CN111884832B

CN111884832B - Method for acquiring passive network topology information and related equipment

Info

Publication number: CN111884832B
Application number: CN202010606959.5A
Authority: CN
Inventors: 万星; 张可力; 汪鹏云; 陈市
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2020-06-29
Filing date: 2020-06-29
Publication date: 2022-06-14
Anticipated expiration: 2040-06-29
Also published as: CN111884832A

Abstract

The embodiment of the application provides a method and a related device for acquiring passive network topology information, wherein a passive network comprises a plurality of node devices, the plurality of node devices comprise at least one intermediate node device and at least one end node device, and the method for acquiring the passive network topology information comprises the following steps: acquiring characteristic data of one or more terminal node devices in the passive network at a target moment; performing cluster analysis on the one or more terminal node devices according to the characteristic data of the one or more terminal node devices to obtain a cluster list corresponding to the target moment; and fusing cluster lists corresponding to a plurality of target moments respectively to obtain the topology information of the passive network. By implementing the embodiment of the application, the topological connection relation of the passive network can be more accurately determined.

Description

Method for acquiring passive network topology information and related equipment

Technical Field

The present application relates to the field of communications technologies, and in particular, to a method for acquiring passive network topology information and a related device.

Background

The existing passive network is composed of part or all of passive devices, and because part or all of the passive network devices are passive devices, the topology connection relationship of the maintenance equipment cannot be automatically updated through the network, so that the topology connection information of the passive network devices generally mainly depends on the maintenance update of professionals. When passive network devices are added or reduced in the passive network, a professional may not enter and update topology information in time, so that the topology information is lost or wrong, and the loss and the mistake of the topology information of the passive network devices cause that the related operation and maintenance work is difficult to be performed. For example: the fault of the home broadband access network is accurately positioned, if topological information of an optical path distribution network ODN is lost, the fault position is difficult to accurately position, whether equipment at all levels of the ODN fails or not can be checked only by installation and maintenance personnel step by step, the fault removing efficiency is low, repeated or invalid station-climbing is easily caused, and manpower and material resources are greatly wasted.

At present, in order to determine the topology information of the passive network, a professional may be required to actively interrupt the working state of the main and passive network devices; then collecting the alarm information and performance index data generated by the end node device under the main passive network device, if the end node is set up, i.e. generating alarm or interruption of performance index data, it belongs to the same passive network device. However, in the active data identification process, the implementation of the scheme also needs to interrupt the use of the passive network by the user, and affects the user service.

Therefore, how to accurately determine the topological connection relationship of the passive network without affecting the user service is an urgent problem to be solved.

Disclosure of Invention

The embodiment of the application provides a method for acquiring passive network topology information and related equipment, so as to accurately determine the topology connection relation of a passive network.

In a first aspect, an embodiment of the present application provides a method for acquiring topology information of a passive network, where the passive network includes a plurality of node devices, where the plurality of node devices includes at least one intermediate node device and at least one end node device; the method comprises the following steps:

acquiring feature data of one or more end node devices in the passive network at a target moment, wherein the target moment is a moment when performance index information of the one or more end node devices changes beyond a preset fluctuation range and/or alarm information appears, the feature data comprises the performance index information and/or the alarm information, and the one or more end node devices are one or more of the at least one end node device; performing cluster analysis on the one or more end node devices according to the characteristic data of the one or more end node devices to obtain a cluster list corresponding to the target time, wherein the cluster list comprises at least one first cluster, and each first cluster in the at least one first cluster comprises the end node device in the one or more end node devices under the same intermediate node device; and fusing cluster lists respectively corresponding to a plurality of target moments to acquire topology information of the passive network, wherein the topology information comprises at least one second cluster, and each second cluster in the at least one second cluster comprises part or all of terminal node equipment under the same intermediate node equipment in the passive network.

By implementing the embodiment of the application, the cluster list of each target moment in a plurality of target moments is obtained, and the cluster lists corresponding to the plurality of target moments are fused to obtain the topological information of the passive network. The target moment is the moment when one or more terminal node devices in the passive network have performance index information change exceeding a preset fluctuation range and/or alarm information; at this time, the characteristic data of one or more terminal node devices with performance index information change exceeding a preset fluctuation range and/or with alarm information can be acquired; according to the acquired feature data, obtaining a cluster list corresponding to the target moment through cluster analysis; further, similarly, the cluster lists corresponding to the plurality of target times can be obtained, and then the cluster lists corresponding to the plurality of target times are fused to obtain the topology information of the passive network. The characteristic data comprises performance index information and/or the alarm information, and the terminal node equipment with the performance index information change exceeding a preset fluctuation range and/or the alarm information appearing at each target moment in a plurality of target moments may be different. Therefore, the end node equipment under the same intermediate node equipment is clustered and analyzed from one or more end node equipment generating fluctuation or alarm information from the performance data at a target moment, and the implementation mode of acquiring the topology information corresponding to the passive network can greatly reduce the workload of operation and maintenance personnel, does not need related staff to actively acquire a large amount of data information, and only needs to supervise the occurrence of characteristic data or the change of the characteristic data to exceed a preset range. Secondly, the clustering lists corresponding to a plurality of target moments are fused to finally obtain the topology information of the passive network, so that the problem of inaccurate topology information reduction caused by only one clustering list of the target moments can be avoided, and the accuracy of the topology information of the passive network is improved. The method can realize the reduction of the topology information of the passive network by realizing the reduction of the topology information of the passive network so as to further automatically maintain and update the passive network, assist the accurate delimitation of faults, reduce the repeated and invalid station-climbing, and reduce the labor cost of operation.

In a possible implementation manner, the performing cluster analysis on the one or more end node devices according to the feature data of the one or more end node devices to obtain a cluster list corresponding to the target time includes: calculating the similarity between the one or more terminal node devices at the target moment according to the characteristic data of the one or more terminal node devices to obtain a similarity matrix; and performing cluster analysis on the one or more terminal node devices based on the similarity matrix to obtain a cluster list corresponding to the target moment. By implementing the embodiment of the application, when the end node equipment changes, the passive network is embodied on the monitored end node equipment, namely the change of the characteristic data of the end node equipment, namely the change of the performance index information exceeds a preset fluctuation range or alarm information appears; moreover, the data fluctuation of the end node devices under the same intermediate node device is similar, the alarm types of the alarm information are also similar, and the connection is tighter when the similarity is larger, so that the intermediate node devices to which a plurality of end node devices belong can be distinguished by performing cluster analysis on the end node devices with data fluctuation based on the similarity matrix determined by the characteristic data, and the accuracy of the topology information is improved.

In a possible implementation manner, the passive network is an optical path distribution network, the end node device is an optical network unit, and the intermediate node device is an optical splitter. By implementing the embodiment of the application, firstly, the unit identifiers and the characteristic data of one or more optical network units at a plurality of times of optical path change are obtained, then, clustering analysis is performed according to the characteristic data of the one or more optical network units, clustering lists respectively corresponding to the plurality of times of optical path change are obtained, and finally, the clustering lists respectively corresponding to the plurality of times of optical path change are combined, so that the topology information of the optical path distribution network can be obtained. The time when the optical path distribution network changes, that is, the time when the optical network unit generates abnormal performance data or alarm information, at this time, the optical network units under the same optical splitter can be clustered and analyzed from one or more optical network units generating abnormal performance data or alarm information. Secondly, merging a plurality of cluster lists in the acquired preset time period to finally acquire the topology information of the optical path distribution network, so that the problem of inaccurate topology information restoration when the optical path fluctuates for only one time can be avoided, and the accuracy of the topology information of the optical path distribution network is improved.

In a possible implementation manner, a target sub-graph corresponding to the target time is constructed according to the cluster list corresponding to the target time, where the target sub-graph includes a fully-connected graph or a minimum spanning tree construction graph, and an edge weight between a node i and a node j in the target sub-graph is a similarity metric function and/or an inherent attribute between an end node device i and an end node device j in the one or more end node devices corresponding to the target time; the fusing the cluster lists corresponding to the target moments respectively to obtain the topology information of the passive network comprises: fusing target subgraphs respectively corresponding to a plurality of target moments based on a graph to obtain a topological graph, wherein the edge weight calculation mode between nodes in the topological graph is as follows:

wherein k is the kth target time in the plurality of target times, T is the current time point,

for the weight kernel function of the k-th target moment in the plurality of target moments, g_k(i, j) represents the nodes i and j in the target subgraph corresponding to the kth target momentEdge weights between the nodes j; and partitioning the topological graph by using a graph-based community detection algorithm or an embedding algorithm to obtain the topological information. By implementing the embodiment of the application, a graph-based fusion mode is adopted for the topology sequence, the problem of conflict of recognition results at different moments can be effectively solved while the clustering lists at multiple moments are fused, and the accuracy of determining the topology information of the passive network is improved.

In a possible implementation manner, the fusing the cluster lists corresponding to the plurality of target moments to obtain the topology information of the passive network includes: respectively fusing the first clustering clusters corresponding to the same intermediate node equipment in the clustering cluster lists corresponding to the target moments to obtain the corresponding second clustering clusters; and acquiring the topological information according to the plurality of second clustering clusters. By implementing the embodiment of the application, the first cluster clusters corresponding to different target moments and under the same intermediate node device can be merged into the second cluster, and the merged cluster list is obtained, namely the topology information of the passive network, so that the problem of inaccuracy of topology information determination when only one optical path fluctuates can be avoided, and the accuracy of the topology information of the passive network is improved.

In a second aspect, an embodiment of the present application provides an apparatus for acquiring topology information of a passive network, where the passive network includes a plurality of node devices, where the plurality of node devices includes at least one intermediate node device and at least one end node device; the device comprises:

an obtaining unit, configured to obtain feature data of one or more end node devices in the passive network at a target time, where the target time is a time when performance index information of the one or more end node devices changes beyond a preset fluctuation range and/or alarm information occurs, the feature data includes the performance index information and/or the alarm information, and the one or more end node devices are one or more of the at least one end node device;

a clustering unit, configured to perform cluster analysis on the one or more end node devices according to feature data of the one or more end node devices, to obtain a cluster list corresponding to the target time, where the cluster list includes at least one first cluster, and each first cluster in the at least one first cluster includes an end node device in the one or more end node devices that is under the same intermediate node device;

and the fusion unit is used for fusing cluster lists respectively corresponding to a plurality of target moments to acquire topology information of the passive network, wherein the topology information comprises at least one second cluster, and each second cluster in the at least one second cluster comprises part or all of terminal node equipment under the same middle node equipment in the passive network.

In a possible implementation manner, the clustering unit is specifically configured to: calculating the similarity between the one or more terminal node devices at the target moment according to the characteristic data of the one or more terminal node devices to obtain a similarity matrix; and performing cluster analysis on the one or more terminal node devices based on the similarity matrix to obtain a cluster list corresponding to the target moment.

In a possible implementation manner, the passive network is an optical path distribution network, the end node device is an optical network unit, and the intermediate node device is an optical splitter.

In one possible implementation, the apparatus further includes: a sub-graph unit, configured to construct a target sub-graph corresponding to the target time according to the cluster list corresponding to the target time, where the target sub-graph includes a fully-connected graph or a minimum spanning tree construction graph, and an edge weight between a node i and a node j in the target sub-graph is a similarity metric function and/or an inherent attribute between an end node device i and an end node device j in the one or more end node devices corresponding to the target time; the fusion unit is specifically configured to: fusing target subgraphs respectively corresponding to a plurality of target moments based on a graph to obtain a topological graph, wherein the edge weight calculation mode between nodes in the topological graph is as follows:

for the weight kernel function of the k-th target moment in the plurality of target moments, g_k(i, j) is the edge weight between the node i and the node j in the target subgraph corresponding to the kth target moment; and partitioning the topological graph by using a graph-based community detection algorithm or an embedding algorithm to obtain the topological information.

In a possible implementation manner, the fusion unit is specifically configured to: respectively fusing the first clustering clusters corresponding to the same intermediate node equipment in the clustering cluster lists corresponding to the target moments to obtain the corresponding second clustering clusters; and acquiring the topological information according to the plurality of second clustering clusters.

In a third aspect, an embodiment of the present application provides a service device, where the service device includes a processor, and the processor is configured to support the service device to implement a corresponding function in the method for acquiring passive network topology information provided in the first aspect. The service device may also include a memory, coupled to the processor, that stores program instructions and data necessary for the service device. The service device may also include a communication interface for the service device to communicate with other devices or a communication network.

In a fourth aspect, an embodiment of the present application provides a computer storage medium for storing computer software instructions for an apparatus for acquiring passive network topology information provided in the second aspect, which includes a program designed to execute the above aspects.

In a fifth aspect, the present application provides a computer program, where the computer program includes instructions, and when the computer program is executed by a computer, the computer may execute the process performed by the apparatus for acquiring passive network topology information in the second aspect.

In a sixth aspect, the present application provides a chip system, where the chip system includes a processor, configured to enable a terminal device to implement the functions referred to in the first aspect, for example, to generate or process information referred to in the method for acquiring passive network topology information. In one possible design, the system-on-chip further includes a memory for storing program instructions and data necessary for the data transmission device. The chip system may be constituted by a chip, or may include a chip and other discrete devices.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments or the background art of the present application, the drawings required to be used in the embodiments or the background art of the present application will be described below.

Fig. 1A is a schematic diagram of a system architecture for acquiring topology information of a passive network according to an embodiment of the present disclosure.

Fig. 1B is a schematic diagram of a system architecture for acquiring optical path distribution network ODN topology information according to an embodiment of the present disclosure.

Fig. 2 is a schematic structural diagram of a topology information acquiring device according to an embodiment of the present application.

Fig. 3 is a schematic flowchart of a method for acquiring topology information of a passive network according to an embodiment of the present disclosure.

Fig. 4 is a schematic diagram of a change in optical power received by an optical network unit according to an embodiment of the present application.

Fig. 5 and fig. 6 are minimum spanning tree construction diagrams formed by a set of end node devices corresponding to a target time provided by an embodiment of the present application.

Fig. 7 is a full connection diagram formed by end node devices corresponding to a target time according to an embodiment of the present application.

Fig. 8 is a topology diagram provided in an embodiment of the present application.

Fig. 9 is a schematic flowchart of fusing multiple target subgraphs according to the embodiment of the present application.

Fig. 10 is a plurality of target subgraphs and a topological graph obtained by fusing the plurality of target subgraphs, which are provided in the embodiment of the present application.

Fig. 11 is a schematic structural diagram of a topology information acquisition apparatus according to an embodiment of the present application.

Fig. 12 is a schematic structural diagram of another topology information acquisition apparatus according to an embodiment of the present application.

Detailed Description

The embodiments of the present application will be described below with reference to the drawings.

The terms "first" and "second," and the like in the description and claims of this application and in the drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

As used in this specification, the terms "component," "module," "system," and the like are intended to refer to a computer-related entity, either hardware, firmware, a combination of hardware and software, or software in execution. For example, a component may be, but is not limited to being, a process running on a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of illustration, both an application running on a computing device and the computing device can be a component. One or more components can reside within a process and/or thread of execution and a component can be localized on one computer and/or distributed between 2 or more computers. In addition, these components can execute from various computer readable media having various data structures stored thereon. The components may communicate by way of local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from two components interacting with another component in a local system, distributed system, and/or across a network such as the internet with other systems by way of the signal).

First, some terms in the present application are explained so as to be easily understood by those skilled in the art.

(1) An Optical Distribution Network (ODN), which is an FTTH Optical cable Network based on PON devices. The main function of the ODN is to provide an optical transmission channel between the OLT and the ONU, thereby completing the distribution of optical signal power. The ODN is a purely passive optical distribution network composed of passive optical devices (such as optical fibers, optical connectors, optical attenuators, optical couplers, and optical wavelength division multiplexers).

(2) The passive device is used for working in the presence of signals in the whole passive network under the condition of not needing an external power supply, and mainly comprises a resistor, a capacitor, an inductor, a converter, a graduator, a light splitter, a matching network, a resonator, a filter, a mixer, a switch, a passive optical device and the like.

(3) A Passive Optical Network (PON), which is a pure medium Network, avoids electromagnetic interference and lightning influence of external devices, reduces the failure rate of lines and external devices, improves system reliability, saves maintenance cost, and is a technology expected by telecommunication maintenance departments for a long time. The lightless network is a point-to-multipoint optical fiber transmission and access technology, the downlink adopts a broadcasting mode, the uplink adopts a time division multiple access mode, tree, star, bus and other topological structures can be flexibly formed, and only a simple optical splitter needs to be installed at an optical branch point, so that the lightless network has the advantages of saving optical cable resources, sharing bandwidth resources, saving machine room investment, high network building speed, low comprehensive network building cost and the like. The passive optical network comprises an ATM-PON and an Ethernet-PON.

In order to facilitate understanding of the embodiments of the present application, a description will be given below of one of the system architectures on which the embodiments of the present application are based. Referring to fig. 1A, fig. 1A is a schematic diagram of a system architecture for acquiring topology information of a passive network according to an embodiment of the present disclosure. As shown in fig. 1A, the system architecture mainly includes a service device, at least one intermediate node device, at least one end node device, and the like. Wherein,

the service device is used for supervising the terminal device of the passive network, and for example, may include one or more servers (a plurality of servers may form a server cluster), and may include but is not limited to a backend server, a cloud server, a data processing server, and the like. Wherein part or all of the passive network may be formed by passive devices. As shown in fig. 1A, a service device may obtain feature data of one or more end node devices in the passive network at a target time, where the target time is a time when performance indicator information of the one or more end node devices changes beyond a preset fluctuation range and/or alarm information occurs, the feature data includes the performance indicator information and/or the alarm information, and the one or more end node devices are one or more of the at least one end node device; performing cluster analysis on the one or more end node devices according to the characteristic data of the one or more end node devices to obtain a cluster list corresponding to the target time, wherein the cluster list comprises at least one first cluster, and each first cluster in the at least one first cluster comprises the end node device in the one or more end node devices under the same intermediate node device; and fusing cluster lists respectively corresponding to a plurality of target moments to acquire topology information of the passive network, wherein the topology information comprises at least one second cluster, and each second cluster in the at least one second cluster comprises part or all of terminal node equipment under the same intermediate node equipment in the passive network.

The intermediate node device can be a passive network device, is used for working when signals exist in the whole passive network without adding a power supply, and can be a resistor, a capacitor, an inductor, a converter, a fader, a light splitter, a matching network, a resonator, a filter, a frequency mixer, a switch and the like.

An end node device is a passive network device of an end node in a passive network, and there are different types of end node devices in different passive networks, such as an optical network unit in a passive optical network, a resistance of a passive two-terminal network terminal, and so on.

It should be noted that the Performance Indicator information of the end node device mentioned in the present application may be understood as Key Performance Indicator (KPI) information of the end node device, which is used to represent Performance data, function information, or operating state of the end node device. Wherein, the performance index information matches with the type of the passive network, for example: when the passive network allocates a network for the optical path, the performance index information may be received optical power, optical link loss, and the like; when the passive network is a passive two-terminal network, the performance indicator information may be voltage, current, resistance, and the like.

It is further noted that the passive network includes a plurality of node devices, and the plurality of node devices includes at least one intermediate node device and at least one end node device; when the intermediate node device is connected to the two end node devices, there are two data streams that can be sent to the two end node devices, and at this time, the two end node devices may be considered as node devices under the intermediate node device. As shown in fig. 1A, the end node devices of the three gray levels are node devices below the intermediate node devices connected thereto.

It should be further noted that the system architecture for acquiring passive network topology information in fig. 1A is only a partial exemplary implementation manner in the embodiment of the present application, and the system architecture for acquiring passive network topology information in the embodiment of the present application includes, but is not limited to, the above system architecture for acquiring passive network topology information.

Referring to fig. 1B, please refer to a system architecture provided in fig. 1A, where fig. 1B is a schematic diagram of a system architecture for acquiring optical path distribution network ODN topology information according to an embodiment of the present disclosure. As shown in fig. 1B, the system architecture mainly includes a resource management system, an optical cable cross-connecting box, a first-level optical splitter, a second-level optical splitter, an optical network unit/terminal (ONU/ONT), and other passive devices, and may further include a network management device and an optical line terminal. Wherein the resource management system is equivalent to the service device in fig. 1A; the optical cable cross connecting cabinet, the first-stage optical splitter, the second-stage optical splitter, the network management equipment and the optical line terminal are equivalent to the intermediate node equipment in the figure 1A; the optical network unit/terminal (ONU/ONT) corresponds to the end node device in fig. 1A described above. Wherein,

an optical cable cross-connecting box is cross-connecting equipment for providing optical cable terminating and jumper connection for optical cables of a main layer and an optical cable of a wiring layer. After the optical cable is introduced into the optical cable cross-connecting box, after fixing, terminating and fiber distributing, the main layer optical cable and the wiring layer optical cable are communicated by using the jump fiber.

The optical splitter is a passive device, also called an optical splitter, and does not need external energy, but only needs input light. The beam splitter consists of entrance and exit slits, a mirror and a dispersive element, and has the function of separating out the required resonance absorption lines. The key component of the optical splitter is a dispersive element, and the optical gratings are used in the current commercial instruments. The first-level optical splitter is generally applied to a user concentration place and is suitable for one-time access, and the optical splitter is generally large. The two-stage optical splitter is generally applied to a place where users are scattered, such as a town, and the ratio is generally small.

An Optical Network Unit/terminal (ONU/ONT) is divided into an active Optical Network Unit and a passive Optical Network Unit, where the ONU/terminal in this application generally refers to a passive Optical Network Unit/terminal, and refers to a device or a functional block that provides a user-side interface (direct or remote) and is connected to an Optical distribution Network ODN in an Optical access Network. An ONU is a fiber access terminal device that should be used in conjunction with an optical line termination OLT, which typically stores the central office of an ISP.

The optical line terminal, on one hand, converges signals carrying various services at the local side, and sends the signals to an access network according to a certain signal format so as to transmit the signals to a terminal user, and on the other hand, sends the signals from the terminal user to various service networks according to service types. The realized functions are as follows: 1. the optical signal is converted into optical signal by connecting with the front-end (convergence layer) switch through network cable, and is interconnected with the optical splitter at the user end through a single optical fiber. 2. The functions of controlling, managing, ranging and the like of the user side equipment ONU are realized. 3. The OLT device is also an opto-electronic integrated device, as is the ONU device. Such as: in embodiments of the present application, a frame/slot type passive optical network interface may be provided.

Network management equipment, also known as internetwork connectors, protocol converters, is a computer system or equipment that provides data conversion services among multiple networks.

The resource management system can utilize the scheme for determining the ODN topological information of the optical path distribution network to restore the topological connection relation of passive equipment (such as an optical network unit/terminal) in the ODN and realize automatic completion and correction of topological data in the resource management data.

In a first case, the resource management system may be a server in the cloud, and the server and the local passive device form a system, as shown in fig. 1B, the system architecture may include one or more servers (a plurality of servers may form a server cluster), which may include, but are not limited to, a backend server, a cloud server, a data processing server, and the like, and when the resource management system is a server, the server may run a corresponding server-side program to provide a topology information restoration service of the corresponding optical path distribution network. For example, feature data of one or more end node devices in the passive network at a target time is obtained, where the target time is a time when a light path change occurs in the light path distribution network, and the feature data includes at least one of received light power, optical link loss, and alarm information of an optical network unit; performing cluster analysis on the one or more optical network units according to the characteristic data of the one or more optical network units to obtain a cluster list corresponding to the target time, wherein the cluster list comprises at least one first cluster, and each first cluster in the at least one first cluster comprises optical network units in the one or more optical network units under the same optical splitter; and fusing cluster lists corresponding to a plurality of target moments respectively to obtain topology information of the passive network, wherein the topology information comprises at least one second cluster, and each second cluster in the at least one second cluster comprises part or all optical network units under the same optical splitter in the passive network.

In case two, the resource management system may be a device, which may be a local terminal, and the system of the terminal device includes, but is not limited to, windows, iOS, Android, and other different platforms. For example, the terminal may obtain characteristic data of one or more end node devices in the passive network at a target time; according to the characteristic data of the one or more optical network units, carrying out cluster analysis on the one or more optical network units to obtain a cluster list corresponding to the target moment; and fusing cluster lists corresponding to a plurality of target moments respectively to obtain the topology information of the passive network. The terminal in this embodiment may include, but is not limited to, any electronic product capable of running a browser, which can perform human-computer interaction with a user through an input device such as a keyboard, a virtual keyboard, a touch pad, a touch screen, and a voice control device, such as a smart phone, a tablet computer, and a personal computer. Smart operating systems include, but are not limited to, any operating system that enriches device functionality by providing various mobile applications to a mobile device, such as: android (Android)^TM)、iOS^TM、Windows Phone^TMAnd the like.

Based on the system architecture, an embodiment of the present application provides a service device that can be applied to the system architecture shown in fig. 1A and a resource management system shown in the system architecture shown in fig. 1B, please refer to fig. 2, and fig. 2 is a schematic structural diagram of a topology information acquiring device provided in an embodiment of the present application, and as shown in fig. 2, the topology information acquiring device may include a data acquisition module 001, a topology restoring algorithm module 002, a restoring result module 003, and a topology data correcting module 004.

The topology information acquisition equipment firstly acquires data of terminal node equipment, including performance index data, alarm data and the like, of a passive network, then inputs the data into a topology reduction algorithm module to carry out topology reduction to obtain a reduction result, then corrects and confirms topology data by combining prestored topology data, and finally feeds back the corrected topology data to original topology data to form a topology data correction closed loop. The passive network includes a plurality of node devices including at least one intermediate node device, at least one end node device. Wherein,

a data collection module 001, configured to collect characteristic data of an end node device, where the characteristic data includes the performance index information or the alarm information of the end node device, where the performance index information and the alarm information are matched with a type of a passive network, for example: when the passive network allocates a network for the optical path, the performance index information may be received optical power, optical link loss, and the like; when the passive network is a passive two-terminal network, the performance indicator information may be voltage, current, resistance, and the like. The data acquisition module 001 comprises a data acquisition module and an alarm data acquisition module. The data acquisition module is used for acquiring performance index information, and the performance index information can be key performance index KPI data; the alarm data acquisition module is used for acquiring alarm data, and the alarm data may include: at least one of an alarm type, a device identification of the alarm end node device, an alarm start time, and an alarm end time.

And the topology restoring algorithm module 002 is configured to restore topology information of the passive network according to the feature data acquired by the data acquisition module 001 and the device identifier of the end node device corresponding to the feature data. For example: the topology reduction algorithm module 002 may obtain feature data of one or more end node devices in the passive network at a target time, where the target time is a time when the performance index information of the one or more end node devices changes beyond a preset fluctuation range and/or alarm information occurs, the feature data includes the performance index information and/or the alarm information, and the one or more end node devices are one or more of the at least one end node device; performing cluster analysis on the one or more end node devices according to the characteristic data of the one or more end node devices to obtain a cluster list corresponding to the target time, wherein the cluster list comprises at least one first cluster, and each first cluster in the at least one first cluster comprises an end node device in the one or more end node devices under the same intermediate node device; and fusing cluster lists respectively corresponding to a plurality of target moments to acquire topology information of the passive network, wherein the topology information comprises at least one second cluster, and each second cluster in the at least one second cluster comprises part or all of terminal node equipment under the same intermediate node equipment in the passive network. Wherein the device identification of the end node device is used to identify the end node device.

The restoration result module 003 is configured to obtain topology information of the passive network restored by the topology restoration algorithm module 002 and topology information of the passive network originally stored.

And the topology data correction module 004 is used for correcting the topology data in the resource management data by combining the resource management data and the restored topology information, and finally feeding back and updating the corrected topology information to the topology data.

It is to be understood that the architecture of the topology information acquiring device in fig. 2 is only an exemplary implementation manner in the embodiment of the present application, and the topology information acquiring device in the embodiment of the present application includes, but is not limited to, the above topology information acquiring device.

Based on the system architecture provided in fig. 1A and 1B and the structure of the topology information acquisition device provided in fig. 2, the method for acquiring the topology information of the passive network provided in the present application is combined to specifically analyze and solve the technical problem provided in the present application.

Referring to fig. 3, fig. 3 is a schematic flowchart of a method for acquiring topology information of a passive network according to an embodiment of the present disclosure, where the method may be applied to the system architectures described in fig. 1A and fig. 1B, and a topology information acquiring device may be configured to support and execute steps S301 to S304 of the method shown in fig. 3. The following will describe from the topology information acquisition apparatus side with reference to fig. 3. The method may include the following steps S301, S302, and S304, and optionally may further include step S303.

Step S301: feature data of one or more end node devices in the passive network at a target time is obtained.

Specifically, the topology information obtaining device obtains feature data of one or more end node devices in the passive network at a target time, where the target time is a time when a change in performance index information of the one or more end node devices exceeds a preset fluctuation range and/or when alarm information occurs, the feature data includes the performance index information and/or the alarm information, and the one or more end node devices are one or more of the at least one end node device. The device identifier of the end node device may also be obtained to identify the end node device. The performance index information and the alarm information are both matched with the type of the passive network, for example: when the passive network allocates a network for the optical path, the performance index information may be received optical power, optical link loss, and the like; when the passive network is a passive two-terminal network, the performance indicator information may be voltage, current, resistance, and the like. The alarm information includes one or more of an alarm type, an alarm identification, an alarm start time, and an alarm end time. For example, when a change in performance index information of an end node device in the passive network exceeds a preset fluctuation range or an alarm occurs, the time may be understood as a target time, and at this time, characteristic data of the end node device that has changed may be acquired. Such as: when the change of the performance index information exceeds a preset fluctuation range, acquiring performance index data; and when the alarm information appears, acquiring the alarm information. In addition, it is not excluded that the performance index data is obtained when the alarm information occurs, and this is not specifically limited in the embodiment of the present application. Another example is: when the performance index information change of one end node device in the passive network exceeds a preset fluctuation range, the other end node device generates alarm information, and the time can be understood as target time. In addition, at different target times, the end node devices where the performance index information changes beyond the preset fluctuation range and/or the alarm information occurs may be different, and the number of the end node devices may also be different.

Optionally, the multiple target times are multiple in a preset time period, where the preset time period is a time period between a preset time point and a current time point. It should be noted that, a plurality of times of the change of the performance index information exceeding the preset fluctuation range or the occurrence of the alarm information, that is, a plurality of target times, may occur within the preset time period. Because the terminal node devices with performance index information change exceeding the preset fluctuation range or with alarm information are possibly different at each target moment, the topology information acquisition device can periodically determine the characteristic data at multiple moments, restore the topology information of the passive network, integrate the recognition results of multiple times of topology information and improve the accuracy of topology information restoration in the passive network. It should be noted that, when the optical path of the passive network does not change, or the degree of change of the performance index information is not obvious and does not exceed the preset change range, the topology information acquiring device cannot acquire the device identifier and the feature data of the end node device.

In a possible implementation manner, when the passive network is an optical path distribution network, the passive network is the optical path distribution network, the end node device is an optical network unit, and the intermediate node device is an optical splitter. When the optical path distribution network has optical path change, the changed characteristic data of the optical network unit can be obtained for analyzing whether the optical network unit is positioned under the same optical splitter. The optical path change of a part or all of the optical network units in the optical path distribution network may be considered that an alarm message occurs in an optical network unit ONU or performance index data of the optical network unit ONU changes (for example, the received optical power changes), or the change of the performance index data is outside a certain threshold range. Please refer to table 1 below, where table 1 is an alarm information table of alarm information occurring on an ONU in an embodiment of the present application.

Table 1: alarm information table

ONU unit identification	Type of alarm	Alarm mark	Alarm start time	End time of alarm
					005	A	Aaaaa1	2020-05-26 22:29.39	2020-05-26 22:32.30
…	…	…	…	…
					198	B	Bbbbb2	2020-05-2912:29.39	2020-05-2912:32.52
201	B	Bbbbb2	2020-05-2912:29.39	2020-05-2912:33.09

The alarm information table includes: the ONU unit identifier, the alarm type, the alarm identifier, the alarm start time, the alarm end time and the like are used for expressing the alarm type and the alarm time when the optical network unit generates the alarm, so that the topology information acquisition equipment can conveniently perform cluster analysis on the optical network unit generating the alarm information. When the time and the alarm type of the alarm information appearing in the two optical network units are similar, the two optical network units can be considered to be under the same optical splitter. As shown in table 1, when the time when the alarm information occurs and the alarm type are similar for the two optical network units of the ONU unit identifier 198 and the ONU unit identifier 201, the two optical network units may be considered to be located in the same optical splitter.

Referring to fig. 4, when performance index data of an ONU changes, taking received optical power change as an example, fig. 4 is a schematic diagram of received optical power change of the ONU according to an embodiment of the present disclosure. Wherein: the characteristic that the received optical power of the optical network unit ONU changes may include: the method includes the steps of calculating the variation degree of the received optical power data of the ONU in a unit time, wherein the variation degree can be the variation degree of the received optical power data of the ONU in a unit time, the jitter frequency is the accumulated frequency that the jitter degree of the ONU is larger than a preset threshold value, the cliff degree is used for indicating the attenuation variation size that the received optical power of the ONU is attenuated from a stable value to another stable value in a unit time, and the trend degradation degree is indicated by a trend coefficient which is linearly fitted after the received optical power in the certain time is subjected to exponential weighting sliding average. When the characteristics of changes of the received optical powers of the plurality of optical network units ONU are similar or within a certain threshold range, the plurality of optical network units ONU may be considered to be located in the same optical splitter. As shown in fig. 4, a schematic diagram of the optical power variation received by the optical network unit is shown, where the left side is the unit identifier of the optical network unit, and the right side is the size of the optical power received by the corresponding optical network unit over time. As shown in fig. 4, three optical network units identified as

ONU units

015, 016, and 017 all have similar received optical power jitter degree, jitter frequency, cliff degree, trend degradation degree, etc., and thus the three optical network units may be considered to be under the same optical splitter. The ONU units identified as 005 and 053 have different performance index fluctuations from 015, 016, and 017 ONU units, and it may be considered that the

ONU units

005 and 053 are not located in the same optical splitter as the aforementioned three ONU units.

In the embodiments of the present application, the time when the optical path starts to change is taken as the target time, and the time when the change rate is the maximum in the optical path changing process may also be taken as the target time, which is not specifically limited in the embodiments of the present application.

Step S302: and according to the characteristic data of one or more terminal node devices, performing cluster analysis on the one or more terminal node devices to obtain a cluster list corresponding to the target moment.

Specifically, the topology information obtaining device performs cluster analysis on the one or more end node devices according to the feature data of the one or more end node devices to obtain a cluster list corresponding to the target time, where the cluster list includes at least one first cluster, and each first cluster in the at least one first cluster includes an end node device in the one or more end node devices that is under the same intermediate node device. It should be noted that cluster analysis refers to an analysis process for grouping a set of physical or abstract objects into a plurality of classes composed of similar objects. It should be noted that, when performing cluster analysis on one or more end node devices, the types of the characteristic data are the same, such as all performance indicators or all alarm information. The end node devices belonging to the same intermediate node device can be classified into one class through cluster analysis to restore topology information of the passive network, wherein the topology information comprises the end node devices under different intermediate node devices in the passive network. For example, embodiments of the present application may use a Density-Based Spatial Clustering algorithm (DBSCAN) that defines clusters as Density-connected pointsMaximum set, it is possible to divide areas with a sufficiently high density into clusters and find clusters of arbitrary shape in a spatial database of noise. Therefore, the number of clusters does not need to be set, the centroid of the clusters does not need to be calculated, noise points can be identified, and after cluster analysis, the topological information acquisition device can output a cluster list of the tth target moment, wherein the cluster list can be expressed as: { c₁,c₂,…,c_n}_t. Wherein, c_nAnd representing the nth end node device in the cluster clustering list for the device identifier of the nth end node device corresponding to the tth target moment. The topological information at the moment is obtained through data analysis of the plurality of terminal node devices corresponding to the moment when each optical path changes, the method is simple and rapid, the obtained topological information is accurate, and the topological information of the passive network device is not required to be maintained through manual input.

Optionally, performing cluster analysis on the one or more end node devices according to the feature data of the one or more end node devices to obtain a cluster list corresponding to the target time includes: calculating the similarity between the one or more terminal node devices at the target moment according to the characteristic data of the one or more terminal node devices to obtain a similarity matrix; and performing cluster analysis on the one or more terminal node devices based on the similarity matrix to obtain a cluster list corresponding to the target moment. Because the passive network is embodied on the monitored end node equipment when the end node equipment changes, namely the change of the characteristic data of the end node equipment, namely the change of the performance index information exceeds a preset fluctuation range or alarm information appears; moreover, the data fluctuation of the end node devices under the same intermediate node device is similar, the alarm types of the alarm information are also similar, and the connection is tighter when the similarity is larger, so that the intermediate node devices to which a plurality of end node devices belong can be distinguished by performing cluster analysis on the end node devices with data fluctuation based on the similarity matrix determined by the characteristic data, and the accuracy of the topology information is improved.

In aIn a possible implementation manner, the passive network is a light path distribution network, the end node device is an optical network unit, the intermediate node device is an optical splitter, and the characteristic data is received optical power of the end node device; calculating the similarity between the one or more end node devices at the target moment according to the characteristic data of the one or more end node devices to obtain a similarity matrix, including: calculating the similarity between one or more optical network units corresponding to each target time according to the received optical power and a first calculation formula to obtain a similarity matrix S, wherein the first calculation formula is

Where t is the tth target time of the m target times, norm (i)_tA normalization function of the received optical power of the optical network unit i corresponding to the t-th target moment, norm (j)_tA normalization function L of the received optical power of the optical network unit j corresponding to the t-th target moment₁(Norm(i)_t,Norm(j)_t) For a distance measurement function between the optical network unit i and the optical network unit j based on the received optical power, count _ nan (i { [ u ] j) is a null value counting function after the optical network unit i and the optical network unit j are combined, α is a preset null value penalty coefficient, t ═ 1 and 2 … … m, m is a positive integer greater than 1, and i and j are identifiers of the optical network units respectively. The topology information obtaining device may calculate, according to the received optical power of the optical network units, a similarity between one or more optical network units in which an optical path changes at each target time, and when the similarity between two optical network units is within a certain threshold range, the two optical network units may be considered to be located under the same optical splitter. Further, when the topology information acquiring device calculates the similarity between the optical network units, the topology information acquiring device may first perform normalization processing on the received optical power of one or more optical network units, and then calculate the similarity between the one or more optical network units through a distance measurement function based on the received optical power after the normalization processing, which is beneficial to improving the accuracy of the cluster analysis.

In a possible implementation manner, the passive network is an optical path distribution network, the end node device is an optical network unit, the intermediate node device is an optical splitter, the characteristic data is alarm information of the end node device, and the alarm information includes an alarm start time and an alarm end time; the calculating, according to the feature data of the one or more end node devices, a similarity between the one or more end node devices at the target time to obtain a similarity matrix includes: calculating the similarity between one or more optical network units corresponding to the target time according to the alarm information and a second calculation formula to obtain a similarity matrix S, wherein the second calculation formula is

Wherein t is the tth target time in the m target times, As (i) is the alarm starting time of the optical network unit i corresponding to the tth target time, A_e(i) An alarm ending time, A, of the optical network unit i corresponding to the tth target moment_s(j) An alarm start time, A, of the optical network unit j corresponding to the tth target moment_e(j) The alarm ending time L of the optical network unit j corresponding to the tth target moment₁(A_s(i),A_s(j) L) a distance metric function between the ONU i and the ONU j based on the alarm start time₁(A_e(i),A_e(j) Is a distance metric function between the onu i and the onu j based on the alarm end time, where t is 1 and 2 … … m, m is a positive integer greater than 1, and i and j are identifiers of the onu, respectively. The topology information acquisition device may calculate, according to the alarm start time and the alarm end time, a similarity between one or more optical network units in which the alarm information occurs at each target time, and when the similarities of two optical network units are within a certain threshold range, the two optical network units may be considered to be in the same sub-divisionUnder the light device. Furthermore, when calculating the similarity between the optical network units, the start time and the end time of the alarm information appearing in one or more optical network units may be determined first, and then the similarity between the one or more optical network units is calculated through a distance measurement function based on the alarm start time and the alarm end time, which is beneficial to improving the accuracy of the cluster analysis.

Step S303: and constructing a target subgraph corresponding to the target moment according to the cluster list corresponding to the target moment.

Specifically, the topology information acquisition device constructs a target subgraph corresponding to the target time according to the cluster list corresponding to the target time, where the target subgraph includes a fully-connected graph or a minimum spanning tree constructed graph, and an edge weight between a node i and a node j in the target subgraph is a similarity measurement function and/or an inherent attribute between an end node device i and an end node device j in the one or more end node devices corresponding to the target time. And i, j is the equipment identifier of the corresponding end node equipment.

For example: referring to fig. 5 and fig. 6, fig. 5 and fig. 6 are minimum spanning tree construction diagrams formed by a set of end node devices corresponding to a target time according to an embodiment of the present application. When the number of the one or more terminal node devices corresponding to the target time is less than or equal to a preset threshold (for example, the preset threshold is defaulted to 3, which can be adjusted according to a specific scene), a full-connection graph can be constructed, and when the number of the one or more terminal node devices corresponding to the target time is greater than the preset threshold, a minimum spanning tree can be used for constructing the graph. As shown in fig. 5, the four nodes of device number 000,037,041,019 represent end node devices under the same intermediate node device, respectively, wherein the number between two nodes of the four nodes of 000,037,041,019 represents the edge weight between the nodes. As shown in fig. 6, the target sub-graph is a minimum spanning tree construction graph including 009,027,016,033,034,044,043,023,001,024,042,018 nodes, where six end node devices identified as (009,027,016,024,042,018) in the graph are end node devices under the same middle node device, and therefore, as can be seen from fig. 6, the graph construction mode of the minimum spanning tree is such that nodes corresponding to the six end node devices tend to gather together. Referring to fig. 7, fig. 7 is a full connection diagram formed by end node devices corresponding to a target time according to an embodiment of the present application. As shown in fig. 7, three nodes, identified as 043,031,005, represent end node devices under the same intermediate node device, respectively, wherein the number between two nodes of the three nodes of 043,031,005 represents the edge weight between the nodes. Since the number of end node devices is less than or equal to the preset threshold, 043,031,005 three end node devices constitute a fully connected graph.

Step S304: and fusing the cluster lists corresponding to the target moments respectively to acquire the topology information of the passive network.

Specifically, the topology information obtaining device fuses clustering cluster lists corresponding to a plurality of target moments respectively to obtain topology information of the passive network, where the topology information includes at least one second clustering cluster, and each second clustering cluster in the at least one second clustering cluster includes part or all of terminal node devices in the passive network under the same intermediate node device. The obtained multiple clustering lists in the preset time period are combined to finally obtain the topology information of the passive network, so that the problem of inaccurate topology information reduction when the light path fluctuates for only one time can be avoided, and the accuracy of the topology information of the passive network is improved. After the topology information of the passive network is obtained by fusing the cluster lists respectively corresponding to the target moments, the topology information can be further divided into at least one cluster, and each cluster in the at least one cluster comprises equipment identifications of part or all of the end node equipment under the intermediate node equipment. For example: please refer to table 2 below, where table 2 is a segmented end node device topology information table provided in this embodiment of the present application.

Table 2: topology information table

Group number	Segmented cluster
		1	{'009','027','016'}
2	{'034','004','021'}
		3	{'002','042','001','018'}
4	{'011','008'}
		5	{'041','037','019','000'}
6	{'033','029','044','022'}
		7	{'040','100'}
8	{'030','038'}
		9	{'031','043','023','005','024'}
10	{'039','013','012'}
		…	…

As shown in table 2, each group of partitioned cluster includes a device identifier of an end node device under an intermediate node device. The complete topology information is divided into one or more cluster clusters, so that a user can visually know the topology information of the terminal node equipment under the same intermediate node equipment in the passive network.

Optionally, the first cluster corresponding to the same intermediate node device in the cluster list corresponding to the plurality of target moments is respectively fused to obtain the corresponding second cluster; and obtaining the topology information according to the second cluster. That is, the topology information obtaining device may merge first cluster clusters corresponding to different target times and under the same intermediate node device into a second cluster, and the obtained merged cluster list is the topology information of the passive network, so that the obtained cluster lists corresponding to a plurality of target times within a preset time period are merged to finally obtain the topology information of the passive network, thereby avoiding the problem of inaccurate topology information restoration when only one optical path fluctuates, and improving the accuracy of the topology information of the passive network. And secondly, automatic maintenance and updating of topology information in the resource management can be realized, fault accurate delimitation is assisted, repeated and invalid station-climbing is reduced, and the labor cost of operation is reduced.

Optionally, target subgraphs respectively corresponding to multiple target moments are fused based on a graph to obtain a topological graph, where edge weight between nodes in the topological graph is calculated in a manner that:

for the weight kernel function of the kth target moment in the plurality of target moments, g_k(i, j) is the target subgraph corresponding to the k-th target momentAn edge weight between the node i and the node j; and partitioning the topological graph by using a graph-based community detection algorithm or an embedding algorithm to obtain the topological information. The weight kernel function represents the weight of each target time in a plurality of target times in part or all of the target times. For example: can be provided with

That is, the weight of each target time is related to the current time point; in addition, can also be provided with

The time attribute of the topological sequence is considered, namely, the closer the time to the current time, the greater the weight of the target time at part or all of the target time is; can also be provided with

That is, the weight of each target time is the same, where m is the number of target times. It should be noted that the edge weights between the node i and the node j in the topology map are determined only by one or more target subgraphs including both the node i and the node j. For example: referring to fig. 8, fig. 8 is a topological diagram according to an embodiment of the present application. Based on the information of the end node devices shown in table 2, the topology map of the example, in which the segmentation result is visualized, as shown in fig. 8, is obtained by merging a plurality of target subgraphs, and after the topology map is segmented based on the community detection algorithm or the embedding algorithm of the graph, the topology information in table 2 can be obtained, and from the graph segmentation result of table 2, it can be analyzed in combination with each subgraph, and group 1 in the topology map is a fully-connected subgraph formed by merging subgraphs, and includes three end node devices of '009', '027', '016'; group 2 is a fully connected subgraph present in the original target subgraph, group 5 is an isolated subgraph including four end node devices { '041', '037', '019', '000', }, group 10 is the result of merging (039, 012), (039, 013) two subgraphs, and so on.

Please refer to fig. 9, where fig. 9 is a schematic flowchart illustrating a process of fusing multiple target subgraphs according to an embodiment of the present application. As shown in fig. 9, in a preset time period from a preset time point to a current time point, at a time when the end node device generates abnormal performance index information or alarm information, device identifiers and feature data of one or more end node devices at a plurality of target times are obtained, then, cluster analysis is performed according to the feature data of the one or more end node devices, a cluster list corresponding to each of the plurality of path change times is obtained, and a target subgraph is constructed based on the cluster list corresponding to each target time; and finally, fusing and dividing the plurality of target subgraphs respectively corresponding to the moment when the light path changes, and obtaining the topology information of the passive network. Referring to fig. 10, fig. 10 is a schematic diagram of a process for merging multiple target subgraphs and a topology graph obtained by merging the multiple target subgraphs, which is provided in an embodiment of the present application, and based on the schematic diagram of the process for merging the multiple target subgraphs, as shown in fig. 9, as shown in fig. 10, a topology information obtaining device synthesizes the multiple target subgraphs into one topology graph, where the topology graph includes a topology connection relationship of end node devices in a passive network, and after division, a topology information table shown in table 2 may be generated.

In the embodiment of the application, the cluster list of each target time in a plurality of target times is obtained, and the cluster lists corresponding to the target times are fused to obtain the topology information of the passive network. The target moment is the moment when one or more terminal node devices in the passive network have performance index information change exceeding a preset fluctuation range and/or alarm information; at this time, the characteristic data of one or more terminal node devices with performance index information change exceeding a preset fluctuation range and/or with alarm information can be acquired; according to the acquired feature data, a cluster list corresponding to the target moment can be obtained through cluster analysis; further, similarly, cluster lists corresponding to a plurality of target moments can be obtained, so that the cluster lists corresponding to the plurality of target moments are fused to obtain topology information of the passive network. The characteristic data comprises performance index information and/or the alarm information, and one or more end node devices of which the performance index information changes beyond a preset fluctuation range and/or the alarm information appears at each of a plurality of target moments may be different. Therefore, the terminal node equipment under the same intermediate node equipment is clustered and analyzed from one or more terminal node equipment with performance data generating fluctuation or alarm information, and the implementation mode of acquiring the topology information corresponding to the passive network can greatly reduce the workload of operation and maintenance personnel, does not need related personnel to actively acquire a large amount of data information, and only needs to supervise the occurrence of characteristic data or the change of the characteristic data exceeding a preset range. Secondly, merging a plurality of cluster lists in the acquired preset time period to finally acquire the topology information of the passive network, so that the problem of inaccurate topology information restoration when only one characteristic data appears or the characteristic data changes beyond a preset range can be avoided, and the accuracy of the topology information of the passive network is improved. The method can realize the automatic maintenance and updating of the topology information in the information management by restoring the topology information of the passive network, assist the accurate delimitation of faults, reduce the repeated and invalid station-climbing, and reduce the labor cost of operation.

The method of the embodiments of the present application is explained in detail above, and the related apparatus of the embodiments of the present application is provided below.

Referring to fig. 11, fig. 11 is a schematic structural diagram of a topology information acquiring apparatus provided in an embodiment of the present application, where the topology information acquiring apparatus 10 may include an acquiring unit 101, a clustering unit 102, and a fusing unit 103, and may further include a sub-graph unit 104, configured to determine a topology connection relationship of an intermediate node device. The details of each unit are as follows.

An obtaining unit 101, configured to obtain feature data of one or more end node devices in the passive network at a target time, where the target time is a time when performance indicator information of the one or more end node devices changes beyond a preset fluctuation range and/or alarm information occurs, the feature data includes the performance indicator information and/or the alarm information, and the one or more end node devices are one or more of the at least one end node device;

a clustering unit 102, configured to perform cluster analysis on the one or more end node devices according to feature data of the one or more end node devices, to obtain a cluster list corresponding to the target time, where the cluster list includes at least one first cluster, and each first cluster in the at least one first cluster includes an end node device in the one or more end node devices that is under the same intermediate node device;

a fusing unit 103, configured to fuse cluster lists corresponding to multiple target moments respectively, and acquire topology information of the passive network, where the topology information includes at least one second cluster, and each second cluster in the at least one second cluster includes part or all of terminal node devices in the passive network under the same middle node device.

In a possible implementation manner, the clustering unit 102 is specifically configured to: calculating the similarity between the one or more terminal node devices at the target moment according to the characteristic data of the one or more terminal node devices to obtain a similarity matrix; and performing cluster analysis on the one or more terminal node devices based on the similarity matrix to obtain a cluster list corresponding to the target moment.

In one possible implementation, the apparatus further includes: a sub-graph unit 104, configured to construct a target sub-graph corresponding to the target time according to the cluster list corresponding to the target time, where the target sub-graph includes a fully-connected graph or a minimum spanning tree construction graph, and an edge weight between a node i and a node j in the target sub-graph is a similarity metric function and/or an inherent attribute between an end node device i and an end node device j in the one or more end node devices corresponding to the target time; the fusion unit 103 is specifically configured to: fusing target subgraphs respectively corresponding to a plurality of target moments based on graphs to obtain a topological graph, wherein the topology isThe edge weight calculation method between the nodes in the graph is as follows:

In a possible implementation manner, the fusion unit 103 is specifically configured to: respectively fusing the first clustering clusters corresponding to the same intermediate node equipment in the clustering cluster lists corresponding to the target moments to obtain the corresponding second clustering clusters; and acquiring the topological information according to the plurality of second clustering clusters.

It should be noted that, for the functions of each functional unit in the apparatus 10 for determining the ODN topology information of the passive network described in the embodiment of the present application, reference may be made to the description of step S301 to step S304 in the embodiment of the method described in fig. 3, and details are not described here again.

As shown in fig. 12, fig. 12 is a schematic structural diagram of another topology information acquiring apparatus provided in this embodiment, where the apparatus 20 includes at least one processor 201, at least one memory 202, and at least one communication interface 203. In addition, the device may also include common components such as an antenna, which will not be described in detail herein.

The processor 201 may be a general purpose Central Processing Unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of programs according to the above schemes.

Communication interface 203 for communicating with other devices or communication Networks, such as ethernet, Radio Access Network (RAN), core network, Wireless Local Area Networks (WLAN), etc.

The Memory 202 may be a Read-Only Memory (ROM) or other type of static storage device that can store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that can store information and instructions, an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc Read-Only Memory (CD-ROM) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to these. The memory may be self-contained and coupled to the processor via a bus. The memory may also be integral to the processor.

The memory 202 is used for storing application program codes for executing the above scheme, and is controlled by the processor 201 to execute. The processor 201 is configured to execute application program code stored in the memory 202.

The memory 202 stores code that may perform the method of obtaining passive network topology information provided above in fig. 3, such as: acquiring feature data of one or more end node devices in the passive network at a target moment, wherein the target moment is a moment when performance index information of the one or more end node devices changes beyond a preset fluctuation range and/or alarm information appears, the feature data comprises the performance index information and/or the alarm information, and the one or more end node devices are one or more of the at least one end node device; performing cluster analysis on the one or more end node devices according to the characteristic data of the one or more end node devices to obtain a cluster list corresponding to the target time, wherein the cluster list comprises at least one first cluster, and each first cluster in the at least one first cluster comprises the end node device in the one or more end node devices under the same intermediate node device; and fusing cluster lists respectively corresponding to a plurality of target moments to acquire topology information of the passive network, wherein the topology information comprises at least one second cluster, and each second cluster in the at least one second cluster comprises part or all of terminal node equipment under the same intermediate node equipment in the passive network.

It should be noted that, for the functions of each functional unit in the apparatus 20 for acquiring passive network topology information described in the embodiment of the present application, reference may be made to the description related to step S301 to step S304 in the method embodiment described in fig. 3, and details are not described here again.

In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art will recognize that the embodiments described in this specification are preferred embodiments and that acts or modules referred to are not necessarily required for this application.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit may be stored in a computer-readable storage medium if it is implemented in the form of a software functional unit and sold or used as a separate product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a storage medium, and including several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, and may specifically be a processor in the computer device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. The storage medium may include: a U-disk, a removable hard disk, a magnetic disk, an optical disk, a Read-Only Memory (ROM) or a Random Access Memory (RAM), and the like.

The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present application.

Claims

1. A method for obtaining topology information of a passive network is characterized in that the passive network comprises a plurality of node devices, wherein the plurality of node devices comprise at least one intermediate node device and at least one end node device; the method comprises the following steps:

acquiring feature data of one or more end node devices in the passive network at a target moment, wherein the target moment is a moment when performance index information of the one or more end node devices changes beyond a preset fluctuation range and/or alarm information appears, the feature data comprises the performance index information and/or the alarm information, and the one or more end node devices are one or more of the at least one end node device;

performing cluster analysis on the one or more end node devices according to the characteristic data of the one or more end node devices to obtain a cluster list corresponding to the target time, wherein the cluster list comprises at least one first cluster, and each first cluster in the at least one first cluster comprises the end node device in the one or more end node devices under the same intermediate node device;

and fusing cluster lists respectively corresponding to a plurality of target moments to acquire topology information of the passive network, wherein the topology information comprises at least one second cluster, and each second cluster in the at least one second cluster comprises part or all of terminal node equipment under the same intermediate node equipment in the passive network.

2. The method of claim 1, wherein the performing cluster analysis on the one or more end node devices according to the characteristic data of the one or more end node devices to obtain a cluster list corresponding to the target time includes:

calculating the similarity between the one or more terminal node devices at the target moment according to the characteristic data of the one or more terminal node devices to obtain a similarity matrix;

and performing cluster analysis on the one or more terminal node devices based on the similarity matrix to obtain a cluster list corresponding to the target moment.

3. The method of claim 1, wherein the passive network is a light path distribution network, the end node device is an optical network unit, and the intermediate node device is an optical splitter.

4. The method according to any one of claims 1-3, further comprising:

constructing a target sub-graph corresponding to the target time according to the cluster list corresponding to the target time, wherein the target sub-graph comprises a fully-connected graph or a minimum spanning tree construction graph, and the edge weight between a node i and a node j in the target sub-graph is a similarity measurement function and/or an inherent attribute between an end node device i and an end node device j in the one or more end node devices corresponding to the target time;

the fusing the cluster lists corresponding to the target moments respectively to obtain the topology information of the passive network comprises:

and fusing target subgraphs respectively corresponding to a plurality of target moments based on a graph to obtain a topological graph, wherein the edge weight calculation mode between nodes in the topological graph is as follows:

for the weight kernel function of the k-th target moment in the plurality of target moments, g_k(i, j) is the node i and the node j in the target sub-graph corresponding to the k-th target momentThe edge weight between;

and partitioning the topological graph by using a graph-based community detection algorithm or an embedding algorithm to obtain the topological information.

5. The method according to any one of claims 1 to 3, wherein the fusing the cluster lists corresponding to the plurality of target moments to obtain the topology information of the passive network includes:

respectively fusing the first clustering clusters corresponding to the same intermediate node equipment in the clustering cluster lists corresponding to the target moments to obtain the corresponding second clustering clusters;

and acquiring the topological information according to the plurality of second clustering clusters.

6. An apparatus for obtaining topology information of a passive network, wherein the passive network comprises a plurality of node devices, and the plurality of node devices comprise at least one intermediate node device and at least one end node device; the device comprises:

7. The apparatus according to claim 6, wherein the clustering unit is specifically configured to:

8. The apparatus according to claim 6, wherein the passive network is a light path distribution network, the end node device is an optical network unit, and the intermediate node device is an optical splitter.

9. The apparatus according to any one of claims 6-8, wherein the apparatus further comprises:

a sub-graph unit, configured to construct a target sub-graph corresponding to the target time according to the cluster list corresponding to the target time, where the target sub-graph includes a fully-connected graph or a minimum spanning tree construction graph, and an edge weight between a node i and a node j in the target sub-graph is a similarity metric function and/or an inherent attribute between an end node device i and an end node device j in the one or more end node devices corresponding to the target time;

the fusion unit is specifically configured to:

fusing target subgraphs respectively corresponding to a plurality of target moments based on a graph to obtain a topological graph, wherein the edge weight calculation mode between nodes in the topological graph is as follows:

for the weight kernel function of the k-th target moment in the plurality of target moments, g_k(i, j) is the edge weight between the node i and the node j in the target subgraph corresponding to the kth target moment;

10. The device according to any one of claims 6 to 8, wherein the fusion unit is specifically configured to:

11. A chip system, comprising at least one processor, a memory, and an interface circuit, the memory, the interface circuit, and the at least one processor interconnected by a line, the at least one memory having instructions stored therein; the method of any of claims 1-5 when executed by the processor.

12. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the method of any of the preceding claims 1-5.