1995-09-19 | Nippon Telegr & Teleph Corp <Ntt> | Method for diagnosing fault of network based on network fault propagation model |
| CN101640617A (en) * | 2008-07-30 | 2010-02-03 | 华为技术有限公司 | Method, system and device for detecting and positioning network failure |
| CN101777997A (en) * | 2010-01-21 | 2010-07-14 | 中兴通讯股份有限公司 | Method and system for switching flow of network link |
| CN101924697A (en) * | 2010-06-30 | 2010-12-22 | 北京科技大学 | Two-way startup recovery method based on link back backtracking strategy |
| CN104597892A (en) * | 2014-12-16 | 2015-05-06 | 北京航天测控技术有限公司 | Hierarchical fault diagnosis method for electronic information equipment |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101407943B1 (en) * | 2010-06-23 | 2014-06-17 | 한국전자통신연구원 | Bottom-up multilayer network recovery method based on Root-Cause analysis |
-
2017
- 2017-01-09 CN CN201710013936.1A patent/CN108289031B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH07245609A (en) * | 1994-03-07 | 1995-09-19 | Nippon Telegr & Teleph Corp <Ntt> | Method for diagnosing fault of network based on network fault propagation model |
| CN101640617A (en) * | 2008-07-30 | 2010-02-03 | 华为技术有限公司 | Method, system and device for detecting and positioning network failure |
| CN101777997A (en) * | 2010-01-21 | 2010-07-14 | 中兴通讯股份有限公司 | Method and system for switching flow of network link |
| CN101924697A (en) * | 2010-06-30 | 2010-12-22 | 北京科技大学 | Two-way startup recovery method based on link back backtracking strategy |
| CN104597892A (en) * | 2014-12-16 | 2015-05-06 | 北京航天测控技术有限公司 | Hierarchical fault diagnosis method for electronic information equipment |
Non-Patent Citations (1)
| Title |
|---|
| 《：基于贝叶斯网络的分层网络故障诊断》;王占孔 等;《软件》;20111231;全文 * |
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