Network probe data checking method, device, equipment, storage medium and product

Abstract

Embodiments of the present application disclose a network detection data verification method, device, equipment, storage medium and product. The method comprises: obtaining a to-be-verified network detection data set and a previous network detection data set corresponding to the to-be-verified network detection data; performing integrity verification on the to-be-verified network detection data set according to the previous network detection data set; when the integrity verification result is that the detection data is complete, performing anomaly verification on each node data subset in the to-be-verified network detection data set according to the previous network detection data set; determining a node data subset with no anomaly in the anomaly verification result as a target node data subset, performing difference verification on each target node data subset according to the previous network detection data set, and determining a difference verification result; and determining a corresponding overall verification result according to the integrity verification result, each anomaly verification result and each difference verification result. The technical solution provided by the embodiments of the present application improves the data verification efficiency and accuracy.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of communication, and in particular to a network probe data verification method and device, equipment, a storage medium and a product. BACKGROUND

[0002] With the rapid construction of multimedia services and the rapid popularization of audio and video communication software, the real-time audio and video field has been greatly promoted on the Internet. For example, in the field of real-time audio and video calls, network quality probe data is the main basis for media distribution. If there is data anomaly or data loss, it will directly affect the selection of the best route.

[0003] Currently, in the process of verifying data files transmitted via a network, the data files are often divided into the smallest granularity for timeliness and integrity verification, or the differences in network events are measured in multiple dimensions. However, for network quality probe data, only a single integrity or difference consideration is still difficult to meet the network quality determination requirements, and the same standard is used for verification of different types and dimensions of data, resulting in low accuracy of the verification result. SUMMARY

[0004] Embodiments of the present application provide a network probe data verification method and device, equipment, a storage medium and a product, which can solve the problem that the existing data verification method is difficult to meet the network quality probe data verification determination requirements and has low accuracy.

[0005] According to an aspect of the present application, a network probe data verification method is provided, which comprises:

[0006] obtaining a to-be-verified network probe data set and a previous network probe data set corresponding to the to-be-verified network probe data;

[0007] performing integrity verification on the to-be-verified network probe data set according to the previous network probe data set;

[0008] when the integrity verification result is that the probe data is complete, performing anomaly verification on each node data subset in the to-be-verified network probe data set according to the previous network probe data set;

[0009] determining a node data subset with no anomaly in the anomaly verification result as a target node data subset, performing difference verification on each target node data subset according to the previous network probe data set, and determining a difference verification result;

[0010] determining an overall verification result corresponding to the to-be-verified network probe data set according to the integrity verification result, each anomaly verification result and each difference verification result.

[0011] According to another aspect of the present application, a network probe data verification device is provided, the device comprising:

[0012] a data set obtaining module configured to obtain a network probe data set to be verified and a previous network probe data set corresponding to the network probe data set to be verified;

[0013] an integrity verification module configured to perform integrity verification on the network probe data set to be verified according to the previous network probe data set;

[0014] an anomaly verification module configured to, when the integrity verification result is that the probe data is complete, perform anomaly verification on each node data subset in the network probe data set to be verified according to the previous network probe data set;

[0015] a difference verification module configured to determine a node data subset with no anomaly in the anomaly verification result as a target node data subset, perform difference verification on each target node data subset according to the previous network probe data set, and determine a difference verification result;

[0016] a verification result determining module configured to determine an overall verification result corresponding to the network probe data set to be verified according to the integrity verification result, each anomaly verification result, and each difference verification result.

[0017] According to another aspect of the present application, a network probe data verification device is provided, the device comprising:

[0018] at least one processor; and

[0019] a memory in communication with the at least one processor; wherein

[0020] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the network probe data verification method of any of the embodiments of the present application.

[0021] According to another aspect of the present application, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program, the computer program being configured to enable a processor to implement the network probe data verification method of any of the embodiments of the present application when executed by the processor.

[0022] According to another aspect of the present application, a computer program product is provided, and the computer program product comprises a computer program, the computer program being configured to implement the network probe data verification method of any of the embodiments of the present application when executed by a processor.

[0023] The network detection data verification scheme provided in the embodiments of the present application comprises the following steps: obtaining a to-be-verified network detection data set and a previous network detection data set corresponding to the to-be-verified network detection data; performing integrity verification on the to-be-verified network detection data set according to the previous network detection data set; when the integrity verification result is that the detection data is complete, performing anomaly verification on each node data subset in the to-be-verified network detection data set according to the previous network detection data set; determining a target node data subset as a node data subset with no anomaly in the anomaly verification result, performing difference verification on each target node data subset according to the previous network detection data set, and determining a difference verification result; and determining an overall verification result corresponding to the to-be-verified network detection data set according to the integrity verification result, each anomaly verification result and each difference verification result. By using the above technical scheme, the to-be-verified network detection data set is sequentially subjected to integrity verification, anomaly verification and difference verification according to the to-be-verified network detection data set and the previous network detection data set corresponding thereto, and each verification is performed on the basis of the successful verification of the previous step, so that the data integrity and data accuracy of the network detection data set used for network quality detection can be fully verified. Meanwhile, the sequential verification is used in the verification process, for example, only the data meeting the integrity verification is subjected to anomaly verification, and only the node data subset with no anomaly in the anomaly verification result is subjected to difference verification, so that the amount of data to be verified is reduced, the accuracy of the overall verification result determined according to the verification results of each step is improved, the efficiency of the verification of the to-be-verified network detection data set is improved, and the determination of the network quality according to the overall verification result is more accurate, thereby ensuring the selection of the best route.

[0024] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0026] Figure 1 A scene architecture diagram of an application scenario to which a network detection data verification method provided in an embodiment of the present application is applied;

[0027] Figure 2 A flowchart of a network detection data verification method provided in an embodiment of the present application;

[0028] Figure 3A flowchart of a network probe data verification method provided by an embodiment of the present application is shown in FIG. 1;

[0029] Figure 4 A flowchart of a network probe data verification method provided by an embodiment of the present application is shown in FIG. 1;

[0030] Figure 5 A flowchart of a network probe data verification method provided by an embodiment of the present application is shown in FIG. 1;

[0031] Figure 6 A flowchart of a network probe data verification method provided by an embodiment of the present application is shown in FIG. 1;

[0032] Figure 7 A flowchart of a network probe data verification method provided by an embodiment of the present application is shown in FIG. 1;

[0033] Figure 8 A flowchart of a network probe data verification method provided by an embodiment of the present application is shown in FIG. 1;

[0034] Figure 9 A flowchart of a network probe data verification method provided by an embodiment of the present application is shown in FIG. 1;

[0035] Figure 10 A flowchart of a network probe data verification method provided by an embodiment of the present application is shown in FIG. 1;

[0036] Figure 11 A flowchart of a network probe data verification method provided by an embodiment of the present application is shown in FIG. 1;

[0037] Figure 12 A flowchart of a network probe data verification method provided by an embodiment of the present application is shown in FIG. 1;

[0038] Figure 13 A flowchart of a network probe data verification method provided by an embodiment of the present application is shown in FIG. 1. DETAILED DESCRIPTION

[0039] In the following, the technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the drawings in the embodiments of the present application, so that those skilled in the art can better understand the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work should fall within the scope of protection of the present application.

[0040] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to the process, method, product or device.

[0041] Figure 1 A scenario architecture diagram of an application scenario to which a network probe data verification method provided by an embodiment of the present application is applicable. Specifically, referring to Figure 1 , the application scenario can include a client 10, a network connection node 11 and a server set 12.

[0042] In the embodiment, the client 10 can be specifically understood as a client that needs to perform real-time audio and video calls in a multimedia service, and a plurality of clients 10 with the same belonging place, user type or network initiation type can access a network through the same network connection node 11 to perform data transmission; the network connection node 11 can be specifically understood as a communication node for accessing a plurality of clients 10 with the same characteristics to perform data transmission with each server 121 in a server set 12 corresponding to each different region; the server set 12 can be specifically understood as a set composed of a plurality of servers 121 located in the same region, and the regions corresponding to different server sets 12 are different, wherein each server 121 can provide the same service for the clients 10 connected thereto via the network connection node 11. The server sets 12 in different regions can be specifically understood as server sets arranged in different geographical location regions, or server sets divided according to actual business needs, and the server sets in the same region have the same characteristics. The division mode of the region is not limited in the embodiment of the present application.

[0043] Figure 2A flowchart of a network probe data verification method provided by the embodiment is shown in the figure. The embodiment can be applied to the case of verifying the integrity and reliability of a network probe data set used for network quality probe. The method can be executed by a network probe data verification device, which can be realized in the form of hardware and / or software and can be configured in a network probe data verification apparatus. As shown in Figure 2 The method comprises the following steps.

[0044] In step 101, a network probe data set to be verified and a previous network probe data set corresponding to the network probe data to be verified are obtained.

[0045] In the embodiment, the network probe data set to be verified can be understood as a set of multiple packet train map (PTM) probe data collected in a preset time period before the current time and used for determining network communication quality. The previous network probe data set can be understood as a set of multiple PTM probe data collected in the same preset time period and adjacent to the collection time of the network probe data set to be verified. Optionally, the time span of different network probe data sets to be verified can be different, and the time span of the previous network probe data set should be the same as that of the corresponding network probe data set to be verified.

[0046] For example, assuming that the preset time period corresponding to the network probe data set to be verified is one hour, the network probe data set to be verified obtained is a set of multiple PTM probe data collected by one or more network connection nodes in the previous one hour, and the previous network probe data set is a set of multiple PTM probe data collected by one or more network connection nodes in the previous two hours to the previous one hour.

[0047] Specifically, when a user needs real-time audio and video communication, the quality of the network accessed by the user's client needs to be determined to determine the network quality between the client and different routes according to the network probe data set, so as to select the best route to provide real-time audio and video communication service for the user. In order to ensure the correctness of the selection of the best route, the integrity and reliability of the network probe data set used for the judgment of the best route need to be ensured. Therefore, after the network probe data in each preset time period is generated, it needs to be taken as the network probe data set to be verified and compared with the corresponding previous network probe data set to verify the integrity and reliability of the entire network probe data set to be verified.

[0048] In step 102, the integrity of the network probe data set to be verified is verified according to the previous network probe data set.

[0049] In the embodiment, the integrity check can be specifically understood as a check on whether there is a data missing phenomenon in the to-be-checked network probe data set. The data missing can be missing of the entire data or missing of some fields in the data.

[0050] Specifically, the data in the to-be-checked network probe data set is compared with the previous network probe data set in different dimensions, to determine whether the to-be-checked network probe data set contains the same dimensions as the previous network probe data set and has the same data amount in each dimension, thereby realizing the integrity check on the to-be-checked network probe data set.

[0051] Generally, the evaluation on data integrity can be evaluated by the record value and the unique value in data statistics. For the integrity judgment of the network probe data set in the application, the dimensions involved can be more refined and complex. Optionally, the to-be-checked network probe data set in the application can include a plurality of PTM probe data collected by different network connection nodes. For the data collected for the same network connection node, the data generated by communication of a plurality of server sets in different regions that can communicate with the network connection node, and the data collected for the same server set containing a plurality of different network index items, the integrity check on the to-be-checked network probe data set in the embodiment of the application can involve the check on the missing dimensions and the check on whether the statistical indicators in the same dimensions are missing. The evaluation of the integrity check is more complex and accurate.

[0052] In step 103, when the integrity check result is that the probe data is complete, each node data subset in the to-be-checked network probe data set is subjected to an abnormality check according to the previous network probe data set.

[0053] In the embodiment, the node data subset can be specifically understood as a set of to-be-checked network probe data obtained by the same network connection node in the to-be-checked network probe data set. The abnormality check can be specifically understood as a check on whether the data amount and the data value of each node data subset in the data satisfying the integrity check in the to-be-checked network probe data set are within the confidence interval, and whether the statistical data in each node data subset exist.

[0054] Specifically, when the integrity check result is that the probe data is complete, it can be determined that the to-be-checked network probe data set includes at least the same number of dimensions as the previous network probe data set, and the data amount in each dimension is the same, but it cannot be determined whether there is an abnormality in the data amount and the data value of the network connection node dimension in the to-be-checked network probe data set. At this time, at least one node data subset in the to-be-checked network probe data set that needs to be subjected to an abnormality check is determined according to the previous network probe data set, and then the data amount and the data value of the abnormality check are subjected to an abnormality check on the data statistical information in each node data subset.

[0055] In the embodiment of the present application, only the to-be-verified network probe data with the integrity verification result of complete probe data is subjected to the anomaly verification, thereby reducing the amount of data that needs to be subjected to the anomaly verification and improving the efficiency of the network probe data verification. Meanwhile, since the to-be-verified network probe data that passes the integrity verification is subjected to the anomaly verification, the accuracy and the amount of data are evaluated from multiple dimensions on the basis of evaluating the integrity of the network probe data from multiple dimensions, so that the to-be-verified network probe data set that meets the verification condition is more suitable for determining the network quality of a complex network environment.

[0056] In step 104, the node data subset with the anomaly verification result of no anomaly is determined as a target node data subset, and difference verification is performed on each target node data subset according to the previous network probe data set to determine a difference verification result.

[0057] In the embodiment, the difference verification can be specifically understood as comparing the data in the to-be-verified network probe data set that meets both the integrity verification and the anomaly verification with the corresponding data in the previous network probe data set to determine whether there is data that is abnormally large or small, thereby causing significant difference between the previous network probe data set and the to-be-verified network probe data set.

[0058] Specifically, when the anomaly verification result is no anomaly, it can be determined that at least the amount of data and the data statistical information in the node data subset corresponding to the anomaly verification result are not abnormal, at this time, the node data subset corresponding to the anomaly verification result is determined as the target node data subset, and the target node data subset is compared with the corresponding node data subset in the previous network probe data set, and the mean difference between the two is taken as the difference verification result.

[0059] In the embodiment of the present application, after the anomaly verification, only the node data subset with the anomaly verification result of no anomaly is subjected to the difference verification, thereby reducing the amount of data that needs to be subjected to the difference verification and improving the efficiency of the network probe data verification, and meanwhile, the data that may have significant difference is determined from the data that has passed the integrity verification and the anomaly verification through the difference verification, so that the determination of the network quality according to the to-be-verified network probe data set that meets the verification condition is more accurate.

[0060] In step 105, an overall verification result corresponding to the to-be-verified network probe data set is determined according to the integrity verification result, each anomaly verification result and each difference verification result.

[0061] In the embodiment, the overall verification result can be specifically understood as a detection result for reflecting the data integrity, the data accuracy and the data difference in the to-be-verified network probe data set.

[0062] Optionally, the type of data in the to-be-verified network detection data set that has a missing problem is determined according to the integrity verification result, the data in each node data subset in the to-be-verified network detection data set that has a data anomaly is determined according to each anomaly verification result, and the network index item in the to-be-verified network detection data set that has a large difference compared with the previous network detection data set is determined according to each difference verification result. Then, each of the above anomalies is statistically integrated, and the integrated result is determined as the overall verification result corresponding to the to-be-verified network detection data set.

[0063] The network detection data verification scheme provided in the embodiments of the present application includes the following steps: obtaining a to-be-verified network detection data set and a previous network detection data set corresponding to the to-be-verified network detection data; performing integrity verification on the to-be-verified network detection data set according to the previous network detection data set; when the integrity verification result is that the detection data is complete, performing anomaly verification on each node data subset in the to-be-verified network detection data set according to the previous network detection data set; determining a target node data subset as a node data subset that has no anomaly in the anomaly verification result, performing difference verification on each target node data subset according to the previous network detection data set, and determining a difference verification result; and determining an overall verification result corresponding to the to-be-verified network detection data set according to the integrity verification result, each anomaly verification result, and each difference verification result. By using the above technical scheme, the to-be-verified network detection data set is sequentially subjected to integrity verification, anomaly verification, and difference verification according to the to-be-verified network detection data set and the previous network detection data set corresponding thereto, and each verification is performed on the basis of the success of the previous step, so that the data integrity and data accuracy of the network detection data set used for network quality detection can be fully verified. Meanwhile, the verification process uses a sequential verification manner, such as anomaly verification only on data that meets the integrity verification, and difference verification only on a node data subset that has no anomaly in the anomaly verification result, thereby reducing the amount of data to be verified, improving the accuracy of the overall verification result determined according to each step verification result, improving the efficiency of verification of the to-be-verified network detection data set, and making the determination of network quality according to the overall verification result more accurate, thereby ensuring the selection of the best route.

[0064] Figure 3 The flowchart of the network detection data verification method provided in the embodiments of the present application is further optimized on the basis of the above optional technical schemes, and the method of performing integrity verification on the to-be-verified network detection data set in the network connection node dimension, the server set corresponding to each node dimension, and the network index item corresponding to each server set dimension is determined. Specifically, the method can include the following steps:

[0065] In step 201, a to-be-verified network detection data set and a previous network detection data set corresponding to the to-be-verified network detection data are obtained.

[0066] Step 202, obtaining a previous node number corresponding to a previous network probe data set and a current node number corresponding to a network probe data set to be verified.

[0067] In this embodiment, the previous node number can be specifically understood as the number of network connection nodes in the previous network probe data set. The current node number can be specifically understood as the number of network connection nodes in the network probe data set to be verified.

[0068] Specifically, since each network probe data set is composed of PTM probe data collected by multiple different network connection nodes, assuming that different network connection nodes have different node numbers, the number of nodes in different network probe data sets can be determined according to the node numbers. For the previous network probe data set obtained in this application, the corresponding node numbers can be obtained and the determined number of nodes is determined as the first node number. For the network probe data set to be verified obtained in this application, the corresponding node numbers can be obtained and the determined number of nodes is determined as the current node number.

[0069] Step 203, determining whether the previous node number and the current node number are the same, if the same, executing step 205; if different, executing step 204.

[0070] Specifically, in order to ensure the completeness of the network probe data set to be verified, it should be the same as the previous network probe data set corresponding to the previous period in each dimension type and contain the same amount of data, which is reflected in the network connection node dimension. The number of network connection nodes can be used to reflect whether the previous node number and the current node number are the same. If the same, it can be considered that the network probe data set to be verified is complete in the network connection node dimension, and step 205 is executed. If different, it can be considered that the network probe data set to be verified is incomplete in the network connection node dimension, and step 204 is executed.

[0071] Step 204, determining the missing node number according to the previous network probe data set and the network probe data set to be verified, and associating the incomplete probe data and the missing node number to determine the integrity verification result.

[0072] In this embodiment, the missing node number can be specifically understood as the node number corresponding to the missing network connection node in the network probe data set to be verified relative to the previous network probe data set.

[0073] Specifically, since the previous network probe data set and the network probe data set to be verified are two network probe data sets collected continuously, the network connection nodes corresponding to the two network probe data sets should be the same in theory. The node numbers in the previous network probe data set and the node numbers in the network probe data set to be verified are compared one by one. The node numbers that are contained in the previous network probe data set and not contained in the network probe data set to be verified are determined as the missing node numbers of the network probe data set to be verified. Then, the missing node numbers are associated with the information representing the incomplete probe data to determine the integrity verification result.

[0074] In step 205, for each node data subset in the network probe data set to be verified, the current server set number corresponding to the node data subset is obtained.

[0075] In this embodiment, the current server set number can be specifically understood as the number of server sets in different regions that communicate with the node corresponding to a node data subset in the network probe data set to be verified.

[0076] Specifically, since one network connection node can correspond to multiple server sets in different regions, for each node data subset in the network probe data set to be verified, the number of server sets that communicate with the node corresponding to the node data subset is determined, and the number is determined as the current server set number corresponding to the node data subset. The number of current server set numbers determined in the network probe data set to be verified is the same as the number of network connection nodes contained therein.

[0077] In step 206, the previous node data subset corresponding to the node data subset is obtained from the previous network probe data set, and the previous server set number corresponding to the previous node data subset is obtained.

[0078] In this embodiment, the previous node data subset can be specifically understood as the set of previous network probe data obtained by the same network connection node in the previous network probe data set. The previous server set number can be specifically understood as the number of server sets in different regions that communicate with the node corresponding to a previous node data subset in the previous network probe data set.

[0079] Specifically, the previous node data subset corresponding to the node data subset in the network probe data set to be verified is determined from the previous network probe data set. The corresponding node data subset and the previous node data subset can be determined by the node number. The number of server sets that communicate with the node corresponding to the previous node data subset is determined, and the number is determined as the previous server set number corresponding to the previous node data subset.

[0080] Step 207, judging whether the last server set number and the current server set number are same, if same, executing step 209; if different, executing step 208.

[0081] Specifically, in order to ensure the completeness of the to-be-verified network detection data set, the to-be-verified network detection data set should have the same dimension type and contain the same amount of data as the last network detection data set corresponding to the last period. In the dimension of a single network connection node, the number of server sets communicating with the network connection node can be used to reflect the same. Comparing whether the last server set number and the current server set number corresponding to the same network connection node are same, if same, it can be considered that the to-be-verified network detection data set is complete in the dimension of the network connection node, and step 209 is executed; if different, it can be considered that the to-be-verified network detection data set is incomplete in the dimension of the network connection node, and the missing server set needs to be determined, and step 208 is executed.

[0082] Step 208, determining the missing server set according to the last network detection data set and the to-be-verified network detection data set, and determining the first mapping relationship between the missing server set and the corresponding node data subset, and associating the incomplete detection data and the first mapping relationship to determine the completeness verification result.

[0083] In the embodiment, the missing server set can be understood as a network connection node in the to-be-verified network detection data set, and the server set missing relative to the network connection node corresponding to the last network detection data set. The first mapping relationship can be understood as the mapping relationship between the node number of the network connection node with the missing server set. Optionally, different server sets can also have corresponding server set numbers, and the first mapping relationship can include the mapping of node number->missing server set number.

[0084] Specifically, since the last network detection data set and the to-be-verified network detection data set are two network detection data sets collected continuously, the server sets corresponding to each network connection node in the two network detection data sets should be the same in theory. Comparing the server sets corresponding to the same node number in the last network detection data set and the to-be-verified network detection data set, the server set contained in the last network detection data set but not contained in the to-be-verified network detection data set is determined as the missing server set, the mapping relationship between the node number and the missing server set is determined as the first mapping relationship, and the first mapping relationship and the information representing the incomplete detection data are associated to determine the completeness verification result.

[0085] Step 209, for each current server set in the to-be-verified network detection data set, acquiring the current network index item set corresponding to the current server set.

[0086] In the embodiment, the current network indicator item set can be specifically understood as a set of network indicator items of different types included in a server set corresponding to a node data subset in the to-be-verified network probe data set.

[0087] Specifically, since one network connection node can correspond to server sets of multiple different regions, and for one server set, the network probe data collected by the server set includes multiple types of network indicator items, for each node data subset in the to-be-verified network probe data set, a server set expected to correspond to the node communication is determined, and then for each server set, the server set is taken as a current server set, each network indicator item in the network probe data corresponding to the current server set is obtained, and a set of the network indicator items is determined as a current network indicator item set corresponding to the current server set.

[0088] Step 210, determining whether there is a missing network indicator item in the current network indicator item set, if yes, performing step 211; if no, performing step 212.

[0089] Specifically, to ensure the completeness of the to-be-verified network probe data set, the to-be-verified network probe data set should have the same dimensions and contain the same amount of data as the last network probe data set corresponding to the last period, which is reflected in the dimension of a single server set, which can be reflected by the network indicator items in the server set. The types of network indicator items contained in the to-be-verified network probe data set should be the same as those in the last network probe data set, so it can be determined whether there is a missing network indicator item in the current network indicator item set. If there is, it can be considered that the to-be-verified network probe data set is incomplete in the dimension of the server set, and the missing network indicator item needs to be determined. At this time, step 211 is performed; if not, it can be considered that the to-be-verified network probe data set is complete in the dimension of the server set, and step 212 is performed.

[0090] Step 211, determining a second mapping relationship corresponding to the missing network indicator item according to the to-be-verified network probe data set, and determining the completeness of the to-be-verified network probe data set and the second mapping relationship as the integrity verification result.

[0091] The second mapping relationship includes a mapping relationship between the missing network indicator item and the corresponding current server set, and a mapping relationship between the corresponding current server set and the corresponding node data subset.

[0092] In the embodiment, the missing network index item can be understood as a network index item missing in a server set in the network probe data set to be verified, relative to a server set corresponding to the previous network probe data set. The second mapping relationship can be understood as a mapping relationship among the missing network index item, the current server set in which the missing network index item exists, and the network connection node containing the current server set. Optionally, in the case where the number of the current server set corresponding to the missing network index item and the node number of the network connection node in which the current server set is located are known, the second mapping relationship can contain the mapping of node number->current server set number->missing network index item.

[0093] Specifically, since the previous network probe data set and the network probe data set to be verified are two network probe data sets successively collected, the server sets corresponding to each network connection node and the network index items corresponding to each server set contained therein should be the same in theory. When it is determined that there is a missing network index item in the current network index item set corresponding to the current server set, the mapping relationship among the missing network index item, the current server set, and the node data subset corresponding to the current server set is determined as the second mapping relationship, and the second mapping relationship and the information representing the incomplete probe data are associated to determine the integrity verification result.

[0094] Step 212: determining the probe data completeness as the integrity verification result.

[0095] Step 213: performing anomaly verification on each node data subset in the network probe data set to be verified according to the previous network probe data set.

[0096] Step 214: determining the node data subset with no anomaly in the anomaly verification result as a target node data subset, performing difference verification on each target node data subset according to the previous network probe data set, and determining a difference verification result.

[0097] Step 215: determining an overall verification result corresponding to the network probe data set to be verified according to the integrity verification result, each anomaly verification result, and each difference verification result.

[0098] The network detection data verification scheme provided by the embodiments of the present application comprises the following steps: after obtaining a to-be-verified network detection data set and a previous network detection data set, the corresponding current node number in the to-be-verified network detection data set, the corresponding current server set number of each node data subset, and the corresponding current network index item set of each current server set are sequentially compared with the corresponding dimension item in the previous network detection data set, so as to determine a completeness verification result containing missing items and missing item mapping relationships according to the comparison results. By using the above technical scheme, the to-be-verified network detection data set is sequentially verified in the network connection node dimension, the server set dimension corresponding to the node, and the network index item dimension corresponding to each server set. The verification in the next dimension is only performed on the basis of the successful verification in the previous dimension, that is, in the case of failed verification in the network connection node dimension, the subsequent verification in the server set dimension and the network index item dimension is not required, thereby reducing the amount of data to be verified, improving the efficiency of the completeness verification of the to-be-verified network detection data set, and making the completeness verification result that the to-be-verified network detection data set is complete in each dimension. Subsequent abnormality verification and difference verification are performed, so that the determination of the network quality according to the overall verification result is more accurate, and the selection of the best route is ensured.

[0099] Figure 4 The flowchart of the network detection data verification method provided by the embodiments of the present application is further optimized on the basis of the above optional technical solutions, and the method of performing abnormality verification on each node data subset in the to-be-verified network detection data set that meets the completeness condition in the network connection node dimension of the to-be-verified network detection data set is determined. Specifically, the following steps are included:

[0100] Step 301: obtaining a to-be-verified network detection data set and a previous network detection data set corresponding to the to-be-verified network detection data.

[0101] Step 302: performing completeness verification on the to-be-verified network detection data set according to the previous network detection data set.

[0102] Step 303: when the completeness verification result is that the detection data is complete, traversing the node data subset with the same node number in the to-be-verified network detection data set and the previous network detection data set.

[0103] Specifically, when the integrity check result is that the detection data is complete, it can be considered that the network connection nodes in the network detection data set to be checked and the network connection nodes in the previous network detection data set have the same number, but it cannot be determined whether the network connection nodes are the same, and the previous network detection data set as a reference can only perform abnormal check on the network connection nodes in the network detection data set to be checked which are the same as those in the previous network detection data set. In the case of assuming that different network connection nodes have different node numbers, the node data subsets in the network detection data set to be checked which have the same node numbers can be determined as the node data subsets which need to be checked for abnormalities by comparing the node numbers of the network connection nodes corresponding to each node data subset in the network detection data set to be checked and the node numbers of the network connection nodes corresponding to each previous node data subset in the previous network detection data set.

[0104] Step 304, determining whether the node data subset includes call volume statistical information, if yes, executing step 306; if no, executing step 305.

[0105] In the embodiment, the call volume statistical information can be specifically understood as statistical information obtained by counting the call volume generated by one network connection node in communication with one or more servers within a certain time. Generally, the call volume statistical information is a necessary statistical item for judging the communication network quality between one network connection node and other nodes, and therefore when the call volume statistical information is missing in the node data subset, it can be considered that the network connection node corresponding to the node data subset has an abnormality.

[0106] Specifically, in order to ensure the accuracy of the network detection data set to be checked, the amount and type of data recorded in the node data subset corresponding to each network connection node in the network detection data set to be checked are judged, whether the node data subset includes call volume statistical information is determined, whether there is a record abnormality of the type of data in the node data subset is determined, if yes, it can be considered that there is no abnormality related to the call volume statistical information in the node data subset corresponding to the network connection node, and step 306 is executed; if no, it can be considered that the information related to the call volume statistics is missing in the node data subset corresponding to the network connection node, which will affect the judgment of the network quality, and step 305 is executed.

[0107] Step 305, determining that the abnormal check result corresponding to the node data subset is a call volume statistical abnormality.

[0108] Specifically, the abnormal check result corresponding to the node data subset in which the call volume statistical information is missing is determined as a call volume statistical abnormality.

[0109] Step 306, determining whether the node data subset includes detection frequency statistical information, if yes, executing step 308; if no, executing step 307.

[0110] In the embodiment, the detection frequency statistical information can be specifically understood as statistical information obtained by counting the number of times of detecting the network quality between one network connection node and one or more servers within a certain time. In the embodiment of the application, the detection frequency statistical information is used as a statistical item for judging the network quality between one network connection node and other nodes. Therefore, when the detection frequency statistical information is missing in the node data subset, it can be considered that the network connection node corresponding to the node data subset is abnormal, so that the abnormal correction for the network connection node dimension is more accurate.

[0111] Specifically, in order to ensure the accuracy of the network detection data set to be verified, the amount and type of data recorded in the node data subset corresponding to each network connection node in the network detection data set to be verified are judged. Whether the detection frequency statistical information is included in the node data subset is judged to determine whether the number of detections between the network connection node and each server is recorded in the node data subset, that is, whether the record abnormality of the data type exists in the node data subset. If yes, it can be considered that the node data subset corresponding to the network connection node does not have an abnormality related to the detection frequency statistical information, and step 308 is performed. If no, it can be considered that the information related to the detection frequency is missing in the node data subset corresponding to the network connection node, and the number of network quality detections in the node data subset cannot be determined, which affects the judgment of the network quality. At this time, step 307 is performed.

[0112] In step 307, the abnormal verification result of the node data subset is determined as a detection frequency statistical abnormality.

[0113] Specifically, the abnormal verification result of the node data subset in which the detection frequency statistical information is missing is determined as a detection frequency statistical abnormality.

[0114] In step 308, the abnormal verification result of the node data subset is determined according to a preset detection frequency threshold and the detection frequency statistical information.

[0115] In the embodiment, the preset detection frequency threshold can be specifically understood as a value set in advance according to actual conditions, which is used to determine whether the amount of data recorded in the node data subset meets the determination of the network quality in a complex network environment. It should be noted that the preset detection frequency threshold needs to be set according to the data acquisition time span of the node data subset and other actual requirements, and the preset detection frequency threshold corresponding to different data acquisition time spans is different. The specific value of the preset detection frequency threshold is not limited in the embodiment of the application.

[0116] Specifically, in order to ensure the accuracy of the to-be-verified network detection data set, the amount of data and the type of data recorded in the node data subset corresponding to each network connection node in the to-be-verified network detection data set are judged. The number of times of detection of the node data subset in the collection time period is determined according to the detection number statistical information, and then it is determined whether the amount of data recorded in the node data subset is sufficient to support the subsequent judgment of network quality. The number of times is compared with the preset detection number threshold, and the abnormal verification result corresponding to the node data subset is determined according to the comparison result.

[0117] Further, Figure 5 A flowchart for determining the abnormal verification result corresponding to the node data subset according to the preset detection number threshold and the detection number statistical information provided by the embodiment of the present application is provided, which specifically includes the following steps:

[0118] Step 3081, determining the detection number according to the detection number statistical information.

[0119] Specifically, the detection number corresponding to the node data subset for network quality detection is extracted from the detection number statistical information.

[0120] Step 3082, judging whether the detection number is less than the preset detection number threshold. If yes, step 3083 is performed; if no, step 3084 is performed.

[0121] Specifically, whether the detection number is less than the preset detection number threshold is judged to determine whether the amount of data contained in the node data subset is sufficient to support the subsequent determination of network quality. If yes, it is considered that the amount of data in the node data subset is insufficient, and there is an abnormality related to the detection number, and step 3083 is performed at this time. If no, it is considered that the amount of data in the node data subset is sufficient to support the determination of the network quality of the network connection node corresponding to the node data subset, and step 3084 is performed at this time.

[0122] Step 3083, determining the abnormal verification result corresponding to the node data subset as a detection number abnormality.

[0123] Step 3084, determining the abnormal verification result corresponding to the node data subset as no abnormality.

[0124] Step 309, determining the node data subset with no abnormality in the abnormal verification result as a target node data subset, and performing difference verification on each target node data subset according to the previous network detection data set to determine a difference verification result.

[0125] Step 310, determining the overall verification result corresponding to the to-be-verified network detection data set according to the integrity verification result, each abnormal verification result, and each difference verification result.

[0126] The network detection data verification scheme provided by the embodiments of the present application, after obtaining the to-be-verified network detection data set and the previous network detection data set and determining that the to-be-verified network detection data set meets the requirement of integrity, judges the node data subsets with the same node number in the to-be-verified network detection data and the previous network detection data set in turn about the call volume statistical information, the detection frequency statistical information and whether the detection frequency is abnormal. The above technical scheme is adopted to realize the abnormal verification of each node data subset, and the to-be-verified network detection data set is verified abnormally in turn from the call volume statistical dimension, the detection frequency statistical dimension and the data volume corresponding to the detection frequency dimension. The data volume to be verified is reduced only on the basis of the successful verification of the previous dimension, the efficiency of the abnormal verification of the to-be-verified network detection data set is improved, and through the verification of the detection frequency, the data volume in the to-be-verified network detection data set meeting the abnormal verification is sufficient to support the determination of network quality, so that the subsequent determination of network quality according to the overall verification result is more accurate, and the selection of the best route is ensured.

[0127] Figure 6 The flowchart of the network detection data verification method provided by the embodiments of the present application is further optimized on the basis of the above-mentioned optional technical schemes, and the method of performing difference verification on each network index item in each server set in the to-be-verified network detection data set meeting the integrity and no abnormality in the server set dimension of the to-be-verified network detection data set is determined. Specifically, the following steps are included:

[0128] Step 401, obtaining a to-be-verified network detection data set and a previous network detection data set corresponding to the to-be-verified network detection data.

[0129] Step 402, performing integrity verification on the to-be-verified network detection data set according to the previous network detection data set.

[0130] Step 403, when the integrity verification result is that the detection data is complete, performing abnormal verification on each node data subset in the to-be-verified network detection data set according to the previous network detection data set.

[0131] Step 404, determining the node data subset with no abnormality in the abnormal verification result as a target node data subset.

[0132] In the embodiment, the target node data subset can be understood as a node data subset in the to-be-verified network detection data set meeting the integrity verification and containing no abnormal data, which can be subjected to difference verification.

[0133] Step 405, traverse all current server sets corresponding to the target node data subset, and for the same current server set, obtain a current network index item set corresponding to the current server set, and obtain a previous network index item set corresponding to the current network index item set from the previous network detection data set.

[0134] Specifically, for a target node data subset, all current server sets contained therein are traversed. Since a current server set contains multiple network index items, for the same current server set, all network index item sets therein can be determined as a current network index item set, and a previous server set corresponding to the current server set is determined in the previous network detection data set, and all network index item sets in the previous server set are determined as a previous network index item set.

[0135] Step 406, traverse the current network index item data and the previous network index item data of the same index item type in the current network index item set and the previous network index item set, and determine target current network index item data and target previous network index item data satisfying a preset difference check condition.

[0136] In this embodiment, the preset difference check condition can be understood as a judgment condition for determining whether the data quantity of two data is sufficient and whether there is a significant difference between the data before comparison, which is set in advance according to actual conditions.

[0137] Specifically, since there are network index items of different index item types in the current network index item set and the previous network index item set, and the difference check needs to occur between network index items of the same type, the current network index item set and the previous network index item set need to be traversed to extract current network index item data and previous network index item data of the same index item type. Then, according to the preset difference check condition, the data quantity of the current network index item data and the previous network index item data of the same index item type and whether there is a significant difference between them are judged, the current network index item data satisfying the preset difference check condition is determined as target current network index item data, and the previous network index item data corresponding thereto is determined as target previous network index item data.

[0138] Further, Figure 7 A flowchart for determining target current network index item data and target previous network index item data satisfying a preset difference check condition provided by the embodiment of the application, specifically comprising the following steps:

[0139] Step 4061, determine first current network index item data and first previous network index item data with an index item data quantity greater than a preset index item quantity threshold.

[0140] In the embodiment, the preset index item quantity threshold can be understood as a value that is set in advance according to actual conditions and used to determine whether the data quantity of the index item data of the index item type in the current server set meets the value for determining the network quality in the complex network environment. It should be noted that the preset index item quantity threshold needs to be set according to the data collection time span corresponding to the current server set and other actual requirements, and the preset index item quantity threshold corresponding to different data collection time spans is different. The specific value of the preset index item quantity threshold is not limited in the embodiment of the application.

[0141] Specifically, when the quantity of index item data is greater than the preset index item quantity threshold, it can be considered that the data quantity of the network index item data is sufficient to meet the requirement of determining the network quality in the complex network environment, that is, the network index item data with the data quantity has the value and requirement of difference checking. The quantity of index item data corresponding to each current network index item data and the last network index item data is compared with the preset index item quantity threshold, the current network index item data with the quantity of index item data greater than the preset index item quantity threshold is determined as the first current network index item data, and the last network index item data with the quantity of index item data greater than the preset index item quantity threshold is determined as the first last network index item data.

[0142] In the embodiment of the application, by setting the index item quantity threshold, the current network index item data and the last network index item data are first screened, and only the network index item data meeting the data quantity requirement is subjected to difference checking, thereby reducing the quantity of data to be checked and improving the checking efficiency.

[0143] Step 4062, determining the mean value of the first current network index item data as a first current mean value and determining the mean value of the first last network index item data as a first last mean value.

[0144] Step 4063, when the first current mean value is located in the first preset numerical interval and / or the mean value deviation is less than a preset deviation threshold, determining the first current network index item data corresponding to the first current mean value as a target current network index item data and determining the first last network index item data as a target last network index item data.

[0145] The mean value deviation is determined according to the first current mean value and the first last mean value.

[0146] In the embodiment, the first preset numerical interval can be understood as a numerical interval used to determine whether the first current network index item data of the index item type is in the safe range, which is determined according to the index item type and the data collection time span. The mean deviation can be understood as the deviation between the first current mean value and the first previous mean value. Optionally, the mean deviation can be the absolute value of the difference between the first current mean value and the first previous mean value, and the embodiment of the application does not limit this. The preset deviation threshold can be understood as a numerical value used to determine whether there is a significant difference between the first current network index item data and the first previous network index item data, which is set in advance according to actual conditions.

[0147] Specifically, when the first current mean value is in the first preset numerical interval, it can be considered that the value corresponding to the first current network index item data is in the safe range. When the mean deviation is less than the preset deviation threshold, it can be considered that there is no significant difference between the first current network index item data and the first previous network index item data. At least one of the above conditions is met, that is, it can be considered that the difference between the first current network index item data and the first previous network index item data can be checked. At this time, the first current network index item data that meets the above condition is determined as the target current network index item data, and the first previous network index item data that meets the above condition is determined as the target previous network index item data.

[0148] Step 407, determining a target difference value according to the target current network index item data and the target previous network index item data.

[0149] In the embodiment, the target difference value can be understood as a value used to reflect the significant difference between two network index item data.

[0150] Specifically, the target current network index item data and the target previous network index item data are substituted into the difference comparison algorithm to determine the significant difference, and the calculated result is determined as the target difference value. For example, the difference comparison algorithm can be N-sigma algorithm, or other difference comparison algorithms that can achieve the same function, and the embodiment of the application does not limit this.

[0151] Further, Figure 8 A flowchart for determining a target difference value according to a target current network index item data and a target previous network index item data is provided in the embodiment of the application, which specifically includes the following steps:

[0152] Step 4071, determining a current data square sum, a current data statistical number and a second current mean value according to the target current network index data.

[0153] In the embodiment, the current data square sum can be specifically understood as a result of solving square sum of all data in the target current network index data; the current data statistical quantity can be specifically understood as a data quantity in the target current network index data; and the second current mean value can be specifically understood as a mean value of all data in the target current network index data.

[0154] In step 4072, a previous data square sum, a previous data statistical quantity and a second previous mean value are determined according to the target previous network index item data.

[0155] In the embodiment, the previous data square sum can be specifically understood as a result of solving square sum of all data in the target previous network index data; the previous data statistical quantity can be specifically understood as a data quantity in the target previous network index data; and the second previous mean value can be specifically understood as a mean value of all data in the target network index data.

[0156] In step 4073, the target data variance is determined according to the current data square sum, the previous data square sum, the current data statistical quantity and the previous data statistical quantity.

[0157] For example, assuming that the current data square sum can be represented as newSumsq, the previous data square sum can be represented as oldSumsq, the current data statistical quantity can be represented as newCnt, the previous data statistical quantity can be represented as oldCnt, and the target data variance can be represented as stderrDelta, the solving method of the target data variance is shown in the following formula:

[0158] stderrDelta = Coef * Sqrt(Sum(oldSumsq + newSumsq) / Max(oldCnt, newCnt)

[0159] Wherein, Coef is a calculation coefficient.

[0160] In step 4074, a difference between the second current mean value and the second previous mean value is determined as a target data difference value.

[0161] For example, assuming that the second current mean value can be represented as newAvg, and the second previous mean value can be represented as oldAvg, the target data difference value delta can be represented by the following formula:

[0162] delta = newAvg - oldAvg

[0163] In step 4075, the target difference value is determined according to the index item type corresponding to the target current network index item data, and a ratio of the target data difference value to the target data variance.

[0164] Specifically, since the network index items corresponding to different index item types have different calculation requirements for the target difference value, a corresponding calculation method can be selected according to the index item type corresponding to the target current network index item data, and the ratio of the target data difference value to the target data variance is substituted into the corresponding calculation method to obtain the target difference value.

[0165] Taking the above example, assuming that the target difference mean value can be represented as deltaNSigma, for network index item data such as RTT type, the smaller the index expectation is, the better, and the target difference mean value determined therefor can be represented as:

[0166] deltaNSigma = -1 * delta / stderrDelta

[0167] For network index item data such as success rate index type, the larger the index expectation is, the better, and the target difference mean value determined therefor can be represented as:

[0168] deltaNSigma = delta / stderrDelta

[0169] Step 408, determining the difference check result corresponding to the target node data subset according to the target difference values.

[0170] Specifically, the target difference values corresponding to different index types are compared with a pre-set numerical interval to determine whether the difference values are abnormal, and then the network index item types with difference abnormality in the target node data subset are determined, and the network index item data of the network index item types with abnormality are aggregated to obtain the difference check result corresponding to the target node data subset.

[0171] Further, Figure 9 A flowchart for determining the difference check result corresponding to the target node data subset according to the target difference values is provided in the embodiment of the present application, and specifically includes the following steps:

[0172] Step 4081, determining the current network index corresponding to the target difference value not in the second preset numerical interval as an abnormal network index.

[0173] In the embodiment, the second preset numerical interval can be understood as a numerical interval used to determine whether the difference value is in the normal range according to the difference comparison algorithm type. For example, when the difference comparison algorithm is the N-Sigma algorithm, the value of the second preset numerical interval can be [-10, +10], or other numerical value range, which is not limited in the embodiment of the present application.

[0174] Specifically, the target difference value is compared with the second preset numerical interval. If the target difference value is not located in the second preset numerical interval, it is considered that there is a significant difference between the current network indicator item data corresponding to the target difference value and the previous network indicator item data. At this time, the current network indicator item corresponding to the target difference value is determined as the abnormal network indicator item with the abnormality.

[0175] Step 4082, the abnormal network indicator item, and the target difference value, the second current mean value and the second previous mean value corresponding to the abnormal network indicator item, are determined as the difference indicator data.

[0176] Specifically, the indicator item type of the abnormal network indicator item, the target difference value, the second current mean value and the second previous mean value corresponding to the abnormal network indicator item, and the mapping relationship between the current server set and the network connection node corresponding to the abnormal network indicator item are associated and determined as the difference indicator data.

[0177] Step 4083, the set of each difference indicator data is determined as the difference checking result corresponding to the target node data subset.

[0178] Specifically, the set of all abnormal difference indicator data in the target node data subset is determined as the difference checking result corresponding to the target node data subset.

[0179] Step 409, according to the integrity checking result, each abnormal checking result and each difference checking result, the overall checking result corresponding to the network detection data set to be checked is determined.

[0180] Further, Figure 10 A flowchart for determining the overall checking result corresponding to the network detection data set to be checked according to the integrity checking result, each abnormal checking result and each difference checking result is provided for the embodiments of the present application, and specifically includes the following steps:

[0181] Step 4091, according to the integrity checking result, the missing item in the network detection data set to be checked is determined.

[0182] Specifically, according to the integrity checking result, the network connection node, the server set and the network indicator item with missing problems in the network detection data set to be checked are determined, and the above network connection node, server set and network indicator item are determined as the missing item in the network detection data set to be checked.

[0183] Step 4092, according to each abnormal checking result, the abnormal item in each node data subset in the network detection data set to be checked is determined.

[0184] Specifically, according to the abnormality check result, a node data subset with call volume statistical abnormality, probe number statistical abnormality and probe number abnormality in the to-be-checked network probe data set is determined, and the call volume statistical abnormality, the probe number statistical abnormality and the probe number abnormality are determined as abnormal items in the to-be-checked network probe data set.

[0185] Step 4093, determining abnormal indicators in the to-be-checked network probe data set according to the difference check result.

[0186] Specifically, according to the difference check result, a difference indicator data existing in the to-be-checked network probe data set and a network indicator item corresponding to each difference indicator data are determined, the network indicator item with abnormality is determined as an abnormal network indicator item under the server set, and all abnormal network indicator items under the server set in the to-be-checked network probe data set are determined as abnormal indicators.

[0187] Step 4094, integrating the missing items, the abnormal items and the abnormal indicators to determine the overall check result corresponding to the to-be-checked network probe data set.

[0188] Specifically, the missing items, the abnormal items and the abnormal indicators are counted according to different abnormal reasons, and the missing items, the abnormal items and the abnormal indicators are combined with the corresponding number statistics to obtain the overall check result corresponding to the to-be-checked network probe data set.

[0189] Further, after determining all difference check results, the embodiments of the present application can further perform aggregation processing on each data to generate alarm information. For example, the message form of the alarm information can be represented by the following way:

[0190] Abnormal indicator information:

[0191] “Bad metrics in {live report / daily report}, ptm: {type} res: {region_cnt} bad regions: {region_name} with {cc_cnt} bad ccs: {cc_name} -> {node_id} {metric_name} [{nsigma}, {old_avg}, {new_avg}]”;

[0192] Node missing message:

[0193] “Missing node in {live report / daily report}, ptm: {type} res: {missing_nodes}”.

[0194] Wherein, "live report / daily report" is used to represent the data collection time span of the abnormal index in the network probe data set to be verified; "type" is used to represent the abnormal type; "region_cnt" is used to represent the number of server set; "region_name" is used to represent the server set name or server set number; "cc_cnt" is used to represent the number of different countries; "cc_name" is used to represent the country code; "node_id" is used to represent the node number corresponding to the node data subset; "nsigma" is used to represent the target difference value; "old_avg" is used to represent the second last average corresponding to the target difference value; "new_avg" is used to represent the second current average corresponding to the target difference value; "missing_nodes" is used to represent the node number of the missing node.

[0195] The network probe data verification scheme provided by the embodiments of the present application, after obtaining the network probe data set to be verified and the last network probe data set, and determining that each server set in the network probe data set to be verified meets the integrity and abnormality verification requirements, sequentially performs abnormality verification on the network index item set corresponding to each server set. First, according to the preset difference verification condition, the network index item data that can be subjected to difference verification is determined from the current network index item set and the last network index item set. Then, according to the data sum of squares, the data statistical number, the average value and the index item type corresponding to each network index item data, the target difference value is determined. Then, according to the target difference value, the difference verification result corresponding to the target node data subset is determined. By using the above technical scheme, the difference verification of each target node data subset in the network probe data set to be verified is realized, the data amount of the target node data subset subjected to difference verification is ensured, the data amount in the network probe data set to be verified that meets the difference verification is sufficient to support the subsequent determination of network quality, and whether there is significant difference in the network probe data set to be verified compared with the last network probe data set is determined by the difference algorithm. The content of the overall verification result determined according to the integrity verification result, each abnormality verification result and each difference verification result is more complete and accurate, the subsequent determination of network quality according to the overall verification result is more accurate, and the selection of the best route is ensured.

[0196] Figure 11 The flowchart of the network probe data verification method provided by the embodiments of the present application is further optimized on the basis of the above-mentioned optional technical solutions, and the method for ensuring route selection when the data quality requirement of the network probe data set to be verified determined according to the overall verification result does not meet the subsequent network quality determination requirement is clarified. Specifically, the following steps are included:

[0197] Step 501, obtaining a network probe data set to be verified and a previous network probe data set corresponding to the network probe data set to be verified.

[0198] Step 502, performing integrity verification on the network probe data set to be verified according to the previous network probe data set.

[0199] Step 503, when the integrity verification result is that the probe data is complete, performing anomaly verification on each node data subset in the network probe data set to be verified according to the previous network probe data set.

[0200] Step 504, determining a node data subset with no anomaly in the anomaly verification result as a target node data subset, performing difference verification on each target node data subset according to the previous network probe data set, and determining a difference verification result.

[0201] Step 505, determining an overall verification result corresponding to the network probe data set to be verified according to the integrity verification result, each anomaly verification result, and each difference verification result.

[0202] Step 506, judging whether the overall verification result meets a preset data quality requirement, if yes, performing step 507, and if no, performing step 508.

[0203] In the embodiment, the preset data quality requirement can be specifically understood as a condition for judging, according to actual conditions, whether the data completeness and data accuracy in the network probe data set to be verified obtained according to the overall verification result are sufficient to support the detection of network quality. Optionally, the preset data quality requirement can include a quantity threshold set for each missing item, each abnormal item, and each abnormal index. When any missing item, abnormal item, or abnormal index exceeds the corresponding quantity threshold, it can be considered that the network probe data corresponding to the overall verification result does not meet the preset data quality requirement and cannot be used to determine the network quality.

[0204] Specifically, the overall verification result is judged by the preset data quality requirement to determine whether the network probe data set corresponding to the overall verification result can be used for the detection of network quality. When the preset data quality requirement is met, step 507 is performed; if not, the time length corresponding to the network probe data set to be verified corresponding to the overall verification result and the previous network probe data set corresponding to the network probe data set to be verified are determined to replace the network probe data set to be verified, so as to ensure the smooth progress of the detection of network quality, and step 508 is performed.

[0205] Step 507, determining the network probe data set to be verified as a target network probe data set to perform route selection according to the target network probe data set.

[0206] Step 508, judging whether the last network detection data set meets the preset data quality requirement, and determining the target network detection data set according to the judgment result.

[0207] In the embodiment, the to-be-verified network detection data set includes a first time length of to-be-verified network detection data set, and a second time length of to-be-verified network detection data set; wherein the second time length is greater than the first time length. That is, the second time length of to-be-verified network detection data set can be considered to contain the data of the first time length of to-be-verified network detection data set. For example, the first time length can be one hour, and the second time length can be one day, that is, the first time length of to-be-verified network detection data set is an hour-level network detection data set, and the second time length of to-be-verified network detection data set is a day-level network detection data set. Correspondingly, the preset detection number threshold and index item number threshold and other threshold data are different when verifying the to-be-verified network detection data set of different time lengths, and should be adaptively set according to the different time lengths.

[0208] Specifically, when it is determined that the overall verification result of the current to-be-verified network detection data set does not meet the preset data quality requirement, in order to ensure the smooth progress of network quality detection, the data quality of the last network detection data set corresponding to the to-be-verified network detection data set needs to be judged. When the last network detection data set meets the preset data quality requirement, the last network detection data set can be directly determined as the target network detection data set, so as to perform route selection according to the target network detection data set, thereby ensuring the smooth progress of network quality detection.

[0209] When the last network detection data set does not meet the preset data quality requirement, and the to-be-verified network detection data set is the first time length of to-be-verified network detection data set, the first time length of to-be-verified network detection data set corresponding to the first time length of to-be-verified network detection data set can be extracted from the second time length of to-be-verified network detection data set corresponding to the first time length of to-be-verified network detection data set, and the set of to-be-verified network detection data is determined as the target network detection data set, so as to perform route selection according to the target network detection data set, thereby ensuring the smooth progress of network quality detection.

[0210] For example, assuming a first time length of one hour and a second time length of one day, the network probe dataset to be verified for the first time length, which does not currently meet the preset data quality requirements, is a set of network probe data collected between 7 PM and 8 PM on the current day. Then, the network probe dataset to be verified for the second time length, corresponding to this first time length dataset, is determined; that is, the set of network probe data collected between 8 PM on the previous day and 8 PM on the current day. The network probe data collected between 7 PM and 8 PM on the current day is extracted from this dataset, and the extracted set of network probe data is determined as the target network probe dataset. Note that the sampling intervals for the probe data in the first and second time length datasets are different.

[0211] In this embodiment, the previous network probe dataset is used to ensure the data availability of the current network probe dataset to be verified. A longer-duration network probe dataset is used to ensure the data availability of the shorter-duration network probe dataset to be verified. This ensures the availability of network probe data from two different dimensions. If the currently detected network probe dataset to be verified is found to be unavailable, the previous available backup data can be used in a timely manner. If the previous available backup data is unavailable, it can be replaced by backup data of other durations, without affecting the real-time detection of network quality and subsequent route allocation.

[0212] Furthermore, when executing the network probe data verification method provided in any embodiment of this application, the network probe dataset to be verified can first be divided into multiple subsets based on the node numbers corresponding to the data subsets of each node in the dataset to be verified. The aforementioned network probe data verification method is then executed on each subset, and the overall verification results corresponding to each subset are combined to obtain the overall verification result of the entire network probe dataset. This method achieves distributed verification of the network probe data, ensuring the high efficiency of the entire data verification process.

[0213] Figure 12 This is a structural block diagram of a network detection data verification device provided in an embodiment of this application. The device can be implemented by software and / or hardware, and is generally integrated into a network detection data verification equipment. It can be implemented by executing a network detection data verification method. Figure 12 As shown, the device includes: a dataset acquisition module 601, an integrity verification module 602, an anomaly verification module 603, a difference verification module 604, and a verification result determination module 605.

[0214] The data set acquisition module 601 is configured to acquire a network probe data set to be verified and a previous network probe data set corresponding to the network probe data set to be verified.

[0215] The technical scheme of the embodiment of the application reduces the data amount of the network probe data set to be verified that needs to be verified, improves the accuracy of the overall verification result determined according to the verification results of each step, improves the efficiency of verification of the network probe data set to be verified, makes the determination of network quality according to the overall verification result more accurate, and guarantees the selection of the best route.

[0216] Optionally, the integrity verification module 602 comprises:

[0217] The node verification unit is configured to acquire a previous node number corresponding to the previous network probe data set and a current node number corresponding to the network probe data set to be verified; if the previous node number is different from the current node number, the missing node number is determined according to the previous network probe data set and the network probe data set to be verified, and the integrity verification result is determined by associating the incomplete probe data and the missing node number.

[0218] The server verification unit is configured to, if the previous node number is the same as the current node number, acquire, for each node data subset in the network probe data set to be verified, a current server set number corresponding to the node data subset; acquire, from the previous network probe data set, a previous node data subset corresponding to the node data subset and a previous server set number corresponding to the previous node data subset; if the previous server set number is different from the current server set number, determine a missing server set according to the previous network probe data set and the network probe data set to be verified, determine a first mapping relationship between the missing server set and the corresponding node data subset, and determine the integrity verification result by associating the incomplete probe data and the first mapping relationship.

[0219] The network index checking unit is configured to: if the number of each previous server set and the number of each corresponding current server set are the same, acquire, for each current server set in the set of network probe data to be checked, a set of current network index items corresponding to the current server set; if no network index item is missing in each set of current network index items, determine the set of probe data to be complete as the integrity checking result; if a missing network index item exists in each set of current network index items, determine, according to the set of network probe data to be checked, a second mapping relationship corresponding to the missing network index item, and determine, in association with the second mapping relationship, that the set of probe data is incomplete as the integrity checking result; wherein the second mapping relationship includes a mapping relationship between the missing network index item and the corresponding current server set, and a mapping relationship between the corresponding current server set and the corresponding node data subset.

[0220] Optionally, the anomaly checking module 603 includes:

[0221] The call volume checking unit is configured to: traverse, in the set of network probe data to be checked, a node data subset with the same node number as that in the previous set of network probe data; if the node data subset does not include call volume statistical information, determine the anomaly checking result corresponding to the node data subset as a call volume statistical anomaly.

[0222] The probe statistical checking unit is configured to: if the node data subset includes the call volume statistical information and does not include probe frequency statistical information, determine the anomaly checking result corresponding to the node data subset as a probe frequency statistical anomaly.

[0223] The probe frequency checking unit is configured to: if the node data subset includes both the call volume statistical information and the probe frequency statistical information, determine, according to a preset probe frequency threshold and the probe frequency statistical information, the anomaly checking result corresponding to the node data subset.

[0224] Optionally, the probe frequency checking unit is specifically configured to:

[0225] determine the probe frequency according to the probe frequency statistical information;

[0226] if the probe frequency is greater than or equal to the preset probe frequency threshold, determine the anomaly checking result corresponding to the node data subset as no anomaly;

[0227] if the probe frequency is less than the preset probe frequency threshold, determine the anomaly checking result corresponding to the node data subset as a probe frequency anomaly.

[0228] Optionally, the difference checking module 604 includes:

[0229] The index item set determination unit is configured to traverse all current server sets corresponding to the target node data subset, obtain a current network index item set corresponding to each current server set, and obtain a previous network index item set corresponding to the current network index item set from the previous network detection data set.

[0230] The index item data determination unit is configured to traverse current network index item data and previous network index item data of the same type in the current network index item set and the previous network index item set, and determine target current network index item data and target previous network index item data that satisfy a preset difference check condition.

[0231] The difference value determination unit is configured to determine a target difference value according to the target current network index item data and the target previous network index item data.

[0232] The difference result determination unit is configured to determine a difference check result corresponding to the target node data subset according to the target difference value.

[0233] Optionally, the index item data determination unit is specifically configured to:

[0234] determine first current network index item data and first previous network index item data whose number of index item data is greater than a preset index item quantity threshold value;

[0235] determine a first current mean value of the first current network index item data and a first previous mean value of the first previous network index item data;

[0236] when the first current mean value is located in a first preset numerical interval and / or a mean value deviation is less than a preset deviation threshold value, determine the first current network index item data corresponding to the first current mean value as the target current network index item data, and determine the first previous network index item data as the target previous network index item data, wherein the mean value deviation is determined according to the first current mean value and the first previous mean value.

[0237] Optionally, the difference value determination unit is specifically configured to:

[0238] determine a current data sum of squares, a current data statistical quantity, and a second current mean value according to the target current network index data;

[0239] determine a previous data sum of squares, a previous data statistical quantity, and a second previous mean value according to the target previous network index data;

[0240] determine a target data variance according to the current data sum of squares, the previous data sum of squares, the current data statistical quantity, and the previous data statistical quantity;

[0241] determine a target data difference value as a difference between the second current mean value and the second last mean value;

[0242] determine a target difference value according to a target current network index item data corresponding index item type, and a ratio of the target data difference value and the target data variance.

[0243] Optionally, the difference result determination unit is specifically configured to:

[0244] determine a current network index item corresponding to the target difference value not in the second preset numerical interval as an abnormal network index item;

[0245] determine the abnormal network index item, and the target difference value, the second current mean value and the second last mean value corresponding to the abnormal network index item, as difference index data;

[0246] determine a set of the difference index data as a difference checking result corresponding to the target node data subset.

[0247] Optionally, the checking result determination module 605 includes:

[0248] The missing item determination unit is configured to determine a missing item in the network probe data set to be checked according to the integrity checking result.

[0249] The abnormal item determination unit is configured to determine an abnormal item in each node data subset in the network probe data set to be checked according to each abnormal checking result.

[0250] The abnormal index determination unit is configured to determine an abnormal index in the network probe data set to be checked according to each difference checking result.

[0251] The checking result determination unit is configured to integrate each missing item, each abnormal item and each abnormal index, and determine a whole checking result corresponding to the network probe data set to be checked.

[0252] Further, the network probe data set to be checked includes a first time length network probe data set to be checked, and a second time length network probe data set to be checked; wherein the second time length is greater than the first time length.

[0253] Optionally, the device further includes:

[0254] The target data set determination module is configured to, if the whole checking result meets the preset data quality requirement, determine the network probe data set to be checked as a target network probe data set, and perform route selection according to the target network probe data set; if the whole checking result does not meet the preset data quality requirement, determine whether a last network probe data set meets the preset data quality requirement, and determine the target network probe data set according to the determination result.

[0255] Further, if the set of to-be-verified network probe data is a set of to-be-verified network probe data of a first time length, the target data set determination module is further configured to:

[0256] If the determination result is satisfied, the last set of network probe data is determined as the target set of network probe data; otherwise, a second set of to-be-verified network probe data corresponding to the first set of to-be-verified network probe data of the first time length is determined, and from the second set of to-be-verified network probe data of the second time length, a set of to-be-verified network probe data corresponding to the first set of to-be-verified network probe data of the first time length is extracted, and the set of to-be-verified network probe data is determined as the target set of network probe data.

[0257] The network probe data verification apparatus provided in the embodiments of the present application can perform the network probe data verification method provided in any of the embodiments of the present application, and has the corresponding function modules and beneficial effects of performing the method.

[0258] The embodiments of the present application provide a network probe data verification device, and the network probe data verification device can integrate the network probe data verification apparatus provided in the embodiments of the present application. Figure 13 A structural block diagram of a network probe data verification device provided in the embodiments of the present application is provided. The network probe data verification device 700 includes a processor 701 and a memory 702 connected with the processor 701, wherein the memory 702 stores a computer program executable by the processor 701, and the computer program is executed by the processor 701 to enable the processor 701 to perform the network probe data verification method provided in any of the embodiments of the present application. The number of processors can be one or more. Figure 13 The processor is taken as an example in the embodiment.

[0259] The embodiments of the present application further provide a computer readable storage medium, which stores a computer program, and the computer program is used to enable the processor to perform the network probe data verification method provided in any of the embodiments of the present application when the processor executes the computer program.

[0260] Storage media - any various types of memory devices or storage devices. The term "storage media" is intended to include an installation medium, e.g., CD-ROM, floppy disks, or tape device; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; or a nonvolatile memory such as a flash, magnetic media (e.g., a hard disk or optical storage); registers, or other similar types of memory elements, etc. The memory media can also include other types of storage media and combinations thereof. In addition, the memory media can reside in a first computer system that is connected to a second computer system over a network such as the Internet. The second computer system can provide program instructions to the first computer system for execution. The term "memory media" can include two or more memory media that can reside in different locations, e.g., in different computer systems that are connected over a network. The memory media can store program instructions (e.g., as an installed program) that can be executed by one or more processors.

[0261] The embodiments of the present application further provide a computer program product, which comprises a computer program, and the computer program, when executed by a processor, implements the network probe data verification method provided by the embodiments of the present application.

[0262] The network probe data verification apparatus, device, storage medium and product provided in the above embodiments can execute the network probe data verification method provided by any of the embodiments of the present application, and have the corresponding function modules and beneficial effects of executing the method. The technical details not described in the above embodiments can be referred to the network probe data verification method provided by any of the embodiments of the present application.

[0263] Note that the above are only the preferred embodiments of the present application. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and that various obvious changes, re-adjustments and substitutions can be made by those skilled in the art without departing from the scope of the present application. Therefore, although the present application has been described in detail through the above embodiments, the present application is not limited to the above embodiments, and can include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the claims.

Claims

1. A network probe data verification method, characterized in that, The method comprises the following steps: obtaining a to-be-verified network probe data set and a previous network probe data set corresponding to the to-be-verified network probe data set; performing integrity verification on the to-be-verified network probe data set according to the previous network probe data set; when the integrity verification result is that the probe data is complete, performing anomaly verification on each node data subset in the to-be-verified network probe data set according to the previous network probe data set; determining a node data subset with no anomaly in the anomaly verification result as a target node data subset, performing difference verification on each target node data subset according to the previous network probe data set, and determining a difference verification result; determining an overall verification result corresponding to the to-be-verified network probe data set according to the integrity verification result, each anomaly verification result, and each difference verification result; wherein the overall verification result comprises a data type with missing problems, data with anomalies, and network index items that are different from the previous network probe data set; wherein the integrity verification comprises missing node verification, missing server set verification, and missing network index item verification.

2. The method of claim 1, wherein, The integrity verification on the to-be-verified network probe data set according to the previous network probe data set comprises the following steps: obtaining a previous node number corresponding to the previous network probe data set and a current node number corresponding to the to-be-verified network probe data set; if the previous node number is different from the current node number, determining a missing node number according to the previous network probe data set and the to-be-verified network probe data set, and determining that the probe data is incomplete and the missing node number as the integrity verification result.

3. The method of claim 2, wherein, The integrity verification on the to-be-verified network probe data set according to the previous network probe data set further comprises the following steps: if the previous node number is the same as the current node number, for each node data subset in the to-be-verified network probe data set, obtaining a current server set number corresponding to the node data subset; obtaining a previous node data subset corresponding to the node data subset from the previous network probe data set, and obtaining a previous server set number corresponding to the previous node data subset; if the previous server set number is different from the current server set number, determining a missing server set according to the previous network probe data set and the to-be-verified network probe data set, determining a first mapping relationship between the missing server set and the corresponding node data subset, and determining that the probe data is incomplete and the first mapping relationship as the integrity verification result.

4. The method of claim 3, wherein, The integrity verification on the to-be-verified network probe data set according to the previous network probe data set further comprises the following steps: if each previous server set number is the same as the corresponding current server set number, for each current server set in the to-be-verified network probe data set, obtaining a current network index item set corresponding to the current server set; if there is no missing network index item in each current network index item set, determining that the probe data is complete as the integrity verification result; If there is a missing network indicator item in each of the current network indicator item set, a second mapping relationship corresponding to the missing network indicator item is determined according to the to-be-verified network probe data set, and the second mapping relationship is associated with incomplete probe data to determine a completeness verification result; The second mapping relationship includes a mapping relationship between the missing network indicator item and a corresponding current server set, and a mapping relationship between the corresponding current server set and a corresponding node data subset.

5. The method of claim 1, wherein, The anomaly verification of each node data subset in the to-be-verified network probe data set according to the last network probe data set includes: Traverse the node data subset in the to-be-verified network probe data set with the same node number as that in the last network probe data set; If the node data subset does not include call volume statistical information, the anomaly verification result corresponding to the node data subset is determined as call volume statistical anomaly; If the node data subset includes call volume statistical information and does not include probe frequency statistical information, the anomaly verification result corresponding to the node data subset is determined as probe frequency statistical anomaly; If the node data subset includes both call volume statistical information and probe frequency statistical information, the anomaly verification result corresponding to the node data subset is determined according to a preset probe frequency threshold and the probe frequency statistical information.

6. The method of claim 5, wherein, The anomaly verification result corresponding to the node data subset is determined according to a preset probe frequency threshold and the probe frequency statistical information, including: Determine the probe frequency according to the probe frequency statistical information; If the probe frequency is greater than or equal to the preset probe frequency threshold, the anomaly verification result corresponding to the node data subset is determined as no anomaly; If the probe frequency is less than the preset probe frequency threshold, the anomaly verification result corresponding to the node data subset is determined as probe frequency anomaly.

7. The method of claim 1, wherein, The difference verification of each target node data subset according to the last network probe data set includes: Traverse all current server sets corresponding to the target node data subset, and for the same current server set, obtain a current network indicator item set corresponding to the current server set, and obtain a last network indicator item set corresponding to the current network indicator item set from the last network probe data set; Traverse the current network indicator item data and the last network indicator item data with the same indicator item type in the current network indicator item set and the last network indicator item set to determine target current network indicator item data and target last network indicator item data satisfying a preset difference verification condition; Determine a target difference value according to the target current network indicator item data and the target last network indicator item data; Determine the difference verification result corresponding to the target node data subset according to each target difference value.

8. The method of claim 7, wherein, The target current network indicator item data and the target last network indicator item data satisfying the preset difference verification condition include: Determine the first current network indicator item data and the first last network indicator item data with a number of indicator item data greater than a preset indicator item quantity threshold; The mean of the first current network indicator data is determined as the first current mean, and the mean of the first previous network indicator data is determined as the first previous mean. When the first current mean is within a first preset value range and / or the mean deviation is less than a preset deviation threshold, the first current network indicator data corresponding to the first current mean is determined as the target current network indicator data, and the first previous network indicator data is determined as the target previous network indicator data, wherein the mean deviation is determined based on the first current mean and the first previous mean.

9. The method of claim 7, wherein, The step of determining the target difference value based on the target's current network indicator data and the target's previous network indicator data includes: Based on the target current network indicator data, determine the current data sum of squares, the current data count, and the second current mean; Based on the target network indicator data, determine the sum of squares of the previous data, the number of statistics of the previous data, and the second previous mean; The target data variance is determined based on the sum of squares of the current data, the sum of squares of the previous data, the number of statistics in the current data, and the number of statistics in the previous data. The difference between the second current mean and the second previous mean is determined as the target data difference. The target difference value is determined based on the type of the target current network indicator data and the ratio of the target data difference to the target data variance.

10. The method of claim 9, wherein, The step of determining the difference verification result corresponding to the target node data subset based on each of the target difference values ​​includes: The current network indicator item corresponding to the target difference value that is not in the second preset value range is identified as an abnormal network indicator item. The abnormal network indicator item, along with the target difference value, the second current mean, and the second previous mean corresponding to the abnormal network indicator item, are determined as difference indicator data. The set of all the aforementioned difference index data is determined as the difference verification result corresponding to the subset of data of the target node.

11. The method of claim 1, wherein, The step of determining the overall verification result corresponding to the network probe dataset to be verified based on the integrity verification result, each of the anomaly verification results, and each of the difference verification results includes: Based on the integrity verification results, determine the missing items in the network probe dataset to be verified; Based on the anomaly verification results, determine the anomalies in each node subset of the network probe dataset to be verified; Based on the results of each difference verification, determine the abnormal indicators in the network probe dataset to be verified; The missing items, abnormal items, and abnormal indicators are integrated to determine the overall verification result corresponding to the network detection dataset to be verified.

12. The method according to any one of claims 1-11, characterized in that, The network probe dataset to be verified includes a network probe dataset of a first time length and a network probe dataset of a second time length; wherein the second time length is greater than the first time length.

13. The method of claim 12, wherein, After determining the overall verification result corresponding to the network probe dataset to be verified, the method further includes: If the overall check result meets the preset data quality requirement, the network probe data set to be checked is determined as a target network probe data set, and route selection is performed according to the target network probe data set; If the overall check result does not meet the preset data quality requirement, it is determined whether the last network probe data set meets the preset data quality requirement, and a target network probe data set is determined according to the determination result.

14. The method of claim 13, wherein, If the network probe data set to be checked is the network probe data set to be checked of the first time length, the target network probe data set is determined according to the determination result, including: If the determination result is that it is met, the last network probe data set is determined as the target network probe data set; Otherwise, a second time length of the network probe data set to be checked corresponding to the network probe data set to be checked of the first time length is determined, and a first time length of the network probe data set to be checked corresponding to the network probe data set to be checked of the first time length is extracted from the second time length of the network probe data set to be checked. The network probe data set to be checked is determined as the target network probe data set.

15. A network probe data verification apparatus, comprising: Including: The data set acquisition module is configured to acquire a network probe data set to be checked and a last network probe data set corresponding to the network probe data to be checked; The integrity check module is configured to perform integrity check on the network probe data set to be checked according to the last network probe data set; The anomaly check module is configured to perform anomaly check on each node data subset in the network probe data set to be checked according to the last network probe data set when the integrity check result is that the probe data is complete; The difference check module is configured to determine a target node data subset as a node data subset with no anomaly according to the anomaly check result, perform difference check on each target node data subset according to the last network probe data set, and determine a difference check result; The check result determination module is configured to determine an overall check result corresponding to the network probe data set to be checked according to the integrity check result, each anomaly check result and each difference check result; The overall check result includes a data type with missing problems, data with data anomalies and network index items different from the last network probe data set. The integrity check includes missing node check, missing server set check and missing network index item check.

16. A network probe data verification apparatus, comprising: The network probe data checking device includes: At least one processor; and The memory is in communication connection with the at least one processor; wherein The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the network probe data checking method in any one of claims 1-14.

17. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is used to enable the processor to implement the network probe data checking method in any one of claims 1-14 when executed.

18. A computer program product, characterised in that, The computer program product comprises a computer program which, when executed by a processor, implements the network probe data verification method according to any one of claims 1-14.

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