A multi-AP coordinated control method and system based on big data comparison

Abstract

The present invention discloses a multi-AP coordinated control method and system based on big data comparison. The method includes: determining the AP type of each wireless AP among multiple wireless APs, detecting the first working parameters of each wireless AP, performing big data comparison on the multiple wireless APs according to the first working parameters, determining the priority of each wireless AP according to the comparison result and the AP type of each wireless AP, and allocating respective wireless network resources for each wireless AP based on the priority of each wireless AP and performing intelligent coordinated control on the wireless network resources according to subsequent second working parameters. It is possible to allocate reasonable and sufficient network resources for each wireless AP according to its actual usage situation, so as to ensure that the access devices of each wireless AP can use the network stably, improving the stability and the user experience.

Description

Technical Field

[0001] The present invention relates to the technical field of AP management and control, and in particular to a multi-AP coordinated management and control method and system based on big data comparison. Background Art

[0002] At present, with the rapid development of the mobile Internet, intelligent terminals such as smart phones and tablet computers are becoming more and more popular. Since the mobile Internet access fees of operators remain high, people prefer to use WiFi to access the Internet. WiFi is a technology that allows intelligent terminals to connect to a wireless local area network. Currently, places such as companies, hotels, and shopping malls provide WiFi hotspots, enabling employees or customers to safely and conveniently access Internet resources while working or consuming. There are many people using WiFi in these places, and a single WiFi access point may not meet the demand. Therefore, multiple APs may need to be deployed in such an environment. Since network resources are fixed, deploying multiple wireless APs will lead to a slowdown in network speed and network disconnection during the connection process, reducing the user experience and network stability. Therefore, while increasing the number of deployed wireless APs, it is necessary to reasonably control network resources. The existing AP management and control method is to evenly distribute network resources to multiple wireless APs to ensure the network stability of the access devices of each wireless AP. However, the above method has the following problems: Since the types of deployed wireless APs are different, the user groups are also different. Evenly distributing network resources will cause some wireless APs with high network requirements to be unable to meet the demand, resulting in network disconnection and low network speed of the connection devices of these wireless APs, reducing the overall stability. Summary of the Invention

[0003] In view of the problems shown above, the present invention provides a multi-AP coordinated management and control method and system based on big data comparison to solve the problems mentioned in the background art, that is, since the types of deployed wireless APs are different, the user groups are also different, and evenly distributing network resources will cause some wireless APs with high network requirements to be unable to meet the demand, resulting in network disconnection and low network speed of the connection devices of these wireless APs, reducing the overall stability.

[0004] A multi-AP coordinated management and control method based on big data comparison includes the following steps:

[0005] Determine the AP type of each wireless AP among multiple wireless APs;

[0006] Detect the first working parameter of each wireless AP, and perform big data comparison on multiple wireless APs according to the first working parameter;

[0007] Determine the priority of each wireless AP according to the comparison result and the AP type of each wireless AP;

[0008] Allocate respective wireless network resources to each wireless AP based on the priority of each wireless AP and perform intelligent coordinated management and control on the wireless network resources according to subsequent second working parameters.

[0009] Preferably, the types of APs include: home wireless AP, 4G wireless AP, intelligent wireless AP, 3G wireless AP, portable wireless AP, and enterprise-level wireless AP.

[0010] Preferably, determining the type of each wireless AP among multiple wireless APs includes:

[0011] Detect the encryption type of each wireless AP, and divide the multiple wireless APs into encrypted APs and unencrypted APs according to the encryption type;

[0012] Obtain the network access type of the first wireless AP belonging to the unencrypted AP type, and divide the first wireless AP into public shared APs and private shared APs according to the network access type;

[0013] Detect the standard data transmission efficiency and the maximum number of device connections of each wireless encrypted AP;

[0014] Evaluate the types of the second wireless AP belonging to the encrypted AP type, the shared APs, and the third wireless AP belonging to the private shared AP type according to the standard data transmission efficiency and the maximum number of device connections of each wireless AP, and determine the type of each wireless AP according to the evaluation results.

[0015] Preferably, detecting the first working parameter of each wireless AP and performing big data comparison on the multiple wireless APs according to the first working parameter includes:

[0016] Detect the working power, wireless signal quality, and wireless signal strength of each wireless AP and use them as the first working parameter;

[0017] Convert the first working parameter of each wireless AP into structured data;

[0018] After the conversion, perform hierarchical big data comparison on the structured data of each wireless AP to obtain a comparison result;

[0019] Determine the comparison information of each dimension of each wireless AP according to the comparison result.

[0020] Preferably, determining the priority of the wireless AP according to the comparison result and the type of each wireless AP includes:

[0021] Evaluate the communication quality of the corresponding link of the wireless AP according to the comparison information of each dimension of each wireless AP;

[0022] Determine the range of users of each wireless AP according to the type of the wireless AP;

[0023] Determine the retrieval priority of each wireless AP based on the range of users of each wireless AP and the communication quality of its corresponding link;

[0024] Determine the priority of each wireless AP according to the retrieval priority of each wireless AP.

[0025] Preferably, allocate respective wireless network resources to each wireless AP based on the priority of each wireless AP and perform intelligent coordinated management and control on the wireless network resources according to subsequent second working parameters, including:

[0026] Retrieve the network management protocol of each wireless AP;

[0027] Set the wireless network resource call ratio for the wireless AP based on the priority of each wireless AP;

[0028] After setting, parse the network management protocol of each wireless AP to generate control instructions;

[0029] Perform wireless network resource scheduling on the wireless AP based on the control instruction of each wireless AP and the wireless network resource call ratio of the wireless AP;

[0030] Detect the subsequent second working parameters of each wireless AP to evaluate the usage status intensity of the wireless AP, and perform intelligent coordinated management and control on all wireless network resources according to the usage status intensity of each wireless AP.

[0031] Preferably, the method further includes:

[0032] Set a unique working channel for each wireless AP;

[0033] Collect beacon frames sent by the wireless AP based on the unique working channel of each wireless AP;

[0034] Configure candidate APs for the wireless AP according to the beacon frames sent by each wireless AP;

[0035] Perform change frequency analysis on the beacon frames of each wireless AP, and determine whether the wireless AP fails according to the analysis result. If so, start the candidate AP corresponding to the wireless AP to replace the wireless AP.

[0036] Preferably, the method further includes:

[0037] Obtain the network configuration information of each wireless AP;

[0038] Determine the network coverage information of the wireless AP according to the network configuration information of each wireless AP;

[0039] Construct the capacity model of each wireless AP based on the network coverage information of each wireless AP and the beacon frames sent by the wireless AP on its unique working channel;

[0040] Determine the spatial degree of freedom of each wireless AP according to the capacity model of each wireless AP and the current network resource usage of the wireless AP;

[0041] Evaluate the maximum number of connected terminals that the spatial degree of freedom can bear, and display the maximum number of connected terminals that each wireless AP can bear on the management and control server.

[0042] Preferably, the method further includes:

[0043] Obtain the terminal configuration requirement information of each terminal device to be connected to the network and the status information of each wireless AP;

[0044] Screen out the recommended connected wireless APs according to the terminal configuration requirement information of each terminal device to be connected to the network;

[0045] Evaluate the matching degree between the recommended connected wireless AP and the terminal device to be connected to the network according to the status information of each recommended connected wireless AP;

[0046] Generate a network selection strategy for each terminal device to be connected to the network according to the matching degree between each terminal device to be connected to the network and each recommended connected wireless AP, and upload it to the terminal device to be connected to the network.

[0047] A multi-AP coordinated management and control system based on big data comparison, the system includes:

[0048] The first determination module is used to determine the AP type of each wireless AP among multiple wireless APs;

[0049] The comparison module is used to detect the first working parameter of each wireless AP, and perform big data comparison on multiple wireless APs according to the first working parameter;

[0050] The second determination module is used to determine the priority of the wireless AP according to the comparison result and the AP type of each wireless AP;

[0051] The management and control module is used to allocate respective wireless network resources to each wireless AP based on the priority of each wireless AP, and perform intelligent coordinated management and control on the wireless network resources according to the subsequent second working parameter.

[0052] Other features and advantages of the present invention will be described in the subsequent specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained by the structures specifically pointed out in the written specification and the drawings.

[0053] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Description of the Drawings

[0054] The accompanying drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention, but do not constitute a limitation to the present invention.

[0055] Figure 1 It is a working flowchart of a multi-AP coordinated management and control method based on big data comparison provided by the present invention;

[0056] Figure 2 It is another working flowchart of a multi-AP coordinated management and control method based on big data comparison provided by the present invention;

[0057] Figure 3 It is yet another working flowchart of a multi-AP coordinated management and control method based on big data comparison provided by the present invention;

[0058] Figure 4 It is a schematic structural diagram of a multi-AP coordinated management and control system based on big data comparison provided by the present invention. Detailed Embodiments

[0059] Exemplary embodiments will be described in detail herein, and examples thereof are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0060] At present, with the rapid development of the mobile Internet, intelligent terminals such as smart phones and tablet computers are becoming increasingly popular. Due to the high fees of mobile phone Internet access charged by operators, people prefer to use WiFi for Internet access. WiFi is a technology that allows intelligent terminals to connect to a wireless local area network. At present, places such as companies, hotels, and shopping malls all provide WiFi hotspots, which facilitate employees or customers to safely and conveniently access Internet resources while working or consuming. There are many people using WiFi in these places, and one WiFi access point may not meet the demand. Therefore, multiple APs may need to be deployed in such an environment. Since network resources are fixed, deploying multiple wireless APs will lead to a slowdown in network speed and network disconnection during the connection process, reducing the user experience and network stability. Therefore, while increasing the number of deployed wireless APs, it is necessary to reasonably control network resources. The existing AP control method is to evenly distribute network resources to multiple wireless APs to ensure the network stability of the access devices of each wireless AP. However, the above method has the following problems: Since the types of deployed wireless APs are different, the user groups are also different. Evenly distributing network resources will cause some wireless APs with high network requirements to be unable to meet the demand, resulting in network disconnection and low network speed of the connected devices of this wireless AP, reducing the overall stability. To solve the above problems, this embodiment discloses a multi-AP coordinated control method based on big data comparison.

[0061] A multi-AP coordinated control method based on big data comparison, as Figure 1 shown, includes the following steps:

[0062] Step S101, determine the AP type of each wireless AP among multiple wireless APs;

[0063] Step S102, detect the first working parameter of each wireless AP, and perform big data comparison on multiple wireless APs according to the first working parameter;

[0064] Step S103, determine the priority of each wireless AP according to the comparison result and the AP type of each wireless AP;

[0065] Step S104, allocate respective wireless network resources to each wireless AP based on the priority of each wireless AP and perform intelligent coordinated control on the wireless network resources according to the subsequent second working parameter.

[0066] The working principle of the above technical solution is as follows: Determine the AP type of each wireless AP among multiple wireless APs, detect the first working parameters of each wireless AP, perform big data comparison on multiple wireless APs according to the first working parameters, determine the priority of each wireless AP according to the comparison result and the AP type of each wireless AP, and allocate respective wireless network resources to each wireless AP based on the priority of each wireless AP and perform intelligent coordinated management and control on the wireless network resources according to subsequent second working parameters.

[0067] The beneficial effects of the above technical solution are as follows: By comprehensively determining the priority of each wireless AP according to the AP type of each wireless AP and the comparison situation of the working parameters of this wireless AP with the working parameters of other wireless APs, and then allocating reasonable network resources for it, it is possible to allocate reasonable and sufficient network resources according to the actual usage situation of each wireless AP, so as to ensure that the access devices of each wireless AP can use the network stably, improving stability and the user experience. It solves the problem that in the prior art, due to the different types of wireless APs deployed, the user groups are also different, and the average allocation of network resources will cause some wireless APs with high network requirements to be unable to meet the needs, resulting in situations such as network disconnection and low network speed for the connected devices of this wireless AP, reducing the overall stability.

[0068] In one embodiment, the AP types include: home wireless AP, 4G wireless AP, intelligent wireless AP, 3G wireless AP, portable wireless AP, and enterprise-level wireless AP.

[0069] The beneficial effects of the above technical solution are as follows: Different types of wireless APs can be deployed for different people and their terminals, so as to meet the needs of most users as much as possible, improving practicality and further enhancing the user experience.

[0070] In one embodiment, as Figure 2 shown, the determining the AP type of each wireless AP among multiple wireless APs includes:

[0071] Step S201: Detect the encryption type of each wireless AP, and divide multiple wireless APs into encrypted APs and unencrypted APs according to the encryption type;

[0072] Step S202: Obtain the network access type of the first wireless AP in the unencrypted AP type, and divide the first wireless AP into common shared APs and private shared APs according to the network access type;

[0073] Step S203: Detect the standard data transmission efficiency and the maximum number of device connections of each wireless encrypted AP;

[0074] Step S204: Perform type evaluation on the second wireless APs belonging to the encrypted AP type, the shared APs, and the third wireless APs belonging to the private shared AP type according to the standard data transmission efficiency and the maximum number of device connections of each wireless AP, and determine the AP type of each wireless AP according to the evaluation results.

[0075] The beneficial effects of the above technical solution are as follows: By screening all wireless APs under multiple conditions and finally determining their AP types, the AP types of each wireless AP can be quickly determined in the form of large-category distribution investigation, improving the investigation efficiency and work efficiency.

[0076] In one embodiment, detecting the first working parameters of each wireless AP and performing big data comparison on multiple wireless APs according to the first working parameters includes:

[0077] Detect the working power, wireless signal quality, and wireless signal strength of each wireless AP and use them as the first working parameters;

[0078] Convert the first working parameters of each wireless AP into structured data;

[0079] After the conversion is completed, perform hierarchical big data comparison on the structured data of each wireless AP to obtain a comparison result;

[0080] Determine the comparison information of each dimension of each wireless AP according to the comparison result.

[0081] The beneficial effects of the above technical solution are as follows: By converting the first working parameters of each wireless AP into structured data and then performing hierarchical comparison, the difference parameters between two wireless APs can be quickly obtained in all directions from multiple dimensions, laying a data reference foundation for subsequent priority evaluation, and further improving stability and practicability.

[0082] In this embodiment, after the above conversion is completed, perform hierarchical big data comparison on the structured data of each wireless AP to obtain a comparison result, including:

[0083] Obtain the structured vector corresponding to the structured data of each wireless AP;

[0084] Extract the hierarchical abstract features of the structured vector corresponding to the structured data of each wireless AP;

[0085] Determine the hierarchical attributes corresponding to the hierarchical abstract features of the structured vector corresponding to the structured data of each wireless AP;

[0086] Based on the hierarchical attributes, construct a dynamic hierarchical data retrieval framework for the structured data of each wireless AP;

[0087] Determine the data format corresponding to each layer of the framework, and determine the data admittance matrix of the framework of this layer based on the data format and the framework structure;

[0088] Determine the data arrangement characteristics in the framework of this layer according to the data admittance matrix of each layer of the framework;

[0089] Based on the data arrangement characteristics in each layer of the architecture and the hierarchical abstraction characteristics of the structured vectors corresponding to the structured data of each wireless AP, sequentially fill the structured data of this wireless AP into each layer of the dynamic hierarchical data retrieval framework of the structured data of this wireless AP;

[0090] After filling is completed, use a preset big data comparison algorithm to compare the hierarchical data in two dynamic hierarchical data retrieval frameworks to obtain the comparison result.

[0091] The beneficial effects of the above technical solution are as follows: By constructing a dynamic hierarchical data retrieval framework for the structured data of each wireless AP, the hierarchical comparison method and data storage method can be accurately screened according to the data attributes of the structured data of this wireless AP, avoiding data damage and loss, improving practicability and stability. Further, by arranging the data according to the characteristics of each layer of the framework, the structured data of each wireless AP can be quickly and accurately stored in layers, further improving usability and work efficiency, and at the same time laying a solid foundation for subsequent data comparison.

[0092] In one embodiment, as Figure 3 shown, determine the priority of this wireless AP according to the comparison result and the AP type of each wireless AP, including:

[0093] Step S301: Evaluate the communication quality of the link corresponding to this wireless AP according to the comparison information of each dimension of each wireless AP;

[0094] Step S302: Determine the range of users of this wireless AP according to the AP type of each wireless AP;

[0095] Step S303: Determine the retrieval priority of this wireless AP based on the range of users of this wireless AP and the communication quality of its corresponding link;

[0096] Step S304: Determine the priority of this wireless AP according to the retrieval priority of each wireless AP.

[0097] The beneficial effects of the above technical solution are as follows: By determining the priority of each wireless AP according to the communication quality and the range of users of each wireless AP, the usage intensity of each wireless AP can be comprehensively evaluated according to the usage parameters and applicable user population of each wireless AP, and then the limit of its allocated network resources can be determined, further ensuring the stability of network usage.

[0098] In one embodiment, wireless network resources are allocated to each wireless AP based on the priority of each wireless AP, and intelligent coordinated control is performed on the wireless network resources according to subsequent second working parameters, including:

[0099] Retrieve the network management protocol of each wireless AP;

[0100] Set the wireless network resource call ratio for this wireless AP based on the priority of each wireless AP;

[0101] After setting, analyze the network management protocol of each wireless AP to generate control instructions;

[0102] Perform wireless network resource scheduling for this wireless AP based on the control instruction of each wireless AP and the wireless network resource call ratio of this wireless AP;

[0103] Detect the subsequent second working parameters of each wireless AP to evaluate the usage status intensity of this wireless AP, and perform intelligent coordinated control on all wireless network resources according to the usage status intensity of each wireless AP.

[0104] The beneficial effects of the above technical solution are: The network resources of each wireless AP can be intelligently controlled at any time to ensure that the network requirements of each wireless AP are met, further improving the practicability, stability and user experience.

[0105] In one embodiment, the method further includes:

[0106] Set a unique working channel for each wireless AP;

[0107] Collect beacon frames sent by this wireless AP based on the unique working channel of each wireless AP;

[0108] Configure candidate APs for this wireless AP according to the beacon frames sent by each wireless AP;

[0109] Perform change frequency analysis on the beacon frames of each wireless AP, and determine whether this wireless AP is faulty according to the analysis result. If so, start the candidate AP corresponding to this wireless AP to replace this wireless AP.

[0110] The beneficial effects of the above technical solution are: By configuring candidate APs for each wireless AP, reasonable replacement APs can be planned effectively for the potential faults of each wireless AP, thereby ensuring the working stability of each wireless AP and further improving the practicability.

[0111] In one embodiment, the method further includes:

[0112] Obtain the network configuration information of each wireless AP;

[0113] Determine the network coverage information of each wireless AP according to its network configuration information;

[0114] Construct the capacity model of each wireless AP based on the network coverage information of each wireless AP and the beacon frames sent by the wireless AP on its unique working channel;

[0115] Determine the spatial degrees of freedom of each wireless AP according to the capacity model of each wireless AP and the current network resource usage of the wireless AP;

[0116] Evaluate the maximum number of connectable terminals that the spatial degrees of freedom can bear, and display the maximum number of connectable terminals of each wireless AP on the management and control server.

[0117] The beneficial effects of the above technical solution are as follows: By evaluating the maximum number of connectable terminals of each wireless AP and displaying it on the management and control server, it is possible to intelligently adjust the network resources of each wireless AP according to the real-time device connection situation of each wireless AP, so that each wireless AP will not lack network resources due to too many connected devices and cause network disconnection, thereby further improving the stability and practicality.

[0118] In one embodiment, the method further includes:

[0119] Obtain the terminal configuration requirement information of each terminal device to be connected to the network and the status information of each wireless AP;

[0120] Screen out the recommended connected wireless APs according to the terminal configuration requirement information of each terminal device to be connected to the network;

[0121] Evaluate the matching degree between the recommended connected wireless AP and the terminal device to be connected to the network according to the status information of each recommended connected wireless AP;

[0122] Generate a network selection strategy for each terminal device to be connected to the network according to the matching degree between each terminal device to be connected to the network and each recommended connected wireless AP, and upload it to the terminal device to be connected to the network.

[0123] The beneficial effects of the above technical solution are as follows: By intelligently generating a network selection strategy for each terminal device to be connected to the network, it is possible to comprehensively recommend the most suitable recommended connected wireless AP for it according to the hardware parameters and requirement information of each terminal device to be connected to the network in combination with the status information of each wireless AP, thereby further improving the user experience and network usage stability.

[0124] This embodiment also discloses a multi-AP coordinated management and control system based on big data comparison, as Figure 4 shown, the system includes:

[0125] The first determination module 401 is configured to determine the AP type of each wireless AP among multiple wireless APs;

[0126] The comparison module 402 is configured to detect the first working parameters of each wireless AP, and perform big data comparison on the multiple wireless APs according to the first working parameters;

[0127] The second determination module 403 is configured to determine the priority of each wireless AP according to the comparison result and the AP type of each wireless AP;

[0128] The management and control module 404 is configured to allocate respective wireless network resources to each wireless AP based on the priority of each wireless AP, and perform intelligent coordination management and control on the wireless network resources according to subsequent second working parameters.

[0129] The working principle and beneficial effects of the above technical solution have been described in the method claims and will not be elaborated here.

[0130] Those skilled in the art should understand that the first and second in the present invention refer to different application stages.

[0131] After considering the specification and practicing the disclosure herein, those skilled in the art will readily conceive of other embodiments of the present disclosure. This application is intended to cover any variations, uses, or adaptations of the present disclosure, which follow the general principles of the present disclosure and include known common knowledge or conventional technical means in the technical field not disclosed in the present disclosure. The specification and examples are only considered exemplary, and the true scope and spirit of the present disclosure are pointed out by the following claims.

[0132] It should be understood that the present disclosure is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present disclosure is only limited by the appended claims.

Claims

1. A multi-AP coordinated control method based on big data comparison, characterized in that Including the following steps: Determine the AP type of each wireless AP among multiple wireless APs; Detect the first working parameters of each wireless AP, and perform big data comparison on multiple wireless APs according to the first working parameters; Determine the priority of each wireless AP according to the comparison result and the AP type of each wireless AP; Based on the priority of each wireless AP, allocate respective wireless network resources for each wireless AP and perform intelligent coordinated control on the wireless network resources according to subsequent second working parameters; The step of detecting the first working parameters of each wireless AP and performing big data comparison on multiple wireless APs according to the first working parameters includes: Detect the working power, wireless signal quality, and wireless signal strength of each wireless AP and use them as the first working parameters; Convert the first working parameters of each wireless AP into structured data; After the conversion is completed, perform hierarchical big data comparison on the structured data of each wireless AP to obtain a comparison result; Determine the comparison information of each dimension of each wireless AP according to the comparison result; After the conversion is completed, perform hierarchical big data comparison on the structured data of each wireless AP to obtain a comparison result, including: Obtain the structured vector corresponding to the structured data of each wireless AP; Extract the hierarchical abstract features of the structured vector corresponding to the structured data of each wireless AP; Determine the hierarchical attributes corresponding to the hierarchical abstract features of the structured vector corresponding to the structured data of each wireless AP; Based on the hierarchical attributes, construct a dynamic hierarchical data retrieval framework for the structured data of each wireless AP; Determine the data format corresponding to each layer of the framework, and determine the data admittance matrix of the layer of the framework based on the data format and the framework structure; Determine the data arrangement characteristics in the layer of the framework according to the data admittance matrix of each layer of the framework; Based on the data arrangement characteristics in each layer of the architecture and the hierarchical abstract features of the structured vector corresponding to the structured data of each wireless AP, fill the structured data of the wireless AP into each layer of the dynamic hierarchical data retrieval framework of the structured data of the wireless AP in sequence; After the filling is completed, use a preset big data comparison algorithm to compare the hierarchical data in two dynamic hierarchical data retrieval frameworks to obtain the comparison result.

2. The multi-AP coordinated control method based on big data comparison according to claim 1, wherein The AP types include: home wireless AP, 4G wireless AP, smart wireless AP, 3G wireless AP, portable wireless AP, and enterprise-level wireless AP.

3. The multi-AP coordinated control method based on big data comparison according to claim 1, characterized in that, The step of determining the AP type of each wireless AP among multiple wireless APs includes: Detect the encryption type of each wireless AP, and divide multiple wireless APs into encrypted APs and unencrypted APs according to the encryption type; Obtain the network access type of the first wireless AP in the unencrypted AP type, and divide the first wireless AP into common shared APs and private shared APs according to the network access type; Detect the standard data transmission efficiency and the maximum number of device connections of each wireless encrypted AP; Perform type evaluation on the second wireless AP in the encrypted AP type, the shared APs, and the third wireless AP in the private shared AP type according to the standard data transmission efficiency and the maximum number of device connections of each wireless AP, and determine the AP type of each wireless AP according to the evaluation result.

4. The multi-AP coordinated control method based on big data comparison according to claim 1, characterized in that Determine the priority of each wireless AP according to the comparison result and the AP type of each wireless AP, including: Evaluate the communication quality of the link corresponding to each wireless AP according to the comparison information of each dimension of each wireless AP; Determine the range of users of each wireless AP according to the AP type of each wireless AP; Determine the retrieval priority of each wireless AP based on the range of users of each wireless AP and the communication quality of its corresponding link; Determine the priority of each wireless AP according to the retrieval priority of each wireless AP.

5. The multi-AP coordinated control method based on big data comparison according to claim 1, characterized in that Based on the priority of each wireless AP, allocate respective wireless network resources to each wireless AP and perform intelligent coordination and control on the wireless network resources according to subsequent second working parameters, including: Retrieve the network management protocol of each wireless AP; Set the wireless network resource call ratio for each wireless AP based on the priority of each wireless AP; After setting, parse the network management protocol of each wireless AP to generate control instructions; Perform wireless network resource scheduling on each wireless AP based on the control instruction of each wireless AP and the wireless network resource call ratio of this wireless AP; Detect the subsequent second working parameters of each wireless AP to evaluate the usage status intensity of this wireless AP, and perform intelligent coordination and control on all wireless network resources according to the usage status intensity of each wireless AP.

6. The multi-AP coordinated control method based on big data comparison according to claim 1, wherein The method further includes: Set a unique working channel for each wireless AP; Collect beacon frames sent by each wireless AP based on the unique working channel of each wireless AP; Configure candidate APs for each wireless AP according to the beacon frames sent by each wireless AP; Perform a change frequency analysis on the beacon frames of each wireless AP, and determine whether this wireless AP is faulty according to the analysis result. If so, start the candidate AP corresponding to this wireless AP to replace this wireless AP.

7. The multi-AP coordinated control method based on big data comparison according to claim 6, characterized in that The method further includes: Obtain the network configuration information of each wireless AP; Determine the network coverage information of each wireless AP according to the network configuration information of each wireless AP; Construct a capacity model of each wireless AP based on the network coverage information of each wireless AP and the beacon frames sent by this wireless AP on its unique working channel; Determine the spatial degree of freedom of each wireless AP according to the capacity model of each wireless AP and the current network resource usage situation of this wireless AP; Evaluate the maximum number of connectable terminals that the spatial degree of freedom can carry, and display the maximum number of connectable terminals of each wireless AP on the management and control server.

8. The multi-AP coordinated control method based on big data comparison according to claim 1, characterized in that The method further includes: Obtain the terminal configuration requirement information of each terminal device to be connected to the network and the status information of each wireless AP; Screen out the recommended connection wireless APs according to the terminal configuration requirement information of each terminal device to be connected to the network; Evaluate the matching degree between the recommended connection wireless AP and the terminal device to be connected to the network according to the status information of each recommended connection wireless AP; Generate a network selection strategy for each terminal device to be connected to the network according to the matching degree between each terminal device to be connected to the network and each recommended connection wireless AP and upload it to this terminal device to be connected to the network.

9. A multi-AP coordinated management and control system based on big data comparison, characterized in that, The system includes: A first determination module, configured to determine the AP type of each wireless AP among multiple wireless APs; A comparison module, configured to detect first working parameters of each wireless AP, and perform big data comparison on multiple wireless APs according to the first working parameters; A second determination module, configured to determine the priority of each wireless AP according to the comparison result and the AP type of each wireless AP; A management and control module, configured to allocate respective wireless network resources for each wireless AP based on the priority of each wireless AP, and perform intelligent coordinated management and control on the wireless network resources according to subsequent second working parameters; The detecting first working parameters of each wireless AP and performing big data comparison on multiple wireless APs according to the first working parameters includes: Detecting the working power, wireless signal quality, and wireless signal strength of each wireless AP and taking them as the first working parameters; Converting the first working parameters of each wireless AP into structured data; After the conversion, performing hierarchical big data comparison on the structured data of each wireless AP to obtain a comparison result; Determining comparison information of each dimension of each wireless AP according to the comparison result; After the conversion, performing hierarchical big data comparison on the structured data of each wireless AP to obtain a comparison result, including: Obtaining a structured vector corresponding to the structured data of each wireless AP; Extracting hierarchical abstract features of the structured vector corresponding to the structured data of each wireless AP; Determining hierarchical attributes corresponding to the hierarchical abstract features of the structured vector corresponding to the structured data of each wireless AP; Constructing a dynamic hierarchical data retrieval framework for the structured data of each wireless AP based on the hierarchical attributes; Determining the data format corresponding to each layer of the framework, and determining the data admittance matrix of the layer of the framework based on the data format and the framework structure; Determining the data arrangement characteristics in the layer of the framework according to the data admittance matrix of each layer of the framework; Based on the data arrangement characteristics in each layer of the architecture and the hierarchical abstract features of the structured vector corresponding to the structured data of each wireless AP, sequentially filling the structured data of the wireless AP into each layer of the dynamic hierarchical data retrieval framework of the structured data of the wireless AP; After the filling is completed, comparing the hierarchical data in two dynamic hierarchical data retrieval frameworks by using a preset big data comparison algorithm to obtain the comparison result.

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