CN105207797A - Fault locating method and fault locating device - Google Patents
Fault locating method and fault locating device Download PDFInfo
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- CN105207797A CN105207797A CN201410277788.0A CN201410277788A CN105207797A CN 105207797 A CN105207797 A CN 105207797A CN 201410277788 A CN201410277788 A CN 201410277788A CN 105207797 A CN105207797 A CN 105207797A
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Abstract
The invention discloses a fault locating method and a fault locating device realized based on big data, and relates to the field of fault locating. According to an embodiment of the invention, the method comprises the steps of acquiring a large amount of alarm information and network resource information, making fault correlation analysis of the alarm information through machine learning, and locating a fault according to the correlation relationship obtained from analysis and the network resource information. Therefore, a difficult fault on which no artificial experience can be used for reference can be located and handled, and fault handling is accelerated.
Description
Technical field
The present invention relates to fault location field, particularly a kind of Fault Locating Method of realizing based on large data and device.
Background technology
In Integrated Network Management System troubleshooting, existing technology mainly contains following two kinds:
The first technology, Integrated Network Management System is by each professional network management system, the warning information of 24 hours various network elements of Real-time Collection, the filtration of the information of carrying out, format match, model conversion, unification is converted to comprehensive network management data model, and provides alarm list real time monitoring mode and alarm topological diagram real time monitoring mode, when there being alarm to produce, the different color of system represents the alarm of different stage, carries out auditory tone cues for great alarm.When the alarm meeting transmission condition occurs, be then sent to Email and specify E-mail address or be sent to office system with fault ticket form, remind webmaster personnel process.Webmaster personnel, according to artificial experience, carry out failure-description after determining the reason of fault, and the handling suggestion of filling in suggestion sends to Pai Xiu department.
The second technology, network management system monitor supervision platform realizes Real-time Alarm location, shows and notice, can be directly targeted to the equipment in topology by warning content.Specifically, the detection that the Fault Management System in monitor supervision platform provides fault to occur and report, maintenance and mistake in daily record, tracking and the function such as localizing faults, the test of execution failure diagnosis.Attendant can by improving the troubleshooting process of network management and monitoring system, alarm filter sends single gauge then with associating, and simplify overelaborated work, and the experience that realizes shared.
For prior art, what have can only by manually realizing fault location and process, although have can automatically realize fault location and diagnosis, but still need manual maintenance handling process and dependency rule.This just causes troubleshooting speed on the one hand comparatively slow, is difficult on the other hand locate and process the exceptional fault that there is no artificial experience.
Summary of the invention
An embodiment of the present invention technical problem to be solved is: solve in existing fault location and processing procedure comparatively slow and be difficult to locate and process there is no the problem of the exceptional fault of artificial experience owing to manually participating in the troubleshooting speed that causes.
According to an aspect of the embodiment of the present invention, propose a kind of Fault Locating Method, comprising: obtain warning information and network resource information; Trouble correlation analytic is carried out according to described warning information; The incidence relation obtained according to analysis and described network resource information carry out fault location.
In one embodiment, carry out trouble correlation analytic according to described warning information to comprise:
If two alarms occur reaching preset times simultaneously, determine whether one of them alarm is caused by another alarm;
Or,
If same alarm appears at least two equipment simultaneously, determine whether to cause other equipment to occur this alarm by same source equipment;
Or,
If high-level alarm and low level alarm of the same type occur simultaneously, determine that whether this low level alarm is produced by this high-level alarm, or determine the quantity of the low level alarm that can cause this high-level alarm;
Or,
If dissimilar alarm occurs simultaneously, according to the type of alarm, determine the incidence relation between dissimilar alarm.
In one embodiment, carry out fault location comprise according to analyzing the incidence relation that obtains and described network resource information:
Determine and the equipment of fault correlation to be solved or alarm according to analyzing the incidence relation obtained;
According to the equipment of association or alarm and described network resource information, fault location is carried out to fault to be solved.
In one embodiment, Fault Locating Method also comprises: determine whether fault to be solved is exceptional fault, performs the described step according to analyzing the incidence relation that obtains and described network resource information and carry out fault location for exceptional fault.
In one embodiment, Fault Locating Method also comprises: export fault location corresponding to fault to be solved and resolution policy.
According to another aspect of the embodiment of the present invention, propose a kind of fault locator, comprising: network resource information module, for obtaining network resource information; And machine learning module, for obtaining warning information; Trouble correlation analytic is carried out according to described warning information; Network resource information according to analyzing incidence relation and the described network resource information module acquisition obtained carries out fault location.
In one embodiment, machine learning module comprises association analysis unit, for carrying out trouble correlation analytic according to described warning information, specifically comprises:
If two alarms occur reaching preset times simultaneously, determine whether one of them alarm is caused by another alarm;
Or,
If same alarm appears at least two equipment simultaneously, determine whether to cause other equipment to occur this alarm by same source equipment;
Or,
If high-level alarm and low level alarm of the same type occur simultaneously, determine that whether this low level alarm is produced by this high-level alarm, or determine the quantity of the low level alarm that can cause this high-level alarm;
Or,
If dissimilar alarm occurs simultaneously, according to the type of alarm, determine the incidence relation between dissimilar alarm.
In one embodiment, machine learning module comprises failure location unit, for according to analyzing the incidence relation that obtains and described network resource information carries out fault location, specifically comprises:
Determine and the equipment of fault correlation to be solved or alarm according to analyzing the incidence relation obtained;
According to the equipment of association or alarm and described network resource information, fault location is carried out to fault to be solved.
In one embodiment, fault locator also comprises: failure analysis module, for determining whether fault to be solved is exceptional fault, and exceptional fault is sent to machine learning module.
In one embodiment, machine learning module, also for exporting fault location corresponding to fault to be solved and resolution policy.
The embodiment of the present invention obtains a large amount of warning information and network resource information, by the method for machine learning, trouble correlation analytic is carried out to warning information, and according to analyzing the incidence relation that obtains and network resource information carries out fault location, location and the process of the exceptional fault that there is no artificial experience can be realized, and accelerate the processing speed of fault.
By referring to the detailed description of accompanying drawing to exemplary embodiment of the present invention, further feature of the present invention and advantage thereof will become clear.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is the schematic flow sheet of a Fault Locating Method of the present invention embodiment.
Fig. 2 is that the present invention carries out some situation schematic diagrames of trouble correlation analytic according to warning information.
Fig. 3 is the structural representation of a fault locator of the present invention embodiment.
Fig. 4 is the structural representation of another embodiment of fault locator of the present invention.
Fig. 5 is a schematic flow sheet of the fault locator course of work of the present invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Illustrative to the description only actually of at least one exemplary embodiment below, never as any restriction to the present invention and application or use.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
Unless specifically stated otherwise, otherwise positioned opposite, the numerical expression of the parts of setting forth in these embodiments and step and numerical value do not limit the scope of the invention.
Meanwhile, it should be understood that for convenience of description, the size of the various piece shown in accompanying drawing is not draw according to the proportionate relationship of reality.
May not discuss in detail for the known technology of person of ordinary skill in the relevant, method and apparatus, but in the appropriate case, described technology, method and apparatus should be regarded as a part of authorizing specification.
In all examples with discussing shown here, any occurrence should be construed as merely exemplary, instead of as restriction.Therefore, other example of exemplary embodiment can have different values.
It should be noted that: represent similar terms in similar label and letter accompanying drawing below, therefore, once be defined in an a certain Xiang Yi accompanying drawing, then do not need to be further discussed it in accompanying drawing subsequently.
Fig. 1 is the schematic flow sheet of a Fault Locating Method of the present invention embodiment.As shown in Figure 1, the method for this embodiment comprises the following steps:
Step S102, obtains warning information and network resource information.
Wherein, warning information and network resource information can obtain from network management system, usually can obtain from multiple network management system, such as, and data network management system, transmission network management system etc.Warning information such as comprises the information such as alarm type, alarm name, alarm equipment type, alarm equipment, alarm time.Network resource information such as comprises the information such as circuit or route, and route can be such as system route or omnidistance route.
Step S104, carries out trouble correlation analytic according to warning information.
Step S106, the incidence relation obtained according to analysis and network resource information carry out fault location.
In one embodiment, step S104 carries out trouble correlation analytic according to warning information can comprise following several situation, as shown in Figure 2:
1) incidence relation between two alarms is excavated
If two alarms occur reaching preset times simultaneously, can think that these two alarms often occur, determine whether one of them alarm is caused by another alarm.
Such as, if alarm A and alarm B often occurs simultaneously, then analyze the incidence relation between alarm A and alarm B, as whether alarm A is caused by alarm B.If alarm A is caused by alarm B, then can carry out fault location for alarm B, and the Fault Locating Method of such alarm can be exported, that is, for alarm B carry out fault location when alarm A and alarm B occurs simultaneously.
In one embodiment, can determine according at least one information in the alarm type of two alarms, alarm name, alarm equipment type, alarm equipment whether one of them alarm is caused by another alarm.
2) incidence relation between excavating equipment
If same alarm appears at least two equipment simultaneously, determine whether to cause other equipment to occur this alarm by same source equipment.
Such as, if alarm A appears in multiple equipment simultaneously, then analyze whether because source equipment fault causes other equipment in follow-up relevant route also to occur alarm A.If source equipment fault causes other equipment to occur alarm A simultaneously, then can carry out fault location for source equipment, and the Fault Locating Method of such alarm can be exported, if that is, alarm A appears in multiple equipment simultaneously, carry out fault location for source equipment.
In one embodiment, can circuit belonging to the multiple equipment simultaneously occurring same alarm or route, whether the performance data analyzing each equipment or its port in this circuit or route there is degradation phenomena, if there is obvious or lasting performance degradation phenomenon, then the equipment that performance degradation phenomenon occurs is the source equipment causing other equipment to occur same alarm.
3) incidence relation between low level alarm and high-level alarm is excavated
If high-level alarm and low level alarm of the same type occur simultaneously, determine that whether this low level alarm is produced by this high-level alarm, or determine the quantity of the low level alarm that can cause this high-level alarm.
Such as, high-level alarm and low level alarm of the same type occur simultaneously, and low-level alarm is produced by this high-level alarm, then can carry out fault location for high-level alarm, and the Fault Locating Method of such alarm can be exported, that is, when high-level alarm and low level alarm of the same type occur simultaneously, fault location is carried out for high-level alarm.
Such as, high-level alarm and low level alarm of the same type occur simultaneously, and N number of low level alarm can cause a high-level alarm, then can export fault early warning method, that is, the early warning of corresponding high-level alarm is exported when the alarm of n (n≤N) individual low level being detected.
In one embodiment, can determine whether this low level alarm is produced by this high-level alarm according at least one information in the alarm type of high-level alarm and low level alarm, alarm name, alarm equipment type, alarm equipment.
In one embodiment, a large amount of statisticss that simultaneously can occur according to high-level alarm and low level alarm of the same type, determine the quantity of the low level alarm causing this high-level alarm.Such as, statistics shows, cause the quantity of the low level alarm of this high-level alarm to have 5,7,9 etc., minimum value 5 can be got as the quantity of low level alarm causing this high-level alarm, also can using mean value 7 as the quantity of low level alarm causing this high-level alarm.
4) incidence relation between dissimilar alarm is excavated
If dissimilar alarm occurs simultaneously, according to the type of alarm, determine the incidence relation between dissimilar alarm, and can fault early warning method be exported.Wherein, the type of alarm such as comprises communication class, syncsort, equipment class etc., and according to different dividing mode, alarm type such as can also comprise transmission class, data class etc.Such as, the alarm of C type and the alarm of D type have incidence relation, then can export fault early warning method, that is, export the early warning of the alarm of D type when the alarm of C type being detected.
In one embodiment, the incidence relation between dissimilar alarm can be determined according at least one information in the alarm type of two alarms and alarm name, alarm equipment type, alarm equipment.
In one embodiment, step S106 carries out fault location specifically can realize in the following ways according to analyzing the incidence relation that obtains and network resource information: determine and the equipment of fault correlation to be solved or alarm according to analyzing the incidence relation obtained; According to the equipment of association or alarm and network resource information, fault location is carried out to fault to be solved.Illustrate below.
Example 1: if same alarm appears in two equipment simultaneously, determine to cause other equipment to occur this alarm by same source equipment, and for this source equipment and network resource information, fault location is carried out to fault to be solved, such as determine that source equipment self breaks down, or the link failure between source equipment and its higher level equipment.Detailed process is as follows:
Suppose same circuit or route AAA have successively equipment 1, equipment 2, equipment 3, equipment 4, equipment 5 and equipment 6, monitoring discovering device 4 and equipment 6 occur that error code transfinites alarm simultaneously, same circuit or route AAA is belonged to by network resource information discovering device 4 and equipment 6, before transferring on circuit or route AAA equipment 4, equipment (namely, equipment 1, equipment 2, equipment 3) performance data, performance data (as the optical power value) continuous decrease of discovering device 3, then determine equipment 3 be exactly cause other equipment to occur error code transfinites the source equipment of alarm.Fault location can be carried out to fault to be solved below for this source equipment (that is, equipment 3) and network resource information.The property indices of traversal equipment 3, whether normally judged whether it is the problem of equipment 3 self by the property indices of equipment 3, if, fault location is equipment 3 for this reason, if not, find out the port between equipment 3 and higher level equipment 2, if this port performance degradation (as optical power value declines obviously), then fault location is link failure between equipment 3 and higher level equipment 2.
In one embodiment, Fault Locating Method can also comprise: export fault location corresponding to fault to be solved and resolution policy, and the location of exceptional fault and processing method are promoted, and makes follow-up similar fault to be located rapidly and to process.It should be noted that, when orienting fault, resolution policy can be provided according to the existing solution for this fault.
In one embodiment, Fault Locating Method can also comprise: determine whether fault to be solved is exceptional fault, performs step S106, for non-exceptional fault, then directly can export fault location corresponding to fault to be solved and resolution policy for exceptional fault.Wherein, can judge whether fault to be solved is exceptional fault according to processing fault to be solved, if have fault location corresponding to fault to be solved and resolution policy, then fault can process, not think it is exceptional fault, if do not store fault location corresponding to fault to be solved and resolution policy, then fault cannot process, and thinks exceptional fault.For exceptional fault, can automatically obtain corresponding Fault Locating Method and resolution policy by the method for the machine learning described by aforesaid step S102 ~ S106.
Fig. 3 is the structural representation of a fault locator of the present invention embodiment.As shown in Figure 3, the device of the present embodiment comprises:
Network resource information module 302, for obtaining network resource information; And,
Machine learning module 304, for obtaining warning information; Trouble correlation analytic is carried out according to warning information; Network resource information according to analyzing incidence relation and the network resource information module acquisition obtained carries out fault location.
In one embodiment, machine learning module comprises association analysis unit, for carrying out trouble correlation analytic according to warning information, specifically comprises:
If two alarms occur reaching preset times simultaneously, determine whether one of them alarm is caused by another alarm;
Or,
If same alarm appears at least two equipment simultaneously, determine whether to cause other equipment to occur this alarm by same source equipment;
Or,
If high-level alarm and low level alarm of the same type occur simultaneously, determine that whether this low level alarm is produced by this high-level alarm, or determine the quantity of the low level alarm that can cause this high-level alarm;
Or,
If dissimilar alarm occurs simultaneously, according to the type of alarm, determine the incidence relation between dissimilar alarm.
In one embodiment, machine learning module comprises failure location unit, for according to analyzing the incidence relation that obtains and network resource information carries out fault location, specifically comprises:
Determine and the equipment of fault correlation to be solved or alarm according to analyzing the incidence relation obtained;
According to the equipment of association or alarm and network resource information, fault location is carried out to fault to be solved.
In one embodiment, as shown in Figure 4, fault locator also comprises: failure analysis module 406, for determining whether fault to be solved is exceptional fault, and exceptional fault is sent to machine learning module 304.
In one embodiment, machine learning module 304, also for exporting fault location corresponding to fault to be solved and resolution policy, such as, can export to failure analysis module 406, the location of exceptional fault and processing method are promoted.
Fig. 5 is a schematic flow sheet of the fault locator course of work of the present invention.As shown in Figure 5, the fault locator course of work of the present embodiment comprises following content:
Step S502, failure analysis module 406 pairs of warning information carry out Automatic analysis fast;
Step S504, determines whether exceptional fault;
If accessible fault, then export fault location and resolution policy (step S506);
If exceptional fault, then go to machine learning module and carry out processing (step S508).
Step S508, the network resource information that machine learning module 304 provides in conjunction with network resource information module 302, carries out association analysis by the method for machine learning to exceptional fault:
Step S510, judges whether exceptional fault solves;
Step S512, if complete fault location and the resolution policy of exceptional fault, then fault message, fault location, resolution policy etc. are fed back to failure analysis module 406, enrich its disposal decision, so that the process of after this similar fault, simultaneous faults analysis module 406 exports fault location and resolution policy;
Step S514, if exceptional fault is still difficult to location, then temporarily leaves the exceptional fault district to be analyzed in machine learning module in, until follow-up have more related analysis information or disposal decision to upgrade after, then analyzing and processing is carried out to it.
The embodiment of the present invention obtains a large amount of warning information and network resource information, by the method for machine learning, trouble correlation analytic is carried out to warning information, and according to analyzing the incidence relation that obtains and network resource information carries out fault location, location and the process of the exceptional fault that there is no artificial experience can be realized, and accelerate the processing speed of fault.In addition, can be combined with existing trouble analysis system, be the technical support that it provides fault location and resolution policy, and the location of exceptional fault and processing method are promoted.
One of ordinary skill in the art will appreciate that all or part of step realizing above-described embodiment can have been come by hardware, the hardware that also can carry out instruction relevant by program completes, described program can be stored in a kind of computer-readable recording medium, the above-mentioned storage medium mentioned can be read-only memory, disk or CD etc.
The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention, within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (10)
1. a Fault Locating Method, comprising:
Obtain warning information and network resource information;
Trouble correlation analytic is carried out according to described warning information;
The incidence relation obtained according to analysis and described network resource information carry out fault location.
2. method according to claim 1, is characterized in that, describedly carries out trouble correlation analytic according to described warning information and comprises:
If two alarms occur reaching preset times simultaneously, determine whether one of them alarm is caused by another alarm;
Or,
If same alarm appears at least two equipment simultaneously, determine whether to cause other equipment to occur this alarm by same source equipment;
Or,
If high-level alarm and low level alarm of the same type occur simultaneously, determine that whether this low level alarm is produced by this high-level alarm, or determine the quantity of the low level alarm that can cause this high-level alarm;
Or,
If dissimilar alarm occurs simultaneously, according to the type of alarm, determine the incidence relation between dissimilar alarm.
3. method according to claim 1, is characterized in that, describedly carries out fault location comprise according to analyzing the incidence relation that obtains and described network resource information:
Determine and the equipment of fault correlation to be solved or alarm according to analyzing the incidence relation obtained;
According to the equipment of association or alarm and described network resource information, fault location is carried out to fault to be solved.
4. method according to claim 1, is characterized in that, also comprises:
Determine whether fault to be solved is exceptional fault, the described step according to analyzing the incidence relation that obtains and described network resource information and carry out fault location is performed for exceptional fault.
5. method according to claim 1, is characterized in that, also comprises:
Export fault location corresponding to fault to be solved and resolution policy.
6. a fault locator, comprising:
Network resource information module, for obtaining network resource information; And,
Machine learning module, for obtaining warning information; Trouble correlation analytic is carried out according to described warning information; Network resource information according to analyzing incidence relation and the described network resource information module acquisition obtained carries out fault location.
7. device according to claim 6, is characterized in that, described machine learning module comprises association analysis unit, for carrying out trouble correlation analytic according to described warning information, specifically comprises:
If two alarms occur reaching preset times simultaneously, determine whether one of them alarm is caused by another alarm;
Or,
If same alarm appears at least two equipment simultaneously, determine whether to cause other equipment to occur this alarm by same source equipment;
Or,
If high-level alarm and low level alarm of the same type occur simultaneously, determine that whether this low level alarm is produced by this high-level alarm, or determine the quantity of the low level alarm that can cause this high-level alarm;
Or,
If dissimilar alarm occurs simultaneously, according to the type of alarm, determine the incidence relation between dissimilar alarm.
8. device according to claim 6, is characterized in that, described machine learning module comprises failure location unit, for according to analyzing the incidence relation that obtains and described network resource information carries out fault location, specifically comprises:
Determine and the equipment of fault correlation to be solved or alarm according to analyzing the incidence relation obtained;
According to the equipment of association or alarm and described network resource information, fault location is carried out to fault to be solved.
9. device according to claim 6, is characterized in that, also comprises:
Failure analysis module, for determining whether fault to be solved is exceptional fault, and sends to described machine learning module by exceptional fault.
10. device according to claim 6, is characterized in that, described machine learning module, also for exporting fault location corresponding to fault to be solved and resolution policy.
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| CN108156019A (en) * | 2017-11-29 | 2018-06-12 | 全球能源互联网研究院有限公司 | A kind of network based on SDN derives alarm filtering system and method |
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Application publication date: 20151230 |