CN110752938B - Intelligent fault positioning method and system for VOLTE (Voice over Long term evolution) service - Google Patents
Intelligent fault positioning method and system for VOLTE (Voice over Long term evolution) service Download PDFInfo
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Abstract
The invention provides a method and a system for intelligently positioning faults of VOLTE (voice over long term evolution) service, wherein the method comprises the following steps: acquiring a corresponding dynamic end-to-end service chain of a user in different preset time periods according to the signaling data of the user; acquiring network elements in the abnormal service chain in each preset time period, and performing duplicate removal processing on the network elements according to names to obtain a network element set; calculating the abnormal probability corresponding to each network element by adopting a preset maximum matching rule and an influence factor rule; sorting each type of network elements according to the sequence of the abnormal probabilities from high to low, and screening the network elements which are ranked first N as abnormal fault points if the sum of the abnormal probabilities corresponding to the network elements which are ranked first N is greater than a preset threshold; and if the abnormal fault point simultaneously comprises a first service network element and a first bearer network router corresponding to the first service network element, deleting the first service network element from the abnormal fault point. The method and the system can improve the accuracy of fault positioning and reduce the maintenance cost.
Description
Technical Field
The invention relates to the technical field of communication, in particular to a method and a system for intelligently positioning faults of a VOLTE service.
Background
VOLTE is a LTE voice solution, is a new technology and new service, needs EPC network, IMS network and CS network three networks to work cooperatively, and at present, there is no processing method capable of quickly processing faults of EPC, IMS and CS network in a correlated manner, aiming at VOLTE service related faults, only a traditional fault processing method can be adopted, multi-system information is collected, and manual judgment and positioning are detailed as follows: 1) analyzing the network element information (static network element during registration) registered by the complaint user through the HSS, and judging whether the network element has centralization; 2) checking whether related alarms, performance indexes and engineering operations exist in EPC, IMS and CS networks through multiple sets of network managers; 3) and manually positioning and checking the fault point by using expert experience through complaint phenomena, alarm indexes, dial-testing results and engineering information.
Network faults are often complained due to the fact that a large number of user services are abnormally used, and in the traditional fault locating process, the method for analyzing the information of the registered network elements of the complained users and searching for concentrated network elements is a quick and effective fault locating means. The VOLTE service is used as a new network technology, a pure PS-based LTE network provides high-quality voice service for users, the flow is complex, the service scenes are multiple, and the problem of effective positioning cannot be solved through traditional registered network element analysis. Meanwhile, the user registration network element analysis is a static analysis, which cannot represent the current state of the user and further cannot reflect the real service perception of the user, for example, the voice service of the user not only relates to the local terminal registration network element, but also needs the cooperative cooperation of the opposite terminal network.
The existing VOLTE service fault processing method has the following defects: 1) a fault processing method of the VOLTE service of the system is lacked, the fault processing experience of the traditional EPC network and the CS network can only be carried out, the fault processing method cannot be suitable for new characteristics of the VOLTE new service, and the fault processing efficiency is low; 2) a user registration service chain is obtained through an HSS, and the real end-to-end service chain of a user complaint service cannot be truly reflected; 3) relevant information of fault processing such as alarm, index, dial testing, engineering and the like comes from a plurality of systems, is very dispersed, needs to be acquired manually, is tedious and time-consuming, and is easy to make mistakes and lack numbers; 4) the collected fault related information needs manual correlation processing, expert experience is needed, positioning processing is slow, the requirement on the skills of maintenance personnel is high, and maintenance cost is high.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a method and a system for intelligently positioning faults of VOLTE service.
In a first aspect, an embodiment of the present invention provides a method for intelligently positioning a fault of a VOLTE service, where the method includes:
acquiring a corresponding dynamic end-to-end service chain of each user in different preset time periods according to the signaling data of each user; wherein the service chain comprises: registering a service chain and calling the service chain;
acquiring network elements in abnormal service chains of a plurality of users in each preset time period, and performing duplicate removal processing on the network elements according to names to obtain a network element set; wherein the network element comprises: the router comprises service network elements and a load-bearing network router corresponding to each service network element;
calculating the abnormal probability corresponding to each network element in the network element set by adopting a preset maximum matching rule and a preset influence factor rule;
sorting each type of network elements according to the sequence of the corresponding abnormal probability from high to low, and screening the network elements which are ranked at the top N as abnormal fault points if the sum of the abnormal probabilities corresponding to the network elements which are ranked at the top N is greater than a preset threshold; wherein N is a positive integer;
and if the abnormal fault point simultaneously comprises a first service network element and a first bearer network router corresponding to the first service network element, deleting the first service network element from the abnormal fault point.
In a second aspect, an embodiment of the present invention provides an intelligent positioning system for VOLTE faults, where the system includes:
the first obtaining module is used for obtaining a corresponding dynamic end-to-end service chain of each user in different preset time periods according to the signaling data of each user; wherein the service chain comprises: registering a service chain and calling the service chain;
the second acquisition module is used for acquiring network elements in the abnormal service chains of the multiple users in each preset time period and carrying out duplicate removal processing on the network elements according to names to obtain a network element set; wherein the network element comprises: the router comprises service network elements and a load-bearing network router corresponding to each service network element;
the computing module is used for computing the abnormal probability corresponding to each network element in the network element set by adopting a preset maximum matching rule and a preset influence factor rule;
the screening module is used for sequencing each type of network elements from high to low according to the corresponding abnormal probability, and screening the network elements which are ranked at the top N as abnormal fault points if the sum of the abnormal probabilities corresponding to the network elements which are ranked at the top N is greater than a preset threshold value; wherein N is a positive integer;
and a deleting module, configured to delete the first service network element from the abnormal fault point if the abnormal fault point includes both the first service network element and the first bearer network router corresponding to the first service network element.
In a third aspect, an embodiment of the present invention provides an electronic device, where the device includes a memory and a processor, where the processor and the memory complete communication with each other through a bus; the memory stores program instructions executable by the processor, and the processor calls the program instructions to perform the method for intelligently locating a fault in a VOLTE service according to the first aspect.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for intelligently positioning a fault of a VOLTE service in the first aspect.
According to the method and the system for intelligently positioning the fault of the VOLTE service, provided by the embodiment of the invention, the dynamic end-to-end service chain of the user is obtained according to the signaling data of the user, the real perception of the service of the user can be reflected, the fault positioning treatment is more accurate, the maximum matching rule, the influence factor rule and the bearing priority rule are comprehensively used through curing the expert experience, the abnormal fault point is intelligently positioned, the skill requirement of maintenance personnel can be reduced, the maintenance cost is reduced, and the maintenance efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flowchart of a method for intelligently positioning a fault of a VOLTE service according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a fault intelligent positioning system for VOLTE services according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. 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 invention.
Fig. 1 is a flowchart of a fault intelligent positioning method for VOLTE service according to an embodiment of the present invention, and as shown in fig. 1, the method includes:
step 10, acquiring a corresponding dynamic end-to-end service chain of each user in different preset time periods according to the signaling data of each user; wherein the service chain comprises: registering a service chain and calling the service chain;
step 11, obtaining network elements in the abnormal service chains of a plurality of users in each preset time period, and performing deduplication processing on the network elements according to names to obtain a network element set; wherein the network element comprises: the router comprises service network elements and a load-bearing network router corresponding to each service network element;
Specifically, the VOLTE services used by the user at different times may be different, where each VOLTE service corresponds to one service flow, and the system may obtain signaling data of the user in each service flow, for example, the system may obtain a call ticket record in each service flow, and determine the service used by the user according to the call ticket record. The services used by the user may include: the method comprises the steps of registering services and calling services, wherein one registering service corresponds to one registering service chain, one calling service corresponds to one calling service chain, and each service chain can comprise a plurality of network element information.
The system can obtain the registration service chain of the user according to the call ticket record related to the registration service flow. Specifically, the system can acquire service network elements of which the types are P-CSCF, I-CSCF, S-CSCF and ATS respectively in the registered service chain according to the SIP ticket related to the registered service; acquiring a service network element with the type of HSS in a registration service chain according to a Cx ticket related to the registration service; acquiring a service network element with the type of PCRF in a registration service chain according to a Gx call ticket related to the registration service; and acquiring service network elements of which the types are ECGI, ENB, MME and SAEGW in the registration service chain according to the S1-MME call ticket related to the registration service. The system can integrate a registration service chain of a user according to the four call tickets, and the registration service chain can comprise one or more service network elements with the types of ECGI, ENB, MME, SAEGW, PCRF, HSS, P-CSCF, I-CSCF, S-SCCF and ATS.
The system can obtain the call service chain of the user according to the call ticket record related to the call service flow. Specifically, the system can obtain service network elements of types of calling P-CSCF, calling S-CSCF, calling ATS, called I-CSCF, called S-CSCF and called P-CSCF in the call service chain according to the SIP ticket related to the call service, and obtain the call service chain of the user.
The system may obtain the dynamic end-to-end service chain of each user in different preset time periods according to the signaling data of each user in different preset time periods according to the method. In each preset time period, one user may correspond to one or more service chains. The preset time period can be specifically set, for example, the system can acquire a dynamic end-to-end service chain of each user in the preset time period of 9: 00-9: 05.
For each preset time period, the service chain of the user may be a normal service chain or an abnormal service chain. The system may screen the abnormal service chains corresponding to the multiple users within the preset time period, and obtain the network element corresponding to each abnormal service chain, where the network element includes: service network elements and a bearer network router corresponding to each service network element. The system may first perform deduplication processing on all the obtained network elements according to names, and store the remaining network elements in a network element set.
The system can calculate the abnormal probability of each network element in the network element set by adopting a preset maximum matching rule and a preset influence factor rule. And then, sequencing the service network elements of the same type according to the sequence of the abnormal probabilities from high to low, and screening the network elements of the N-th rank as abnormal fault points if the sum of the abnormal probabilities corresponding to the network elements of the N-th rank is greater than a preset threshold. N is a positive integer, and may be set to 3, for example, and the preset threshold may also be specifically set, and may be set to 60%, for example.
For example, there are 30 service network elements of the types MME in the network element set, the system may sort the 30 MME service network elements in order from high to low abnormal probability, if the MME service network elements of the top 3 are MME1, MME2, and MME3, respectively, and if the sum of the abnormal probabilities corresponding to the 3 service network elements is 75%, and 75% is greater than 60%, the system may screen the 3 service network elements as abnormal failure points.
The abnormal fault points screened by the system according to the method may simultaneously include a service network element and a bearer network router corresponding to the service network element. The service network element may be denoted as a first service network element, and the bearer network router corresponding to the first service network element may be denoted as a first bearer network router. At this time, the system may preferentially consider that the router of the bearer network is abnormal according to a bearer priority principle, and delete the first service network element from the abnormal fault point.
For example, the system screens both the service network element MME1 and the bearer network router R1 corresponding to the MME1 as abnormal points of failure according to the above method, and then the system may delete the service network element MME1 from the abnormal points of failure according to a bearer priority principle.
According to the intelligent fault positioning method for the VOLTE service, provided by the embodiment of the invention, the dynamic end-to-end service chain of the user is obtained according to the signaling data of the user, the real service perception of the user can be reflected, the fault positioning processing is more accurate, the maximum matching rule, the influence factor rule and the bearing priority rule are comprehensively used through curing the expert experience, the abnormal fault point is intelligently positioned, the skill requirement of maintenance personnel can be reduced, the maintenance cost is reduced, and the maintenance efficiency is improved.
Optionally, on the basis of the foregoing embodiment, the calculating, by using a preset maximum matching rule and a preset influence factor rule, an abnormal probability corresponding to each network element in the network element set includes:
calculating the first abnormal probability of each service network element by adopting the maximum matching rule;
calculating a second abnormal probability of each service network element and a second abnormal probability of each bearing network router by adopting the influence factor rule;
and obtaining the abnormal probability of each service network element according to the first abnormal probability and the second abnormal probability of each service network element, and taking the second abnormal probability of the router of the bearer network as the abnormal probability of the router of the bearer network.
Specifically, the network elements in the network element set may include service network elements and a bearer network router, and for each service network element, the system may calculate a first abnormal probability of the service network element by using a preset maximum matching rule, and may calculate a second abnormal probability of the service network element by using a preset influence factor rule.
For each bearer network router in the network element set, the system may calculate the second abnormal probability of the bearer network router by using a preset impact factor rule.
The system can obtain the abnormal probability of the service network element according to the first abnormal probability and the second abnormal probability of the service network element, and the second abnormal probability of each bearing network router is used as the second abnormal probability of the bearing network router.
For example, the first abnormal probability corresponding to a service network element in the network element set is P1ijThe second anomaly probability is P2ijThen the system can obtain the abnormal probability P of the service network element according to the following formulaij:
If the second abnormal probability corresponding to one bearer network router in the network element set is P, the system may use P as the abnormal probability of the bearer network router.
The system can obtain the abnormal probability of each network element in the network element set according to the method.
According to the method for intelligently positioning the faults of the VOLTE service, provided by the embodiment of the invention, the first abnormal probability of each service network element is calculated by adopting a maximum matching rule, the second abnormal probability of each service network element and the second abnormal probability of each bearing network router are calculated by adopting an influence factor rule, the abnormal probability of each service network element is obtained according to the first abnormal probability and the second abnormal probability of each service network element, and the second abnormal probability of the bearing network router is used as the abnormal probability of the bearing network router, so that the method is more scientific.
Optionally, on the basis of the foregoing embodiment, the calculating, by using the maximum matching rule, the first anomaly probability of each service network element includes:
for each service network element in the network element set, determining a first type of the service network element and a first abnormal service chain to which the service network element belongs;
counting a first number of first type service network elements in the network element set and the first abnormal service chain;
counting the second number of the first type of service network elements in all abnormal service chains in the network element set;
and obtaining the first probability of the service network element according to the first number and the second number.
Specifically, the system may calculate the first anomaly probability of one service network element in the network element set according to the following method.
The service network elements in the network element set may be from one or more abnormal service chains, and each service network element has a specific network element type, for example, may be an MME, a P-CSCF, an I-CSCF, or an ATS.
The system can determine each serviceThe type of the network element and the abnormal service chain to which the network element belongs, for example, a service network element in the network element set may be written as: ne (line of contact)ikThe network element type of the service network element is TiThe abnormal service chain is a service chain k.
The system can count the type of the service chain k in the network element set as TiThe number of the service network elements can be recorded as a first number Fik. The system can also count the type T in all abnormal service chains in the network element setiThe number of the service network elements can be recorded as a second numberThe system can calculate the service network element Ne according to the following formulaikFirst anomaly probability P ofik:
The system may calculate the first anomaly probability of each service network element in the network element set according to the above method.
In the method for intelligently locating a fault of a VOLTE service provided by the embodiment of the present invention, for each service network element in a network element set, a first type of the service network element and a first abnormal service chain to which the service network element belongs are determined, a first number of the service network elements of the first type in the first abnormal service chain in the network element set and a second number of the service network elements of the first type in all the abnormal service chains are counted, and a first probability of the service network element is obtained according to the first number and the second number, so that the method is more scientific.
Optionally, on the basis of the foregoing embodiment, the calculating, by using the impact factor rule, the second abnormal probability of each service network element includes:
acquiring an abnormal event corresponding to each service network element in the network element set; wherein the exception event comprises: equipment alarm, performance index, dial testing verification and engineering operation;
dividing each type of abnormal event into three levels according to a preset rule;
for each service network element, calculating the probability of the four types of abnormal events by adopting a preset formula according to the type and the level of the corresponding abnormal event;
and obtaining a second abnormal probability of the service network element according to the four types of abnormal event probabilities.
Specifically, the system may calculate the second anomaly probability of each service network element in the network element set according to the following method.
Firstly, the system can obtain an abnormal event corresponding to each service network element in the network element set from the database, wherein the abnormal event can be divided into four types, which are respectively: equipment alarm, performance index, dial testing verification and engineering operation.
The system can regard equipment alarm, performance index, dial testing verification and engineering operation as 4 influence factors x1,x2,x3,x4The method is divided into a first-level, a second-level and a third-level for each type of abnormal event.
Specifically, the system may divide the device alarm into three levels according to the service impact degree, for example, the device restart and the link break may be set as a first-level device alarm; the system can divide the performance index into three levels according to different indexes and cracking degrees, for example, the service success rate lower than 30% can be set as a first-level problem; the system can divide the dial testing verification into three levels according to the cracking degree, for example, the success rate lower than 30% can be set as a first-level problem; the system may classify the engineering operation into three levels according to importance, for example, important engineering may be set as a first level problem.
For each influence factor xmWherein, m is 1,2,3,4, according to the first, second and third problem conditions, respectively calculating the corresponding four types of abnormal event probability P according to the following formulam:
Pm=Pm1+Pm2+Pm3
Wherein:
wherein, Xm1,Xm2,Xm3The first, second and third problem sets, card (X), representing the m-th influencing factor, respectivelymn) Indicating the number of such questions.
The system can then determine the probability of an abnormal event P according to the four types mentioned above1、P2、P3And P4Obtaining a second abnormal probability of the service network element according to the following formula:
the system can calculate the second abnormal probability of each service network element in the network element set and the second abnormal probability of each bearer network router according to the method.
According to the method for intelligently positioning the fault of the VOLTE service, provided by the embodiment of the invention, the abnormal event corresponding to each service network element in the network element set is obtained, each type of abnormal event is divided into three levels according to the preset rule, for each network element, the probabilities of four types of abnormal events are calculated by adopting the preset formula according to the type and the level of the corresponding abnormal event, and the second abnormal probability of the network element is obtained according to the probabilities of the four types of abnormal events, so that the method is more scientific.
Optionally, on the basis of the foregoing embodiment, the method further includes:
determining VOLTE service corresponding to each user and service result corresponding to each VOLTE service according to a service chain of the user; wherein the service result comprises: normal, failure and timeout;
and displaying the VOLTE service and the service result corresponding to the plurality of users in each preset time period in a matrix form to obtain a signaling matrix.
Specifically, after acquiring a dynamic end-to-end service chain of each user in different preset time periods according to the method described in the above embodiment, the user may determine, according to the acquired service chain, the VOLTE service corresponding to the user in different preset time periods and the service result corresponding to each VOLTE service.
One registration service chain indicates that the user uses a side registration service, one call service chain indicates that the user uses a call service, and the result of each service can be normal, failure or connection overtime.
The system can present the services used by all users in each preset time period and the corresponding service results in a matrix form to obtain a signaling matrix. Each row in the signaling matrix represents a user, each column represents a preset time period, and the signaling matrix can show which services are used by each user in a certain specific time period and what the service result of each service is. The services used by the user may include: registration, calling and calling, etc., the system may use different colors to indicate different service results, for example, green may be used to indicate normal, red may be used to indicate failure, and yellow may be used to indicate timeout. The abnormal service conditions of the user can be visually displayed through the signaling matrix, such as whether the abnormal services are concentrated or not, whether all the abnormal services are unavailable for calling or not, and whether all the abnormal services start to be abnormal at a certain time point or not.
According to the method for intelligently positioning the faults of the VOLTE service, the VOLTE service corresponding to each user and the service result corresponding to each VOLTE service are determined according to the service chain of the user, the VOLTE service and the service result corresponding to a plurality of users in each preset time period are displayed in a matrix mode, a signaling matrix is obtained, the abnormal conditions of the services of the users can be intuitively mastered through the signaling matrix, and convenience is provided for subsequent fault processing.
Optionally, on the basis of the foregoing embodiment, the method further includes:
based on the bearer network, adopting a preset shortest path algorithm to draw an end-to-end service chain topological graph between a service network element in each service chain and a corresponding bearer network router; in the drawing process, if a public carrying network router exists, deleting a topological graph of an upper layer of the public carrying network router;
and loading corresponding key information and abnormal events for each service chain, each service network element and each bearing network router on the end-to-end service chain topological graph.
Specifically, after the system obtains the dynamic end-to-end service chain of the user, an end-to-end service chain topological graph can be drawn according to the following method based on the bearer network and the bearer network router corresponding to each service network element in the service chain.
The service network elements in the service chain are mainly loaded through a China Mobile IP bearer network (IPNET) and a China Mobile Internet network (CMNET), the network architectures of the IPNET and the CMNET are basically the same, the IPNET and the CMNET can be divided into a core layer, a convergence layer, an access layer and a user edge layer from an upper layer to a lower layer, and routers of the bearer networks corresponding to the four layers can be respectively provided with a number R1、R2、R3And R4And (4) showing.
The system can draw an end-to-end service chain topological graph between the service network element in each service chain and the corresponding bearing network router according to a minimum path algorithm. The method comprises the following specific steps:
for a service network element NejBased on the service chain topological graph between the service network element and the corresponding router of the bearing network in the sequence from the lower layer to the upper layer, the path is drawn as follows: ne (line of contact)j——R4j/R4j+1—R3j/R3j+1—R2j/R2j+1—R1j/R1j+1. Wherein R is4j/R4j+1Is a user edge layer and a service network element NejCorresponding bearer network router pair, R4j/R4j+1Is in the access layer andservice network element NejCorresponding bearer network router pair, R4j/R4j+1Is a service network element Ne in the convergence layerjCorresponding bearer network router pair, R4j/R4j+1Is a core layer and a service network element NejA corresponding pair of bearer network routers. In the drawing process, if a common bearer network router exists between two or more service network elements, deleting the upper-layer topological graph of the common bearer network router. If no common bearing network router exists, all service chain topological graphs are reserved.
In order to beautify the presentation, the system may present each service network element type in a circular manner with a carrying network cloud as a center, and present each specific service network element in a sector form according to a sequence of MME, SAEGW, PCRF, ATS, ISBG, PSBC, and HSS from the left down, and may present 3 service network elements on a topological graph by default, and hide other service network elements.
The system can load corresponding key information and abnormal events for each service chain, each service network element and each bearing network router on an end-to-end service chain topological graph generated based on actual service of a user to form a visual dynamic topological monitoring graph and comprehensively control the state of the network elements.
According to the method for intelligently positioning the faults of the VOLTE service, provided by the embodiment of the invention, an end-to-end service chain topological graph between a service network element in each service chain and a corresponding router of a bearing network is drawn by adopting a preset shortest path algorithm based on the bearing network, and corresponding key information and abnormal events are loaded for each service chain, each service network element and each router of the bearing network on the topological graph, so that the topological graph can be more visually presented, and a point represents a network element comprising the service network element and the router of the bearing network; the line represents a link, and both the network element and the link can be loaded with abnormal events, such as link load and the like; and each network element or link loads key information and abnormal events, and outputs network element preliminary diagnosis information according to the current state, such as 'XX engineering operation exists in the network element, please check'. The system can also be distinguished by colors, wherein red represents abnormal, green represents normal, and gray represents that data is not acquired; the system can select proper alarms and indexes to present, select and present corresponding alarms and indexes according to different network elements and different scenes, and carry out hierarchical management on the alarms and indexes; defining analysis rules for abnormal events, if corresponding threshold values are set for alarm and index, and if the threshold values are exceeded, determining that the abnormal events are abnormal; analyzing the correlation between engineering operation and alarm complaints, and the like; one 'sand table' visually presents all the information of the fault, and meanwhile, the subsequent remote scheduling processing directly through the 'sand table' is carried out, such as directly restarting a certain network element node. Starting from the real service of a complaint user, visually presenting abnormal service related network elements (including EPC, IMS and CS service network elements, IPNET routers and the like) through an end-to-end topological graph, loading alarm, index, dial test and engineering related information, presenting originally scattered multi-system information in a topological graph mode in a related mode, and finally visually presenting all information of a fault scene to a network expert in a sand table mode in the part, thereby facilitating fault positioning and dispatching command processing.
Fig. 2 is a schematic structural diagram of a fault intelligent positioning system for VOLTE services provided in an embodiment of the present invention, and as shown in fig. 2, the system includes: a first obtaining module 20, a second obtaining module 21, a calculating module 22, a screening module 23, and a deleting module 24, wherein:
the first obtaining module 20 is configured to obtain, according to the signaling data of each user, a corresponding dynamic end-to-end service chain of each user in different preset time periods; wherein the service chain comprises: registering a service chain and calling the service chain; the second obtaining module 21 is configured to obtain network elements in the abnormal service chains of the multiple users in each preset time period, and perform deduplication processing on the network elements according to names to obtain a network element set; wherein the network element comprises: the router comprises service network elements and a load-bearing network router corresponding to each service network element; the calculating module 22 is configured to calculate an abnormal probability corresponding to each network element in the network element set by using a preset maximum matching rule and a preset influence factor rule; the screening module 23 is configured to sort each type of network element according to a sequence from high to low of the corresponding abnormal probability, and if a sum of the abnormal probabilities corresponding to the network element of N before ranking is greater than a preset threshold, screen the network element of N before ranking as an abnormal fault point; wherein N is a positive integer; the deleting module 24 is configured to delete the first service network element from the abnormal fault point if the abnormal fault point includes both the first service network element and the first bearer network router corresponding to the first service network element.
Specifically, the intelligent positioning system for VOLTE faults provided by the embodiment of the present invention may include: a first obtaining module 20, a second obtaining module 21, a calculating module 22, a screening module 23 and a deleting module 24.
The first obtaining module 20 may obtain a dynamic end-to-end service chain of each user in different preset time periods according to signaling data of each user in different preset time periods. In each preset time period, one user may correspond to one or more service chains. The preset time period can be specifically set, for example, the system can acquire a dynamic end-to-end service chain of each user in the preset time period of 9: 00-9: 05.
For each preset time period, the service chain acquired by the first acquiring module 20 may be a normal service chain or an abnormal service chain. The second obtaining module 21 may screen the abnormal service chains corresponding to the multiple users in the preset time period, and obtain the network element corresponding to each abnormal service chain, where the network element includes: service network elements and a bearer network router corresponding to each service network element. The second obtaining module 21 may first perform deduplication processing on all obtained network elements according to names, and store the remaining network elements in a network element set.
The calculating module 22 may calculate the abnormal probability corresponding to each network element in the network element set by using a preset maximum matching rule and a preset influence factor rule. The screening module 23 may sort the service network elements of the same type in order from high to low in the abnormal probability, and if the sum of the abnormal probabilities corresponding to the network element N before the ranking is greater than a preset threshold, screen the network element N before the ranking as an abnormal fault point. Wherein N is a positive integer, and may be set to 3, for example, and the preset threshold may be specifically set to 60%, for example.
For example, there are 30 service network elements of the types MME in the network element set, the system may sort the 30 MME service network elements in order from high to low abnormal probability, if the MME service network elements of the top 3 are MME1, MME2, and MME3, respectively, and if the sum of the abnormal probabilities corresponding to the 3 service network elements is 75%, and 75% is greater than 60%, the system may screen the 3 service network elements as abnormal failure points.
The screening module 23 may also include a service network element and a bearer network router corresponding to the service network element in the abnormal fault points screened by the method. The service network element may be denoted as a first service network element, and the bearer network router corresponding to the first service network element may be denoted as a first bearer network router. The deleting module 24 may preferentially consider that the router of the bearer network is abnormal according to a bearer priority principle, and delete the first service network element from the abnormal fault point.
For example, the screening module 23 screens both the service network element MME1 and the bearer network router R1 corresponding to the MME1 as the abnormal fault point according to the above method, and the deleting module 24 may delete the service network element MME1 from the abnormal fault point according to the bearer priority principle.
The functions of the intelligent positioning system for VOLTE faults provided by the embodiments of the present invention refer to the above method embodiments specifically, and are not described herein again.
According to the intelligent fault positioning system for the VOLTE service, provided by the embodiment of the invention, the dynamic end-to-end service chain of the user is obtained according to the signaling data of the user, the real perception of the service of the user can be reflected, the fault positioning processing is more accurate, the maximum matching rule, the influence factor rule and the bearing priority rule are comprehensively used by solidifying the expert experience, the abnormal fault point is intelligently positioned, the skill requirement of maintenance personnel can be reduced, the maintenance cost is reduced, and the maintenance efficiency is improved.
Optionally, on the basis of the foregoing embodiment, the calculation module includes: a first computation submodule, a second computation submodule, and a third computation submodule, wherein:
the first calculation submodule is used for calculating the first abnormal probability of each service network element by adopting the maximum matching rule; the second calculation submodule is used for calculating a second abnormal probability of each service network element and a second abnormal probability of each bearing network router by adopting the influence factor rule; and the third calculation submodule is used for obtaining the abnormal probability of each service network element according to the first abnormal probability and the second abnormal probability of each service network element, and taking the second abnormal probability of the bearing network router as the abnormal probability of the bearing network router.
Specifically, the computing module described in the above embodiment may include: the device comprises a first calculation submodule, a second calculation submodule and a third calculation submodule.
Specifically, the network elements in the network element set may include service network elements and a bearer network router, and for each service network element, the first calculating sub-module may calculate the first abnormal probability of the service network element by using a preset maximum matching rule, and the second calculating sub-module may calculate the second abnormal probability of the service network element by using a preset influence factor rule.
For each bearer network router in the network element set, the second calculation sub-module may calculate the second abnormal probability of the bearer network router by using a preset influence factor rule.
The third calculation submodule may obtain the abnormal high probability of the service network element according to the first abnormal probability and the second abnormal probability of the service network element, and use the second abnormal probability of each bearer network router as the second abnormal probability of the bearer network router.
For example, the first abnormal probability corresponding to a service network element in the network element set is P1ijThe second anomaly probability is P2ijThen, the third computing submodule may obtain the abnormal probability P of the service network element according to the following formulaijComprises the following steps:
if the second abnormal probability corresponding to one bearer network router in the network element set is P, the third computing sub-module may use P as the abnormal probability of the bearer network router.
The system can obtain the abnormal probability of each network element in the network element set according to the method.
According to the fault intelligent positioning system for the VOLTE service, provided by the embodiment of the invention, the first abnormal probability of each service network element is calculated by adopting the maximum matching rule, the second abnormal probability of each service network element and the second abnormal probability of each bearing network router are calculated by adopting the influence factor rule, the abnormal probability of each service network element is obtained according to the first abnormal probability and the second abnormal probability of each service network element, and the second abnormal probability of the bearing network router is used as the abnormal probability of the bearing network router, so that the system is more scientific.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 3, the electronic device includes: a processor (processor)31, a memory (memory)32, and a bus 33, wherein:
the processor 31 and the memory 32 complete communication with each other through the bus 33; the processor 31 is configured to call program instructions in the memory 32 to perform the methods provided by the above-mentioned method embodiments, for example, including: acquiring a corresponding dynamic end-to-end service chain of each user in different preset time periods according to the signaling data of each user; wherein the service chain comprises: registering a service chain and calling the service chain; acquiring network elements in abnormal service chains of a plurality of users in each preset time period, and performing duplicate removal processing on the network elements according to names to obtain a network element set; wherein the network element comprises: the router comprises service network elements and a load-bearing network router corresponding to each service network element; calculating the abnormal probability corresponding to each network element in the network element set by adopting a preset maximum matching rule and a preset influence factor rule; sorting each type of network elements according to the sequence of the corresponding abnormal probability from high to low, and screening the network elements which are ranked at the top N as abnormal fault points if the sum of the abnormal probabilities corresponding to the network elements which are ranked at the top N is greater than a preset threshold; wherein N is a positive integer; and if the abnormal fault point simultaneously comprises a first service network element and a first bearer network router corresponding to the first service network element, deleting the first service network element from the abnormal fault point.
An embodiment of the present invention discloses a computer program product, which includes a computer program stored on a non-transitory computer readable storage medium, the computer program including program instructions, when the program instructions are executed by a computer, the computer can execute the methods provided by the above method embodiments, for example, the method includes: acquiring a corresponding dynamic end-to-end service chain of each user in different preset time periods according to the signaling data of each user; wherein the service chain comprises: registering a service chain and calling the service chain; acquiring network elements in abnormal service chains of a plurality of users in each preset time period, and performing duplicate removal processing on the network elements according to names to obtain a network element set; wherein the network element comprises: the router comprises service network elements and a load-bearing network router corresponding to each service network element; calculating the abnormal probability corresponding to each network element in the network element set by adopting a preset maximum matching rule and a preset influence factor rule; sorting each type of network elements according to the sequence of the corresponding abnormal probability from high to low, and screening the network elements which are ranked at the top N as abnormal fault points if the sum of the abnormal probabilities corresponding to the network elements which are ranked at the top N is greater than a preset threshold; wherein N is a positive integer; and if the abnormal fault point simultaneously comprises a first service network element and a first bearer network router corresponding to the first service network element, deleting the first service network element from the abnormal fault point.
Embodiments of the present invention provide a non-transitory computer-readable storage medium, which stores computer instructions, where the computer instructions cause the computer to perform the methods provided by the above method embodiments, for example, the methods include: acquiring a corresponding dynamic end-to-end service chain of each user in different preset time periods according to the signaling data of each user; wherein the service chain comprises: registering a service chain and calling the service chain; acquiring network elements in abnormal service chains of a plurality of users in each preset time period, and performing duplicate removal processing on the network elements according to names to obtain a network element set; wherein the network element comprises: the router comprises service network elements and a load-bearing network router corresponding to each service network element; calculating the abnormal probability corresponding to each network element in the network element set by adopting a preset maximum matching rule and a preset influence factor rule; sorting each type of network elements according to the sequence of the corresponding abnormal probability from high to low, and screening the network elements which are ranked at the top N as abnormal fault points if the sum of the abnormal probabilities corresponding to the network elements which are ranked at the top N is greater than a preset threshold; wherein N is a positive integer; and if the abnormal fault point simultaneously comprises a first service network element and a first bearer network router corresponding to the first service network element, deleting the first service network element from the abnormal fault point.
The above-described embodiments of the electronic device and the like are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may also be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment may be implemented by software plus a necessary general hardware platform, and may also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
The above examples are only for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. An intelligent fault positioning method for VOLTE service is characterized by comprising the following steps:
acquiring a corresponding dynamic end-to-end service chain of each user in different preset time periods according to the signaling data of each user; wherein the service chain comprises: registering a service chain and calling the service chain;
acquiring network elements in abnormal service chains of a plurality of users in each preset time period, and performing duplicate removal processing on the network elements according to names to obtain a network element set; wherein the network element comprises: the router comprises service network elements and a load-bearing network router corresponding to each service network element;
calculating the abnormal probability corresponding to each network element in the network element set by adopting a preset maximum matching rule and a preset influence factor rule;
sorting each type of network elements according to the sequence of the corresponding abnormal probability from high to low, and screening the network elements which are ranked at the top N as abnormal fault points if the sum of the abnormal probabilities corresponding to the network elements which are ranked at the top N is greater than a preset threshold; wherein N is a positive integer;
if the abnormal fault point simultaneously comprises a first service network element and a first bearer network router corresponding to the first service network element, deleting the first service network element from the abnormal fault point;
the calculating the abnormal probability corresponding to each network element in the network element set by using the preset maximum matching rule and the preset influence factor rule includes:
calculating the first abnormal probability of each service network element by adopting the maximum matching rule;
calculating a second abnormal probability of each service network element and a second abnormal probability of each bearing network router by adopting the influence factor rule;
obtaining the abnormal probability of each service network element according to the first abnormal probability and the second abnormal probability of each service network element, and taking the second abnormal probability of the router of the bearer network as the abnormal probability of the router of the bearer network;
the abnormal probability of the service network element is determined by the following formula:
wherein, PijIs the abnormal probability, P, of the service network element1ijIs the first anomaly probability, P, of the service network element2ijAnd the second abnormal probability is the second abnormal probability of the service network element.
2. The method of claim 1, wherein the calculating the first anomaly probability for each service network element using the maximum matching rule comprises:
for each service network element in the network element set, determining a first type of the service network element and a first abnormal service chain to which the service network element belongs;
counting a first number of first type service network elements in the first abnormal service chain in the network element set;
counting a second number of the first type of service network elements in all abnormal service chains in the network element set;
and obtaining the first probability of the service network element according to the first number and the second number.
3. The method of claim 1, wherein said calculating a second anomaly probability for each of said service network elements using said impact factor rule comprises:
acquiring an abnormal event corresponding to each service network element in the network element set; wherein the exception event comprises: equipment alarm, performance index, dial testing verification and engineering operation;
dividing each type of abnormal event into three levels according to a preset rule;
for each service network element, calculating the probability of the four types of abnormal events by adopting a preset formula according to the type and the level of the corresponding abnormal event;
obtaining a second abnormal probability of the service network element according to the four types of abnormal event probabilities;
the abnormal event probability is determined by the following formula:
Pm=Pm1+Pm2+Pm3;
wherein, XmThe mth influence factor, m is 1,2,3, 4; x1、X2、X3、X4Respectively representing the four types of abnormal events; xm1,Xm2,Xm3Respectively representing a first-level problem set, a second-level problem set and a third-level problem set of the mth influence factor; card (X)mn) The number of the problems is represented;
the second abnormal probability of the service network element is determined by the following formula:
wherein P is the second of the service network elementProbability of abnormality, P1、P2、P3And P4Respectively representing the probabilities of the four types of abnormal events.
4. The method of any of claims 1-3, further comprising:
determining VOLTE service corresponding to each user and service result corresponding to each VOLTE service according to a service chain of the user; wherein the service result comprises: normal, failure and timeout;
and displaying the VOLTE service and the service result corresponding to the plurality of users in each preset time period in a matrix form to obtain a signaling matrix.
5. The method of any of claims 1-3, further comprising:
based on the bearer network, adopting a preset shortest path algorithm to draw an end-to-end service chain topological graph between a service network element in each service chain and a corresponding bearer network router; in the drawing process, if a public carrying network router exists, deleting a topological graph of an upper layer of the public carrying network router;
and loading corresponding key information and abnormal events for each service chain, each service network element and each bearing network router on the end-to-end service chain topological graph.
6. A VOLTE fault intelligent positioning system is characterized by comprising:
the first obtaining module is used for obtaining a corresponding dynamic end-to-end service chain of each user in different preset time periods according to the signaling data of each user; wherein the service chain comprises: registering a service chain and calling the service chain;
the second acquisition module is used for acquiring network elements in the abnormal service chains of the multiple users in each preset time period and carrying out duplicate removal processing on the network elements according to names to obtain a network element set; wherein the network element comprises: the router comprises service network elements and a load-bearing network router corresponding to each service network element;
the computing module is used for computing the abnormal probability corresponding to each network element in the network element set by adopting a preset maximum matching rule and a preset influence factor rule;
the screening module is used for sequencing each type of network elements from high to low according to the corresponding abnormal probability, and screening the network elements which are ranked at the top N as abnormal fault points if the sum of the abnormal probabilities corresponding to the network elements which are ranked at the top N is greater than a preset threshold value; wherein N is a positive integer;
a deleting module, configured to delete a first service network element from the abnormal fault point if the abnormal fault point includes both the first service network element and a first bearer network router corresponding to the first service network element;
the calculation module comprises:
the first calculation submodule is used for calculating the first abnormal probability of each service network element by adopting the maximum matching rule;
the second calculation submodule is used for calculating a second abnormal probability of each service network element and a second abnormal probability of each bearing network router by adopting the influence factor rule;
the third computing submodule is used for obtaining the abnormal probability of each service network element according to the first abnormal probability and the second abnormal probability of each service network element, and taking the second abnormal probability of the router of the bearer network as the abnormal probability of the router of the bearer network;
the abnormal probability of the service network element is determined by the following formula:
wherein, PijIs the abnormal probability, P, of the service network element1ijIs the first anomaly probability, P, of the service network element2ijAnd the second abnormal probability is the second abnormal probability of the service network element.
7. An electronic device, comprising a memory and a processor, wherein the processor and the memory communicate with each other via a bus; the memory stores program instructions executable by the processor, the processor invoking the program instructions to perform the method of any of claims 1-5.
8. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-5.
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Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108012283A (en) * | 2016-11-01 | 2018-05-08 | 中国移动通信集团广东有限公司 | A kind of Fault Locating Method and device of VoLTE business |
CN108093427A (en) * | 2016-11-23 | 2018-05-29 | 中国移动通信集团公司 | A kind of VoLTE evaluation the quality method and system |
CN108199916A (en) * | 2017-12-27 | 2018-06-22 | 中国移动通信集团山东有限公司 | A kind of VoLTE voice quality monitors method and system |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP3972664B2 (en) * | 2002-01-23 | 2007-09-05 | 日本電気株式会社 | Path failure recovery method, failback method after failure recovery, and nodes using them |
WO2010061119A1 (en) * | 2008-11-26 | 2010-06-03 | France Telecom | Method and system for regulating reboot traffic in a telecommunications network |
-
2018
- 2018-07-23 CN CN201810813654.4A patent/CN110752938B/en active Active
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108012283A (en) * | 2016-11-01 | 2018-05-08 | 中国移动通信集团广东有限公司 | A kind of Fault Locating Method and device of VoLTE business |
CN108093427A (en) * | 2016-11-23 | 2018-05-29 | 中国移动通信集团公司 | A kind of VoLTE evaluation the quality method and system |
CN108199916A (en) * | 2017-12-27 | 2018-06-22 | 中国移动通信集团山东有限公司 | A kind of VoLTE voice quality monitors method and system |
Non-Patent Citations (2)
Title |
---|
基于IMS的IP电话单通故障详解;许南希;《数字通信世界》;20170701(第07期);全文 * |
基于网元仿真的VoLTE业务质量监测系统研究;贾金良等;《通信管理与技术》;20171215(第06期);全文 * |
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