Network equipment operation data management system and method based on artificial intelligence

Abstract

The invention relates to the technical field of data management, in particular to a network equipment operation data management system and method based on artificial intelligence. Comprising a data acquisition unit, a data processing unit and a data management unit, the first data set and the second data set are formed by calculating the calling probability of the operation data and the mutual information among the operation data and establishing the implicit association, so that the limitation that only the data is concerned and the association among the data is ignored in the traditional data management is broken through; the first buffer data set and the second buffer data set are constructed according to the buffer preset threshold value, the first data set and the second data set, and the buffer data sets are updated in real time, so that common data and associated data can be pre-stored in the buffer area, and when operation data needs to be called, the data response speed is greatly increased, and the data processing efficiency is improved. The delay of data reading is reduced, the use frequency and relevance of the data are fully considered, and the overall performance of the system and the efficiency of data calling are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and particularly to a network device operation data management system and method based on artificial intelligence. Background Art

[0002] In today's digital age, network technology has developed rapidly, and network devices are increasingly widely and deeply applied in various fields. From the office networks and data centers within enterprises to the Internet infrastructure spread across the globe, the quantity and variety of network devices are continuously increasing. They undertake key tasks such as data transmission, storage, and processing, and have become an important cornerstone for supporting the informatization operation of modern society.

[0003] Traditional data collection methods often rely on manual configuration and manual operations, with low efficiency and prone to errors. At the same time, for the collected data, traditional methods usually only perform simple storage and basic statistical analysis, unable to deeply explore the potential value behind the data, difficult to discover the complex associations between data, and slow in response speed when retrieving operation data.

[0004] Based on this, the present invention provides a network device operation data management system and method based on artificial intelligence to solve the above-mentioned technical problems. Summary of the Invention

[0005] The purpose of the present invention is to provide a network device operation data management system and method based on artificial intelligence, which breaks through the limitation of traditional data management that only focuses on the data itself and ignores the associations between data. At the same time, it can pre-store common data and associated data in the buffer area, greatly improving the response speed of the data and reducing the latency of data reading when retrieving operation data, fully considering the usage frequency and relevance of the data, enhancing the overall performance of the system and the efficiency of data retrieval. In addition, it continuously updates historical operation data and retrieval records to achieve a dynamic data buffer storage effect.

[0006] To achieve the above purpose, the present invention provides the following technical solutions:

[0007] The first aspect of the present invention: provides a network device operation data management system based on artificial intelligence, including a data acquisition unit, a data processing unit, and a data management unit, wherein:

[0008] The data acquisition unit is used to collect the operation data of network devices and preprocess the collected operation data;

[0009] The data processing unit is used to construct a first data set, and based on the constructed first data set, construct a second data set among the collected operation data, and respectively construct a first buffer data set and a second buffer data set according to a buffer preset threshold, the constructed first data set and second data set, and update the first buffer data set and the second buffer data set. The data processing unit is connected to the data acquisition unit;

[0010] The data management unit is used to display the received information and a preset buffer preset threshold. The data management unit is connected to both the data acquisition unit and the data processing unit.

[0011] A further setting of the present invention is that: the data acquisition unit includes a data collection module, a data identification module, and a first communication module, where:

[0012] The data collection module is used to collect operation data information of network devices;

[0013] The data identification module is used to assign a type identification and a time identification to the collected operation data. The data identification module is connected to the data collection module;

[0014] The first communication module is used to realize information interaction between the data acquisition unit and the data processing unit and the data management unit.

[0015] A further setting of the present invention is that: the data processing unit includes a second communication module, a first data module, a second data module, a buffer data module, a data update module, and a database module, where:

[0016] The second communication module is used to realize information interaction between the data processing unit and the data acquisition unit and the data management unit;

[0017] The first data module is used to construct a first data set. The first data module is connected to the second communication module. Among them, the process of constructing the first data set is as follows:

[0018] Obtain the historical operation data retrieved within the historical data period T and the corresponding retrieval times, and calculate the retrieval probability of each operation data In the formula, C i is the retrieval times of the i-th type of operation data within the period T;

[0019] Calculate the mutual information between each operation data In the formula, X and Y are respectively the value sets of the operation data D i and D j The value set of p(x, y) is D i =x and D j= the joint probability of y, p(x) and p(y) are the marginal probabilities of D i = x and D j = the marginal probability of y;

[0020] Sort the historical operation data according to the number of times of retrieving operation data, and establish the implicit association between the sorted historical operation data according to the mutual information between the operation data, to obtain the first data set;

[0021] The calculation process of the joint probability is as follows:

[0022] Create an n×n matrix M to record the co-occurrence times between different operation data;

[0023] Traverse all data retrieval records. For each retrieval operation, if operation data D i and D j are retrieved simultaneously, then add 1 to the value of the matrix element M ij . When i = j, the recorded is the number of times the operation data is retrieved itself;

[0024] Calculate the joint probability In the formula, M 次数 is the co-occurrence times of operation data D i and D j , and N is the total number of retrievals;

[0025] The second data module constructs a second data set between the collected operation data according to the constructed first data set, and the second data module is connected to the first data module;

[0026] The buffer data module constructs a first buffer data set and a second buffer data set according to the buffer preset threshold, the constructed first data set and the second data set. The buffer data module is connected to both the second communication module and the second data module. Among them, the process of constructing the first buffer data set and the second buffer data set is as follows:

[0027] Obtain the retrieval ratios of the historical first data set and the second data set according to the historical data retrieval records;

[0028] Within the buffer preset threshold, retrieve the operation data corresponding to the ratios in the first data set and the second data set respectively according to the retrieval ratios, and construct the first buffer data set and the second buffer data set;

[0029] The data update module is used to update the historical operation data and retrieval records, and the data update module is connected to both the second communication module and the first data module;

[0030] The database module is used to store the received information, and the database module is connected to both the buffer data module and the data update module.

[0031] The present invention is further configured as follows: The data management unit includes a third communication module, an information display module, and a preset information module, where:

[0032] The third communication module is used to implement information interaction between the data management unit and the data acquisition unit and the data processing unit;

[0033] The information display module is used to display the received information, and the information display module is connected to the third communication module;

[0034] The preset information module is used to upload preset threshold information, and the preset information module is connected to both the third communication module and the information display module.

[0035] The second aspect of the present invention: There is also provided a method for managing operation data of a network device based on artificial intelligence, including the following steps:

[0036] Collect the operation data of the network device, and preprocess the collected operation data;

[0037] Based on the historical operation data and retrieval records of the network device, construct a first data set;

[0038] According to the constructed first data set, construct a second data set among the collected operation data;

[0039] According to the buffer preset threshold, the constructed first data set and the second data set, respectively construct a first buffer data set and a second buffer data set;

[0040] Update the historical operation data and retrieval records to obtain updated first and second buffer data sets, and complete the management of the operation data of the network device.

[0041] The present invention is further configured as follows: The process of the preprocessing is as follows:

[0042] According to the network device type of the collected operation data, assign a type identifier to the operation data;

[0043] Then assign a collection time identifier to the collected operation data.

[0044] The present invention is further configured as follows: The process of constructing the first data set is as follows:

[0045] Obtain the historical operation data retrieved within the historical data period T, and the corresponding retrieval times, and calculate the retrieval probability of each operation data In the formula, Ci The number of times of retrieving the i-th type of operation data within the period T;

[0046] Calculate the mutual information between the operation data Where X and Y are the value sets of the operation data D i and D j respectively, p(x, y) is the joint probability that D i =x and D j =y, and p(x), p(y) are the marginal probabilities that D i =x and D j =y respectively;

[0047] Sort the historical operation data according to the magnitudes of the retrieval times of the operation data, and establish a latent association between the sorted historical operation data based on the mutual information between the operation data to obtain the first data set.

[0048] A further setting of the present invention is that the calculation process of the joint probability is as follows:

[0049] Create an n×n matrix M for recording the co-occurrence times between different operation data;

[0050] Traverse all the data retrieval records. For each retrieval operation, if the operation data D i and D j are retrieved simultaneously, then increment the value of the matrix element M ij by 1. When i = j, the recorded value is the number of times the operation data itself is retrieved;

[0051] Calculate the joint probability Where M 次数 is the co-occurrence times of the operation data D i and D j , and N is the total number of retrievals.

[0052] A further setting of the present invention is that the process of constructing the second data set between the collected operation data is as follows:

[0053] Construct the second data set between the collected operation data according to the retrieval times and latent association of the data types in the constructed first data set.

[0054] A further setting of the present invention is that the process of constructing the first buffer data set and the second buffer data set is as follows:

[0055] Obtain the retrieval ratios of the historical first data set and the second data set according to the historical data retrieval records;

[0056] Within the buffer preset threshold, according to the retrieval ratio, retrieve the corresponding ratio of operation data in the first data set and the second data set respectively, and construct the first buffer data set and the second buffer data set.

[0057] Compared with the prior art, the beneficial effects of the present invention are:

[0058] The present invention calculates the retrieval probability of operation data and the mutual information between operation data, and establishes a latent association to form the first data set and the second data set, breaking the limitation of traditional data management that only focuses on the data itself and ignores the association between data. According to the buffer preset threshold, the first data set and the second data set, the first buffer data set and the second buffer data set are constructed, and these buffer data sets are updated in real time. It can pre-store the frequently used data and associated data in the buffer area. When retrieving operation data is required, the response speed of the data is greatly improved, the delay of data reading is reduced, the usage frequency and relevance of the data are fully considered, the overall performance of the system and the efficiency of data retrieval are improved. At the same time, the historical operation data and retrieval records are continuously updated, so that the buffer data set can reflect the latest data situation in real time, achieving a dynamic data buffer storage effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a system diagram of a network device operation data management system based on artificial intelligence of the present invention.

[0060] Figure 2 It is a system diagram of a data acquisition unit in a network device operation data management system based on artificial intelligence of the present invention.

[0061] Figure 3 It is a system diagram of a data processing unit in a network device operation data management system based on artificial intelligence of the present invention.

[0062] Figure 4 It is a system diagram of a data management unit in a network device operation data management system based on artificial intelligence of the present invention.

[0063] Explanation of the reference numerals in the drawings:

[0064] 100, data acquisition unit; 110, data collection module; 120, data identification module; 130, first communication module; 200, data processing unit; 210, second communication module; 220, first data module; 230, second data module; 240, buffer data module; 250, data update module; 260, database module; 300, data management unit; 310, third communication module; 320, information display module; 330, preset information module. DETAILED DESCRIPTION OF THE INVENTION

[0065] Next, in combination with the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0066] Embodiment:

[0067] As Figures 1-4 shown, this embodiment provides a network device operation data management system based on artificial intelligence, including a data acquisition unit 100, a data processing unit 200, and a data management unit 300, where: the data acquisition unit 100 is used to collect the operation data of the network device and preprocess the collected operation data; the data processing unit 200 is used to construct a first data set, and based on the constructed first data set, construct a second data set between the collected operation data, and based on a buffer preset threshold, the constructed first data set and second data set, respectively construct a first buffer data set and a second buffer data set, and update the first buffer data set and the second buffer data set. The data processing unit 200 is connected to the data acquisition unit 100; the data management unit 300 is used to display the received information and a preset buffer preset threshold. The data management unit 300 is connected to both the data acquisition unit 100 and the data processing unit 200.

[0068] In this embodiment, it should be noted that the data acquisition unit 100 adopts the operation data of each network device, and assigns a type identifier and a time identifier to the collected operation data to facilitate the subsequent identification and processing of the operation data, and then uploads the operation data to the data processing unit 200. After receiving the operation data, the data processing unit 200 will use the historical operation data information to construct a first data set, and based on the constructed first data set, construct a second data set between the collected operation data, and then based on the buffer preset threshold, the constructed first data set and second data set, construct a first buffer data set and a second buffer data set, and update the first buffer data set and the second buffer data set, and perform buffer storage on the first buffer data set and the second buffer data set. When the operation data needs to be retrieved, the response speed can be effectively improved. At the same time, the buffer storage of the corresponding associated data can be provided, further improving the response speed of retrieving the associated data. The management personnel can use the data management unit 300 to preset the buffer preset threshold in advance, so as to effectively ensure that the buffered operation data does not exceed the storage threshold, causing buffer jams, and ensuring the stability and reliability of the retrieval of the operation data.

[0069] In the present invention, the data acquisition unit 100 includes a data collection module 110, a data identification module 120, and a first communication module 130, where: the data collection module 110 is used to collect the operation data information of network devices; the data identification module 120 is used to assign a type identifier and a time identifier to the collected operation data, and the data identification module 120 is connected to the data collection module 110; the first communication module 130 is used to realize the information interaction between the data acquisition unit 100, the data processing unit 200, and the data management unit 300.

[0070] In this embodiment, it should be noted that the operation data information of network devices is collected by the provided data collection module 110 and uploaded to the data identification module 120. The data identification module 120 assigns a type identifier and a time identifier to the collected operation data, and uploads the operation data information with the type identifier and the time identifier to the data processing unit 200 and the data management unit 300 through the first communication module 130.

[0071] In the present invention, the data processing unit 200 includes a second communication module 210, a first data module 220, a second data module 230, a buffer data module 240, a data update module 250, and a database module 260, where: the second communication module 210 is used to realize the information interaction between the data processing unit 200, the data acquisition unit 100, and the data management unit 300; the first data module 220 is used to construct a first data set, and the first data module 220 is connected to the second communication module 210. The process of constructing the first data set is as follows:

[0072] Obtain the historical operation data retrieved within the historical data period T and the corresponding retrieval times, and calculate the retrieval probability of each operation data In the formula, C i is the retrieval times of the i-th type of operation data within the period T;

[0073] Calculate the mutual information between each operation data In the formula, X and Y are respectively the value sets of the operation data D i and D j , p(x, y) is the joint probability that D i =x and D j =y, and p(x), p(y) are respectively the marginal probabilities that D i =x and D j =y;

[0074] Sort the historical operation data according to the magnitude of the retrieval times of the operation data, and establish an implicit association between the sorted historical operation data according to the mutual information between each operation data to obtain the first data set;

[0075] The calculation process of the joint probability is as follows:

[0076] Create an n×n matrix M to record the co-occurrence times between different operation data;

[0077] Traverse all data retrieval records. For each retrieval operation, if operation data D i and D j are retrieved simultaneously, then increment the value of matrix element M ij . When i = j, the recorded value is the number of times the operation data itself is retrieved;

[0078] Calculate the joint probability In the formula, M 次数 is the co-occurrence times of operation data D i and D j , and N is the total number of retrievals;

[0079] The second data module 230 constructs a second data set among the collected operation data according to the constructed first data set. The second data module 230 is connected to the first data module 220. The buffer data module 240 constructs a first buffer data set and a second buffer data set according to the buffer preset threshold, the constructed first data set, and the second data set. The buffer data module 240 is connected to both the second communication module 210 and the second data module 230. Among them, the process of constructing the first buffer data set and the second buffer data set is as follows:

[0080] Obtain the retrieval ratios of the historical first data set and the second data set according to the historical data retrieval records;

[0081] Within the buffer preset threshold, retrieve the operation data corresponding to the ratios in the first data set and the second data set respectively according to the retrieval ratios, and construct the first buffer data set and the second buffer data set;

[0082] The data update module 250 is used to update the historical operation data and retrieval records. The data update module 250 is connected to both the second communication module 210 and the first data module 220. The database module 260 is used to store the received information. The database module 260 is connected to both the buffer data module 240 and the data update module 250.

[0083] In this embodiment, it should be noted that the second communication module 210 receives the operation data information of the data acquisition unit 100 and transmits it to the first data module 220. The first data module 220 calculates the retrieval probability of each operation data and the mutual information between each operation data according to the historical operation data retrieved within the historical data period T and the corresponding retrieval times. The historical operation data is sorted according to the size of the retrieval times of each operation data, and a latent association between the sorted historical operation data is established according to the mutual information between each operation data, obtaining a first data set, so as to realize the sorting of data based on the retrieval probability and construct the latent association between operation data. Then, the second data module 230 constructs a second data set of the collected data according to the constructed first data set, and transmits the first data set and the second data set to the buffer data module 240. The buffer data module 240 constructs a first buffer data set and a second buffer data set according to the buffer preset threshold, the constructed first data set and the second data set. Furthermore, when the operation data needs to be retrieved, the response speed can be effectively improved. At the same time, buffer storage of the corresponding associated data can be provided, further improving the response speed of retrieving the associated data. In addition, the data update module 250 updates the historical operation data and the retrieval records, thus realizing the real-time update of the buffer data to achieve dynamic data buffer storage.

[0084] In the present invention, the data management unit 300 includes a third communication module 310, an information display module 320, and a preset information module 330, where: the third communication module 310 is used to realize information interaction between the data management unit 300 and the data acquisition unit 100 and the data processing unit 200; the information display module 320 is used to display the received information, and the information display module 320 is connected to the third communication module 310; the preset information module 330 is used to upload preset threshold information, and the preset information module 330 is connected to both the third communication module 310 and the information display module 320.

[0085] In this embodiment, it should be noted that the management personnel can preset the buffer preset threshold through the preset information module 330, upload it to the data processing unit 200 through the third communication module 310, and store it in the database module 260. At the same time, the information display module 320 can display the received information for the management personnel to view.

[0086] In addition, this embodiment also provides a method for managing the operation data of a network device based on artificial intelligence, including the following steps:

[0087] S1. Collect the operation data of the network device and preprocess the collected operation data.

[0088] Among them, the preprocessing process is as follows:

[0089] Assign a type identifier to the operation data according to the type of network device from which the operation data is collected;

[0090] Then assign a collection time identifier to the collected operation data.

[0091] In this embodiment, it should be noted that by collecting the operation data of the network device, the original information reflecting the actual working state of the network device can be obtained, and the preprocessing of the collected operation data, that is, assigning a type identifier to the operation data and assigning a collection time identifier, enables more convenient and accurate identification and processing of these operation data subsequently, improving the orderliness and operability of the data.

[0092] S2. Construct a first data set based on the historical operation data and retrieval records of the network device.

[0093] Among them, the process of constructing the first data set is as follows:

[0094] Obtain the historical operation data retrieved within the historical data period T and the corresponding retrieval times, and calculate the retrieval probability of each operation data In the formula, C i is the retrieval times of the i-th type of operation data within the period T;

[0095] Calculate the mutual information between each operation data In the formula, X and Y are respectively the value sets of the operation data D i and D j , p(x, y) is the joint probability that D i =x and D j =y, and p(x), p(y) are respectively the marginal probabilities that D i =x and D j =y;

[0096] Sort the historical operation data according to the magnitude of the retrieval times of the operation data, and establish an implicit association between the sorted historical operation data according to the mutual information between each operation data to obtain the first data set.

[0097] Furthermore, the calculation process of the joint probability is as follows:

[0098] Create an n×n matrix M to record the co-occurrence times between different operation data;

[0099] Traverse all the data retrieval records. For each retrieval operation, if the operation data D i and D j are retrieved simultaneously, then increment the value of the matrix element M ij by 1. When i = j, the recorded is the number of times the operation data itself is retrieved;

[0100] Calculate the joint probability In the formula, M 次数 is the co-occurrence times of the operation data D i and D j , and N is the total retrieval times.

[0101] In this embodiment, it should be noted that by obtaining the historical operation data retrieved within the historical data period T and the corresponding retrieval times, calculating the retrieval probability of each operation data, the frequency of use of different operation data can be clarified, which helps to understand which data are commonly used and which are relatively less used, calculating the mutual information between each operation data, and establishing and sorting the implicit associations between the historical operation data according to the mutual information to obtain the first data set, potential relationships between the operation data can be mined, providing a more valuable data structure for subsequent data buffer storage and associated data retrieval.

[0102] As an example, assume a network device operation data scenario, involving 5 different types of operation data, denoted as A, B, C, D, and E respectively, and the historical data period T is 10 days. Within the T period, the retrieval times of each operation data are counted as shown in Table 1.

[0103] Table 1: Retrieval Times Statistics Table

[0104]

[0105]

[0106] The total retrieval times is 20 + 15 + 10 + 8 + 7 = 60 times. Calculate the retrieval probability of each operation data:

[0107] P A ≈0.333, P B = 0.25, P C ≈0.167, P D ≈0.133, P E ≈0.177.

[0108] Create a 5×5 matrix M to record the co-occurrence times between different operation data. Assume that after traversing all data retrieval records, the obtained matrix M is as follows:

[0109]

[0110] p(A, B)≈0.083, calculate the mutual information between A and B

[0111] A larger mutual information indicates a stronger correlation between them. The implicit correlation information is combined with the sorted operation data to obtain the first data set, which not only contains the sorting information of the operation data but also the implicit correlation information between them.

[0112] S3. Construct a second data set among the collected operation data according to the constructed first data set.

[0113] Among them, the process of constructing the second data set among the collected operation data is as follows:

[0114] Construct a second data set among the collected operation data according to the number of times of data type retrieval and implicit correlation in the constructed first data set.

[0115] In this embodiment, it should be noted that based on the first data set, by referring to the number of times of data type retrieval and implicit correlation therein to construct the second data set, the relationship between the collected operation data becomes more comprehensive and detailed. When more information related to the current operation data is needed, the second data set can provide a more comprehensive reference, which helps to analyze and understand the operation of the network device more deeply and improves the utilization value of the data.

[0116] S4. Construct a first buffer data set and a second buffer data set respectively according to the buffer preset threshold, the constructed first data set and the second data set.

[0117] Among them, the process of constructing the first buffer data set and the second buffer data set is as follows:

[0118] Obtain the retrieval ratios of the historical first data set and the second data set according to the historical data retrieval records;

[0119] Within the buffer preset threshold, according to the retrieval ratios, retrieve the corresponding ratios of the operation data in the first data set and the second data set respectively to construct the first buffer data set and the second buffer data set.

[0120] In this embodiment, it should be noted that obtaining the retrieval ratios of the first data set and the second data set according to the historical data retrieval records and retrieving the operation data from the two data sets according to this ratio within the buffer preset threshold to construct the buffer data set can, under the condition of meeting the storage resource limit (buffer preset threshold), pre-store the frequently retrieved and related data in the buffer data set. When the operation data needs to be retrieved, it can be quickly obtained directly from the buffer data set, greatly improving the response speed of data retrieval, reducing the time delay of data reading, enhancing the overall performance of the system, and at the same time providing buffer storage for the corresponding related data for convenient and quick retrieval of related data.

[0121] S5. Update the historical operation data and retrieval records to obtain the updated first buffer data set and second buffer data set, and complete the management of the operation data of the network device.

[0122] In this embodiment, it should be noted that continuously updating the historical operation data and retrieval records can enable the first buffer data set and the second buffer data set to always reflect the latest data situation. As the network device operates, new data is continuously generated, and the usage of the data is also changing. Through real-time updating, the timeliness and accuracy of the buffer data are ensured, and dynamic data buffer storage is achieved.

[0123] In the description of this specification, the description referring to terms such as "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0124] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and changes can be made according to the content of this specification. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and utilize the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A network device operation data management system based on artificial intelligence, characterized in that, It includes a data acquisition unit (100), a data processing unit (200) and a data management unit (300), where: The data acquisition unit (100) is used to collect the operation data of network devices and preprocess the collected operation data; The data processing unit (200) is used to construct a first data set, and based on the constructed first data set, construct a second data set among the collected operation data, and respectively construct a first buffer data set and a second buffer data set according to the buffer preset threshold, the constructed first data set and second data set, and update the first buffer data set and the second buffer data set. The data processing unit (200) is connected to the data acquisition unit (100); The data management unit (300) is used to display the received information and the preset buffer preset threshold. The data management unit (300) is connected to both the data acquisition unit (100) and the data processing unit (200).

2. The network device operation data management system based on artificial intelligence according to claim 1, wherein The data acquisition unit (100) includes a data collection module (110), a data identification module (120) and a first communication module (130), where: The data collection module (110) is used to collect the operation data information of network devices; The data identification module (120) is used to assign type identification and time identification to the collected operation data. The data identification module (120) is connected to the data collection module (110); The first communication module (130) is used to realize the information interaction between the data acquisition unit (100) and the data processing unit (200) and the data management unit (300).

3. An operation data management system for network devices based on artificial intelligence according to claim 1, characterized in that The data processing unit (200) includes a second communication module (210), a first data module (220), a second data module (230), a buffer data module (240), a data update module (250) and a database module (260), where: The second communication module (210) is used to realize the information interaction between the data processing unit (200) and the data acquisition unit (100) and the data management unit (300); The first data module (220) is used to construct a first data set. The first data module (220) is connected to the second communication module (210). The process of constructing the first data set is as follows: Obtain the historical operation data retrieved within the historical data period T and the corresponding retrieval times, and calculate the retrieval probability of each operation data In the formula C i is the retrieval times of the i-th type of operation data within the period T; Calculate the mutual information between the operating data where X and Y are the value sets of the operating data D i and D j respectively, p(x, y) is the joint probability that D i = x and D j = y, and p(x) and p(y) are the marginal probabilities that D i = x and D j = y respectively; Sort the historical operation data according to the size of the retrieval times of the operation data, and establish an implicit association between the sorted historical operation data according to the mutual information between the operation data to obtain the first data set; The calculation process of the joint probability is as follows: Create an n×n matrix M to record the co-occurrence times between different operation data; Traverse all data retrieval records. For each retrieval operation, if the running data D i and D j are retrieved simultaneously, then increment the value of the matrix element M ij by 1. When i = j, the recorded value is the number of times the running data itself is retrieved; Calculate the joint probability In the formula, M 次数 is the co-occurrence times of the operation data D i and D j , and N is the total retrieval times; The second data module (230) constructs a second data set among the collected operation data according to the constructed first data set. The second data module (230) is connected to the first data module (220); The buffer data module (240) constructs a first buffer data set and a second buffer data set according to a buffer preset threshold, the constructed first data set and second data set. The buffer data module (240) is connected to both the second communication module (210) and the second data module (230). Among them, the process of constructing the first buffer data set and the second buffer data set is as follows: According to the historical data retrieval records, obtain the retrieval ratios of the historical first data set and the second data set; Within the buffer preset threshold, according to the retrieval ratios, retrieve the corresponding ratio of the running data in the first data set and the second data set respectively, and construct the first buffer data set and the second buffer data set; The data update module (250) is used to update the historical running data and the retrieval records. The data update module (250) is connected to both the second communication module (210) and the first data module (220); The database module (260) is used to store the received information. The database module (260) is connected to both the buffer data module (240) and the data update module (250).

4. A network device operation data management system based on artificial intelligence according to claim 1, characterized in that, The data management unit (300) includes a third communication module (310), an information display module (320), and a preset information module (330), where: The third communication module (310) is used to realize the information interaction between the data management unit (300) and the data acquisition unit (100) and the data processing unit (200); The information display module (320) is used to display the received information. The information display module (320) is connected to the third communication module (310); The preset information module (330) is used to upload the preset threshold information. The preset information module (330) is connected to both the third communication module (310) and the information display module (320).

5. A method for managing network device operation data based on artificial intelligence, characterized in that, It includes the following steps: Collect the running data of the network device and preprocess the collected running data; Based on the historical running data and retrieval records of the network device, construct a first data set; According to the constructed first data set, construct a second data set among the collected running data; According to the buffer preset threshold, the constructed first data set and second data set, respectively construct a first buffer data set and a second buffer data set; Update the historical running data and retrieval records to obtain the updated first buffer data set and second buffer data set, and complete the management of the running data of the network device.

6. The method for managing network device operation data based on artificial intelligence according to claim 5, characterized in that, The process of the preprocessing is as follows: According to the network device type of the collected running data, assign a type identifier to the running data; Then assign a collection time identifier to the collected running data.

7. A method for managing network device operation data based on artificial intelligence according to claim 5, characterized in that, The process of constructing the first data set is as follows: Obtain the historical operation data retrieved within the historical data period T and the corresponding retrieval times, and calculate the retrieval probability of each operation data In the formula, C i is the retrieval times of the i-th type of operation data within the period T; Calculate the mutual information between each operation data where X and Y are the value sets of operation data D i and D j respectively, p(x, y) is the joint probability that D i = x and D j = y, and p(x) and p(y) are the marginal probabilities that D i = x and D j = y respectively; Sort the historical running data according to the size of the retrieval times of the running data, and establish an implicit association between the sorted historical running data according to the mutual information between the running data to obtain the first data set.

8. A method for managing operation data of a network device based on artificial intelligence according to claim 7, characterized in that, The calculation process of the joint probability is as follows: Create an n×n matrix M to record the co-occurrence times between different running data; Traverse all data retrieval records. For each retrieval operation, if the running data D i and D j are retrieved simultaneously, then increment the value of the matrix element M ij by 1. When i = j, the recorded value is the number of times the running data itself is retrieved; Calculate the joint probability In the formula, M 次数 is the co-occurrence times of the operation data D i and D j , and N is the total retrieval times.

9. A method for managing operation data of a network device based on artificial intelligence according to claim 5, characterized in that, The process of constructing the second data set among the collected running data is as follows: Construct a second data set among the collected operation data according to the retrieval times and implicit associations of data types in the constructed first data set.

10. A method for managing operation data of a network device based on artificial intelligence according to claim 5, characterized in that, The process of constructing the first buffer data set and the second buffer data set is as follows: Obtain the retrieval ratios of the historical first data set and the second data set according to the historical data retrieval records; Within the buffer preset threshold, retrieve the operation data corresponding to the ratios in the first data set and the second data set respectively according to the retrieval ratios, and construct the first buffer data set and the second buffer data set.

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