Monitoring parameter set determination method, system and device and computer equipment

Abstract

The invention relates to a monitoring parameter set determination method, system and device and computer equipment. The method comprises the following steps: determining a monitoring effect when network state monitoring is carried out on a target network by adopting a current monitoring parameter set; under the condition that the monitoring effect does not meet the preset requirement, determining an association relationship among the monitoring parameters in the current monitoring parameter set; and generating a new monitoring parameter set based on the association relationship of each monitoring parameter, and issuing the new monitoring parameter set to the target network, so that the target network performs network state monitoring based on the new monitoring parameter set. By adopting the method, the network monitoring and troubleshooting efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, system, device and computer equipment for determining a monitoring parameter set. Background Art

[0002] With the evolution of technology and the upgrade of architecture, the communication services carried by the network tend to be diversified, and the number of fault monitoring methods and monitoring parameters has also increased exponentially. When the network is running, administrators generally rely on long-term accumulated historical experience or standards to manually combine multiple types of monitoring parameters and start a large number of monitoring tools to achieve network status and performance monitoring.

[0003] However, there are redundancy and duplication of parameters in the monitoring parameter set determined by experience. Since different monitoring parameters generally need to be acquired by calling different monitoring tools, the operation of acquiring monitoring parameters is cumbersome, which greatly reduces the efficiency of network monitoring and troubleshooting. Summary of the invention

[0004] Based on this, it is necessary to provide a method, system, device and computer equipment for determining a monitoring parameter set in response to the above technical problems.

[0005] In a first aspect, the present application provides a method for determining a monitoring parameter set. The method comprises:

[0006] Determine the monitoring effect when the current monitoring parameter set is used to monitor the network status of the target network;

[0007] When the monitoring effect does not meet the preset requirements, determining the correlation relationship between the monitoring parameters in the current monitoring parameter set;

[0008] Based on the association relationship between the monitoring parameters, a new monitoring parameter set is generated, and the new monitoring parameter set is sent to the target network, so that the target network performs network status monitoring based on the new monitoring parameter set.

[0009] In one embodiment, determining a monitoring effect when the current monitoring parameter set is used to monitor the network status of the target network includes:

[0010] The monitoring effect of the current monitoring parameter set on the target network is determined according to at least one of the monitoring complexity, the monitoring coverage, and the difference between the monitoring results of the current monitoring parameter set and the previous monitoring parameter set on the target network.

[0011] In one embodiment, the method further comprises:

[0012] The monitoring complexity is determined according to the number of monitoring tools corresponding to the current monitoring parameter set, and the monitoring coverage is determined according to the number of monitoring parameters corresponding to the current monitoring parameter set.

[0013] In one embodiment, the method further comprises:

[0014] When the monitoring effect is lower than the monitoring effect threshold, it is determined that the monitoring effect does not meet the preset requirement.

[0015] In one of the embodiments, when the monitoring effect does not meet the preset requirement, determining the association relationship between the monitoring parameters in the current monitoring parameter set includes:

[0016] By using a data mining method, the correlation relationship between the monitoring parameters in the current monitoring parameter set is determined.

[0017] In one embodiment, the method further comprises:

[0018] Generate a tuple based on the association relationship of each of the monitoring parameters;

[0019] Each of the tuples is stored in a monitoring parameter relational model warehouse.

[0020] In one embodiment, the method further comprises:

[0021] A monitoring parameter relationship graph is generated according to each of the tuples in the monitoring parameter relationship pattern warehouse.

[0022] In one embodiment, the tuple consists of two monitoring parameters that are associated with each other, and the associated relationship between the two monitoring parameters.

[0023] In one embodiment, generating a new monitoring parameter set based on the association relationship between the monitoring parameters includes:

[0024] For any of the monitoring parameters, determining associated monitoring parameters that have a direct association relationship and an indirect association relationship with the monitoring parameter, and determining a target monitoring parameter from the monitoring parameter and each of the associated monitoring parameters;

[0025] Each of the target monitoring parameters is added to the new monitoring parameter set.

[0026] In one embodiment, after sending the new monitoring parameter set to the target network, the method further includes:

[0027] The new monitoring parameter set is used as the current monitoring parameter set, and the process proceeds to the step of determining a monitoring effect when the current monitoring parameter set is used to perform network status monitoring on the target network, until the monitoring effect meets the preset requirements.

[0028] In a second aspect, the present application also provides a monitoring parameter set determination system. The system includes a monitoring parameter effect analysis module, a monitoring parameter relationship analysis module, and a monitoring parameter selection and aggregation module, wherein:

[0029] The monitoring parameter effect analysis module is used to determine the monitoring effect when the current monitoring parameter set is used to monitor the network status of the target network, and if the monitoring effect does not meet the preset requirements, send the current monitoring parameter set to the monitoring parameter relationship analysis module;

[0030] The monitoring parameter relationship analysis module is used to determine the association relationship between the monitoring parameters in the current monitoring parameter set, and send the association relationship between the monitoring parameters to the monitoring parameter selection and aggregation module;

[0031] The monitoring parameter selection and aggregation module is used to generate a new monitoring parameter set based on the association relationship between the monitoring parameters, and send the new monitoring parameter set to the target network so that the target network performs network status monitoring based on the new monitoring parameter set.

[0032] In one embodiment, the system further comprises a monitoring parameter relationship pattern warehouse,

[0033] The monitoring parameter relationship analysis module is further used to generate tuples based on the association relationship of each monitoring parameter, and store each tuple in the monitoring parameter relationship model warehouse;

[0034] The monitoring parameter relationship pattern warehouse is also used to generate a monitoring parameter relationship graph according to each of the tuples.

[0035] In a third aspect, the present application also provides a monitoring parameter set determination device. The device comprises:

[0036] A first determination module is used to determine the monitoring effect when the current monitoring parameter set is used to monitor the network status of the target network;

[0037] A second determination module is used to determine the association relationship between the monitoring parameters in the current monitoring parameter set when the monitoring effect does not meet the preset requirements;

[0038] The first generating module is used to generate a new monitoring parameter set based on the association relationship between the monitoring parameters, and send the new monitoring parameter set to the target network, so that the target network performs network status monitoring based on the new monitoring parameter set.

[0039] In one embodiment, the first determining module is further used to:

[0040] The monitoring effect of the current monitoring parameter set on the target network is determined according to at least one of the monitoring complexity, the monitoring coverage, and the difference between the monitoring results of the current monitoring parameter set and the previous monitoring parameter set on the target network.

[0041] In one embodiment, the device further comprises:

[0042] The third determination module is used to determine the monitoring complexity according to the number of monitoring tools corresponding to the current monitoring parameter set, and to determine the monitoring coverage according to the number of monitoring parameters corresponding to the current monitoring parameter set.

[0043] In one embodiment, the device further comprises:

[0044] The fourth determination module is used to determine that the monitoring effect does not meet the preset requirement when the monitoring effect is lower than the monitoring effect threshold.

[0045] In one embodiment, the second determining module is further used to:

[0046] By using a data mining method, the correlation relationship between the monitoring parameters in the current monitoring parameter set is determined.

[0047] In one embodiment, the device further comprises:

[0048] A second generating module, used for generating a tuple based on the association relationship of each of the monitoring parameters;

[0049] The storage module is used to store each of the tuples in a monitoring parameter relationship model warehouse.

[0050] In one embodiment, the device further comprises:

[0051] The third generating module is used to generate a monitoring parameter relationship graph according to each tuple in the monitoring parameter relationship pattern warehouse.

[0052] In one embodiment, the tuple consists of two monitoring parameters that are associated with each other, and the associated relationship between the two monitoring parameters.

[0053] In one embodiment, the generating module is further used for:

[0054] For any of the monitoring parameters, determining associated monitoring parameters that have a direct association relationship and an indirect association relationship with the monitoring parameter, and determining a target monitoring parameter from the monitoring parameter and each of the associated monitoring parameters;

[0055] Each of the target monitoring parameters is added to the new monitoring parameter set.

[0056] In one embodiment, the device further comprises:

[0057] The processing module is used to use the new monitoring parameter set as the current monitoring parameter set and jump to the step of determining the monitoring effect when the current monitoring parameter set is used to monitor the network status of the target network until the monitoring effect meets the preset requirements.

[0058] In a fourth aspect, the present application further provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, any one of the above methods is implemented.

[0059] In a fifth aspect, the present application further provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, any of the above methods is implemented.

[0060] In a sixth aspect, the present application further provides a computer program product, wherein the computer program product comprises a computer program, and when the computer program is executed by a processor, any of the above methods is implemented.

[0061] The above-mentioned monitoring parameter set determination method, system, device and computer equipment determine the monitoring effect of using the current monitoring parameter set, and when the monitoring effect does not meet the preset requirements, the monitoring parameter set is updated according to the association relationship of each monitoring parameter in the current monitoring parameter set to obtain a new monitoring parameter set, thereby enabling the target network to perform network status monitoring based on the new monitoring parameter set. The embodiment of the present application can determine the monitoring parameter set that is most suitable for network status monitoring of the target network, improve the efficiency of the target network in collecting monitoring parameters, and thus improve the efficiency of network monitoring and troubleshooting. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A schematic diagram of a flow chart of a method for determining a monitoring parameter set in one embodiment;

[0063] Figure 2 A schematic diagram of a flow chart of a method for determining a monitoring parameter set in one embodiment;

[0064] Figure 3A schematic diagram of a monitoring parameter relationship diagram in one embodiment;

[0065] Figure 4 is a flow chart of step 106 in one embodiment;

[0066] Figure 5 A schematic diagram of a process flow of a monitoring parameter set determination system in one embodiment;

[0067] Figure 6 A schematic diagram of a process flow of a monitoring parameter set determination system in one embodiment;

[0068] Figure 7 A schematic diagram of a flow chart of a method for determining a monitoring parameter set in one embodiment;

[0069] Figure 8 It is a structural block diagram of a monitoring parameter set determination device in one embodiment;

[0070] Fig. 9 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0071] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0072] In one embodiment, Figure 1 As shown, a method for determining a monitoring parameter set is provided. This embodiment is described by applying the method to a server. It can be understood that the method can also be applied to a terminal, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In the embodiment of the present application, the method includes the following steps:

[0073] Step 102: determine the monitoring effect of using the current monitoring parameter set to monitor the network status of the target network.

[0074] In the embodiment of the present application, the monitoring parameter set is used to indicate the parameters that the target network needs to collect when monitoring its own network status, such as latency, jitter, whether the network can be connected, etc. The monitoring parameter set can be determined by the server and sent to the target network, so that the target network collects each monitoring parameter in the monitoring parameter set and performs network status analysis through each monitoring parameter. The current monitoring parameter set is the monitoring parameter set currently being used by the target network.

[0075] During the collection of various monitoring parameters, the target network can obtain a variety of monitoring effect parameters for calculating the monitoring effect, which may include monitoring effect parameters used to characterize the accuracy of the monitoring itself (for example, whether the collected monitoring parameter values ​​are correct, whether they fully reflect the network conditions of the target network, etc.), and monitoring effect parameters used to characterize the resources consumed by the target network when performing network status monitoring (for example, the number of various tools that need to be enabled for the target network collection parameters, the computing power and storage space consumed by the collection parameters, etc.). This application does not limit the specific standards for judging the monitoring effect and the specific monitoring effect parameters used.

[0076] The target network can regularly feed back to the server various monitoring effect parameters when the current network parameter set is used for network status monitoring, such as the values ​​of the monitoring parameters collected, the number of tools enabled for collecting monitoring parameters, the computing power consumed, etc. After receiving the various monitoring effect parameters sent by the target network, the server can further determine the monitoring effect based on the various monitoring effect parameters. Exemplarily, since the higher the monitoring accuracy, the better, and the fewer resources consumed when monitoring the network status, the better, the monitoring effect can be positively correlated with the monitoring effect parameter that characterizes the monitoring accuracy, and the monitoring effect can be negatively correlated with the parameter that characterizes the resources consumed when monitoring the network status. When other monitoring effect parameters are used to determine the monitoring effect, the monitoring effect can also be determined based on similar principles, and the embodiments of the present application do not specifically limit this.

[0077] Step 104: when the monitoring effect does not meet the preset requirement, determine the association relationship between the monitoring parameters in the current monitoring parameter set.

[0078] In the embodiments of the present application, the preset requirements refer to the requirements for the monitoring effect, which may be requirements for the overall monitoring effect, or may also include requirements for the overall monitoring effect and requirements for certain parameters used in calculating the monitoring effect. Assuming that the monitoring effect is characterized by levels, each level includes "excellent", "good", "poor", etc., the preset requirements may be that the monitoring effect is greater than or equal to "good", or that the monitoring effect is greater than or equal to "good", and that the number of tools required to enable the acquisition parameters is less than a certain number, and the embodiments of the present application do not specifically limit this.

[0079] When the monitoring effect does not meet the preset requirements, it indicates that the current monitoring parameter set can be optimized; since there may be a correlation between the monitoring parameters in the monitoring parameter set (the existence of a correlation indicates that the two monitoring parameters have similarities in their changing trends, and one monitoring parameter may be inferred from another parameter), it is possible to determine which monitoring parameter in the monitoring parameter set to change based on the correlation between the monitoring parameters. For example, if there is a correlation between monitoring parameter A and monitoring parameter B, it is possible to determine whether monitoring parameter A (or B) can be expressed by monitoring parameter B (or A) based on monitoring parameter A and monitoring parameter B previously collected by the target network; if so, one of monitoring parameter A and monitoring parameter B can be selected for deletion, thereby optimizing the current monitoring parameter set.

[0080] Whether there is a correlation relationship between the two monitoring parameters can be determined by the change trends of each of the two monitoring parameters. For example, if it can be determined that monitoring parameter A and monitoring parameter B are positively correlated or negatively correlated based on the monitoring parameter A and monitoring parameter B previously collected from the target network, it can be determined that there is a correlation relationship between the two monitoring parameters. Alternatively, it is also possible to determine whether there is a correlation relationship between the monitoring parameters by using an existing algorithm, such as a correlation discovery algorithm, which is not specifically limited in the embodiments of the present application.

[0081] Step 106: Generate a new monitoring parameter set based on the association relationship between the monitoring parameters, and send the new monitoring parameter set to the target network, so that the target network performs network status monitoring based on the new monitoring parameter set.

[0082] In the embodiment of the present application, it is possible to determine how to update the current monitoring parameter set based on the association relationship between the monitoring parameters. For example, when two monitoring parameters have an association relationship, one of them can be selected for deletion; or because the association relationship between monitoring parameters can also be divided into strong association relationships and weak association relationships (for example, the higher the accuracy of another monitoring parameter derived from a certain monitoring parameter, the stronger the association between the two), only one of the monitoring parameters with a strong association relationship can be selected for deletion; it is also possible that when there is no association relationship between the monitoring parameters, or when there is only a weak association relationship between the monitoring parameters, one of the monitoring parameters that have been deleted from the monitoring parameter set can be selected and added back to the current parameter set to obtain a new monitoring parameter set. The embodiment of the present application does not specifically limit this.

[0083] After obtaining the new monitoring parameter set, the server sends the new monitoring parameter set to the target network, so that the target network in turn collects each monitoring parameter in the new monitoring parameter set and monitors its own network status.

[0084] The monitoring parameter set determination method provided in the embodiment of the present application determines the monitoring effect of the current monitoring parameter set, and when the monitoring effect does not meet the preset requirements, the monitoring parameter set is updated according to the association relationship of each monitoring parameter in the current monitoring parameter set to obtain a new monitoring parameter set, thereby enabling the target network to perform network status monitoring based on the new monitoring parameter set. The embodiment of the present application can determine the monitoring parameter set that is most suitable for network status monitoring of the target network, improve the efficiency of the target network in collecting monitoring parameters, and thereby improve the efficiency of network monitoring and troubleshooting.

[0085] In one embodiment, in step 102, determining the monitoring effect of using the current monitoring parameter set to monitor the network status of the target network includes:

[0086] The monitoring effect of the current monitoring parameter set on the target network is determined according to at least one of the monitoring complexity, the monitoring coverage, and the difference between the monitoring results of the current monitoring parameter set and the previous monitoring parameter set on the target network.

[0087] In the embodiment of the present application, the monitoring complexity is used to characterize the resources consumed when the target network collects each monitoring parameter in the current monitoring parameter set, which may be related to the number of monitoring tools that need to be enabled in the target network, the number of processes that need to be enabled, the memory size that needs to be allocated to collect monitoring parameters, etc. The monitoring coverage is used to characterize the number of other monitoring parameters that can be calculated by the target network based on the collected monitoring parameters. The previous monitoring parameter set may include one or more monitoring parameter sets that were previously used for network monitoring by the target network. The difference between the monitoring results of the current monitoring parameter set and the previous monitoring parameter set for the target network can be calculated by the difference between the two in monitoring complexity, monitoring coverage, or the accuracy of the calculated monitoring parameters.

[0088] According to different evaluation criteria for monitoring effects, one or more parameters among monitoring complexity, monitoring coverage and monitoring result gap can be selected to determine the monitoring effect. Generally speaking, the lower the monitoring complexity, the better, and the larger the monitoring coverage, the better. Therefore, when selecting a parameter to determine the monitoring effect, the monitoring complexity and the monitoring effect can be negatively correlated, and the monitoring coverage and the monitoring effect can be positively correlated. Since the smaller the gap between the monitoring results of the current monitoring parameter set and the previous monitoring parameter set with better monitoring effects, the better, and the larger the gap between the monitoring results of the previous monitoring parameter set with poorer monitoring effects, the better, it can be determined based on the selected previous monitoring parameter set whether the monitoring effect should be negatively correlated or positively correlated with the monitoring result gap.

[0089] When selecting multiple parameters to determine the monitoring effect, the specific method of determining the monitoring effect based on the multiple parameters can be determined according to the different emphasis on each parameter. For example, if the monitoring complexity and the monitoring coverage are selected to determine the monitoring effect, and the monitoring coverage is more important than the monitoring complexity, the monitoring effect can be determined by first determining the interval where the monitoring effect is located according to the monitoring coverage, and then adjusting the monitoring effect within the interval according to the monitoring complexity. Alternatively, the monitoring complexity, monitoring coverage, and the difference in monitoring results can be converted into numerical values, and then different weights can be assigned to these three parameters to control the different emphasis on each parameter. The embodiments of the present application do not specifically limit this.

[0090] The monitoring parameter set determination method provided in the embodiment of the present application determines the monitoring effect based on at least one parameter of the monitoring complexity, monitoring coverage, and the difference between the monitoring results of the current monitoring parameter set and the previous monitoring parameter set for the target network. The embodiment of the present application considers three different dimensions when determining the monitoring effect, which can improve the accuracy of determining the monitoring effect, and thereby improve the accuracy of adjusting the current monitoring parameter set according to the monitoring effect.

[0091] In one embodiment, the method further includes:

[0092] The monitoring complexity is determined according to the number of monitoring tools corresponding to the current monitoring parameter set, and the monitoring coverage is determined according to the number of monitoring parameters corresponding to the current monitoring parameter set.

[0093] In the embodiment of the present application, the number of monitoring tools refers to the total number of different monitoring tools required to collect each monitoring parameter in the current monitoring parameter set. Different monitoring parameters may require different monitoring tools to collect. For example, if the monitoring parameters to be collected include latency, packet loss, and whether the link is connected, the latency and packet loss are collected through TWAMP (Two-Way Active Measurement Protocol), and the confirmation of whether the link is connected is completed through ping (Packet Internet Groper), then the number of monitoring tools is equal to 2.

[0094] The number of monitoring parameters refers to the total number of monitoring parameters that can be directly determined and indirectly determined based on the monitoring parameters in the current monitoring parameter set. The monitoring parameters that can be directly determined refer to the monitoring parameters included in the current monitoring parameter set, and the monitoring parameters that can be indirectly determined refer to the total number of other monitoring parameters that can be calculated based on the monitoring parameters included in the current monitoring parameter set. For example, if the current monitoring parameter set includes the delay of link A, the packet loss of link A can be calculated through the delay of link A, and the delay of link B can also be calculated. Then the number of monitoring parameters is the sum of the monitoring parameters that can be directly determined (1) and the monitoring parameters that can be indirectly determined (2), which is equal to 3.

[0095] The number of monitoring tools may be positively correlated with monitoring complexity, and the number of monitoring parameters may be positively correlated with monitoring coverage. After determining the number of monitoring tools and the number of monitoring parameters in the current monitoring parameter set, the monitoring complexity and monitoring coverage may be determined based on the above two parameters.

[0096] The monitoring parameter set determination method provided in the embodiment of the present application determines the monitoring complexity according to the number of monitoring tools, and determines the monitoring coverage according to the number of monitoring parameters, so that the monitoring effect can reflect the number of monitoring tools needed to collect monitoring parameters and the number of monitoring parameters that can be deduced from the collected monitoring parameters, thereby improving the accuracy of determining the monitoring effect, and further improving the accuracy of adjusting the current monitoring parameter set according to the monitoring effect.

[0097] In one embodiment, the method further includes:

[0098] When the monitoring effect is lower than the monitoring effect threshold, it is determined that the monitoring effect does not meet the preset requirements.

[0099] In the embodiment of the present application, the monitoring effect threshold is a preset value, which can be set according to the representation method of the monitoring effect and the demand for the monitoring effect. For example, when the monitoring effect is represented by different levels, the monitoring effect threshold can be a level, and when the monitoring effect is represented by a numerical value, the monitoring effect threshold can be a numerical value.

[0100] The monitoring effect is lower than the monitoring effect threshold value, which means that if the monitoring effect is represented by different levels, the level corresponding to the monitoring effect is lower than the level corresponding to the monitoring effect threshold value; if the monitoring effect is represented by a numerical value, the numerical value of the monitoring effect is lower than the numerical value of the monitoring effect threshold value. When the monitoring effect is lower than the monitoring effect threshold value, the server may start the process of generating a new monitoring parameter set. When the monitoring effect is not lower than the monitoring effect threshold value, the server may not adjust the current monitoring parameter set and continue to periodically determine the monitoring effect until the monitoring effect is lower than the monitoring effect threshold value.

[0101] The monitoring parameter set determination method provided in the embodiment of the present application presets a monitoring effect threshold value. When the monitoring effect is lower than the monitoring effect threshold value, it is determined that the monitoring effect does not meet the preset requirements. When the monitoring effect does not meet the preset requirements, a new monitoring parameter set can be generated, thereby improving the efficiency of the target network in collecting monitoring parameters, thereby improving the efficiency of network monitoring and troubleshooting.

[0102] In one embodiment, in step 104, when the monitoring effect does not meet the preset requirements, determining the association relationship between the monitoring parameters in the current monitoring parameter set includes:

[0103] Through data mining methods, the correlation relationship between the monitoring parameters in the current monitoring parameter set is determined.

[0104] In an embodiment of the present application, the data mining method may include one or more data mining algorithms, such as an association discovery algorithm, a causal relationship discovery algorithm, a clustering algorithm, a decision tree algorithm, etc. The embodiment of the present application does not specifically limit the specific data mining algorithm used.

[0105] According to each data mining algorithm, it can be determined whether there is a correlation between each monitoring parameter. The correlation relationship may include but is not limited to co-occurrence relationship, dependency relationship, causal relationship, etc. Among them, the co-occurrence relationship may refer to that two monitoring parameters usually have abnormal values ​​together (for example, when the delay is high, the packet loss rate will also be high), or it may refer to that the two monitoring parameters have similar changes in trend (for example, when the delay drops from high to low, the packet loss rate will also drop from high to low). Dependency relationship may refer to that a monitoring parameter only has an abnormal value when another monitoring parameter has an abnormal value, but the two monitoring parameters do not necessarily have a causal relationship (for example, link B will not be connected only when link A cannot be connected). Causal relationship may refer to whether a monitoring parameter is abnormal or not depends on whether another monitoring parameter has an abnormal value (for example, the reason why link B cannot be connected is because its predecessor link is link A, so the failure of link A to connect will cause link B to be unable to connect). Exemplarily, it is possible to determine whether the monitoring parameters have a co-occurrence relationship based on an association discovery algorithm, and then determine the monitoring parameters with a dependent relationship and the monitoring parameters with a causal relationship from the monitoring parameters with a co-occurrence relationship, determine or verify whether two monitoring parameters have a causal relationship based on a causal relationship discovery algorithm, and determine whether the values ​​of two monitoring parameters are similar based on a clustering algorithm, etc. The embodiments of the present application do not make specific limitations on this.

[0106] The monitoring parameter set determination method provided in the embodiment of the present application determines the correlation between the monitoring parameters according to the data mining algorithm, and generates a new monitoring parameter set according to the correlation, thereby improving the efficiency of collecting monitoring parameters of the target network, thereby improving the efficiency of network monitoring and troubleshooting.

[0107] In one embodiment, Figure 2 As shown, the above method also includes:

[0108] Step 202: Generate a tuple based on the association relationship between each monitoring parameter.

[0109] Step 204: store each tuple in the monitoring parameter relational model warehouse.

[0110] In the embodiment of the present application, a tuple is used to record the association relationship between various monitoring parameters. A tuple may include two or more monitoring parameters that have an association relationship. For example, if there is an association relationship between monitoring parameters A and B, and there is also an association relationship between A and C, two tuples can be used to record the association relationship between monitoring parameters.<A,B> and<A,C> To record the relationship between A, B, and C, you can also use a tuple<C,A,B> To record the association relationship between A, B, and C (adjacent means there is an association relationship), and the embodiment of the present application does not make any specific limitation on this.

[0111] After obtaining each tuple, the tuple can be stored in a monitoring parameter relationship pattern warehouse. The monitoring parameter relationship pattern warehouse can be composed of one or more databases. When it is necessary to find the association relationship between each monitoring parameter later, the tuple corresponding to the monitoring parameter can be found in the monitoring parameter relationship pattern warehouse, and then the association relationship between each monitoring parameter can be determined based on the tuple.

[0112] The monitoring parameter set determination method provided in the embodiment of the present application generates tuples according to the association relationship between monitoring parameters, and then stores the tuples in a monitoring parameter relationship model warehouse, which can improve the convenience of recording and searching for the association relationship between monitoring parameters.

[0113] In one embodiment, the method further includes:

[0114] A monitoring parameter relationship graph is generated according to each tuple in the monitoring parameter relationship pattern warehouse.

[0115] In the embodiment of the present application, a monitoring parameter relationship diagram can be drawn according to each tuple to more intuitively show the association relationship between each monitoring parameter to the user. Figure 3 As shown, each monitoring parameter can be drawn in the monitoring parameter relationship diagram. When two monitoring parameters belong to the same tuple, that is, when there is an association relationship between the two monitoring parameters, a line is drawn between the two monitoring parameters to represent the association relationship (different lines can be used for different association relationships, such as a solid line to represent a causal relationship, a dotted line to represent a contribution relationship, etc.). When multiple monitoring parameters belong to the same tuple, corresponding markings can also be made in the monitoring parameter relationship diagram, such as using dotted lines to select monitoring parameters belonging to the same tuple, etc., and the embodiments of the present application do not specifically limit this.

[0116] The monitoring parameter set determination method provided in the embodiment of the present application draws a monitoring parameter relationship diagram based on each tuple, which can more intuitively display the association relationship between each monitoring parameter.

[0117] In one embodiment, a tuple consists of two monitoring parameters that have an associated relationship, and the associated relationship between the two monitoring parameters.

[0118] In the embodiment of the present application, a tuple may be a triple, which includes two monitoring parameters with an associated relationship and their associated relationship. The present application does not specifically limit the arrangement order of the monitoring parameters and the associated relationship in the triple. For example, for monitoring parameters A and monitoring parameters B with an associated relationship X, their triple may be<A、X、B> , or<B、A、X> or other forms.

[0119] The monitoring parameter set determination method provided in the embodiment of the present application uses triples to display the association relationship between monitoring parameters, so that the association relationship between monitoring parameters can also be written into the tuple for storage.

[0120] In one embodiment, Figure 4 As shown, in step 106, based on the association relationship of each monitoring parameter, a new monitoring parameter set is generated, including:

[0121] Step 402: for any monitoring parameter, determine the associated monitoring parameters that have a direct association relationship and an indirect association relationship with the monitoring parameter, and determine the target monitoring parameter from the monitoring parameter and the associated monitoring parameters.

[0122] Step 404: Add each target monitoring parameter to the new monitoring parameter set.

[0123] In the embodiment of the present application, for any monitoring parameter, a monitoring parameter that has an association relationship with the monitoring parameter is an associated monitoring parameter that has a direct association relationship with the monitoring parameter, and a monitoring parameter that has an association relationship with any associated monitoring parameter of the monitoring parameter is an associated monitoring parameter that has an indirect association relationship with the monitoring parameter. For example, if there is an association relationship between monitoring parameter A and monitoring parameter B, there is an association relationship between monitoring parameter C and monitoring parameter B, and there is an association relationship between monitoring parameter D and monitoring parameter C, then since monitoring parameter B is a monitoring parameter that has an association relationship with monitoring parameter A, monitoring parameter B is an associated monitoring parameter that has a direct association relationship with monitoring parameter A; since there is an association relationship between monitoring parameter C and an associated monitoring parameter of monitoring parameter A (monitoring parameter B), monitoring parameter C is an associated monitoring parameter that has an indirect association relationship with monitoring parameter A; since there is an association relationship between monitoring parameter D and an associated monitoring parameter of monitoring parameter A (monitoring parameter C), monitoring parameter D is also an associated monitoring parameter that has an indirect association relationship with monitoring parameter A, and so on.

[0124] Since theoretically, each associated monitoring parameter of a monitoring parameter can be derived from one or more monitoring parameters in the associated monitoring parameter, only some target monitoring parameters can be selected from the monitoring parameter and all its associated monitoring parameters to be added to the new monitoring parameter set, and at the same time, the new monitoring parameter set can have the same monitoring coverage as the current monitoring parameter set. Exemplarily, if the associations between the monitoring parameters are strong or weak (for example, causal relationships are stronger than dependency relationships and co-occurrence relationships), several monitoring parameters with the most strong associations with other monitoring parameters can be selected as target monitoring parameters (because monitoring parameters with strong associations with them can be derived from these monitoring parameters), and several monitoring parameters with only weak associations with other monitoring parameters can be selected as target monitoring parameters (because these monitoring parameters cannot be accurately derived from other parameters). If the associations between the monitoring parameters are not strong or weak, several monitoring parameters with the most associations with other monitoring parameters can be selected as target monitoring parameters.

[0125] It should be noted that the above are only two examples of selecting target monitoring parameters. In fact, the embodiments of the present application do not specifically limit the method of selecting target monitoring parameters and the number of target monitoring parameters. Any method of determining target monitoring parameters based on association relationships is applicable to the embodiments of the present application.

[0126] The monitoring parameter set determination method provided in the embodiment of the present application determines a new monitoring parameter set based on the correlation between the monitoring parameters. It can determine which specific monitoring parameters can be derived based on other monitoring parameters that have a correlation with them and therefore do not need to be collected, and the monitoring parameters that may not be added to the new monitoring parameter set. It can determine the monitoring parameter set that is most suitable for network status monitoring of the target network, thereby improving the efficiency of collecting monitoring parameters of the target network, and further improving the efficiency of network monitoring and troubleshooting.

[0127] In one embodiment, in step 106, after sending the new monitoring parameter set to the target network, the method further includes:

[0128] The new monitoring parameter set is used as the current monitoring parameter set, and the process proceeds to the step of determining the monitoring effect when the current monitoring parameter set is used to monitor the network status of the target network, until the monitoring effect meets the preset requirements.

[0129] In an embodiment of the present application, after the server sends a new monitoring parameter set, the new monitoring parameter set becomes the current monitoring parameter set. The server can continue to monitor the monitoring effect of the target network when performing network status monitoring through the new monitoring parameter set, and determine whether the current monitoring parameter set needs to be adjusted based on whether the determined monitoring effect meets the preset requirements.

[0130] It should be noted that, since the monitoring parameters in the new monitoring parameter set are usually monitoring parameters that have appeared in the previous monitoring parameter set before, the associations between the monitoring parameters in the new monitoring parameter set have been determined. When the new monitoring parameter set is used as the current monitoring parameter set and it is determined that a new monitoring parameter set needs to be generated based on the current monitoring parameter set at this time, the step of determining the associations between the monitoring parameters in the current monitoring parameter set may no longer be performed, thereby improving the efficiency of generating the new monitoring parameter set. Alternatively, considering that in the process of using the current monitoring parameter set at this time to monitor the network status of the target network, the target network has collected new data of the monitoring parameters in the current monitoring parameter set, which may cause the associations of the monitoring parameters determined based on these collected data to change, so the step of determining the associations between the monitoring parameters may still be performed, and when the association determined this time is different from the association determined previously, the association between the monitoring parameters is updated to the association determined this time, so that the determined association is more accurate, and the embodiments of the present application do not specifically limit this.

[0131] The monitoring parameter set determination method provided in the embodiment of the present application repeats the steps of taking the new monitoring parameter set as the current monitoring parameter set and determining the monitoring effect of the current monitoring parameter set, and can continuously adjust the monitoring parameter set until the most suitable monitoring parameter set for monitoring the target network is found, thereby improving the efficiency of collecting monitoring parameters of the target network, and further improving the efficiency of network monitoring and troubleshooting.

[0132] In one embodiment, a monitoring parameter set determination system is provided. Figure 5As shown, the system includes a monitoring parameters effect analysis module (Monitoring Parameters Effect Analysis Module, MPEAM) 502, a monitoring parameters relationship analysis module (Monitoring Parameters Relationship Analysis Module, MPRAM) 504, and a monitoring parameters selection and aggregation module (Monitoring Parameters Selection and Aggregation Module, MPSAM) 506. Among them, the monitoring parameters effect analysis module 502 is used to determine the monitoring effect when the current monitoring parameter set is used to monitor the network status of the target network, and when the monitoring effect does not meet the preset requirements, the current monitoring parameter set is sent to the monitoring parameter relationship analysis module 504. The monitoring parameter relationship analysis module 504 is used to determine the association relationship between each monitoring parameter in the current monitoring parameter set, and send the association relationship between each monitoring parameter to the monitoring parameter selection and aggregation module 506. The monitoring parameter selection and aggregation module 506 is used to generate a new monitoring parameter set based on the association relationship between each monitoring parameter, and send the new monitoring parameter set to the target network, so that the target network performs network status monitoring based on the new monitoring parameter set.

[0133] In the embodiment of the present application, the monitoring parameter set determination system can simultaneously perform monitoring effect analysis on the current monitoring parameter set of multiple networks. For any target network, the target network can simultaneously generate multiple monitoring effect parameters when collecting each monitoring parameter in the current monitoring parameter set. The monitoring parameter effect analysis module 502 in the monitoring parameter set determination system can be used to accept each monitoring effect parameter regularly reported by the target network, and determine the monitoring effect corresponding to the current monitoring parameter set according to each monitoring effect parameter. In the case where the monitoring effect does not meet the preset requirements, the monitoring parameter effect analysis module 502 sends the current monitoring parameter set to the monitoring parameter relationship analysis module 504. The monitoring parameter relationship analysis module 504 analyzes the association relationship of each monitoring parameter in the current monitoring parameter set, and then sends the association relationship of each monitoring parameter to the monitoring parameter selection and aggregation module 506. The monitoring parameter selection and aggregation module 506 determines a new monitoring parameter set according to the association relationship of each monitoring parameter, and sends the new monitoring parameter set to the target network, so that the target network performs network status monitoring based on the new monitoring parameter set. Among them, the specific operations performed by each module can refer to the relevant description of the aforementioned embodiment, and the embodiment of the present application will not be repeated here.

[0134] The monitoring parameter set determination system provided in the embodiment of the present application determines the monitoring effect of the current monitoring parameter set, and when the monitoring effect does not meet the preset requirements, the monitoring parameter set is updated according to the association relationship of each monitoring parameter in the current monitoring parameter set to obtain a new monitoring parameter set, thereby enabling the target network to perform network status monitoring based on the new monitoring parameter set. The embodiment of the present application can determine the monitoring parameter set that is most suitable for network status monitoring of the target network, improve the efficiency of the target network in collecting monitoring parameters, and thereby improve the efficiency of network monitoring and troubleshooting.

[0135] In one embodiment, Figure 6 As shown, the above system also includes a monitoring parameter relationship pattern repository (Monitoring Parameter Relationship Patterns Repository, MPRPR) 508, and the monitoring parameter relationship analysis module 504 is also used to generate tuples based on the association relationship of each monitoring parameter, and store each tuple in the monitoring parameter relationship pattern repository 508. The monitoring parameter relationship pattern repository 508 is also used to generate a monitoring parameter relationship map according to each triple.

[0136] In the present application, refer to Figure 7 As shown, the monitoring parameter relationship analysis module 504 can also generate tuples based on the association relationship between the monitoring parameters, and then store the tuples in the monitoring parameter relationship pattern warehouse 508, so as to facilitate the subsequent search for the association relationship between the monitoring parameters. The monitoring parameter relationship pattern warehouse 508 can also generate a monitoring parameter relationship diagram based on each tuple, so that the association relationship between the monitoring parameters is more intuitive. The monitoring parameter selection and aggregation module 506 can read the tuple from the monitoring parameter relationship pattern warehouse 508 to obtain the association relationship between the monitoring parameters, and then determine a new monitoring parameter set based on the association relationship between the monitoring parameters. The specific operations performed by each module can be found in the relevant description of the aforementioned embodiment, and the embodiments of the present application will not be repeated here.

[0137] The monitoring parameter set determination system provided in the embodiment of the present application generates tuples according to the association relationship between the monitoring parameters, and then stores the tuples in a monitoring parameter relationship pattern warehouse, which can improve the convenience of recording and searching for the association relationship between the monitoring parameters; and by drawing a monitoring parameter relationship diagram based on each tuple, the association relationship between the monitoring parameters can be more intuitively displayed.

[0138] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0139] Based on the same inventive concept, the embodiment of the present application also provides a monitoring parameter set determination device for implementing the monitoring parameter set determination method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the one or more monitoring parameter set determination device embodiments provided below can refer to the limitations of the monitoring parameter set determination method above, and will not be repeated here.

[0140] In one embodiment, Figure 8 As shown, a monitoring parameter set determination device 800 is provided, comprising: a first determination module 802, a second determination module 804, and a first generation module 806, wherein:

[0141] A first determination module 802 is used to determine the monitoring effect when the current monitoring parameter set is used to monitor the network status of the target network;

[0142] A second determination module 804 is used to determine the association relationship between the monitoring parameters in the current monitoring parameter set when the monitoring effect does not meet the preset requirements;

[0143] The first generating module 806 is used to generate a new monitoring parameter set based on the association relationship between the monitoring parameters, and send the new monitoring parameter set to the target network, so that the target network performs network status monitoring based on the new monitoring parameter set.

[0144] The monitoring parameter set determination device provided in the embodiment of the present application determines the monitoring effect of the current monitoring parameter set, and when the monitoring effect does not meet the preset requirements, updates the monitoring parameter set according to the association relationship of each monitoring parameter in the current monitoring parameter set to obtain a new monitoring parameter set, thereby enabling the target network to perform network status monitoring based on the new monitoring parameter set. The embodiment of the present application can determine the monitoring parameter set that is most suitable for network status monitoring of the target network, improve the efficiency of the target network in collecting monitoring parameters, and thereby improve the efficiency of network monitoring and troubleshooting.

[0145] In one embodiment, the first determining module 802 is further configured to:

[0146] The monitoring effect of the current monitoring parameter set on the target network is determined according to at least one of the monitoring complexity, the monitoring coverage, and the difference between the monitoring results of the current monitoring parameter set and the previous monitoring parameter set on the target network.

[0147] In one embodiment, the device further comprises:

[0148] The third determination module is used to determine the monitoring complexity according to the number of monitoring tools corresponding to the current monitoring parameter set, and to determine the monitoring coverage according to the number of monitoring parameters corresponding to the current monitoring parameter set.

[0149] In one embodiment, the device further comprises:

[0150] The fourth determination module is used to determine that the monitoring effect does not meet the preset requirement when the monitoring effect is lower than the monitoring effect threshold.

[0151] In one embodiment, the second determining module 804 is further configured to:

[0152] By using a data mining method, the correlation relationship between the monitoring parameters in the current monitoring parameter set is determined.

[0153] In one embodiment, the device further comprises:

[0154] A second generating module, used for generating a tuple based on the association relationship of each of the monitoring parameters;

[0155] The storage module is used to store each of the tuples in a monitoring parameter relationship model warehouse.

[0156] In one embodiment, the device further comprises:

[0157] The third generating module is used to generate a monitoring parameter relationship graph according to each tuple in the monitoring parameter relationship pattern warehouse.

[0158] In one embodiment, the tuple consists of two monitoring parameters that are associated with each other, and the associated relationship between the two monitoring parameters.

[0159] In one embodiment, the generating module 806 is further configured to:

[0160] For any of the monitoring parameters, determining associated monitoring parameters that have a direct association relationship and an indirect association relationship with the monitoring parameter, and determining a target monitoring parameter from the monitoring parameter and each of the associated monitoring parameters;

[0161] Each of the target monitoring parameters is added to the new monitoring parameter set.

[0162] In one embodiment, the device further comprises:

[0163] The processing module is used to use the new monitoring parameter set as the current monitoring parameter set and jump to the step of determining the monitoring effect when the current monitoring parameter set is used to monitor the network status of the target network until the monitoring effect meets the preset requirements.

[0164] Each module in the above-mentioned monitoring parameter set determination device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0165] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Fig. 9 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for determining a monitoring parameter set is implemented.

[0166] Those skilled in the art will understand that Fig. 9 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0167] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0168] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0169] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0170] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0171] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0172] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0173] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for determining a monitoring parameter set, characterized in that: The method comprises: Determine the monitoring effect when the current monitoring parameter set is used to monitor the network status of the target network; When the monitoring effect does not meet the preset requirements, determining the correlation relationship between the monitoring parameters in the current monitoring parameter set; Based on the association relationship between the monitoring parameters, a new monitoring parameter set is generated, and the new monitoring parameter set is sent to the target network, so that the target network performs network status monitoring based on the new monitoring parameter set.

2. The method according to claim 1, characterized in that The determining of the monitoring effect when the current monitoring parameter set is used to monitor the network status of the target network includes: The monitoring effect of the current monitoring parameter set on the target network is determined according to at least one of the monitoring complexity, the monitoring coverage, and the difference between the monitoring results of the current monitoring parameter set and the previous monitoring parameter set on the target network.

3. The method according to claim 2, characterized in that The method further comprises: The monitoring complexity is determined according to the number of monitoring tools corresponding to the current monitoring parameter set, and the monitoring coverage is determined according to the number of monitoring parameters corresponding to the current monitoring parameter set.

4. The method according to claim 1 or 2, characterized in that: The method further comprises: When the monitoring effect is lower than the monitoring effect threshold, it is determined that the monitoring effect does not meet the preset requirement.

5. The method according to claim 1, characterized in that When the monitoring effect does not meet the preset requirement, determining the association relationship between the monitoring parameters in the current monitoring parameter set includes: By using a data mining method, the association relationship between the monitoring parameters in the current monitoring parameter set is determined.

6. The method according to claim 1 or 5, characterized in that: The method further comprises: Generate a tuple based on the association relationship of each of the monitoring parameters; Each of the tuples is stored in a monitoring parameter relational model warehouse.

7. The method according to claim 6, characterized in that The method further comprises: A monitoring parameter relationship graph is generated according to each of the tuples in the monitoring parameter relationship pattern warehouse.

8. The method according to claim 6, characterized in that The tuple consists of the two monitoring parameters that are in an associated relationship, and the associated relationship between the two monitoring parameters.

9. The method according to claim 1, characterized in that: The generating a new monitoring parameter set based on the association relationship of each monitoring parameter includes: For any of the monitoring parameters, determining associated monitoring parameters that have a direct association relationship and an indirect association relationship with the monitoring parameter, and determining a target monitoring parameter from the monitoring parameter and each of the associated monitoring parameters; Each of the target monitoring parameters is added to the new monitoring parameter set.

10. The method according to claim 1, characterized in that After sending the new monitoring parameter set to the target network, the method further includes: The new monitoring parameter set is used as the current monitoring parameter set, and the process proceeds to the step of determining a monitoring effect when the current monitoring parameter set is used to perform network status monitoring on the target network, until the monitoring effect meets the preset requirements.

11. A monitoring parameter set determination system, characterized in that: It includes monitoring parameter effect analysis module, monitoring parameter relationship analysis module and monitoring parameter selection and aggregation module, among which: The monitoring parameter effect analysis module is used to determine the monitoring effect when the current monitoring parameter set is used to monitor the network status of the target network, and if the monitoring effect does not meet the preset requirements, send the current monitoring parameter set to the monitoring parameter relationship analysis module; The monitoring parameter relationship analysis module is used to determine the association relationship between the monitoring parameters in the current monitoring parameter set, and send the association relationship between the monitoring parameters to the monitoring parameter selection and aggregation module; The monitoring parameter selection and aggregation module is used to generate a new monitoring parameter set based on the association relationship between the monitoring parameters, and send the new monitoring parameter set to the target network so that the target network performs network status monitoring based on the new monitoring parameter set.

12. The system according to claim 11, characterized in that The system also includes a monitoring parameter relationship model warehouse, The monitoring parameter relationship analysis module is further used to generate tuples based on the association relationship of each monitoring parameter, and store each tuple in the monitoring parameter relationship model warehouse; The monitoring parameter relationship pattern warehouse is also used to generate a monitoring parameter relationship graph according to each of the tuples.

13. A monitoring parameter set determination device, characterized in that: The device comprises: A first determination module is used to determine the monitoring effect when the current monitoring parameter set is used to monitor the network status of the target network; A second determination module is used to determine the association relationship between the monitoring parameters in the current monitoring parameter set when the monitoring effect does not meet the preset requirements; The first generating module is used to generate a new monitoring parameter set based on the association relationship between the monitoring parameters, and send the new monitoring parameter set to the target network, so that the target network performs network status monitoring based on the new monitoring parameter set.

14. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 10 are implemented.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 10 are implemented.

16. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 10 are implemented.

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