CN113452537B

CN113452537B - Fault positioning method and device based on model

Info

Publication number: CN113452537B
Application number: CN202010213800.7A
Authority: CN
Inventors: 周昭; 李京红; 庞会静
Original assignee: China Mobile Communications Group Co Ltd; China Mobile Group Hebei Co Ltd
Current assignee: China Mobile Communications Group Co Ltd; China Mobile Group Hebei Co Ltd
Priority date: 2020-03-24
Filing date: 2020-03-24
Publication date: 2023-02-28
Anticipated expiration: 2040-03-24
Also published as: CN113452537A

Abstract

The invention discloses a fault positioning method and a fault positioning device based on a model, wherein the method comprises the following steps: constructing a client-service-resource equipment model; the client-service-resource equipment model records the association topological relation among the client, the service and the resource equipment; receiving a declaration request which is triggered by a client and carries unavailable service data; traversing resource equipment in the client-service-resource equipment model, and simulating to obtain a prejudgment result of whether the resource equipment is available for the client and the service in a simulated fault state aiming at any resource equipment; and calculating the matching degree according to the pre-judgment result and the unavailable service data, and positioning the resource equipment with the fault according to the calculated matching degree. According to the invention, based on the constructed client-service-resource equipment model, aiming at the declaration request of the unavailable service triggered by the client, the fault resource equipment is positioned in a simulation mode, so that the dependence on the self-capability of a technician is reduced, and the processing efficiency of manual troubleshooting is improved.

Description

Fault positioning method and device based on model

Technical Field

The invention relates to the technical field of data service and computer software, in particular to a fault positioning method and device based on a model.

Background

An Internet Data Center (IDC for short) is a service platform with perfect equipment (including high-speed Internet access bandwidth, high-performance local area network, safe and reliable computer room environment, etc.), specialized management and perfect application. On the basis of the platform, the IDC service provider provides Internet basic platform services (such as Internet bandwidth, virtual private network, server hosting, virtual host and the like) and various value-added services (such as domain name system services, load balancing systems, data storage and backup, data analysis and processing and the like) for the client.

In the process of maintaining the schedule of the IDC, a declaration that the service is unavailable is received by a client, and for the declaration, a technician is required to find a fault position in a network in time, namely, the fault is positioned, and fault equipment and components are repaired or replaced so as to recover the service of the service as soon as possible. In the prior art, fault location declared by a client mainly depends on maintenance experience and technical level of technicians, equipment with possible faults is manually checked one by one according to service access positions of IDC clients, the equipment needs to be checked by one remote login equipment or checked on site, the location period is long, and whether location is accurate depends on the capability of the technicians.

Disclosure of Invention

In view of the above, the present invention has been made to provide a method and apparatus for model-based fault location that overcomes or at least partially solves the above problems.

According to an aspect of the present invention, there is provided a model-based fault localization method, comprising:

constructing a client-service-resource equipment model; the client-service-resource equipment model records the association topological relation among the client, the service and the resource equipment;

receiving a declaration request which is triggered by a client and carries unavailable service data;

traversing resource equipment in the client-service-resource equipment model, and simulating to obtain a prejudgment result of whether the resource equipment is available for clients and services in a simulated fault state aiming at any resource equipment;

and calculating the matching degree according to the pre-judgment result and the unavailable service data, and positioning the resource equipment with the fault according to the calculated matching degree.

According to another aspect of the present invention, there is provided a model-based fault localization apparatus comprising:

a construction module adapted to construct a client-service-resource device model; the client-service-resource equipment model records the association topological relation among the client, the service and the resource equipment;

the receiving module is suitable for receiving a reporting request which is triggered by a client and carries unavailable service data;

the simulation module is suitable for traversing the resource equipment in the client-service-resource equipment model and simulating to obtain a prejudgment result whether the resource equipment is available for the client and the service in a simulated fault state aiming at any resource equipment;

and the matching module is suitable for calculating the matching degree according to the pre-judgment result and the unavailable service data and positioning the resource equipment with the fault according to the calculated matching degree.

According to still another aspect of the present invention, there is provided an electronic apparatus including: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;

the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the model-based fault location method.

According to yet another aspect of the present invention, a computer storage medium is provided, and at least one executable instruction is stored in the storage medium, and the executable instruction causes a processor to execute operations corresponding to the above-mentioned model-based fault location method.

According to the fault positioning method and device based on the model, a client-service-resource equipment model is constructed; the client-service-resource equipment model records the association topological relation among the client, the service and the resource equipment; receiving a declaration request which is triggered by a client and carries unavailable service data; traversing resource equipment in the client-service-resource equipment model, and simulating to obtain a prejudgment result of whether the resource equipment is available for the client and the service in a simulated fault state aiming at any resource equipment; and calculating the matching degree according to the pre-judgment result and the unavailable service data, and positioning the resource equipment with the fault according to the calculated matching degree. According to the invention, based on the established client-service-resource equipment model, the fault resource equipment is positioned by a simulation mode aiming at the reporting request of the unavailable service triggered by the client, so that the dependence on the self capability of a technician is reduced, and the processing efficiency of manual troubleshooting is improved.

The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:

FIG. 1 shows a flow diagram of a method of model-based fault location according to one embodiment of the invention;

FIG. 2 illustrates a schematic diagram of a client-service-resource device model, according to one embodiment of the invention;

FIG. 3 illustrates a schematic diagram of a client-service-resource device model simulating a resource device failure, according to one embodiment of the invention;

FIG. 4 shows a functional block diagram of a model-based fault locating device according to one embodiment of the present invention;

fig. 5 shows a schematic structural diagram of an electronic device according to an embodiment of the invention.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

FIG. 1 shows a flow diagram of a method of model-based fault location according to one embodiment of the invention. As shown in fig. 1, the method for locating a fault based on a model specifically includes the following steps:

and step S101, constructing a client-service-resource equipment model.

In the prior art, the IDC fault location is mostly implemented by adopting a manual troubleshooting mode of technicians, when receiving the report that IDC client services are unavailable, operation and maintenance personnel manually perform processing, and frequently rely on the experience of the operation and maintenance personnel to troubleshoot equipment, so that the location time is long. And because the equipment itself has no direct association relation with the customer service, the equipment needs to be checked one by one during the checking, and the time is long.

Based on the above problems, the present embodiment constructs a client-service-resource device model, which records the association topological relationship among clients, services, and resource devices. Specifically, resource equipment information of the IDC Internet data center network is scanned and obtained based on a network topology discovery technology. The resource device information includes a resource device type, a north-south link relation, a network type, and the like. For example, the whole network scans to obtain all network resource devices in the IDC network, including port devices, access devices, aggregation devices, routing devices, and the like, and also obtains the north-south link relationship and the network type between the resource devices. Network types such as star networks, hierarchical networks, etc. After a resource device is obtained by using a network topology discovery technology, the next hop address of a direct connection route in a routing table is read, then a subnet mask of the addresses is obtained from the address table, the address range of the subnet is calculated by a gateway address and the subnet mask, then the addresses in the address range are scanned, and then all the resource devices in the IDC network are discovered. And constructing a resource equipment operation and maintenance model according to the resource equipment information. As shown in particular in fig. 2. The resource device operation and maintenance model comprises port devices, access devices, convergence devices, routing devices and south-north multi-stage link connection lines among the resource devices.

For the network topology discovery technology, it specifically includes discovering devices and discovering link relationships. The discovery device has two device discovery modes of network automatic discovery and seed address diffusion and network segment scanning, and can use one of the two modes or can be used in combination with the two modes. The seed address diffusion mode is specifically realized as follows: if the current network address distribution is known, the core device information of the network can be known clearly, and a plurality of core devices can be set as seed addresses. The network automatic discovery function takes the seed addresses as starting points and spreads the information out step by collecting and analyzing the relevant information of the equipment. The seed address diffusion mode is suitable for all network devices with complete device protocol setting and accessible to the monitoring server without barriers. If a plurality of network nodes which are not configured with protocols or cannot be accessed by the monitoring server exist in the network structure, the expansion process can meet barrier points and cannot continue to be expanded and explored. The seed address spreading mode has the advantages that all detection addresses are actual information from resource equipment, and belong to targeted address detection, and time waste caused by redundant empty address detection is avoided; the disadvantage is that the current network architecture needs to be clearly mastered and the device protocol settings and connectivity requirements are complete. The network segment scanning mode is concretely realized as follows: if the address setting of the current network device is not well known, and it cannot be guaranteed that the protocol setting of all the devices is correct or it cannot be determined that the monitoring server can access all the devices with monitoring without obstacles, the devices to be monitored can be roughly included by setting a plurality of network segments. The network automatic discovery function firstly takes all the addresses in the seed network segment as starting addresses, and then gradually expands outwards by the starting addresses. The network segment scanning mode has the advantages that equipment nodes which cannot be accessed can be effectively crossed in a network segment coverage mode, and equipment can be comprehensively discovered; meanwhile, the network coverage mode will generate many detection behaviors of empty addresses, and further generate extra time consumption. The discovery interval is used to limit the testing of ip addresses during address expansion in auto-discovery. If an address outside the address range is encountered in the address expansion process, the automatic discovery function ignores the address and does not perform protocol test and data acquisition. Address constraints of the white list nature. The shielding interval is just opposite to the discovery interval, and addresses in the interval are ignored and belong to the blacklist setting. The mode that the seed network segment is matched with the arrangement of the discovery interval and the shielding interval is adopted, so that the comprehensive discovery of network segment coverage can be ensured, and the time waste caused by the detection of a useless address space can be avoided. Discovering links includes several ways: 1) The routing protocol analysis and automatic discovery function can analyze the relationship of two ends in the routing table entry as physical interfaces according to the routing table data of the equipment, thereby discovering the link between the equipment. 2) cdp event-driven protocol, the auto discovery function collects cdp event-driven protocol data from devices such as Cisco manufacturers, and calculates the interface connection relationship between Cisco devices at link layer. 3) And the ndp machine-ready protocol is acquired by the automatic discovery function for equipment of the Huawei manufacturer, and the interface connection relation of the link layer between the Huawei equipment is calculated. 4) The lldp machine-joining protocol is a cross-manufacturer link layer neighbor discovery protocol. If the lldp protocol is started for the device, the auto discovery function may collect and analyze the lldp protocol to calculate the link layer interface relationship between the devices. In the above various implementation manners, a suitable implementation manner is selected according to actual situations, and is not limited herein.

And after the resource equipment operation and maintenance model is obtained, obtaining client information, service information, port resource equipment information of the IDC network and north-south flow information of the network, and constructing a service operation model. As shown in fig. 2, the service operation model includes client information, service information, port resource device information, and north-south multi-level link connections therebetween. Here, the customer information, the service information, and the port resource device information of the IDC network may be obtained through, for example, an IDC operation platform, and a service operation model is constructed according to a relationship between the customer information, the service information, and the port resource device information, a north-south traffic, and the like, so as to form a service operation model taking a customer as a root, a service as a branch, and a port resource device as a leaf.

The construction sequence of the resource device operation and maintenance model and the service operation model is not particularly limited, and can be generated according to actual implementation conditions.

After the resource device operation and maintenance model and the service operation model are obtained through construction, the same port resource device between the resource device operation and maintenance model and the service operation model is used as a combination point, and combination processing is performed to obtain a client-service-resource device model, as shown in fig. 2.

Step S102, receiving a declaration request which is triggered by a client and carries unavailable service data.

When the client makes a reporting request of the unavailable service data, the reporting request of the client is received, and the unavailable service data carried by the client is obtained. The unavailable service data includes the unavailable service and current customer information.

Step S103, traversing the resource equipment in the client-service-resource equipment model, and simulating to obtain a prejudgment result whether the resource equipment is available for the client and the service in a simulated fault state aiming at any resource equipment.

After the unavailable service data is received, the embodiment analyzes and conducts the influence of the fault simulation according to the northbound link connection line in the client-service-resource device model in a fault simulation device mode, and finally obtains the influence on the client and the service, so that the unavailable service data corresponding to the fault simulation resource device can be determined, and the pre-judgment result of whether the resource device is available to the client and the service in the fault simulation state can be obtained.

Specifically, all resource devices in the client-service-resource device model are traversed, and any resource device is set to be in a simulated fault state in a simulated mode. As shown in fig. 3, the resource device (the rightmost access device in fig. 3 is taken as an example of a simulated fault state) may be marked as a simulated fault state in a coloring manner. Then, each link line in the north direction of the resource device in the client-service-resource device model is set to be in a simulated fault state, for example, four link lines in the north direction of the access device on the rightmost side are marked as the simulated fault state in a dyeing manner in fig. 3. After the simulated fault state of the link connection is determined, the states of other resource devices connected in the north direction of each link connection simulating the fault state are sequentially set, and a prejudgment result whether the client and the service are available is obtained according to the states of the other resource devices. For other resource devices connected in the north direction of each link connection line simulating the fault state, the fault state can be directly extracted and obtained according to a client-service-resource device model, and meanwhile, the operation data of other resource devices can be obtained by detecting other resource devices. And aiming at any other resource equipment, determining the state of the other resource equipment according to the operating data of the other resource equipment and/or the state of the southbound link connection of the other resource equipment. And if the operating data of the other resource equipment is normal and the states of all the southbound link connecting lines of the other resource equipment are normal, determining that the states of the other resource equipment are normal. And if the running data of other resource equipment fails or the states of all southbound link connecting lines of other resource equipment are the simulated fault states, determining that the states of other resource equipment are the simulated fault states. Under the condition that the operating data of other resource equipment is normal, but the states of all southbound link connecting lines are simulated fault states, and the states of other resource equipment are also determined to be simulated fault states in consideration of the conduction influence of the states of the southbound link connecting lines.

And according to the states of other resource equipment, if the states of the other resource equipment are the simulated fault states, setting the northbound link lines of the other resource equipment to be the simulated fault states. And circularly executing the steps, sequentially carrying out the northward direction, and acquiring the states of other resource equipment connected in the northward direction of each link line simulating the fault state until the northward direction is determined to be in the service state, so as to obtain a prejudgment result of whether the client and the service are available. As shown in fig. 3, the two services on the right side are set to be in the pre-determined unavailable state, and the loop is terminated. Here, when the unavailable state of the pre-judged service completely matches the unavailable service data carried by the reporting request, the loop may be terminated. If multiple failed resource devices are considered, the above process may be repeated until a complete match is achieved.

And according to the states of the other resource devices, if the states of the other resource devices are normal states, setting the northbound link connection lines of the other resource devices to be normal states.

Optionally, before executing this step, the embodiment may further determine, according to the reporting request and the client-service-resource device model, the corresponding associated resource device in the southbound direction from the unavailable service. And detecting the associated resource equipment to detect whether the associated resource equipment is in a fault state. And if so, directly repairing the associated resource equipment. If the associated resource equipment is detected not to be in the fault state, the step is executed, and the pre-judgment result of whether the resource equipment is available for the client and the service in the simulated fault state is obtained through simulation so as to position the resource equipment with the fault.

And step S104, calculating the matching degree according to the pre-judgment result and the unavailable service data, and positioning the resource equipment with the fault according to the calculated matching degree.

And calculating the matching degree of the pre-judgment result according to the service pre-judgment available state, the service pre-judgment unavailable state and the unavailable service data contained in the pre-judgment result. The matching degree comprises data such as the accuracy of the pre-judgment result, the recall rate of the pre-judgment result and the like. The calculation of the matching degree is a two-classification prejudgment task for judging whether the client service is available, and the client service is divided into two categories according to whether the client service is available: 0 (available), 1 (unavailable), matching of the prejudged result with the client declaration request, occurs in 4 cases as follows:

	customer declaration services are not available: 1	Client unreported service unavailable: 0
			Service pre-judgment unavailable state: 1	TP(TruePositive)	FP(FalsePositive)
Service pre-judging available state: 0	FN(FalseNegative)	TN(TrueNegative)

TABLE 1

The accuracy of the pre-judgment result is specifically as follows: and (4) correctly pre-judging the ratio of the service number of the service pre-judging available state and the service pre-judging unavailable state in the pre-judging result to the total service number. The total service number comprises the service number of the correct pre-judging service pre-judging available state and the service pre-judging unavailable state and the service number of the error pre-judging service pre-judging available state and the service pre-judging unavailable state. As shown in table 1, the number of services in the state that the correct pre-judgment service is pre-judged to be available is TN, the number of services in the state that the correct pre-judgment service is pre-judged to be unavailable is TP, the number of services in the state that the error pre-judgment service is pre-judged to be available is FN, and the number of services in the state that the error pre-judgment service is pre-judged to be unavailable is FP. TP + FP + FN + TN = total traffic number. The accuracy rate of the prejudgment result = (TP + TN)/(TP + FP + FN + TN) × 100%. In contrast, the error rate of the pre-judgment result =100% -accuracy rate.

The accurate rate of the pre-judgment result is specifically as follows: and the ratio of the number of the services in the unavailable state for service pre-judgment in the pre-judgment result to the number of the services in the unavailable state for service pre-judgment in the pre-judgment result is pre-judged. The accuracy of the prejudgment result is = TP/(TP + FP) × 100%.

The recall rate of the pre-judgment result is specifically as follows: and the proportion of the number of services in the unavailable state of service pre-judgment is correctly pre-judged in the pre-judgment result in the unavailable service data. The recall ratio of the prejudgment result = TP/(TP + FN) × 100%.

And comprehensively considering the accuracy rate of the pre-judgment result and the recall rate of the pre-judgment result, and obtaining the average value of the accuracy rate of the pre-judgment result and the recall rate of the pre-judgment result =2 accuracy rate recall rate/(accuracy rate + recall rate).

And determining the resource equipment with the highest matching degree as the setting resource of the fault according to the calculated data such as the accuracy rate of the pre-judgment result, the recall rate of the pre-judgment result and the like. The highest matching degree is specifically the highest accuracy of the pre-judgment result, or when the accuracy of the pre-judgment results of a plurality of resource devices is equal, the highest average value of the accuracy of the pre-judgment result and the recall rate of the pre-judgment result is the highest matching degree.

And positioning the resource equipment with the highest matching degree as the failed resource equipment, detecting the failed resource equipment and repairing the failed resource equipment in time.

According to the fault positioning method based on the model, provided by the invention, a client-service-resource equipment model is constructed; the client-service-resource equipment model records the association topological relation among the client, the service and the resource equipment; receiving a declaration request which is triggered by a client and carries unavailable service data; traversing resource equipment in the client-service-resource equipment model, and simulating to obtain a prejudgment result of whether the resource equipment is available for the client and the service in a simulated fault state aiming at any resource equipment; and calculating the matching degree according to the pre-judgment result and the unavailable service data, and positioning the resource equipment with the fault according to the calculated matching degree. According to the invention, based on the established client-service-resource equipment model, the fault resource equipment is positioned by a simulation mode aiming at the reporting request of the unavailable service triggered by the client, so that the dependence on the self capability of a technician is reduced, and the processing efficiency of manual troubleshooting is improved. Furthermore, if a plurality of fault resource devices exist, the resource devices are sorted according to the matching degree, so that technicians can conveniently sort the resource devices one by one according to the sorting, and the fault resource devices can be quickly repaired.

FIG. 4 shows a functional block diagram of a model-based fault locating device according to one embodiment of the present invention. As shown in fig. 4, the model-based fault locating device includes the following modules:

a build module 410 adapted to build a client-service-device resource model; the client-service-equipment resource model records the association topological relation among clients, services and equipment resources;

a receiving module 420, adapted to receive a reporting request carrying unavailable service data triggered by a user;

the simulation module 430 is adapted to traverse the device resources in the client-service-device resource model, and for any device resource, simulate to obtain a pre-judgment result of whether the device resource is available for the client and the service in a simulated fault state;

and the matching module 440 is adapted to calculate a matching degree according to the pre-judgment result and the unavailable service data, and locate the failed device resource according to the calculated matching degree.

Optionally, the building module 410 further comprises:

the first construction unit 411 is suitable for scanning and acquiring resource equipment information of the IDC internet data center network; the resource equipment information comprises a resource equipment type, a north-south link relation and a network type; the resource equipment comprises port equipment, access equipment, convergence equipment and routing equipment; constructing a resource equipment operation and maintenance model according to the resource equipment information; the resource equipment operation and maintenance model comprises port equipment, access equipment, convergence equipment, routing equipment and south-north multi-level link lines among the resource equipment;

a second constructing unit 412, adapted to obtain client information, service information, port resource device information of the IDC network, and north-south traffic information of the network, and construct a service operation model; the service operation model comprises client information, service information, port resource equipment information and a south-north multi-level link connection line;

the third constructing unit 413 is adapted to perform combination processing on the same port resource device between the resource device operation and maintenance model and the service operation model to obtain a client-service-resource device model.

Optionally, the apparatus further comprises:

the detection and repair module 450 is adapted to determine the associated resource device corresponding to the unavailable service according to the reporting request and the client-service-resource device model; detecting whether the associated resource equipment is in a fault state; and if so, repairing the associated resource equipment.

Optionally, the simulation module 430 is further adapted to:

traversing resource equipment in the client-service-resource equipment model, and setting the resource equipment to be in a simulated fault state aiming at any resource equipment in a simulated mode;

setting each link connection in the northbound direction of the resource equipment in the client-service-resource equipment model as a simulated fault state;

and sequentially setting the states of other resource equipment in the northward direction of each link connecting line simulating the fault state, and obtaining a prejudgment result whether the client and the service are available according to the states of the other resource equipment.

Optionally, the simulation module 430 is further adapted to:

extracting other resource equipment in the northward direction of each link connecting line simulating the fault state, and acquiring the operating data of the other resource equipment; for any other resource equipment, determining the states of the other resource equipment according to the operating data of the other resource equipment and/or the state of the southbound link connection of the other resource equipment; if the states of other resource equipment are simulated fault states, setting the northbound link connection lines of the other resource equipment as simulated fault states; circularly executing the steps until the state of the service is determined, and obtaining a prejudgment result whether the client and the service are available;

and if the state of the other resource equipment is the normal state, setting the northbound link connection line of the other resource equipment to be the normal state.

Optionally, the simulation module 430 is further adapted to:

if the operating data of other resource equipment is normal and the states of all southbound link connecting lines of other resource equipment are normal, determining that the states of other resource equipment are normal;

and if the running data of other resource equipment fails or the states of all southbound link connecting lines of other resource equipment are the simulated fault states, determining that the states of other resource equipment are the simulated fault states.

Optionally, the matching module 440 is further adapted to:

calculating the matching degree of the pre-judging result according to the service pre-judging available state, the service pre-judging unavailable state and the unavailable service data contained in the pre-judging result;

determining the resource equipment with the highest matching degree as the failed resource equipment; the matching degree comprises the accuracy rate of the pre-judgment result, the accuracy rate of the pre-judgment result and/or the recall rate of the pre-judgment result; the accuracy of the pre-judgment result is specifically as follows: the proportion of the service number of the service pre-judging available state and the service pre-judging unavailable state in the total service number is correctly pre-judged in the pre-judging result; the total service number comprises the service number of the correct pre-judging service pre-judging available state and the service pre-judging unavailable state and the service number of the error pre-judging service pre-judging available state and the service pre-judging unavailable state; the accurate rate of the pre-judgment result is specifically as follows: the ratio of the number of services in the service pre-judging unavailable state in the pre-judging result to the number of services in the service pre-judging unavailable state in the pre-judging result is pre-judged; the recall rate of the prejudgment result is specifically as follows: and the proportion of the number of services in the unavailable state of the service pre-judgment is correctly pre-judged in the pre-judgment result in the unavailable service data.

The descriptions of the modules refer to the corresponding descriptions in the method embodiments, and are not repeated herein.

The present application further provides a non-volatile computer storage medium having at least one executable instruction stored thereon, where the computer executable instruction can execute the model-based fault location method in any of the above method embodiments.

Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and the specific embodiment of the present invention does not limit the specific implementation of the electronic device.

As shown in fig. 5, the electronic device may include: a processor (processor) 502, a Communications Interface 504, a memory 506, and a communication bus 508.

Wherein:

the processor 502, communication interface 504, and memory 506 communicate with one another via a communication bus 508.

A communication interface 504 for communicating with network elements of other devices, such as clients or other servers.

The processor 502 is configured to execute the program 510, and may specifically execute relevant steps in the above-described embodiment of the model-based fault location method.

In particular, program 510 may include program code that includes computer operating instructions.

The processor 502 may be a central processing unit CPU, or an Application Specific Integrated Circuit ASIC (Application Specific Integrated Circuit), or one or more Integrated circuits configured to implement an embodiment of the present invention. The electronic device comprises one or more processors, which can be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.

And a memory 506 for storing a program 510. The memory 506 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.

The program 510 may specifically be adapted to cause the processor 502 to perform a model-based fault localization method in any of the above-described method embodiments. For specific implementation of each step in the program 510, reference may be made to corresponding steps and corresponding descriptions in units in the above-described model-based fault location embodiment, which are not described herein again. It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described devices and modules may refer to the corresponding process descriptions in the foregoing method embodiments, and are not described herein again.

The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. Moreover, the present invention is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.

In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.

Those skilled in the art will appreciate that the modules in the devices in an embodiment may be adaptively changed and arranged in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.

The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components in a model-based fault location apparatus according to embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.

It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.

Claims

1. A method for model-based fault location, the method comprising:

constructing a client-service-resource equipment model; the client-service-resource equipment model records the association topological relation among clients, services and resource equipment;

traversing the resource equipment in the client-service-resource equipment model, and simulating to obtain a prejudgment result of whether the resource equipment is available for the client and the service in a simulated fault state aiming at any resource equipment;

calculating the matching degree according to the pre-judgment result and the unavailable service data, and positioning the resource equipment with the fault according to the calculated matching degree;

the step of traversing the resource device in the client-service-resource device model, for any resource device, obtaining a pre-determination result of whether the resource device is available for the client and the service in a simulated fault state by simulation further includes:

traversing the resource equipment in the client-service-resource equipment model, and setting the resource equipment to be in a simulated fault state aiming at any resource equipment in a simulated mode;

2. The method of claim 1, wherein the building a client-service-resource device model further comprises:

scanning to obtain resource equipment information of an IDC internet data center network; the resource equipment information comprises a resource equipment type, a north-south link relation and a network type; the resource equipment comprises port equipment, access equipment, convergence equipment and routing equipment;

constructing a resource equipment operation and maintenance model according to the resource equipment information; the resource equipment operation and maintenance model comprises port equipment, access equipment, convergence equipment, routing equipment and south-north multi-level link connection among the resource equipment;

acquiring client information, service information, port resource equipment information and north-south flow information of the IDC network, and constructing a service operation model; the service operation model comprises client information, service information, port resource equipment information and a south-north multi-level link connection line;

and combining the same port resource equipment between the resource equipment operation and maintenance model and the service operation model to obtain a client-service-resource equipment model.

3. The method of claim 1, further comprising:

determining associated resource equipment corresponding to unavailable services according to the reporting request and the client-service-resource equipment model;

detecting whether the associated resource equipment is in a fault state;

and if so, repairing the associated resource equipment.

4. The method of claim 1, wherein the sequentially setting the states of other resource devices in the northbound direction of each link connection line simulating the fault state, and obtaining the prediction result of whether the customer and the service are available according to the states of the other resource devices further comprises:

5. The method of claim 4, wherein determining the state of the other resource device according to the operating data of the other resource device and/or the state of the southbound link connection of the other resource device for any other resource device further comprises:

6. The method according to claim 1, wherein the calculating a matching degree according to the pre-determined result and the unavailable service data, and locating the resource device having the fault according to the calculated matching degree further comprises:

determining the resource equipment with the highest matching degree as the failed resource equipment; the matching degree comprises the accuracy rate of the pre-judgment result, the accuracy rate of the pre-judgment result and/or the recall rate of the pre-judgment result; the accuracy of the pre-judgment result is specifically as follows: the proportion of the service number of the service pre-judging available state and the service pre-judging unavailable state in the pre-judging result in the total service number is correctly pre-judged; the total number of services comprises the number of services in a state that the service is available for correct pre-judgment and in a state that the service is unavailable for pre-judgment, and the number of services in a state that the service is available for error pre-judgment and in a state that the service is unavailable for pre-judgment; the accurate rate of the pre-judgment result is specifically as follows: the ratio of the number of services in the service pre-judging unavailable state in the pre-judging result to the number of services in the service pre-judging unavailable state in the pre-judging result is pre-judged; the recall rate of the pre-judgment result is specifically as follows: and the proportion of the number of services in the unavailable state of correct pre-judgment service pre-judgment in the pre-judgment result in the unavailable service data.

7. A model-based fault location device, the device comprising:

a construction module adapted to construct a client-service-resource device model; the client-service-resource equipment model records the association topological relation among clients, services and resource equipment;

the receiving module is suitable for receiving a declaration request which is triggered by a client and carries unavailable service data;

the matching module is suitable for calculating the matching degree according to the pre-judgment result and the unavailable service data and positioning the resource equipment with the fault according to the calculated matching degree;

the simulation module is further adapted to:

8. An electronic device, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface are communicated with each other through the communication bus;

the memory is configured to store at least one executable instruction that causes the processor to perform operations corresponding to the model-based fault localization method of any of claims 1-6.

9. A computer storage medium having stored therein at least one executable instruction that causes a processor to perform operations corresponding to the model-based fault localization method of any one of claims 1-6.