Wireless networking fault location method, device and system based on binary tree algorithm

Abstract

The present invention discloses a wireless networking fault location method, device and system based on a binary tree algorithm, which relates to the technical field of communication network security. The key points of its technical solution are as follows: obtaining the alarm information of the monitored network; judging whether the monitored network has a single-link fault or a multi-link fault according to the alarm information; if it is a single-link fault, locating the position of the fault point based on the topological structure of the monitored network, the alarm information and the pre-obtained binary decision tree model; if it is a multi-link fault, decomposing the monitored network into multiple binary tree sub-networks; for each binary tree sub-network, locating the position of the fault point based on the topological structure of the binary tree sub-network, the alarm information and the pre-obtained binary decision tree model. By adopting the solution provided by the present invention, the timeliness and accuracy of networking fault location can be improved, and the security and reliability of networking communication can be guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of communication network security, and in particular to a wireless networking fault location method based on a binary tree algorithm, a wireless networking fault location device based on a binary tree algorithm, and a wireless networking application system. Background Art

[0002] When devices are connected to the network and form a network wirelessly, it is called wireless networking. There are several typical network topologies for wireless networking, such as star network topology, ring network topology, and tree network topology, etc., which usually belong to multi-level networking and have a large number of network nodes. When a certain (or several) node(s) or link(s) fails, it often causes other network nodes that are connected to the faulty node or have a logical relationship to also send alarm messages. It is very difficult for humans to timely and accurately determine which specific node has a fault, which in turn causes maintenance personnel to be unable to promptly eliminate network faults, seriously affecting the security and reliability of network communication. Summary of the Invention

[0003] To overcome or partially solve the above problems, one of the objectives of the present invention is to provide a wireless networking fault location method and device based on a binary tree algorithm to improve the timeliness and accuracy of networking fault location and ensure the security and reliability of networking communication; another objective of the present invention is to provide a wireless networking application system to improve the fault tolerance, communication security, and reliability of the network.

[0004] To achieve the above objectives, in the first aspect of the present invention, a wireless networking fault location method based on a binary tree algorithm is provided. The method includes: obtaining alarm information of the monitored network; determining whether the monitored network has a single-link fault or a multi-link fault according to the alarm information; if it is a single-link fault, locating the position of the fault point based on the topology of the monitored network, the alarm information, and a pre-obtained binary decision tree model; if it is a multi-link fault, decomposing the monitored network into multiple binary tree sub-networks, where at most one fault link is included in any one binary tree sub-network, and any link in the monitored network is included in and only in one of the binary tree sub-networks; for each binary tree sub-network, locating the position of the fault point based on the topology of the binary tree sub-network, the alarm information, and a pre-obtained binary decision tree model.

[0005] Based on the first aspect, in an embodiment of the present invention, the method for obtaining the binary decision tree model includes: counting all possible faults that may occur in the monitored network; traversing and obtaining the manifestation forms of the faults in the corresponding alarm information when the monitored network has a fault, and classifying the faults based on the manifestation forms; respectively fitting the mapping relationship between the faults and the corresponding manifestation forms according to the fault categories, and establishing multiple binary decision tree models for different fault categories.

[0006] Based on the first aspect, in the embodiments of the present invention, the decomposition of the network to be monitored into multiple binary tree sub-networks includes: A1. Determine the maximum number of links M that a single binary tree sub-network can contain; A2. Obtain the node degrees of each network node in the network to be monitored, and sort all the network nodes in the network to be monitored in descending order according to the node degrees; A3. Take the network node with the largest node degree as the root node; A4. If M>2, select the two network nodes with the largest node degrees adjacent to the root node as the child nodes of the root node; A5. Select the network node with the larger node degree from the two child nodes as the parent node, and select one or two network nodes with the largest node degrees adjacent to the parent node as the child nodes of the parent node; A6. Repeat step A5 until the number of links in the generated binary tree sub-network reaches N, where 2<N≤M; A7. From the remaining network nodes adjacent to the root node, select the two network nodes with the largest node degrees as the child nodes of the root node, and repeat step A5 until the number of links in the generated binary tree sub-network reaches N; A8. Repeat step A7 until all the links directly connected to the root node are included in the generated binary tree sub-network, and reselect a network node as the new root node according to the sorting; A9. Repeat steps A4-A8 until any link in the network to be monitored is included in one of the binary tree sub-networks, and the decomposition of the network to be monitored is completed.

[0007] Based on the first aspect, in the embodiments of the present invention, the calculation formula for the maximum number of links M is as follows:

[0008] ; where d represents the maximum value of the number of faulty links in the network to be monitored, q represents the total number of links included in the network to be monitored, represents rounding down;

[0009] where, ; where E represents the set of network nodes in the network to be monitored. If a fault alarm message appears during the service transmission between any pair of nodes (a, b) in E, then is recorded as 1, otherwise it is recorded as 0; represents the value of when the network to be monitored is in a normal operating state, represents the connection status between nodes (a, b).

[0010] Based on the first aspect, in the embodiments of the present invention, the determination of whether the network to be monitored has a single-link fault or a multi-link fault according to the alarm information includes: obtaining the maximum value d of the number of faulty links in the network to be monitored; if d = 1, it is determined that the network to be monitored has a single-link fault; if d>1, it is determined that the network to be monitored has a multi-link fault.

[0011] Based on the first aspect, in the embodiments of the present invention, the method further includes: for a binary tree sub-network, configuring a signal transmission module at the root node of the binary tree sub-network, and configuring at least K signal monitoring modules at the child nodes of the binary tree sub-network, with at most one signal monitoring module configured at a single child node;

[0012] Determine a faulty link according to the signal reception conditions of each signal monitoring module;

[0013] Wherein, ; in the formula, Q represents the total number of links included in the target binary tree sub-network, represents rounding up, and K represents the number of signal monitoring modules configured in the binary tree sub-network.

[0014] In a second aspect, the present invention provides a wireless networking fault location device based on a binary tree algorithm. The device includes: an acquisition module for acquiring alarm information of a monitored network; a judgment module for judging whether there is a fault in the monitored network according to the alarm information, and whether the monitored network belongs to a single-link fault or a multi-link fault; a first execution module for, when there is a single-link fault in the monitored network, locating the position of the fault point based on the topological structure of the monitored network, the alarm information, and a pre-acquired binary decision tree model; a second execution module for, when there is a multi-link fault in the monitored network, decomposing the monitored network into multiple binary tree sub-networks, and locating the position of the fault point based on the topological structure of the binary tree sub-network, the alarm information, and a pre-acquired binary decision tree model; wherein, at most one faulty link is included in any one binary tree sub-network, and any link in the monitored network is included in one and only one binary tree sub-network.

[0015] In a third aspect, the present invention provides a wireless networking application system, including: an IPRAN networking; a wireless networking fault location device based on a binary tree algorithm as provided in the second aspect for locating the position of a fault in the IPRAN networking; a power supply module for supplying power to the devices in the IPRAN networking and the wireless networking fault location device.

[0016] Based on the third aspect, in the embodiments of the present invention, the core layer of the IPRAN networking is composed of multiple master station devices, and the multiple master station devices are mutually in a primary and standby relationship.

[0017] Based on the third aspect, in the embodiments of the present invention, the power supply module includes a photovoltaic power generation unit, a wind power generation unit, and an energy storage unit; wherein, the photovoltaic power generation unit and the wind power generation unit are respectively connected to the energy storage unit, and the energy storage unit is used to supply power to the devices in the IPRAN networking and the wireless networking fault location device.

[0018] Compared with the prior art, the present invention has at least the following advantages and beneficial effects:

[0019] The wireless networking fault location method and device based on the binary tree algorithm provided by the present invention respectively match different fault location methods according to the different numbers of fault links existing in the fault network (monitored network), ensuring the efficiency and accuracy of fault location. When there are multiple fault links in the fault network, the situation of missed detection can be avoided. In addition, in the wireless networking application system provided by the present invention, by setting multiple master-slave main station devices in the core layer of the wireless networking, the fault tolerance rate of the network, the security and reliability of network communication can be improved; its power supply module includes two clean energy power generation units, namely a photovoltaic power generation unit and a wind power generation unit, which can reduce the operation cost of the networking and improve the reliability of the networking operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings described herein are used to provide a further understanding of the embodiments of the present invention and form a part of the present invention, but do not limit the embodiments of the present invention. In the drawings:

[0021] Figure 1 It is a schematic flowchart of the wireless networking fault location method based on the binary tree algorithm;

[0022] Figure 2 It is a schematic diagram of the binary tree network topology for assembling the signal receiving / transmitting device;

[0023] Figure 3 It is a schematic block diagram of the structure of the wireless networking fault location device based on the binary tree algorithm.

[0024] Reference numerals: 1, acquisition module; 2, judgment module; 3, first execution module; 4, second execution module. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] In order to make the purpose, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with the embodiments and the drawings. The illustrative embodiments of the present invention and their descriptions are only used to explain the present invention and do not limit the present invention.

[0026] It should be noted that the term "comprising" or "may comprise" that can be used in various embodiments of the present invention indicates the existence of the claimed functions, operations or elements, and does not limit the addition of one or more functions, operations or elements. In addition, as used in various embodiments of the present invention, the terms "comprising", "having" and their cognates are only intended to mean the presence of specific features, numbers, steps, operations, elements, components or combinations of the foregoing items, and should not be construed as precluding the existence or addition of one or more other features, numbers, steps, operations, elements, components or combinations of the foregoing items.

[0027] In various embodiments of the present invention, the expression "or" or "at least one of B or / and C" includes any combination or all combinations of the words listed simultaneously. For example, the expression "B or C" or "at least one of B or / and C" may include B, may include C, or may include both B and C.

[0028] It should be understood that in the description of the present invention, the meaning of "a plurality of" is two or more, unless otherwise specifically defined.

[0029] To make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with embodiments and drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and do not limit the present invention.

[0030] Please refer to Figure 1 , this embodiment provides a wireless networking fault location method based on a binary tree algorithm, and the method includes:

[0031] S1. Obtain the alarm information of the monitored network;

[0032] Exemplarily, the existing network management system can be used to obtain the alarm information, and the specific obtaining methods are as follows: 1) SNMP Trap: Reported in real time by network elements, so the timeliness of alarms is high, and generally the collection and processing of alarms are completed within 5s. 2) SNMP Get: The network management system polls the device status regularly, so the setting of the alarm delay depends on the length of the polling period. Considering that too frequent SNMP Get operations will affect the load of network element devices, the polling period is generally set to 5 minutes. 3) Threshold alarm: Generated when the performance index exceeds a certain threshold, such as CPU utilization alarm, optical power anomaly alarm, etc. Since it is necessary to observe the performance index for a certain period of time, the alarm delay is generally about 5 minutes.

[0033] S2. Judge whether the monitored network has a single-link fault or a multi-link fault according to the alarm information;

[0034] Specifically, obtain the maximum value d of the number of faulty links in the monitored network; if d = 0, the monitored network has no fault; if d = 1, it is determined that the monitored network has a single-link fault; if d > 1, it is determined that the monitored network has a multi-link fault (although the value of d here represents the number of suspected faulty links, the actual faulty link may still be 1, but in order not to miss any detection, it is still regarded as the monitored network having a multi-link fault).

[0035] S3. If it is a single-link fault, locate the location of the fault point based on the topology structure, alarm information, and pre-obtained binary decision tree model of the monitored network;

[0036] Specifically, the method for obtaining the binary decision tree model includes:

[0037] Step 1: Count all possible faults that may occur in the monitored network;

[0038] Step 2: Traverse and obtain the manifestation forms of the faults in the corresponding alarm information when the monitored network has faults, and classify the faults based on the manifestation forms. For example, when device A loses power, it will cause a Node Down alarm, and at the same time, the port link status of the peer device B directly connected to device A will show a DOWN alarm.

[0039] Step 3: Fit the mapping relationship between the faults and the corresponding manifestation forms respectively according to the fault categories, and establish multiple binary decision tree models for different fault categories. In this way, the training efficiency of the model, the accuracy of model judgment, and the judgment efficiency can be improved (the fewer the branches, the higher the judgment efficiency).

[0040] Since this embodiment is for single-link faults, when a single-link fault occurs in the monitored network, its alarm information is usually not many, and it is easy to judge the type of fault through the alarm information. In this way, the scope of fault troubleshooting can be greatly reduced. For example, if an alarm information shows that "Device A is offline", the reason for such a fault may be that Device A loses power, or it may be caused by the power failure of other devices connected to it, or poor local network conditions, etc. Specifically, it needs to be analyzed and confirmed in combination with other alarm information. For example, if the alarm information shows that a large number of devices in the same area as Device A are all offline, it can be judged that the cause of this fault is poor local network conditions (the reasons for poor network conditions may be local power failure or base station failure, etc., which will not be delved into here).

[0041] Preferably, an inference tree for accurate fault location is designed based on the binary decision tree, and its construction principle is:

[0042] 1) The alarm importance is reported from the highest layer to the lowest layer. The alarm of the upper-layer device takes precedence over the alarm of the lower-layer device. The alarm of the device takes precedence over the alarm of the board, and the alarm of the board takes precedence over the alarm of the port;

[0043] 2) The importance of the original alarm takes precedence over the derived alarm;

[0044] 3) The more accurately positioned the alarm is, the earlier it is determined;

[0045] 4) The importance of the physical alarm takes precedence over the logical alarm.

[0046] Judging level by level from top to bottom can achieve accurate fault location.

[0047] S4. If it is a multi-link failure, decompose the monitored network into multiple binary tree sub-networks. At most one failed link is included in any one binary tree sub-network, and any link in the monitored network is included in one and only one binary tree sub-network. For each binary tree sub-network, locate the position of the fault point based on the topological structure of the binary tree sub-network, the alarm information, and the pre-obtained binary decision tree model.

[0048] In this step, the main idea is to decompose the monitored network with multiple failed links into multiple binary tree sub-networks, so that at most one failed link is included in each binary tree sub-network. In this way, the multi-link fault location problem can be converted into a single-link fault location problem, and then the method in step S3 can be applied to each binary tree sub-network to locate the single-link fault (single fault point).

[0049] Specifically, the decomposition of the monitored network into multiple binary tree sub-networks includes:

[0050] A1. Determine the maximum number of links M that a single binary tree sub-network can contain;

[0051] A2. Obtain the node degrees of each network node in the monitored network, and sort all the network nodes in the monitored network in descending order of node degree;

[0052] A3. Take the network node with the largest node degree as the root node;

[0053] A4. If M > 2, select the two network nodes with the largest node degrees adjacent to the root node as the child nodes of the root node; if M = 2, select the two network nodes with the largest node degrees adjacent to the root node as the child nodes of the root node to generate a binary tree sub-network; if M = 1, select the network node with the largest node degree adjacent to the root node as the child node of the root node to generate a binary tree sub-network (this situation is relatively extreme and usually does not occur);

[0054] A5. Select the network node with a larger node degree from the two child nodes as the parent node, and select one or two network nodes with the largest node degrees adjacent to the parent node as the child nodes of the parent node;

[0055] A6. Repeat step A5 until the number of links in the generated binary tree sub-network reaches N, where 2 < N ≤ M. Limited by the total number of network nodes in the monitored network and the sub-network decomposition rule (at most one faulty link is included in any binary tree sub-network, and any link in the monitored network is included in exactly one binary tree sub-network), it is not guaranteed that the number of links in each binary tree sub-network can reach M. However, for the binary tree sub-networks generated in the early stage of decomposition, try to make the number of links in the binary tree sub-networks reach M as much as possible. This can reduce the number of generated binary tree sub-networks and improve the fault location efficiency.

[0056] A7. From the remaining network nodes adjacent to the root node, select the two network nodes with the largest node degrees as the children of the root node, and repeat step A5 until the number of links in the generated binary tree sub-network reaches N.

[0057] A8. Repeat step A7 until all the links directly connected to the root node are included in the generated binary tree sub-network, and re-select network nodes as the new root node according to the sorting.

[0058] A9. Repeat steps A4 - A8 until any link in the monitored network is included in one of the binary tree sub-networks, and the decomposition of the monitored network is completed.

[0059] Exemplarily, in this embodiment, it is considered that multiple faulty links in the monitored network follow a Bernoulli distribution. The calculation formula for the maximum number of links M is as follows: , where d represents the maximum value of the number of faulty links in the monitored network, q represents the total number of links included in the monitored network, represents rounding down; that is, when the total number of links in the monitored network is q and the maximum value of the number of faulty links is d, the probability that any sub-network with the number of links not exceeding M contains at most one faulty link approaches 1 infinitely.

[0060] Among them, , where E represents the set of network nodes in the monitored network. If a fault alarm message appears during the service transmission between any pair of nodes (a, b) in E, then is recorded as 1, otherwise it is recorded as 0; represents the value of when the monitored network is in a normal operating state, represents the connection status between nodes (a, b).

[0061] It should be understood that if a fault alarm message appears during the service transmission between nodes (a, b), it means that there is a fault in the connection between nodes (a, b). At this time, is recorded as 1, otherwise it is recorded as 0.

[0062] In the above embodiments, the fault location mainly relies on the analysis and reasoning of the alarm information by the binary decision tree model, and the generation of the alarm information depends on the monitoring trigger of the monitoring device. Therefore, this embodiment provides a method for determining a faulty link using the monitoring device, which is specifically as follows:

[0063] B1. For the binary tree subnet, configure a signal emission module at the root node of the binary tree subnet, and configure at least K signal monitoring modules at the child nodes of the binary tree subnet, with at most one signal monitoring module at a single child node;

[0064] B2. Determine the faulty link according to the signal reception status of each signal monitoring module;

[0065] Wherein, ; in the formula, Q represents the total number of links included in the target binary tree subnet, represents rounding up, and K represents the number of signal monitoring modules configured in the binary tree subnet.

[0066] Exemplarily, as Figure 2 shown, it is a schematic diagram of a binary tree topology with 6 nodes and 5 links (the arrows in the figure represent the signal transmission direction); configure a signal emission module at node 1, and configure signal monitoring modules at nodes 4, 5, and 6 respectively. If a certain link fails, the monitoring signals on the corresponding link and the monitoring signals on its outlet link will be interrupted. Specifically, if link L1 is the faulty link, signal monitoring modules A, B, and C cannot obtain signals; if link L2 is the faulty link, signal monitoring module A can obtain signals, and signal monitoring modules B and C cannot obtain signals; if link L3 is the faulty link, signal monitoring modules B and C can obtain signals, and signal monitoring module A cannot obtain signals; if link L4 is the faulty link, signal monitoring modules A and B can obtain signals, and signal monitoring module C cannot obtain signals; if link L5 is the faulty link, signal monitoring modules A and C can obtain signals, and signal monitoring module B cannot obtain signals.

[0067] After the faulty link is determined, the fault range can be greatly reduced, providing accurate alarm information for the binary decision tree model, which helps to improve the judgment accuracy of the binary decision tree model.

[0068] As Figure 3 shown, this embodiment provides a wireless networking fault location device based on the binary tree algorithm. The device includes:

[0069] An acquisition module 1, configured to acquire alarm information of the monitored network;

[0070] A judgment module 2, configured to determine whether there is a fault in the monitored network according to the alarm information, and whether the monitored network belongs to a single-link fault or a multi-link fault;

[0071] A first execution module 3, when there is a single-link fault in the monitored network, is configured to locate the position where the fault point is located based on the topological structure of the monitored network, the alarm information, and the pre-acquired binary decision tree model;

[0072] A second execution module 4, when there is a multi-link fault in the monitored network, is configured to decompose the monitored network into multiple binary tree sub-networks, and locate the position where the fault point is located based on the topological structure of the binary tree sub-networks, the alarm information, and the pre-acquired binary decision tree model; wherein, at most one fault link is included in any one binary tree sub-network, and any link in the monitored network is included in one and only one binary tree sub-network.

[0073] This embodiment also provides a wireless networking application system, including:

[0074] IPRAN networking;

[0075] A wireless networking fault location device based on the binary tree algorithm, configured to locate the position where the fault is located in the IPRAN networking;

[0076] A power supply module, configured to supply power to the devices in the IPRAN networking and the wireless networking fault location device.

[0077] Further, the core layer of the IPRAN networking is composed of multiple master station devices, and the multiple master station devices are mutually in a primary and standby relationship.

[0078] Further, the power supply module includes a photovoltaic power generation unit, a wind power generation unit, and an energy storage unit; wherein, the photovoltaic power generation unit and the wind power generation unit are respectively connected to the energy storage unit, and the energy storage unit is configured to supply power to the devices in the IPRAN networking and the wireless networking fault location device.

[0079] The wireless networking application system provided by this embodiment can improve the fault tolerance rate, the security and reliability of network communication by setting multiple master station devices that are mutually in a primary and standby relationship in the core layer of the wireless networking; its power supply module includes two clean energy power generation units, namely a photovoltaic power generation unit and a wind power generation unit, which can reduce the operation cost of the networking and improve the reliability of the networking operation.

[0080] The device and system provided by the embodiments of the present invention can be used to execute the methods in the above embodiments, and will not be elaborated herein.

[0081] The specific embodiments described above have further elaborated on the object, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only the specific embodiments of the present invention and is not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A wireless networking fault location method based on a binary tree algorithm, characterized in that: The method comprises: Obtain alarm information of the monitored network; Determine whether the monitored network has a single link failure or multiple link failures based on the alarm information; If it is a single-link fault, the fault point is located based on the topological structure of the monitored network, the alarm information and the pre-acquired binary decision tree model; If it is a multi-link fault, the monitored network is decomposed into multiple binary tree sub-networks, any binary tree sub-network contains at most one faulty link, and any link in the monitored network is contained in only one of the binary tree sub-networks; for each binary tree sub-network, the location of the fault point is located based on the topological structure of the binary tree sub-network, the alarm information and the pre-acquired binary decision tree model; wherein, the decomposition of the monitored network into multiple binary tree sub-networks includes: A1. Determine the maximum number of links M that a single binary tree subnetwork can contain; A2. Obtain the node degree of each network node in the monitored network, and sort all network nodes in the monitored network in descending order of node degree; A3. Take the network node with the largest node degree as the root node; A4. If M>2, select the two network nodes with the largest node degrees adjacent to the root node as the child nodes of the root node; A5. Select the network node with the larger node degree from the two child nodes as the parent node, and select one or two network nodes with the largest node degree adjacent to the parent node as the child nodes of the parent node; A6. Repeat step A5 until the number of links in the generated binary tree subnetwork reaches N, where 2<N≤M; A7. Select two network nodes with the largest node degrees from the remaining network nodes adjacent to the root node as child nodes of the root node, and repeat step A5 until the number of links in the generated binary tree subnetwork reaches N; A8, repeating step A7 until all links directly connected to the root node are included in the generated binary tree subnetwork, and reselecting a network node as a new root node according to the sorting; A9. Repeat steps A4-A8 until any link in the monitored network is included in one of the binary tree subnetworks, and the decomposition of the monitored network is completed.

2. A wireless networking fault location method based on a binary tree algorithm according to claim 1, characterized in that: The method for obtaining the binary decision tree model includes: Collect statistics on all possible faults in the monitored network; Traversing and obtaining the manifestation forms in the corresponding alarm information when a fault occurs in the monitored network, and classifying the fault based on the manifestation forms; The mapping relationship between faults and corresponding manifestations is fitted according to the fault categories, and multiple binary decision tree models for different fault categories are established.

3. The method for locating wireless network faults based on a binary tree algorithm according to claim 1, characterized in that: The calculation formula of the maximum number of links M is as follows: , where d represents the maximum number of faulty links in the monitored network, and q represents the total number of links in the monitored network. Indicates rounding down; in, , where E represents the set of network nodes in the monitored network. If a fault alarm occurs during the service transmission between any pair of nodes (a, b) in E, then The value of is recorded as 1, otherwise it is recorded as 0; Indicates that the monitored network is in normal operation The value of Indicates the connection status between nodes (a, b).

4. The method for locating wireless network faults based on a binary tree algorithm according to claim 1, characterized in that: The determining, according to the alarm information, whether a single link failure or a multi-link failure exists in the monitored network includes: Obtain the maximum value d of the number of faulty links in the monitored network; If d=1, it is determined that a single link failure exists in the monitored network; If d>1, it is determined that there are multiple link failures in the monitored network.

5. The method for locating wireless network faults based on a binary tree algorithm according to claim 1, characterized in that: The method further comprises: For the binary tree sub-network, a signal transmission module is configured at the root node of the binary tree sub-network, at least K signal monitoring modules are configured at the child nodes of the binary tree sub-network, and at most one signal monitoring module is configured at a single child node; Determine the faulty link based on the signal receiving status of each signal monitoring module; in, ; In the formula, Q represents the total number of links contained in the target binary tree subnetwork, represents rounding up, and K represents the number of configured signal monitoring modules in the binary tree subnetwork.

6. A wireless networking fault location device based on a binary tree algorithm, characterized in that: The device includes: An acquisition module, used to obtain alarm information of the monitored network; A judgment module is used to judge whether there is a fault in the monitored network according to the alarm information, and whether the monitored network is a single-link fault or a multi-link fault; A first execution module, when a single link failure occurs in the monitored network, is used to locate the location of the fault point based on the topological structure of the monitored network, the alarm information and the pre-acquired binary decision tree model; The second execution module is used to decompose the monitored network into multiple binary tree sub-networks when there are multi-link faults in the monitored network, and locate the fault point based on the topological structure of the binary tree sub-networks, alarm information and a pre-acquired binary decision tree model; wherein any binary tree sub-network contains at most one faulty link, and any link in the monitored network is contained in only one of the binary tree sub-networks; wherein the decomposition of the monitored network into multiple binary tree sub-networks includes: A1. Determine the maximum number of links M that a single binary tree subnetwork can contain; A2. Obtain the node degree of each network node in the monitored network, and sort all network nodes in the monitored network in descending order of node degree; A3. Take the network node with the largest node degree as the root node; A4. If M>2, select the two network nodes with the largest node degrees adjacent to the root node as the child nodes of the root node; A5. Select the network node with the larger node degree from the two child nodes as the parent node, and select one or two network nodes with the largest node degree adjacent to the parent node as the child nodes of the parent node; A6. Repeat step A5 until the number of links in the generated binary tree subnetwork reaches N, where 2<N≤M; A7. Select two network nodes with the largest node degrees from the remaining network nodes adjacent to the root node as child nodes of the root node, and repeat step A5 until the number of links in the generated binary tree subnetwork reaches N; A8, repeating step A7 until all links directly connected to the root node are included in the generated binary tree subnetwork, and reselecting a network node as a new root node according to the sorting; A9. Repeat steps A4-A8 until any link in the monitored network is included in one of the binary tree subnetworks, and the decomposition of the monitored network is completed.

7. A wireless networking application system, characterized in that: The system includes: IPRAN networking; A wireless networking fault locating device based on a binary tree algorithm as claimed in claim 6, used to locate the location of a fault in an IPRAN network; as well as The power supply module is used to supply power to the equipment in the IPRAN network and the wireless networking fault locating device.

8. A wireless networking application system according to claim 7, characterized in that: The core layer of the IPRAN network is composed of multiple master station devices, and the multiple master station devices serve as master and backup for each other.

9. A wireless networking application system according to claim 7, characterized in that: The power supply module includes a photovoltaic power generation unit, a wind power generation unit and an energy storage unit; wherein the photovoltaic power generation unit and the wind power generation unit are respectively connected to the energy storage unit, and the energy storage unit is used to supply power to the equipment in the IPRAN network and the wireless networking fault locating device.

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