CN105187255A - Fault analysis method, fault analysis device and server - Google Patents
Fault analysis method, fault analysis device and server Download PDFInfo
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Abstract
The embodiment of the invention provides a fault analysis method, a fault analysis device and a server. The fault analysis method provided by the invention may comprise the following steps of: determining a network fault with the highest fault probability in a network; and performing fault analysis on the network fault with the highest fault probability. According to the embodiment of the invention, efficiency of analysis on network survivability may be improved.
Description
Technical field
The embodiment of the present invention relates to the communication technology, particularly relates to a kind of failure analysis methods, fail analysis device and server.
Background technology
In recent years, optical transport network technology has had significant progress, goes up and all reaches its maturity with application from tranmission techniques or network design.Along with the maturation of optical transport network technology, the intellectuality of network and the degree of automation more and more higher, this makes optical-fiber network just progressively develop into ASON by conventional optical network.
For ensureing the reliability of ASON, can be carry out network survivability analysis by this ASON middle controller.This controller carries out network survivability analysis, can be by analyzing network failure, determines the impact of network failure on business, thus provides error protection and fault recovery for business, ensures the normal operation of business, ensures network reliability.Conventional network survivability analysis can be analyze for all network failures.
But analyze for all network failures, malfunction analysis procedure can be made longer, thus the process making network survivability analyze is longer, efficiency is lower.
Summary of the invention
The embodiment of the present invention provides a kind of failure analysis methods, fail analysis device and server, to improve the efficiency that network survivability is analyzed.
First aspect, the embodiment of the present invention provides a kind of failure analysis methods, comprising:
Determine the network failure that in network, probability of malfunction is maximum;
The network failure maximum to described probability of malfunction carries out accident analysis.
According to first aspect, in the first mode in the cards of first aspect, described determine the network failure that in network, probability of malfunction is maximum before, described method also comprises:
Determine the probability of malfunction of each network failure in described network.
According to the first mode in the cards of first aspect, in the second mode in the cards, the described probability of malfunction determining each network failure in network, comprising:
According to the historical failure information of network object each in described network, determine the probability of malfunction of described each network object; Described network object comprises: node and/or link;
The probability of malfunction of described each network object is defined as the probability of malfunction of described each network failure.
According to the second of first aspect mode in the cards, in the third mode in the cards, the described historical failure information according to described each network object, determine that the probability of malfunction of described each network object comprises:
According to the historical failure information of described each network object, formula 1 is adopted to determine the probability of malfunction of described each network object at moment t; Described historical failure information comprises historical failure number of times, and the generation time of each historical failure;
Wherein, e
ibe i-th network object, i is arbitrary element in 1,2,3...N, and N is the network object number in described network;
for e
iat the probability of malfunction of moment t;
for e
ithe time series of k historical failure;
for e
ithe generation time of the 1st historical failure.
According to the second or the third mode in the cards of first aspect, in the 4th kind of mode in the cards, the described historical failure information according to network object each in described network, before determining the probability of malfunction of described each network object, described method also comprises:
Receive the historical failure information of described each network object that controller sends.
According to the third mode in the cards of first aspect, in the 5th kind of mode in the cards, the described network failure determining that in network, probability of malfunction is maximum comprises:
Determine at least one fault combination that probability of malfunction sum is maximum; Wherein, the network failure number in each fault combination equals default network failure number; Described default network failure number is simultaneous network failure number;
Network failure in described at least one fault combination is defined as the maximum network failure of described probability of malfunction.
According to the 5th kind of mode in the cards of first aspect, in the 6th kind of mode in the cards, described determine described probability of malfunction sum maximum at least one fault combination, comprising:
Determine all fault combinations that described default network failure number is corresponding;
By the probability of malfunction sum of described all fault combinations, be defined as total failare probability;
Determine that in described all fault combinations, probability of malfunction sum is more than or equal to described at least one fault combination of predetermined probabilities threshold value; Described predetermined probabilities threshold value is less than described total failare probability.
According to the 6th kind of mode in the cards of first aspect, in the 7th kind of mode in the cards, described by the probability of malfunction sum of described all fault combinations, before being defined as total failare probability, described method also comprises:
Determine the probability of malfunction of each fault combination in described all fault combinations.
According to the 7th kind of mode in the cards of first aspect, in the 8th kind of mode in the cards, if described default network failure number is 1, the described probability of malfunction determining that in described all fault combinations, each fault combines comprises:
By the probability of malfunction of a network failure in described each fault combination, be defined as the probability of malfunction of described each fault combination.
According to the 7th kind of mode in the cards of first aspect, in the 9th kind of mode in the cards, if described default network failure number is more than or equal to 2, the described probability of malfunction determining that in described all fault combinations, each fault combines comprises:
Formula 2 is adopted to determine the probability of malfunction of described each fault combination;
P
m=p (1) * p (2|1) ... p (k ' | k '-1) ... formula 2
Wherein, m is 1,2,3 ... arbitrary element in M; M is fault number of combinations in described all fault combinations, and
k ' is described default network failure number, k '>=2; P
1~ P
mto represent in the combination of described all fault the probability of each fault combination from big to small successively; P (1) is the maximum probability of malfunction in described each fault combination; P (k ' | k '-1) is the probability of malfunction of kth ' individual network failure when probability of malfunction kth '-1 from big to small network failure breaks down in described each fault combination;
Wherein,
y is the historical failure number of times of kth '-1 network failure in described each fault combination;
for the time series of y historical failure of described kth '-1 network failure; X is the historical failure number of times of kth ' individual network failure in described each fault combination;
for the time series of x historical failure of described kth '-1 network failure; t
rfor average time for repair of breakdowns.
According to the 8th kind or the 9th kind of mode in the cards of first aspect, in the tenth kind of mode in the cards, described described at least one fault combination determining that probability of malfunction sum in the combination of described all fault is more than or equal to predetermined probabilities threshold value comprises:
According to described total failare probability and presupposition analysis precision, formula 3 is adopted to determine described at least one fault combination;
Wherein,
for described total failare probability, a is described presupposition analysis precision, and described predetermined probabilities threshold value is the product of described total failare probability and described presupposition analysis precision; N ' is arbitrary element in 1,2,3...N ',
for the probability of malfunction sum of described at least one fault combination, P
1~ P
n 'to represent at least one fault described combination the probability of each fault combination from big to small successively; P
1~ P
n 'corresponding fault is combined as described at least one fault combination.
According in the 5th kind to the tenth kind mode in the cards of first aspect any one, in the 11 kind of mode in the cards, the described network failure maximum to described probability of malfunction carries out accident analysis, comprising:
Accident analysis is carried out to the network failure in fault combination each in described at least one fault combination, determines the impact of described each fault combination on business.
According to the 11 kind of mode in the cards of first aspect, in the 12 kind of mode in the cards, described accident analysis is carried out to the network failure in fault combination each in the combination of described at least one fault, comprising:
The network object corresponding according to each network failure in described each fault combination, the bearer service information of the network object corresponding with described each network failure, determine the business of described each fault combined effect, and/or, not by the business of described each fault combined effect.
Second aspect, the embodiment of the present invention provides a kind of fail analysis device, comprising:
Determination module, for the network failure determining that in network, probability of malfunction is maximum;
Analysis module, carries out accident analysis for the network failure maximum to described probability of malfunction.
According to second aspect, in the first mode in the cards of second aspect, described determination module, also for before determining the network failure that described in described network, probability of malfunction is maximum, determines the probability of malfunction of each network failure in described network.
According to the first mode in the cards of second aspect, in the second mode in the cards, described determination module, also for the historical failure information according to network object each in described network, determine the probability of malfunction of described each network object, and the probability of malfunction of described each network object is defined as the probability of malfunction of described each network failure; Wherein, described network object comprises: node and/or link; .
According to the second of second aspect mode in the cards, in the third mode in the cards, described determination module, also for the historical failure information according to described each network object, adopts formula 1 to determine the probability of malfunction of described each network object at moment t; Described historical failure information comprises historical failure number of times, and the generation time of each historical failure;
Wherein, e
ibe i-th network object, i is arbitrary element in 1,2,3...N, and N is the network object number in described network;
for e
iat the probability of malfunction of moment t;
for e
ithe time series of k historical failure;
for e
ithe generation time of the 1st historical failure.
According to the second or the third mode in the cards of second aspect, in the 4th kind of mode in the cards, described device also comprises:
Receiver module, for receiving the historical failure information of described each network of network object that controller sends.
According to the third mode in the cards of second aspect, in the 5th kind of mode in the cards, described determination module, also for determining at least one fault combination that probability of malfunction sum is maximum, the network failure in described at least one fault combination is defined as the maximum network failure of described probability of malfunction; Wherein, the network failure number in each fault combination equals default network failure number; Described default network failure number is simultaneous network failure number.
According to the 5th kind of mode in the cards of second aspect, in the 6th kind of mode in the cards, described determination module, also for determining all fault combinations that described default network failure number is corresponding; By the probability of malfunction sum of described all fault combinations, be defined as total failare probability; Determine that in described all fault combinations, probability of malfunction sum is more than or equal to described at least one fault combination of predetermined probabilities threshold value; Described predetermined probabilities threshold value is less than described total failare probability.
According to the 6th kind of mode in the cards of second aspect, in the 7th kind of mode in the cards, described determination module, also for determining the probability of malfunction of each fault combination in described all fault combinations.
According to the 7th kind of mode in the cards of second aspect, in the 8th kind of mode in the cards, if described default network failure number is 1, described determination module, also for the probability of malfunction by a network failure in described each fault combination, be defined as the probability of malfunction of described each fault combination.
According to the 7th kind of mode in the cards of second aspect, in the 9th kind of mode in the cards, if described default network failure number is more than or equal to 2, described determination module, the probability of malfunction also for adopting formula 2 to determine described each fault combination;
P
m=p (1) * p (2|1) ... p (k ' | k '-1) ... formula 2
Wherein, m is 1,2,3 ... arbitrary element in M; M is fault number of combinations in described all fault combinations, and
k ' is described default network failure number, k '>=2; P
1~ P
mto represent in the combination of described all fault the probability of each fault combination from big to small successively; P (1) is the maximum probability of malfunction in described each fault combination; P (k ' | k '-1) is the probability of malfunction of kth ' individual network failure when probability of malfunction kth '-1 from big to small network failure breaks down in described each fault combination;
Wherein,
y is the historical failure number of times of kth '-1 network failure in described each fault combination;
for the time series of y historical failure of described kth '-1 network failure; X is the historical failure number of times of kth ' individual network failure in described each fault combination;
for the time series of x historical failure of described kth '-1 network failure; t
rfor average time for repair of breakdowns.
According to the 8th kind or the 9th kind of mode in the cards of second aspect, in the tenth kind of mode in the cards, described determination module, also for according to described total failare probability and presupposition analysis precision, adopts formula 3 to determine described at least one fault combination;
Wherein,
for described total failare probability, a is described presupposition analysis precision, and described predetermined probabilities threshold value is the product of described total failare probability and described presupposition analysis precision; N ' is arbitrary element in 1,2,3...N ',
for the probability of malfunction sum of described at least one fault combination, P
1~ P
n 'to represent at least one fault described combination the probability of each fault combination from big to small successively; P
1~ P
n 'corresponding fault is combined as described at least one fault combination.
According in the 5th kind to the tenth kind mode in the cards of second aspect any one, in the 11 kind of mode in the cards, described analysis module, also for carrying out accident analysis to the network failure in fault combination each in described at least one fault combination, determine the impact of described each fault combination on business.
According to the 11 kind of mode in the cards of second aspect, in the 12 kind of mode in the cards, described analysis module, also for the network object corresponding according to each network failure in described each fault combination, the bearer service information of the network object corresponding with described each network failure, determine the business of described each fault combined effect, and/or, not by the business of described each fault combined effect.
The third aspect, the embodiment of the present invention also provides a kind of server, comprising: as above-mentioned arbitrary as described in fail analysis device.
The failure analysis methods that the embodiment of the present invention provides, fail analysis device and server, by the network failure determining that in network, probability of malfunction is maximum, and accident analysis is carried out to the network failure that this probability of malfunction is maximum, and analyze without the need to the all-network fault in traverses network, reduce the network failure number of accident analysis, shorten the process of accident analysis, thus shorten the process of network survivability analysis, improve the efficiency of survival stress.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, introduce doing one to the accompanying drawing used required in embodiment or description of the prior art simply below, apparently, accompanying drawing in the following describes is 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.
The network architecture schematic diagram that Fig. 1 applies for various embodiments of the present invention;
The flow chart of a kind of failure analysis methods that Fig. 2 provides for the embodiment of the present invention one;
The method flow diagram of the probability of malfunction of each network failure is determined in the failure analysis methods that Fig. 3 provides for the embodiment of the present invention two;
The flow chart of the another kind of failure analysis methods that Fig. 4 provides for the embodiment of the present invention two;
The flow chart of another failure analysis methods that Fig. 5 provides for the embodiment of the present invention two;
The flow chart of another failure analysis methods that Fig. 6 provides for the embodiment of the present invention two;
The flow chart of a kind of failure analysis methods that Fig. 7 provides for the embodiment of the present invention three;
The structural representation of a kind of fail analysis device that Fig. 8 provides for the embodiment of the present invention four;
The structural representation of the server that Fig. 9 provides for the embodiment of the present invention five.
Embodiment
For making the object of the embodiment of the present invention, technical scheme and advantage clearly, below in conjunction with the accompanying drawing in the embodiment of the present invention, technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is the present invention's part embodiment, instead of whole embodiments.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.
The failure analysis methods that the embodiment of the present invention provides, fail analysis device, server, by carrying out accident analysis to network failure, thus carry out the survival stress of network.The survival stress of network refers to the anti-shot ability of network to fault, and namely network failure is on the impact of bearer service in network.This failure analysis methods can be used for carrying out survival stress to ASON.This ASON can be such as traditional intelligence optical-fiber network or software defined network (SoftwareDefinedNetwork is called for short SDN) optical-fiber network.This traditional intelligence optical-fiber network can be such as traditional automatic switchover optical-fiber network (AutomaticSwitchedOpticalNetwork is called for short ASON).This SDN optical-fiber network can be such as the ASON based on SDN.
The network architecture schematic diagram that Fig. 1 applies for various embodiments of the present invention.The method of various embodiments of the present invention can be performed by fail analysis device, and this device realizes in the mode of hardware and/or software usually, is integrated on server 101 as shown in Figure 1.This server 101 can be such as data center server (DataCenter is called for short DC server).OSS (OperationSupportSystem, be called for short OSS) in the terminal 102 of operator or the terminal 103 of user can be provided with application corresponding to this accident analysis (application) program, by this server 101 of this application (application) routine access, thus obtain the failure analysis result of this server 101, or issue analysis instruction to this server 101.Controller 104 in Fig. 1 obtains the historical failure information of this transmission network 105 by each router one 06 in transmission network 105, and send it to server 101, according to the historical failure information of this transmission network 105, accident analysis is carried out to this transmission network by server 101, then carry out network survivability analysis.If this transmission network 105 is SDN optical-fiber network, then this controller 104 can be SDN controller.It should be noted that, this Fig. 1 is only schematic diagram, and therefore, the connection in this Fig. 1 between each equipment can be wired connection, also can be wireless connections.
The embodiment of the present invention one provides a kind of failure analysis methods.The flow chart of a kind of failure analysis methods that Fig. 2 provides for the embodiment of the present invention one.As shown in Figure 2, the method for the present embodiment can comprise:
S201, determine the network failure that in network, probability of malfunction is maximum.
Particularly, this network can be the transmission backbone network of operator deployment.If the transmission signal vector of this transmission backbone network is optical fiber, then this transmission backbone network can be optical transfer network (OpticalTransportNetwork is called for short OTN).The network failure of this maximum probability, can comprise: at least one network failure of the maximum probability that this network breaks down in the same Preset Time in future.This network failure can comprise: node failure and/or link failure.This link failure such as can comprise: multistage (Multi-Segment, be called for short MS) link failure, pipeline (Duct) link failure, cable (Cable) link failure and sharing memory (SharedRiskLinkGroup is called for short SRLG) fault.The maximum network failure of this probability of malfunction can be the subnetwork fault in network.
S202, accident analysis is carried out to the network failure that this probability of malfunction is maximum.
Particularly, the network failure maximum to this probability of malfunction carries out accident analysis, can be analyzed by the analog subsystem in SDH (Synchronous Digital Hierarchy) (SynchronousDigitalHierarchy), thus in determining the network failure that this probability of malfunction is maximum each fault on the impact of business, export accident analysis table, and determine network failure larger to service impact in the network failure that this probability of malfunction is maximum according to this accident analysis table, and/or, the bottleneck in this network.Bottleneck in this network can be that the tender spots of this network such as can comprise: the network failure larger to service impact, and/or, the network failure that probability of malfunction is maximum.
It should be noted that, in this S202, accident analysis is carried out to the network failure that this probability of malfunction is maximum, determine the network failure larger to service impact, also by providing error protection and fault recovery for business, the normal operation of guarantee business, ensures network reliability; Determining the tender spots of this network, also by improving tender spots, thus reducing network vulnerability, the reliability of Strengthens network.
The failure analysis methods that the embodiment of the present invention one provides, by the network failure determining that in network, probability of malfunction is maximum, and accident analysis is carried out to the network failure that this probability of malfunction is maximum, and analyze without the need to the all-network fault in traverses network, reduce the network failure number of accident analysis, shorten the process of accident analysis, thus shorten the process of network survivability analysis, improve the efficiency of survival stress.
The embodiment of the present invention two, on the basis of the failure analysis methods of above-described embodiment one, also provides a kind of failure analysis methods.Optionally, before determining the network failure that in network, probability of malfunction is maximum in the method in S201, the method also can comprise:
Determine the probability of malfunction of each network failure in this network.
The method flow diagram of the probability of malfunction of each network failure is determined in the failure analysis methods that Fig. 3 provides for the embodiment of the present invention two.As shown in Figure 3, this determines that the probability of malfunction of each network failure in this network can comprise:
S301, historical failure information according to network object each in this network, determine the probability of malfunction of this each network object; This network object comprises: node and/or link.
Particularly, the historical failure information of this each network object can comprise historical failure information corresponding at least one fault type of this each network object.Thus, according to the historical failure information of network object each in this network, determine the probability of malfunction of this each network object, can be the historical failure information according to this each network object corresponding to this each fault type, determine the probability of malfunction of this each network object that this each fault type is corresponding.
S302, the probability of malfunction of this each network object is defined as the probability of malfunction of this each network failure.
Particularly, the probability of malfunction of this each network object can be the probability of malfunction of this each network object that this each fault type is corresponding, therefore, the probability of malfunction of this each network failure can be the probability of malfunction of this each network object that this each fault type is corresponding.
Optionally, the embodiment of the present invention two also provides a kind of failure analysis methods.The flow chart of the another kind of failure analysis methods that Fig. 4 provides for the embodiment of the present invention two.Optionally, according to the historical failure information of this each network object in S301 as described above, determine the probability of malfunction of this each network object, can comprise:
S401, historical failure information according to this each network object, adopt formula 1 to determine the probability of malfunction of this each network object at moment t; This historical failure information comprises historical failure number of times, and the generation time of each historical failure.
Wherein, e
ibe i-th network object, i is arbitrary element in 1,2,3...N, and N is the network object number in this network.
for e
iat the probability of malfunction of moment t;
for e
ithe time series of k historical failure;
for e
ithe generation time of the 1st historical failure.
Optionally, according to the historical failure information of this each network object in above-mentioned S301, before determining the probability of malfunction of this each network object, the method also can comprise:
The historical failure information of this each network object that S401a, reception controller send.
Particularly, this controller can be such as SDN controller.The historical failure information of this each network object, such as, can receive the historical failure information of each node and/or link in this transmission backbone network obtained in the network real time information that the router in this transmission backbone network reports for this controller.
Optionally, on the basis of this embodiment two said method, the embodiment of the present invention two also provides another failure analysis methods.The flow chart of another failure analysis methods that Fig. 5 provides for the embodiment of the present invention two.As shown in Figure 5, the method determines the network failure that in network, probability of malfunction is maximum in a kind of S201 of above-described embodiment, can comprise:
S501, determine probability of malfunction sum maximum at least one fault combination; Wherein, the network failure number in each fault combination equals default network failure number; This default network failure number is simultaneous network failure number.
Particularly, this default network failure numerical example is as being simultaneous network failure number in this default network.This default network failure number can be more than or equal to 1.For example, if this default network failure number is 1, then the network failure number in each fault combination can be 1; If this default network failure number is individual for reading, then the network failure number in this each fault combination can be multiple.
S502, by this at least one fault combine in network failure be defined as the maximum network failure of this probability of malfunction.
Optionally, on the basis of this embodiment two said method, this embodiment two also provides another failure analysis methods.The flow chart of another failure analysis methods that Fig. 6 provides for the embodiment of the present invention two.Determine in this S501 this probability of malfunction sum maximum at least one fault combination comprise:
S601, determine all faults combination that this default network failure number is corresponding.
Particularly, all faults combination that this default network failure number is corresponding can be by this default network failure number, network failures all in this networking is carried out to permutation and combination determines.All-network fault in this network can be represented by the mark of all-network object in this network, and wherein, a networking fault can be such as represented by the mark of a network object.
S602, the probability of malfunction sum this all fault combined, be defined as total failare probability.
Particularly, the probability of malfunction sum of this all fault combination can be obtained by the probability summation of the Chinese each fault combination of this all fault combination.
S603, determine that in this all faults combination, probability of malfunction sum is more than or equal to this at least one fault combination of predetermined probabilities threshold value; This predetermined probabilities threshold value is less than this total failare probability.
Optionally, by the probability of malfunction sum of this all fault combination, before being defined as total failare probability, the method also comprises:
Determine the probability of malfunction of each fault combination in this all fault combination.
Optionally, if this default network failure number is 1, this determines the probability of malfunction of each fault combination in this all fault combination, comprising:
By the probability of malfunction of a network failure in this each fault combination, be defined as the probability of malfunction of this each fault combination.
Alternately, if this default network failure number is more than or equal to 2, then the above-mentioned probability of malfunction determining each fault combination in this all fault combination can be comprise:
Formula 2 is adopted to determine the probability of malfunction of this each fault combination.
P
m=p (1) * p (2|1) ... p (k ' | k '-1) ... formula 2
Wherein, m is 1,2,3 ... arbitrary element in M; M is fault number of combinations in this all fault combination, and
k ' is this default network failure number, k '>=2; P
1~ P
mto represent in this all faults combination the probability of each fault combination from big to small successively; P (1) is the maximum probability of malfunction in this each fault combination; P (k ' | k '-1) is the probability of malfunction of kth ' individual network failure when probability of malfunction kth '-1 from big to small network failure breaks down in this each fault combination.
the individual network failure of k ' can be selected to carry out the number of combinations of permutation and combination in N number of network failure.
Wherein,
y is the historical failure number of times of kth '-1 network failure in this each fault combination;
for the time series of y historical failure of this kth '-1 network failure; X is the historical failure number of times of kth ' individual network failure in this each fault combination;
for the time series of x historical failure of this kth '-1 network failure; t
rfor average time for repair of breakdowns.
Optionally, determine in S603 as described above that in this all fault combination, probability of malfunction sum is more than or equal to this at least one fault combination of predetermined probabilities threshold value, can comprise:
According to this total failare probability and presupposition analysis precision, formula 3 is adopted to determine that this at least one fault combines.
Wherein,
for this total failare probability, a is this presupposition analysis precision, and this predetermined probabilities threshold value is the product of this total failare probability and this presupposition analysis precision; N ' is arbitrary element in 1,2,3...N ',
for the probability of malfunction sum of this at least one fault combination, P
1~ P
n 'to represent in the combination of this at least one fault the probability of each fault combination from big to small successively; P
1~ P
n 'corresponding fault is combined as the combination of this at least one fault.
Particularly, according to this total failare probability, and this presupposition analysis precision, determine this predetermined probabilities threshold value, then determine according to this formula 3 N ' meeting this formula 3, then determine P
1~ P
n 'corresponding fault is combined as the combination of this at least one fault.
Optionally, as carried out accident analysis to the network failure that this probability of malfunction is maximum in S202 in above-described embodiment one, can comprise:
Accident analysis is carried out to the network failure in fault combination each in the combination of this at least one fault, determines this impact of each fault combination on business.
Particularly, can be successively accident analysis is carried out to the network failure in each fault combination in the combination of this at least one fault in the present embodiment.Due to separate between different faults combination, thus also can be concurrent fault analysis is carried out to each fault combination in the plurality of fault combination in the present embodiment simultaneously, thus improve analysis efficiency.
Optionally, accident analysis is carried out to the network failure in fault combination each in the combination of this at least one fault, comprising:
The network object corresponding according to each network failure in this each fault combination, the bearer service information of the network object corresponding with this each network failure, determines the business of this each fault combined effect, and/or, not by the business of this each fault combined effect.
The failure analysis methods that the embodiment of the present invention two provides, can on the basis of above-described embodiment one, by providing multiple implementation method determining the network failure that probability of malfunction is maximum in network, thus at reduction malfunction analysis procedure, shorten on the basis of network survivability analysis, also can ensure the precision of survival stress.
The embodiment of the present invention three also provides a kind of failure analysis methods.The flow chart of a kind of failure analysis methods that Fig. 7 provides for the embodiment of the present invention three.As shown in Figure 7, the method can comprise:
S701, controller send the historical failure information of each network object in network to server, and this historical failure information comprises: the historical failure number of times of this each network object, and, the generation time of each historical failure.
S702, the server historical failure number of times according to this each network object, the generation time of each historical failure, determine the probability of malfunction of this each network object.
Can be that link is described by network object in this embodiment.If this link in network comprises: a, b, c, d.According to adopting in this S702 as above-mentioned formula 1, determine that the probability of malfunction of link a can be such as 0.8, the probability of malfunction of link b can be such as 0.7, the probability of malfunction of link c can be such as 0.7, the probability of malfunction of link d can be such as 0.2.
S703, server, according to the network failure number preset, determine all faults combinations that this network failure number in this network is corresponding.
This network failure number can be disconnected fine number of times, i.e. link down number of times.This network failure numerical example is as can be 2.All fault combinations that in this network, this network failure number is corresponding, then can comprise: fault combination a, b, fault combination a, the combination of c, fault a, d, fault combination b, a, fault combination b, c, fault combination b, the combination of d, fault c, a, fault combination c, b, fault combination c, d, fault combination d, a, fault combination d, b and fault combination d, c.
S704, server determine the probability of malfunction of this each fault combination.
Server can be the probability of malfunction according to this each network object, adopts above-mentioned formula 2 to obtain the probability of malfunction of this each fault combination.Wherein, fault combination a, probability P (a of b, b) can be such as 0.9, fault combination a, c probability P (a, c) be 0.1, fault combination a, probability P (a of d, d) be 0, fault combination b, probability P (the b of a, a) probability is 0, probability P (the b of fault combination bc, c) be 0.8, fault combination b, probability P (the b of d, d) be 0, fault combination c, probability P (the c of a, a) be 0, fault combination c, probability P (the c of b, b) be 0, fault combination c, probability P (the c of d, d) be 0, fault combination d, probability P (the d of a, a) be 0, fault combination d, probability P (the d of b, b) be 0, fault combination d, probability P (the d of c, c) be 0.
According to the probability of this all fault combination, line ordering is combined into this all fault, obtains fault combination as follows and the mapping table of probability.
| Fault combines | Probability |
| a,b | 0.9 |
| b,c | 0.8 |
| a,c | 0.1 |
| a,d | 0 |
| b,a | 0 |
| b,d | 0 |
| c,a | 0 |
| c,b | 0 |
| c,d | 0 |
| d,a | 0 |
| d,b | 0 |
| d,c | 0 |
S705, server, to the probability summation of this all fault combination, obtain total failare probability.
The probability sum of this all fault combination can be P (a, b)+P (b, c)+P (a, c)=1.8.
S706, server, according to this total failare probability and presupposition analysis precision, determine that in this all fault combination, probability of malfunction sum is more than or equal at least one fault combination of predetermined probabilities threshold value.
This probability of malfunction is 1.8, this presupposition analysis precision, such as, can be 0.9, and so this predetermined probabilities threshold value can be the product of 1.8 and 0.9, namely 1.62.In this all fault combination, P (a, b)+P (b, c)=1.7, are greater than this predetermined probabilities threshold value 1.62, then the combination of this at least one fault can comprise: { a, bb, c}.
The network object that S707, server are corresponding according to each network failure of fault combination each in the combination of this at least one fault, the bearer service information of the network object corresponding with this each network failure, determine the business of this each fault combined effect, and/or, not by the business of this each fault combined effect.
The embodiment of the present invention three is described by the failure analysis methods of concrete example to the various embodiments described above, and its beneficial effect is similar to the above embodiments, does not repeat them here.
The embodiment of the present invention four provides a kind of fail analysis device.The structural representation of a kind of fail analysis device that Fig. 8 provides for the embodiment of the present invention four.As shown in Figure 8, this fail analysis device 800 can comprise: determination module 801 and analysis module 802.
Determination module 801, for the network failure determining that in network, probability of malfunction is maximum.
Analysis module 802, carries out accident analysis for the network failure maximum to this probability of malfunction.
Optionally, determination module 801, also for before determining the network failure that in this network, this probability of malfunction is maximum, determines the probability of malfunction of each network failure in this network.
Optionally, determination module 801, also for the historical failure information according to network object each in this network, determines the probability of malfunction of this each network object, and the probability of malfunction of this each network object is defined as the probability of malfunction of this each network failure; Wherein, this network object comprises: node and/or link.
Optionally, determination module 801, also for the historical failure information according to this each network object, adopts formula 1 to determine the probability of malfunction of this each network object at moment t; This historical failure information comprises historical failure number of times, and the generation time of each historical failure.
Wherein, e
ibe i-th network object, i is arbitrary element in 1,2,3...N, and N is the network object number in this network;
for e
iat the probability of malfunction of moment t;
for e
ithe time series of k historical failure;
for e
ithe generation time of the 1st historical failure.
Optionally, this fail analysis device 800 also can comprise:
Receiver module, for receiving the historical failure information of this each network object that controller sends.
Optionally, determination module 801, also for determining at least one fault combination that probability of malfunction sum is maximum, the network failure in this at least one fault being combined is defined as the maximum network failure of this probability of malfunction; Wherein, the network failure number in each fault combination equals default network failure number; This default network failure number is simultaneous network failure number.
Optionally, this determination module 801, also for determining all fault combinations that this default network failure number is corresponding; By the probability of malfunction sum of this all fault combination, be defined as total failare probability; Determine that in this all fault combination, probability of malfunction sum is more than or equal to this at least one fault combination of predetermined probabilities threshold value; This predetermined probabilities threshold value is less than this total failare probability.
Optionally, determination module 801, also for determining the probability of malfunction of each fault combination in this all fault combination.
Optionally, if presetting network failure number is 1, determination module 801, also for the probability of malfunction by a network failure in this each fault combination, is defined as the probability of malfunction of this each fault combination.
Alternately, if this default network failure number is more than or equal to 2, determination module 801, the probability of malfunction also for adopting formula 2 to determine this each fault combination.
P
m=p (1) * p (2|1) ... p (k ' | k '-1) ... formula 2
Wherein, m is arbitrary element in 1,2,3...M; M is fault number of combinations in this all fault combination, and
k ' is this default network failure number, k '>=2; P
1~ P
mto represent in this all faults combination the probability of each fault combination from big to small successively; P (1) is the maximum probability of malfunction in this each fault combination; P (k ' | k '-1) is the probability of malfunction of kth ' individual network failure when probability of malfunction kth '-1 from big to small network failure breaks down in this each fault combination.
Wherein,
y is the historical failure number of times of kth '-1 network failure in this each fault combination;
for the time series of y historical failure of this kth '-1 network failure; X is the historical failure number of times of kth ' individual network failure in this each fault combination;
for the time series of x historical failure of this kth '-1 network failure; t
rfor average time for repair of breakdowns.
Optionally, determination module 801, also for according to this total failare probability and presupposition analysis precision, adopts formula 3 to determine that this at least one fault combines.
Wherein,
for this total failare probability, a is this presupposition analysis precision, and this predetermined probabilities threshold value is the product of this total failare probability and this presupposition analysis precision; N ' is arbitrary element in 1,2,3...N ',
for the probability of malfunction sum of this at least one fault combination, P
1~ P
n 'to represent in the combination of this at least one fault the probability of each fault combination from big to small successively; P
1~ P
n 'corresponding fault is combined as the combination of this at least one fault.
Optionally, analysis module 802, also for carrying out accident analysis to the network failure in fault combination each in the combination of this at least one fault, determines this impact of each fault combination on business.
Optionally, analysis module 802, also for the network object corresponding according to each network failure in this each fault combination, the bearer service information of the network object corresponding with this each network failure, determine the business of this each fault combined effect, and/or, not by the business of this each fault combined effect.
The fail analysis device that the embodiment of the present invention four provides, can be used for the failure analysis methods described in any embodiment in above-described embodiment one or embodiment two, its beneficial effect is similar to the above embodiments, does not repeat them here.
The embodiment of the present invention five also provides a kind of server.The structural representation of the server that Fig. 9 provides for the embodiment of the present invention five.As shown in Figure 9, this server 900 can comprise fail analysis device 901.This fail analysis device 901 can be arbitrary described fail analysis device in above-described embodiment four.
The server that the embodiment of the present invention five provides, can comprise the fail analysis device of above-described embodiment four, thus the failure analysis methods that execution above-described embodiment one or embodiment two provide, its beneficial effect is similar to the above embodiments, does not repeat them here.
One of ordinary skill in the art will appreciate that: all or part of step realizing above-mentioned each embodiment of the method can have been come by the hardware that program command is relevant.Aforesaid program can be stored in a computer read/write memory medium.This program, when performing, performs the step comprising above-mentioned each embodiment of the method; And aforesaid storage medium comprises: ROM, RAM, magnetic disc or CD etc. various can be program code stored medium.
Last it is noted that above each embodiment is only in order to illustrate technical scheme of the present invention, be not intended to limit; Although with reference to foregoing embodiments to invention has been detailed description, those of ordinary skill in the art is to be understood that: it still can be modified to the technical scheme described in foregoing embodiments, or carries out equivalent replacement to wherein some or all of technical characteristic; And these amendments or replacement, do not make the essence of appropriate technical solution depart from the scope of various embodiments of the present invention technical scheme.
Claims (27)
1. a failure analysis methods, is characterized in that, comprising:
Determine the network failure that in network, probability of malfunction is maximum;
The network failure maximum to described probability of malfunction carries out accident analysis.
2. method according to claim 1, is characterized in that, described determine the network failure that in network, probability of malfunction is maximum before, described method also comprises:
Determine the probability of malfunction of each network failure in described network.
3. method according to claim 2, is characterized in that, the described probability of malfunction determining each network failure in network, comprising:
According to the historical failure information of network object each in described network, determine the probability of malfunction of described each network object; Described network object comprises: node and/or link;
The probability of malfunction of described each network object is defined as the probability of malfunction of described each network failure.
4. method according to claim 3, is characterized in that, the described historical failure information according to described each network object, determines that the probability of malfunction of described each network object comprises:
According to the historical failure information of described each network object, formula 1 is adopted to determine the probability of malfunction of described each network object at moment t; Described historical failure information comprises historical failure number of times, and the generation time of each historical failure;
Wherein, e
ibe i-th network object, i is 1,2,3 ... arbitrary element in N, N is the network object number in described network;
for e
iat the probability of malfunction of moment t;
for e
ithe time series of k historical failure;
for e
ithe generation time of the 1st historical failure.
5. the method according to claim 3 or 4, is characterized in that, the described historical failure information according to network object each in described network, and before determining the probability of malfunction of described each network object, described method also comprises:
Receive the historical failure information of described each network object that controller sends.
6. method according to claim 4, is characterized in that, the described network failure determining that in network, probability of malfunction is maximum comprises:
Determine at least one fault combination that probability of malfunction sum is maximum; Wherein, the network failure number in each fault combination equals default network failure number; Described default network failure number is simultaneous network failure number;
Network failure in described at least one fault combination is defined as the maximum network failure of described probability of malfunction.
7. method according to claim 6, is characterized in that, described determine described probability of malfunction sum maximum at least one fault combination, comprising:
Determine all fault combinations that described default network failure number is corresponding;
By the probability of malfunction sum of described all fault combinations, be defined as total failare probability;
Determine that in described all fault combinations, probability of malfunction sum is more than or equal to described at least one fault combination of predetermined probabilities threshold value; Described predetermined probabilities threshold value is less than described total failare probability.
8. method according to claim 7, is characterized in that, described by the probability of malfunction sum of described all fault combinations, before being defined as total failare probability, described method also comprises:
Determine the probability of malfunction of each fault combination in described all fault combinations.
9. method according to claim 8, is characterized in that, if described default network failure number is 1, the described probability of malfunction determining that in described all fault combinations, each fault combines comprises:
By the probability of malfunction of a network failure in described each fault combination, be defined as the probability of malfunction of described each fault combination.
10. method according to claim 8, is characterized in that, if described default network failure number is more than or equal to 2, the described probability of malfunction determining that in described all fault combinations, each fault combines comprises:
Formula 2 is adopted to determine the probability of malfunction of described each fault combination;
P
m=p (1) * p (2|1) ... p (k ' | k '-1) ... formula 2
Wherein, m is 1,2,3 ... arbitrary element in M; M is fault number of combinations in described all fault combinations, and
k ' is described default network failure number, k '>=2; P
1~ P
mto represent in the combination of described all fault the probability of each fault combination from big to small successively; P (1) is the maximum probability of malfunction in described each fault combination; P (k ' | k '-1) is the probability of malfunction of kth ' individual network failure when probability of malfunction kth '-1 from big to small network failure breaks down in described each fault combination;
Wherein,
y is the historical failure number of times of kth '-1 network failure in described each fault combination;
for the time series of y historical failure of described kth '-1 network failure; X is the historical failure number of times of kth ' individual network failure in described each fault combination;
for the time series of x historical failure of described kth '-1 network failure; t
rfor average time for repair of breakdowns.
11. methods according to claim 9 or 10, is characterized in that, described described at least one fault combination determining that probability of malfunction sum in described all fault combinations is more than or equal to predetermined probabilities threshold value comprises:
According to described total failare probability and presupposition analysis precision, formula 3 is adopted to determine described at least one fault combination;
Wherein,
for described total failare probability, a is described presupposition analysis precision, and described predetermined probabilities threshold value is the product of described total failare probability and described presupposition analysis precision; N ' is 1,2,3 ... arbitrary element in N ',
for the probability of malfunction sum of described at least one fault combination, P
1~ P
n 'to represent at least one fault described combination the probability of each fault combination from big to small successively; P
1~ P
n 'corresponding fault is combined as described at least one fault combination.
12. methods according to any one of claim 6-11, it is characterized in that, the described network failure maximum to described probability of malfunction carries out accident analysis, comprising:
Accident analysis is carried out to the network failure in fault combination each in described at least one fault combination, determines the impact of described each fault combination on business.
13. methods according to claim 12, is characterized in that, describedly carry out accident analysis to the network failure in fault combination each in the combination of described at least one fault, comprising:
The network object corresponding according to each network failure in described each fault combination, the bearer service information of the network object corresponding with described each network failure, determine the business of described each fault combined effect, and/or, not by the business of described each fault combined effect.
14. 1 kinds of fail analysis devices, is characterized in that, comprising:
Determination module, for the network failure determining that in network, probability of malfunction is maximum;
Analysis module, carries out accident analysis for the network failure maximum to described probability of malfunction.
15. devices according to claim 14, is characterized in that,
Described determination module, also for before determining the network failure that described in described network, probability of malfunction is maximum, determines the probability of malfunction of each network failure in described network.
16. devices according to claim 15, is characterized in that,
Described determination module, also for the historical failure information according to network object each in described network, determines the probability of malfunction of described each network object, and the probability of malfunction of described each network object is defined as the probability of malfunction of described each network failure; Wherein, described network object comprises: node and/or link; .
17. devices according to claim 16, is characterized in that,
Described determination module, also for the historical failure information according to described each network object, adopts formula 1 to determine the probability of malfunction of described each network object at moment t; Described historical failure information comprises historical failure number of times, and the generation time of each historical failure;
Wherein, e
ibe i-th network object, i is 1,2,3 ... arbitrary element in N, N is the network object number in described network;
for e
iat the probability of malfunction of moment t;
for e
ithe time series of k historical failure;
for e
ithe generation time of the 1st historical failure.
18. devices according to claim 16 or 17, it is characterized in that, described device also comprises:
Receiver module, for receiving the historical failure information of described each network object that controller sends.
19. devices according to claim 17, is characterized in that,
Described determination module, also for determining at least one fault combination that probability of malfunction sum is maximum, is defined as the maximum network failure of described probability of malfunction by the network failure in described at least one fault combination; Wherein, the network failure number in each fault combination equals default network failure number; Described default network failure number is simultaneous network failure number.
20. devices according to claim 19, is characterized in that,
Described determination module, also for determining all fault combinations that described default network failure number is corresponding; By the probability of malfunction sum of described all fault combinations, be defined as total failare probability; Determine that in described all fault combinations, probability of malfunction sum is more than or equal to described at least one fault combination of predetermined probabilities threshold value; Described predetermined probabilities threshold value is less than described total failare probability.
21. devices according to claim 20, is characterized in that,
Described determination module, also for determining the probability of malfunction of each fault combination in described all fault combinations.
22. devices according to claim 21, is characterized in that, if described default network failure number is 1, described determination module, also for the probability of malfunction by a network failure in described each fault combination, is defined as the probability of malfunction of described each fault combination.
23. devices according to claim 21, is characterized in that, if described default network failure number is more than or equal to 2, described determination module, and the probability of malfunction also for adopting formula 2 to determine described each fault combination;
P
m=p (1) * p (2|1) ... p (k ' | k '-1) ... formula 2
Wherein, m is 1,2,3 ... arbitrary element in M; M is fault number of combinations in described all fault combinations, and
k ' is described default network failure number, k '>=2; P
1~ P
mto represent in the combination of described all fault the probability of each fault combination from big to small successively; P (1) is the maximum probability of malfunction in described each fault combination; P (k ' | k '-1) is the probability of malfunction of kth ' individual network failure when probability of malfunction kth '-1 from big to small network failure breaks down in described each fault combination;
Wherein,
y is the historical failure number of times of kth '-1 network failure in described each fault combination;
for the time series of y historical failure of described kth '-1 network failure; X is the historical failure number of times of kth ' individual network failure in described each fault combination;
for the time series of x historical failure of described kth '-1 network failure; t
rfor average time for repair of breakdowns.
24. devices according to claim 22 or 23, is characterized in that,
Described determination module, also for according to described total failare probability and presupposition analysis precision, adopts formula 3 to determine described at least one fault combination;
Wherein,
for described total failare probability, a is described presupposition analysis precision, and described predetermined probabilities threshold value is the product of described total failare probability and described presupposition analysis precision; N ' is 1,2,3 ... arbitrary element in N ',
for the probability of malfunction sum of described at least one fault combination, P
1~ P
n 'to represent at least one fault described combination the probability of each fault combination from big to small successively; P
1~ P
n 'corresponding fault is combined as described at least one fault combination.
25. devices according to any one of claim 19-24, is characterized in that,
Described analysis module, also for carrying out accident analysis to the network failure in fault combination each in described at least one fault combination, determines the impact of described each fault combination on business.
26. devices according to claim 25, is characterized in that,
Described analysis module, also for the network object corresponding according to each network failure in described each fault combination, the bearer service information of the network object corresponding with described each network failure, determine the business of described each fault combined effect, and/or, not by the business of described each fault combined effect.
27. 1 kinds of servers, is characterized in that, comprising: the fail analysis device according to any one of the claims 14-26.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107046478A (en) * | 2017-04-06 | 2017-08-15 | 南通大学 | A kind of car networking link survivability evaluation method |
| CN107608837A (en) * | 2017-09-21 | 2018-01-19 | 浪潮软件集团有限公司 | Method, device, readable medium and storage controller for positioning fault environment equipment |
| CN108111361A (en) * | 2018-02-06 | 2018-06-01 | 武汉烽火技术服务有限公司 | Transmission network fault locating analysis method and system based on big data analysis |
| CN108322320A (en) * | 2017-01-18 | 2018-07-24 | 华为技术有限公司 | Business survival stress method and device |
| CN109270910A (en) * | 2018-10-31 | 2019-01-25 | 重庆长安汽车股份有限公司 | Robot fault analysis method, apparatus and system on a kind of production line |
| CN113271216A (en) * | 2020-02-14 | 2021-08-17 | 华为技术有限公司 | Data processing method and related equipment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101345661A (en) * | 2007-07-09 | 2009-01-14 | 大唐移动通信设备有限公司 | Fault diagnosis method and device for communication equipment |
| CN101997709A (en) * | 2009-08-10 | 2011-03-30 | 中兴通讯股份有限公司 | Root alarm data analysis method and system |
| CN104639368A (en) * | 2015-01-13 | 2015-05-20 | 中国联合网络通信集团有限公司 | Method and device for processing faults of communications network equipment |
| CN104796273A (en) * | 2014-01-20 | 2015-07-22 | 中国移动通信集团山西有限公司 | Method and device for diagnosing root of network faults |
-
2015
- 2015-09-29 CN CN201510634107.6A patent/CN105187255B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101345661A (en) * | 2007-07-09 | 2009-01-14 | 大唐移动通信设备有限公司 | Fault diagnosis method and device for communication equipment |
| CN101997709A (en) * | 2009-08-10 | 2011-03-30 | 中兴通讯股份有限公司 | Root alarm data analysis method and system |
| CN104796273A (en) * | 2014-01-20 | 2015-07-22 | 中国移动通信集团山西有限公司 | Method and device for diagnosing root of network faults |
| CN104639368A (en) * | 2015-01-13 | 2015-05-20 | 中国联合网络通信集团有限公司 | Method and device for processing faults of communications network equipment |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108322320A (en) * | 2017-01-18 | 2018-07-24 | 华为技术有限公司 | Business survival stress method and device |
| WO2018133573A1 (en) * | 2017-01-18 | 2018-07-26 | 华为技术有限公司 | Method and device for analyzing service survivability |
| US11108619B2 (en) | 2017-01-18 | 2021-08-31 | Huawei Technologies Co., Ltd. | Service survivability analysis method and apparatus |
| CN107046478A (en) * | 2017-04-06 | 2017-08-15 | 南通大学 | A kind of car networking link survivability evaluation method |
| CN107046478B (en) * | 2017-04-06 | 2020-03-31 | 南通大学 | Survivability evaluation method for Internet of vehicles link |
| CN107608837A (en) * | 2017-09-21 | 2018-01-19 | 浪潮软件集团有限公司 | Method, device, readable medium and storage controller for positioning fault environment equipment |
| CN108111361A (en) * | 2018-02-06 | 2018-06-01 | 武汉烽火技术服务有限公司 | Transmission network fault locating analysis method and system based on big data analysis |
| CN109270910A (en) * | 2018-10-31 | 2019-01-25 | 重庆长安汽车股份有限公司 | Robot fault analysis method, apparatus and system on a kind of production line |
| CN113271216A (en) * | 2020-02-14 | 2021-08-17 | 华为技术有限公司 | Data processing method and related equipment |
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|---|---|
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Effective date of registration: 20200715 Address after: 625, room 269, Connaught platinum Plaza, No. 518101, Qianjin Road, Xin'an street, Shenzhen, Guangdong, Baoan District Patentee after: SHENZHEN SHANGGE INTELLECTUAL PROPERTY SERVICE Co.,Ltd. Address before: 518129 Bantian HUAWEI headquarters office building, Longgang District, Guangdong, Shenzhen Patentee before: HUAWEI TECHNOLOGIES Co.,Ltd. Effective date of registration: 20200715 Address after: Room 102, No.48, Lane 2438, Jinshajiang Road, Putuo District, Shanghai Patentee after: Zhao Xiuwen Address before: 625, room 269, Connaught platinum Plaza, No. 518101, Qianjin Road, Xin'an street, Shenzhen, Guangdong, Baoan District Patentee before: SHENZHEN SHANGGE INTELLECTUAL PROPERTY SERVICE Co.,Ltd. |
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