Method and device for checking statistical value of counter

Abstract

The embodiment of the invention provides a method and a device for checking a statistical value of a counter. The method comprises the following steps: acquiring a performance data statistical result determined by network element equipment; the performance data statistical result comprises a statistical value of a counter administered by the network element equipment; determining a second counter set with missing statistical results in the performance data statistical results by checking whether the performance data statistical results completely contain the statistical values of the first counter set or not; and determining a third counter set of which the corresponding statistical result missing belongs to non-rationality missing by judging whether the statistical result missing corresponding to the second counter set meets a preset rationality missing rule. According to the method, the problem of abnormal and missing statistical results in the performance data statistical results can be automatically positioned.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a method and device for checking counter statistical values. Background Art

[0002] In wireless communication networks, base stations and core networks of 5G (5th generation mobile communication technology) and 4G (4th generation mobile communication technology) monitor wireless network operations by counting a large number of counters. They analyze the operator's Key Performance Indicator (KPI) indicators based on the statistical results of these counters and report these KPI indicators to the base station's network management platform and third-party platforms. Through these platforms, operators can monitor network users, network speed, and network quality in real time.

[0003] Due to the diverse networking environments and statistical objects of 5G networks, the number of counter groups that need to be reported by base stations has reached 161. The number of counters in each group varies, and can reach over 200. Furthermore, the accuracy of the reported counter values ​​needs to be verified based on the triggering conditions. Currently, manual verification of each scenario is required, which is labor-intensive and error-prone. Summary of the Invention

[0004] The purpose of the embodiments of the present invention is to provide a method and apparatus for verifying counter statistics to automatically locate the problem of abnormal missing statistical results in performance data statistics. The specific technical solution is as follows:

[0005] In a first aspect, an embodiment of the present invention provides a method for verifying a counter statistical value, including:

[0006] Obtaining a performance data statistical result determined by a network element device; the performance data statistical result includes a statistical value of a counter managed by the network element device;

[0007] determining whether a second counter set including missing statistical results exists in the performance data statistical result by checking whether the performance data statistical result completely includes statistical values ​​of the first counter set; the first counter set is predetermined;

[0008] By judging whether the missing statistical results corresponding to the second counter set meet the pre-set rationality missing rules, it is determined that the corresponding missing statistical results belong to the third counter set of irrational missing; the rationality missing rules are used to describe the reasons for the rationality missing of the performance data statistical results and the counters targeted by the reasons.

[0009] Optionally, the method further includes:

[0010] Determining statistical values ​​in the performance data statistical results that are non-abnormal values ​​by judging whether the statistical values ​​included in the performance data statistical results satisfy pre-set rationality rules; wherein the rationality rules include: numerical rationality rules for the values ​​of the statistical values, and / or rationality constraint rules between different statistical values ​​with correlation;

[0011] Based on the statistical values ​​that are non-abnormal values ​​in the performance data statistical results, performance analysis is performed on the network element device.

[0012] Optionally, determining whether the missing statistical results corresponding to the second counter set satisfy a preset rationality missing rule to determine whether the missing statistical results belong to the third counter set of irrational missing includes:

[0013] Determining, based on the attributes of the missing statistical values ​​in the performance data statistical results, the missing scenario to which the statistical results corresponding to the second counter set are missing; a plurality of missing scenarios are predefined, and the rationality missing rule includes a sub-scenario missing rule corresponding to each missing scenario; the attributes of the statistical value include: the counter corresponding to the statistical value, and / or the statistical period corresponding to the statistical value;

[0014] The third counter set is determined by judging whether the missing of the statistical result corresponding to the second counter set satisfies the scenario-specific missing rule corresponding to the missing scenario.

[0015] Optionally, the missing scenarios include: missing of individual periods of individual counters, missing of the entire period, and missing of all periods; the missing of individual periods of individual counters is characterized by: missing statistical values ​​corresponding to some statistical periods of some counters of the network element device within the statistical period; missing of the entire period is characterized by: missing statistical values ​​corresponding to all statistical periods of some counters of the network element device in the statistical period; missing of all periods is characterized by: missing statistical values ​​corresponding to one or more statistical periods of all counters of the network element device, or missing statistical values ​​corresponding to one or more statistical periods of all counters of the base station cell.

[0016] Optionally, the scenario-specific missing rules corresponding to the missing of individual periods of individual counters include one or more of the following: in the cell deactivation scenario, the statistical values ​​of some counters of the network element equipment are missing, the statistical values ​​of counters without statistical objects are missing, the RRU of the base station is not connected or not in place, and the RRU is in a non-energy-saving state, and the statistical value of the RRU transmit power counter is missing; the scenario-specific missing rules corresponding to the missing of the entire period include one or more of the following: the statistical values ​​of counters to be delivered are missing, in the cell deactivation scenario, the statistical values ​​of some counters of the network element equipment are missing, the statistical values ​​of counters without statistical objects are missing, the RRU of the base station is not connected or not in place, and the RRU is in a non-energy-saving state, and the statistical value of the RRU transmit power counter is missing; the scenario-specific missing rules corresponding to the missing of all partial periods include: the base station is in any state of upgrading, resetting, cutover, and hosting.

[0017] Optionally, the numerical rationality rules include: the statistical value is a non-invalid value, and / or the statistical value is within a preset range, and / or the statistical value is an invalid value, and reporting an invalid value for the statistical value meets the preset invalid value reporting conditions.

[0018] Optionally, two statistical values ​​with correlation satisfy the rationality constraint rule, indicating that the two statistical values ​​satisfy the corresponding preset association condition, and the preset association condition is: if the first statistical value is not 0, then the second statistical value is not 0, or, the two statistical values ​​satisfy a specific size relationship.

[0019] Optionally, the method is applied to a network element device, and the method further includes:

[0020] receiving a first performance data reporting task issued by a first network element management device;

[0021] Determining a target statistical parameter based on a first statistical parameter of the first performance data reporting task and a second statistical parameter of the second performance data reporting task; wherein the second performance data reporting task is a performance data reporting task currently running in the network element device;

[0022] Performing statistics on the performance data based on the target statistical parameters to obtain target statistical results;

[0023] generating, based on the target statistical result, a first statistical result that meets the first statistical parameter and a second statistical result that meets the second statistical parameter;

[0024] The first statistical result is reported to the first network element management device, and the second statistical result is reported to the second network element management device that issues the second performance data reporting task.

[0025] Optionally, the first statistical parameter includes a first statistical period and a fourth counter set, the second statistical parameter includes a second statistical period and a fifth counter set, and the target statistical parameter includes a target statistical period and a target counter set; the target statistical period is determined based on the first statistical period and the second statistical period, and the target counter set covers the union of the fourth counter set and the fifth counter set.

[0026] Optionally, also include:

[0027] According to the calculation formula of the performance indicator to be analyzed, various statistical data based on the performance indicator are obtained from the performance data statistical results;

[0028] Determining, based on the statistical data, an indicator value of the performance indicator of each cell of the base station;

[0029] The indicator value is compared with a first quality-poor decision threshold to determine a poor-quality cell among the cells.

[0030] Optionally, determining the index value of the performance index of each cell of the base station according to each item of the statistical data includes:

[0031] Determining, for each cell, an indicator value corresponding to each sub-period within a preset decision period based on the statistical data;

[0032] The comparing the indicator value with the first poor quality decision threshold to determine the poor quality cell among the cells includes:

[0033] For each of the cells, comparing the indicator values ​​corresponding to the cell in each sub-time period with the first poor quality decision threshold, and determining the poor quality sub-time period of the cell within the preset decision time period;

[0034] The number of poor-quality sub-periods corresponding to each of the cells is compared with a second poor-quality decision threshold to determine a poor-quality cell among the cells.

[0035] Optionally, when the calculation formula adopts a fractional form, the quality-poor sub-period corresponding to each cell is determined based on the following method:

[0036] For each of the cells, determining a sub-period in which the indicator value corresponding to the cell within the preset decision period meets the first poor quality decision threshold;

[0037] For each determined sub-period, determine whether the denominator value in the calculation formula corresponding to the performance indicator of the cell in the sub-period is not less than the traffic volume decision threshold. If so, determine the sub-period as a poor quality sub-period.

[0038] In a second aspect, an embodiment of the present invention provides a device for checking a counter statistical value, comprising:

[0039] An acquisition module, configured to acquire performance data statistics results determined by a network element device; the performance data statistics results include statistical values ​​of counters managed by the network element device;

[0040] a first determining module, configured to determine whether a second counter set including missing statistical values ​​exists in the performance data statistical result by verifying whether the performance data statistical result completely includes statistical values ​​of a first counter set; wherein the first counter set is predetermined;

[0041] The second determination module is used to determine whether the missing statistical results corresponding to the second counter set meet the pre-set rationality missing rules, and determine whether the corresponding statistical result missing belongs to the third counter set of irrational missing; the rationality missing rules are used to describe the reasons for the rationality missing of the performance data statistical results and the counters targeted by the reasons.

[0042] In a third aspect, an embodiment of the present invention provides an electronic device, including a memory, a transceiver, and a processor:

[0043] A memory for storing a computer program; a transceiver for transmitting and receiving data under the control of the processor; and a processor for reading the computer program in the memory and performing the following operations:

[0044] Obtaining a performance data statistical result determined by a network element device; the performance data statistical result includes a statistical value of a counter managed by the network element device;

[0045] determining whether a second counter set including missing statistical results exists in the performance data statistical result by checking whether the performance data statistical result completely includes statistical values ​​of the first counter set; the first counter set is predetermined;

[0046] By judging whether the missing statistical results corresponding to the second counter set meet the pre-set rationality missing rules, it is determined that the corresponding missing statistical results belong to the third counter set of irrational missing; the rationality missing rules are used to describe the reasons for the rationality missing of the performance data statistical results and the counters targeted by the reasons.

[0047] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements the above-mentioned method for checking the statistical value of any counter.

[0048] In a fifth aspect, an embodiment of the present invention provides a computer program product, comprising computer instructions, which implement the above-mentioned method for checking the statistical value of any counter when executed by a processor.

[0049] Beneficial effects of the embodiments of the present invention:

[0050] The method and apparatus for verifying counter statistics provided by the embodiments of the present invention predetermine a first set of counters corresponding to the statistical values ​​that a network element device should ideally report. Thus, for performance data statistics obtained by the network element device, this first set of counters can be used to locate data missing from the performance data statistics. Furthermore, the embodiments of the present invention configure rationality loss rules based on the cause of rationality loss in the performance data statistics and the counters targeted by the cause. For data missing from the performance data statistics, the rationality loss rules can be used to effectively filter the rationality loss contained therein, resulting in a third set of counters whose corresponding statistical results are abnormally missing. This allows for targeted, accurate, and automated verification of abnormal missing results that may exist in the performance data statistics. Consequently, relevant personnel do not need to manually verify the contents of the performance data statistics one by one to verify any missing statistical results, reducing the workload of manual verification and making it less prone to errors. Furthermore, this effectively prevents the problem of missing some counter statistical values ​​during manual verification.

[0051] Of course, it is not necessary to achieve all of the advantages described above simultaneously in order to implement any product or method of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other embodiments can also be obtained based on these drawings.

[0053] Figure 1 A schematic diagram of a flow chart of a counter statistical value verification method provided by an embodiment of the present invention;

[0054] Figure 2 A schematic diagram of a process for performing rationality analysis on counter statistics provided by an embodiment of the present invention;

[0055] Figure 3 A schematic diagram of a process for automatically checking counter statistics provided by an embodiment of the present invention;

[0056] Figure 4A flow chart of a conflict handling mechanism for performance data reporting tasks provided by an embodiment of the present invention;

[0057] Figure 5 A schematic diagram of a process for conflict resolution of performance data reporting tasks provided by an embodiment of the present invention;

[0058] Figure 6 A schematic diagram of the process of an automated analysis mechanism for poor-quality cells provided by an embodiment of the present invention;

[0059] Figure 7 A schematic diagram of a process for automatically analyzing performance indicators provided by an embodiment of the present invention;

[0060] Figure 8 A schematic diagram of the structure of a counter statistical value verification device provided by an embodiment of the present invention;

[0061] Figure 9 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0062] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field based on this application are within the scope of protection of the present invention.

[0063] Currently, verification of counters on network element devices primarily focuses on accuracy, without any other verification or analysis, or can only be performed manually. The network element devices here specifically refer to base stations or core networks.

[0064] In actual applications, counter statistics reported by network elements may contain missing values. For example, a network element may fail to report a specific counter value when it should. Therefore, it is necessary to verify these missing values ​​and specifically locate the counters whose causes require investigation. Currently, verifying these missing values ​​requires manual work, but given the large number of counters that network elements must report, manual verification is labor-intensive and error-prone.

[0065] In view of this, an embodiment of the present invention provides a method for verifying counter statistics. By applying this method, it is possible to automatically troubleshoot the problem of missing counter statistics. In actual application, this method can be implemented through a new tool or integrated into a network element device or a corresponding network element management device.

[0066] See also Figure 1 , the method specifically comprises the following steps:

[0067] Step S101: Obtain performance data statistics results determined by a network element device; the performance data statistics results include statistical values ​​of counters managed by the network element device.

[0068] As mentioned earlier, network elements monitor wireless network operations using a large number of counters. In practice, these counters can include various types (e.g., count counters, frequency counters), each of which can be used to collect statistics for a specific statistical object (e.g., number of handover requests, number of successful handovers).

[0069] Specifically, the network element device obtains the statistical values ​​of these counters and generates statistical results based on these statistical values ​​and related information (such as the statistical objects targeted by the statistical values ​​and the counter IDs corresponding to the statistical values). In the embodiment of the present invention, such statistical results are called performance data statistical results.

[0070] Step S102: by checking whether the performance data statistical result completely includes the statistical values ​​of the first counter set, it is determined whether there is a second counter set with missing statistical results in the performance data statistical result.

[0071] The first counter set is predetermined.

[0072] It should be understood that to verify missing results in performance data statistics, it is necessary to refer to the statistical values ​​of the counters that the network element device should ideally report, that is, the range of counters for which the network element device should report statistical values. In this embodiment of the present invention, the range of these counters is referred to as the first counter set.

[0073] In an embodiment of the present invention, for a network element device specifically being a base station, the first counter set may be determined based on the base station version, the cell standard used by the base station, and the networking scenario. Specifically, the cell standard includes TDD (Time Division Duplex) and FDD (Frequency Division Duplex). The networking scenario may be a commercial networking scenario or a satellite networking scenario.

[0074] Specifically, different base station versions implement different counter types, quantities, and scenarios. Therefore, it's necessary to verify the base station version to determine the range of counters actually delivered. In practice, each base station version has a corresponding delivered counter document. Once the base station version is determined, this document can be used to determine the range of delivered counters. Additionally, the base station version can be verified by querying the software version information in the base station configuration file.

[0075] Furthermore, the base station supports different counters for reporting statistical values ​​in different cell standards, and the counters required to report statistical values ​​in different networking scenarios may also be different. Therefore, based on the determination of the base station version, the specific first counter set can be determined in combination with the cell standard and networking scenario. This ensures that the counters in the determined first counter set are the counters whose statistical values ​​should ideally be reported by the base station.

[0076] In addition, for network element devices specifically for the core network, the range of corresponding delivered counters can be determined based on the core network version, network type, and networking scenario of the core network, and the first counter set is determined on this basis. The specific principle is similar to the case where the network element device is a base station and is not described in detail here.

[0077] After determining the first counter set, when obtaining the performance data statistical results determined by the network element device, by comparing the first counter set with the counters corresponding to the statistical values ​​actually included in the performance data statistical results, the second counter set for which statistical results are missing in the performance data statistical results can be determined. Since, in actual applications, the network element device needs to summarize and report the counter statistical values ​​according to a predetermined statistical period, the comparison can be performed according to the statistical period. Specifically, for each statistical period, the counter set corresponding to the statistical values ​​recorded in the performance data statistical results for that statistical period is compared with which counters are missing from the first counter set. Therefore, if a counter in the first counter set is missing a statistical value corresponding to any statistical period in the performance data statistical results, it is considered that the counter is missing in the performance data statistical results. Based on this, the second counter set for which statistical results are missing in the performance data statistical results can be determined.

[0078] In specific implementation, two mechanisms can be used to determine whether statistical results in performance data statistics are missing.

[0079] First, missing values ​​are determined based on the granularity of each counter and each cycle. Specifically, for each counter, the performance data statistics may be missing for all statistical cycles, some statistical cycles, or only some statistical cycles.

[0080] Second, missing values ​​are determined at the granularity of counter groups. Specifically, the counters of network element devices are usually divided into multiple counter groups, each of which contains a certain number of counters. In this case, the performance data statistics can be determined on a per-counter-group basis to determine whether statistical values ​​corresponding to certain counter groups are missing, and to determine which counters in each counter group and for which statistical periods have missing statistical values.

[0081] Step S103: determining whether the statistical result missing corresponding to the second counter set meets a preset rationality missing rule, and determining that the corresponding statistical result missing belongs to the third counter set of irrational missing.

[0082] The rationality loss rule is used to describe the reasons for the rationality loss of performance data statistics and the counters targeted by the reasons.

[0083] In actual applications, not all missing statistical results in performance data statistics indicate that an abnormality exists in the communication system. Those skilled in the art will understand that certain phenomena in the communication system may cause the statistical values ​​of some counters to be irrational. In such cases, even if the statistical values ​​of the corresponding counters are missing, such missing values ​​are considered normal and do not require further processing.

[0084] For example, if a cell is deactivated during some statistical periods, it is normal for some of the cell's counters to be missing statistical values ​​corresponding to those statistical periods. For another example, if a counter has not yet been delivered in a network element device, it is also normal for the statistical values ​​corresponding to that counter to be missing.

[0085] In embodiments of the present invention, such phenomena that can cause rationality loss in performance data statistical results can be considered as causes of statistical loss, and rationality loss rules can be pre-set based on the counters for which statistical values ​​are missing due to these causes. Thus, when it is determined that statistical values ​​are missing in performance data statistical results, rationality loss rules can be used to determine which statistical values ​​are missing rationality.

[0086] Specifically, after determining that there are missing statistical results in the performance data statistics, it is possible to determine whether there is a reasonable reason for the missing statistical value in the communication system based on the counter of the specific missing statistical value. If so, the missing statistical value is considered to be a reasonable missing. Otherwise, it is considered that the missing statistical value may be caused by an abnormal situation. This type of missing is defined as an unreasonable missing, and it is necessary to conduct a specific investigation into the cause of this type of missing. In actual applications, it is possible to determine whether the communication system has the cause described in the reasonable missing rule by querying the status information or related information of the base station.

[0087] As an example, if the statistical value of a counter in some statistical periods is missing in the performance data statistical results, and the deactivation of the cell may cause the normal missing of the statistical value of the counter, then you can query the base station whether the cell is in a deactivated state during the corresponding statistical period (if the verification method of the counter statistical value is integrated in the base station, the base station itself records this information). If so, the missing statistical value of the counter is considered to be a rationality missing.

[0088] After determining the statistical missing results in the performance data statistical results and filtering out the rational missing results contained therein in combination with the rational missing rules, the remaining part is the irrational missing results. On this basis, a third counter set with irrational missing results in the performance data statistical results can be obtained.

[0089] For the determined third counter set, since the missing statistical values ​​of the counters in this set may be caused by an abnormal situation, further analysis and processing of these missing values ​​is required. Therefore, in an embodiment of the present invention, an irrational missing value report can be generated for the determined third counter set and output, or reported to the management platform of the network element device, so that relevant responsible personnel can further analyze the causes of the missing statistics. This irrational missing value report should specifically list the counters in the first counter set and can further list the specific statistical periods for which the statistical values ​​of each counter are missing.

[0090] The method for verifying counter statistics provided by an embodiment of the present invention predetermines a first set of counters corresponding to the statistical values ​​that a network element device should ideally report. Thus, for the performance data statistical results obtained by the network element device, the first set of counters can be combined to locate data missing in the performance data statistical results. Furthermore, the embodiment of the present invention configures rationality missing rules based on the cause of the rationality missing in the performance data statistical results and the counters targeted by the cause. For data missing in the performance data statistical results, the rationality missing rules can be combined to effectively filter the rationality missing contained therein, and a third set of counters for which the corresponding statistical result missing is abnormally missing can be obtained. This allows for targeted, accurate, and automated verification of abnormal missing results that may exist in the performance data statistical results. Consequently, relevant responsible personnel do not need to manually verify the contents of the performance data statistical results one by one to verify the missing statistical results, thereby reducing the workload of manual verification and making it less prone to errors. It can also effectively prevent the problem of missing some counter statistical values ​​in manual verification.

[0091] In one embodiment of the present invention, in order to improve the efficiency of checking for irrational omissions in the statistical results of performance data, the above-mentioned step S103 specifically includes the following sub-steps:

[0092] Step 11: Determine, based on the attributes of the missing statistical values ​​in the performance data statistical results, the missing scenario to which the statistical results corresponding to the second counter set are missing; multiple missing scenarios are predefined, and the rationality missing rule includes a sub-scenario missing rule corresponding to each missing scenario; the attributes of the statistical value include: the counter corresponding to the statistical value, and / or the statistical period corresponding to the statistical value;

[0093] Step 12: Determine a third counter set by judging whether the missing statistical results corresponding to the second counter set meet the scenario-specific missing rules corresponding to the missing scenario.

[0094] Specifically, various reasons existing in the communication system may lead to rationality loss in the performance data statistical results. If a unified configuration of rationality loss rules is performed based on these reasons, then for each loss in the performance data statistical results, it may be necessary to determine whether the loss is a rationality loss based on the reasons listed in the rationality loss rule.

[0095] However, in actual application scenarios, the specific circumstances of missing statistical results caused by different reasons are different. For example, base station upgrades and counters not being delivered within the base station are both reasons that lead to the lack of rationality in the statistical results of performance data. However, base station upgrades will specifically cause all counters of the base station to lose corresponding statistical values, and will not cause only the statistical values ​​of some counters to be lost. The reason of non-delivery of counters is unlikely to cause all counters of the base station to lose corresponding statistical values. Therefore, if the missing situation is specifically the missing statistical values ​​of all counters of the base station, it is necessary to determine whether the cause is a base station upgrade in the communication system, without having to determine whether the corresponding counters have not been delivered in the base station; correspondingly, if the missing situation is specifically the missing statistical values ​​of some counters of the base station, there is no need to determine the cause of the base station upgrade.

[0096] Therefore, in the embodiments of the present invention, different missing statistical results can be set as different missing scenarios, and corresponding sub-scenario missing rules can be configured for each missing scenario. The sub-scenario missing rules corresponding to different missing scenarios can cover different reasonable missing reasons. The specific configuration of missing scenarios and the sub-scenario missing rules corresponding to each missing scenario can be determined according to actual circumstances.

[0097] In one possible implementation, the following three missing scenarios can be set:

[0098] First, individual counters are missing for individual periods, indicating that the statistical values ​​of some counters on the network element device are missing for some statistical periods within the statistical period. A statistical period can be understood as the complete period corresponding to the extracted counter statistical values. Specifically, if the performance data statistics are generated by extracting the statistical values ​​of the counters within the period [t1, t2], then the period [t1, t2] is the statistical period.

[0099] Second, full-cycle missing refers to the missing statistical values ​​of some counters of the network element device corresponding to all statistical cycles in the statistical period.

[0100] Third, some periods are completely missing, which means that the statistical values ​​corresponding to all counters of network element devices in one or more statistical periods are missing, or the statistical values ​​corresponding to all counters of base station cells in one or more statistical periods are missing.

[0101] Correspondingly, the scenario-specific missing rules corresponding to the above three missing scenarios can be specifically shown in Tables 1 to 3:

[0102] Table 1

[0103]

[0104] Among them, the contents listed under "Causes and Judgment Principles" in Table 1 can be understood as the sub-scenario missing rules corresponding to the scenario where individual counters are missing for individual periods. For the second item, the corresponding counter has no statistical object. Specifically, it can be understood that the statistical object targeted by the counter does not exist. For example, if a counter is used to count the load of a CPU (Central Processing Unit) of a network element device, but the network element device has removed the CPU and no longer uses it, then the counter has no statistical object. For the third item, if the RRU is in a non-energy-saving state, the RRU should transmit a signal, that is, the RRU transmit power counter should have a corresponding statistical value. However, if the RRU is not actually connected or not in place, the RRU cannot transmit a signal. In this case, the missing statistical value of the RRU transmit power counter is normal.

[0105] Table 2

[0106]

[0107] It should be understood that cell deactivation, counters with no statistical objects, or RRU disconnection or non-availability may only last for one or a few statistical periods, resulting in missing periods for individual counters. Alternatively, these conditions may persist throughout the entire statistical period, resulting in missing periods for all counters. Therefore, items 2-4 in Table 2 correspond to items 1-3 in Table 1.

[0108] In addition, if the counter has not been actually delivered in the current version of the base station, the statistical value of the counter will be missing for the entire period. This missing is also normal, corresponding to the first item listed in Table 2.

[0109] Table 3

[0110]

[0111] Specifically, if the causes listed in Table 3 are present, then missing values ​​for all counters during the statistical period for which the cause persists is normal. The cause of missing statistical results due to base station hosting can also be further identified, but it can be assumed that such missing values ​​are not caused by counter-related issues and are therefore normal.

[0112] After setting the missing scenarios and the sub-scenario missing rules corresponding to each missing scenario, after determining the missing statistical results in the performance data results, it is possible to determine which specific missing scenario the missing statistical results belong to. Then, based on the sub-scenario missing rules corresponding to this type of missing scenario, the missing statistical results corresponding to the second counter set are analyzed, and it can be determined that the corresponding missing statistical results belong to the third counter set with irrational missing.

[0113] During this process, the specific missing scenarios to which the missing statistical results in the performance data statistical results belong can be determined based on the attributes of the missing statistical values ​​in the performance data statistical results, for example, based on which counters' statistical values ​​are missing and in which statistical periods the statistical values ​​of each counter are missing.

[0114] As an example, if the three missing scenarios and corresponding missing rules for each scenario shown in Tables 1 to 3 are specifically configured, after determining that statistical results are missing in the performance data statistical results, if it is determined that the missing statistical results specifically belong to missing of a portion of the period, then by judging whether there is a "base station upgrade, reset, cutover, or trusteeship" situation, it can be determined that the corresponding missing statistical results belong to the third counter set of irrational missing.

[0115] It can be seen that the embodiment of the present invention distinguishes between multiple missing scenarios based on the different situations in which performance data statistical results may be missing, and specifically configures sub-scenario missing rules corresponding to each missing scenario. Therefore, to address the problem of missing statistical results in performance data statistical results, the specific missing scenario to which the missing statistical results belong can be determined, and combined with the corresponding sub-scenario missing rules, a third counter set for the corresponding missing statistical results is determined as abnormal missing. This ensures that the processing efficiency and targetedness of locating abnormal missing problems in performance data statistical results are higher.

[0116] Furthermore, the actual performance data statistics may contain not only missing data but also some abnormal values. Using these values ​​for performance analysis of network elements may result in inaccurate results. Therefore, it is necessary to analyze the rationality of the statistical values ​​included in the performance data statistics.

[0117] In view of this, the embodiment of the present invention also provides a process for analyzing the rationality of the counter statistics, see Figure 2 , the process specifically includes the following steps:

[0118] Step S201: determining whether the statistical values ​​included in the performance data statistical results satisfy a pre-set rationality rule, and determining the statistical values ​​in the performance data statistical results that are non-abnormal values.

[0119] The rationality rules include: numerical rationality rules for statistical values, and / or rationality constraint rules between different statistical values ​​with correlation.

[0120] In actual application scenarios, each counter statistic refers to a statistical object, and this statistical object has actual physical meaning. Therefore, subject to constraints such as the attributes of the statistical object and the physical rules existing in the communication system, the statistical values ​​included in the performance data statistics must meet certain conditions, assuming the statistical values ​​are correct. In this embodiment of the present invention, rationality rules are configured based on these conditions.

[0121] The rationality rules involved in the embodiment of the present invention may specifically include numerical rationality rules for statistical values ​​and rationality constraint rules between different statistical values ​​with correlation.

[0122] Among them, the numerical rationality rule is specifically for the statistical value of a single counter, and can be set according to factors such as the attributes of the statistical object corresponding to the statistical value. As an example, the statistical value of the number counter must be a natural number as a numerical rationality rule.

[0123] The rationality constraint rules refer to the relationship between several statistical values ​​that are correlated. In actual application scenarios, there are various statistical values ​​that are correlated with each other, and when the statistical values ​​are correct, the related statistical values ​​should satisfy a certain relationship. Therefore, the rationality constraint rules can be set based on this relationship that should exist under ideal circumstances. As an example, the number of switching requests is associated with the number of successful switching, and the number of switching requests should not be less than the number of successful switching. The rationality constraint rules can be set based on this. As another example, if one statistical object is the maximum value of a physical quantity and the other statistical object is the mean value of the physical quantity, the statistical values ​​of the two statistical objects are correlated, and the statistical value corresponding to the one statistical object should not be less than the statistical value corresponding to the other statistical object.

[0124] Therefore, when the rationality rules are set, the statistical values ​​in the performance data statistical results can be checked in combination with the rationality rules to determine non-outliers in the performance data statistical results. For example, if the statistical value of the time counter is set to be a natural number, then when checking the statistical value of a certain time counter, if the statistical value is negative, it can be determined that the statistical value is an outlier; if the statistical value is an integer, if the rationality rules do not contain other conditions for the statistical value, it can be determined that the statistical value is a non-outlier. If the rationality rules also contain other conditions for the statistical value, then the remaining conditions will be used to further determine whether the statistical value is an outlier.

[0125] Step S202: Based on the statistical values ​​that are not abnormal values ​​in the performance data statistical results, a performance analysis is performed on the network element device.

[0126] After determining the statistical values ​​that are not outliers in the performance data statistics, performance analysis of the network element device can be performed based on these statistical values. Specifically, the KPI indicators of the network element device can be calculated based on these statistical values, and the performance of the network element device can be measured by the KPI indicators.

[0127] In an embodiment of the present invention, the statistical values ​​contained in the performance data statistical results will be analyzed in combination with pre-set rationality loss rules to obtain non-abnormal values ​​contained in these statistical values, so that performance analysis of network element equipment can be performed directly based on these non-abnormal values. There is no need to manually check the rationality of the data contained in the performance data statistical results one by one, which reduces the workload of manual verification and is less prone to errors. It can also effectively prevent the problem of missing some counter statistical values ​​in manual verification.

[0128] Moreover, when setting the rationality loss rules, the embodiments of the present invention take into account the validity of the statistical values ​​themselves and the constraints that should be satisfied between statistical values ​​with correlation. Verification of the validity of the statistical values ​​on this basis can ensure that the verification results have high accuracy.

[0129] In one embodiment of the present invention, the numerical rationality rules may include any combination of the following three categories:

[0130] Rule A1: The statistical value is not an invalid value.

[0131] Specifically, if the statistical value of a counter is the maximum value that the counter can count, the statistical value is invalid. For example, if the counter can count 32-bit unsigned numbers, the maximum value of a 32-bit unsigned number is 4294967295. Therefore, if the statistical value is 4294967295, the statistical value is invalid. Otherwise, the statistical value is not invalid.

[0132] Therefore, if a statistical value is not an invalid value, then the statistical value satisfies Rule A1; otherwise, the statistical value does not satisfy Rule A1.

[0133] Rule A2 (also called threshold rule): the statistical value is within a preset range.

[0134] Specifically, a preset range can be set for the corresponding statistical value based on the attributes of each statistical object. For example, the preset range corresponding to the statistical value of a number counter can be set to a natural number range. Thus, if the statistical value of a number counter is a negative number, the value of the statistical value is not within the preset range corresponding to the statistical value.

[0135] Therefore, if the value of a statistical value is within the corresponding preset range, the statistical value satisfies Rule A2; otherwise, the statistical value does not satisfy Rule A2.

[0136] Rule A3 (also referred to as an invalid reporting rule) states that the statistical value is an invalid value, and reporting the invalid value for the statistical value complies with a preset invalid value reporting condition.

[0137] Specifically, in actual applications, when certain preset invalid value reporting conditions are met, the network element device will report invalid values ​​for some counters when reporting performance data statistics. Such invalid value reporting is considered normal reporting. Therefore, in this embodiment of the present invention, rule A3 can be set to address this situation.

[0138] For example, rule A3 can be specifically expressed as follows:

[0139] Table 4

[0140]

[0141] Specifically, when the network element device meets the "reserved 5QI value is the default value of 0", the network element device will report invalid values ​​for statistical objects related to the 5QI value. Therefore, it is normal for the corresponding statistical value in the performance data statistical results to be an invalid value.

[0142] Therefore, for a statistical value that is an invalid value in the performance data statistical result, if it meets the preset invalid value reporting condition, then the statistical value satisfies Rule A3; otherwise, the statistical value does not satisfy Rule A3.

[0143] As can be seen, when setting the numerical rationality rules, the embodiments of the present invention simultaneously consider whether the statistical value itself is invalid and whether it falls within a reasonable numerical range. In the case of invalid statistical values, they also consider whether the invalid statistical value is caused by a reasonable mechanism. The setting of numerical rationality rules is relatively comprehensive, so when the validity of the statistical value itself is verified based on this rule, the accuracy of the verification results can be guaranteed.

[0144] In one embodiment of the present invention, two statistical values ​​having a correlation satisfy a rationality constraint rule, specifically indicating that the two statistical values ​​satisfy a preset correlation condition set for the two statistical values. Depending on the judgment content, two categories of preset correlation conditions can be included: one category is for statistical values ​​with a value of 0, and the other category is for the size relationship between different statistical values. In other words, the rationality constraint rule can also be considered to include the following two categories of content:

[0145] Rule B1 (also known as the equal to 0 rationality rule): If the first statistical value is non-zero, then the second statistical value is non-zero.

[0146] In practical applications, the relationship between two specific statistical values, a and b, can be as follows: if the statistical values ​​are correct and a is known to be non-zero, then b can be deterministically deduced to be non-zero. For example, for the number of handover requests and the number of successful handovers, if the number of successful handovers is known to be non-zero, then the number of handover requests can be deterministically deduced to be non-zero. Therefore, rule B1 can be set based on such patterns found in actual application scenarios.

[0147] Continuing from the previous example, Rule B1 can be understood as follows: "a is not 0" constitutes a sufficient condition for "b is not 0." This is equivalent to "b is 0" constituting a sufficient condition for "a is 0." Therefore, if b is 0 in the performance data statistics, but a is not 0, Rule B1 is not satisfied, and the relationship between the counter statistics a and b is abnormal. In cases where this relationship is abnormal, we can infer that both a and b are abnormal, only a is abnormal, or only b is abnormal, based on the actual characteristics of the statistics a and b.

[0148] Based on the above explanation, we can see that Rule B1 is essentially set based on this logic: although a statistical value of 0 may satisfy Rules A1 and A2, if the statistical values ​​of some counters are 0, there may be a statistical anomaly. Therefore, Rule B1 actually applies to statistical values ​​of 0 in the performance data statistics. If the statistical value of 0 satisfies Rule B1, the statistical value of 0 is considered normal. If the statistical value of 0 does not satisfy Rule B1, it is considered an abnormal statistical value relationship.

[0149] As an example, rule B1 may specifically include the following content:

[0150] Table 5

[0151]

[0152]

[0153] As an example, if rule B1 is configured based on Table 5, then when the statistical value of the process counter in the performance data statistics is 0, its rationality needs to be verified based on the first rule in Table 5. If the statistical value of the corresponding delay statistics counter is 0, rule B1 is satisfied, and it is considered that there is no abnormality in the relationship between the statistical values. If the statistical value of the corresponding delay statistics counter is not 0, rule B1 is not satisfied, and it is considered that there is an abnormality in the relationship between the statistical value of the delay statistics counter and the statistical value of the corresponding process counter. Since the statistical value of the process counter is usually correct, it can be inferred that there is an abnormality in the statistical value of the delay statistics counter.

[0154] The application of rules 2 to 8 in Table 5 is similar to that of rule 1 and is not described in detail here.

[0155] Rule B2 (also called the association rule of counter statistics): two statistics satisfy a specific size relationship.

[0156] In actual application scenarios, two specific statistical values ​​c and d may satisfy a specific relationship in magnitude. For example, if the statistical values ​​are correct, c may be no less than d, or c may be no greater than d. For example, if c1 is the maximum value of a physical quantity and d1 is the mean value of a physical quantity, then c1 is no less than d1. Therefore, rule B2 can be set based on such regularities in actual application scenarios.

[0157] When rule B2 is configured, for two statistical values ​​that have a specific size relationship with each other, the actual size relationship between the two statistical values ​​in the performance data statistical results can be checked according to rule B2. If the actual size relationship is consistent with the specific size relationship defined in rule B2 (for example, in the example in the previous paragraph, c1 in the performance data statistical results is not less than d1), then rule B2 is satisfied, and it is considered that the size relationship between the two statistical values ​​is normal; if the actual size relationship is inconsistent with the specific size relationship defined in rule B2 (for example, in the example in the previous paragraph, c1 in the performance data statistical results is less than d1), then rule B2 is not satisfied, and it is considered that the size relationship between the two statistical values ​​is abnormal. In the case of an abnormal size relationship, it can be inferred that both c1 and d1 are abnormal, or that only c1 is abnormal, or that only d1 is abnormal, based on the actual characteristics of the statistical values ​​c1 and d1.

[0158] As an example, rule B2 may specifically include the following content:

[0159] Table 6

[0160]

[0161]

[0162] As an example, if rule B2 is configured based on Table 6, for the number of switching requests for each scenario and the corresponding number of successful switching for each scenario contained in the performance data statistics, it is necessary to verify the size relationship between these two statistical values ​​based on the first rule in Table 6. If the number of switching requests for each scenario in the performance data statistics is greater than or equal to the number of successful switching for each scenario, rule B2 is satisfied, and there is no abnormality in the size relationship between the two statistical values; if the number of switching requests for each scenario in the performance data statistics is less than the number of successful switching for each scenario, rule B2 is not satisfied, and there is an abnormality in the size relationship between the two statistical values. Since statistics on the number of requests are usually correct, it can be inferred that there is an abnormality in the number of successful switching for each scenario.

[0163] In an embodiment of the present invention, when verifying the relationship between different statistical values ​​that have correlations, if a statistical value is 0, the presence of a statistical anomaly can be determined by determining whether another statistical value related to the statistical value is 0. Alternatively, the presence of a statistical anomaly can be determined based on the size relationship that should exist between different statistical values. This shows that the rationality constraint rule covers a relatively comprehensive range of situations, and thus, when locating statistical anomalies in performance data statistical results based on this rule, the judgment results are highly accurate and efficient.

[0164] Figure 3 The present invention provides a flow chart of the automatic verification of the counter statistics. The following takes the network element device as a base station as an example. Figure 3 Further explanation of the automated verification process. Figure 3 , this process specifically includes the following steps:

[0165] Step S301: extracting performance counter statistics reported by the base station.

[0166] Before performing step S301 , a normal connection communication needs to be established between the base station and the network element management device.

[0167] In this step, the performance statistics reported by the base station are the statistical values ​​of all counters managed by the base station, that is, the statistical values ​​of the counters of all statistical objects of the base station.

[0168] Step S302: Obtain the base station version and the corresponding version delivery counter range.

[0169] When the version is obtained, the range of the delivered counter corresponding to the base station of the version can be obtained.

[0170] Step S303: Acquire the cell standard, ie, the counter range corresponding to the standard.

[0171] Specifically, according to whether the cell standard is FDD or TDD, the range of counters that the performance data statistical results should cover (ie, the first counter set mentioned above) is accurately obtained.

[0172] Step S304: Determine whether the counter is missing, if so, go to step S309, if not, go to step S305.

[0173] Specifically, in combination with the counter range obtained in step S303, it is possible to determine the statistical value that the base station should have reported in the statistical result but actually did not report.

[0174] In this step, missing values ​​in the statistical results may be due to the aforementioned missing values ​​for individual counters in individual periods, missing values ​​for all periods, or missing values ​​for all periods. It should be noted that even if a counter's statistical values ​​are missing for some statistical periods, it may still have reported values ​​for other statistical periods. The rationality of these reported values ​​must still be determined in subsequent steps S305-S308.

[0175] Step S305: Determine whether the counter statistical value is a non-invalid value. If so, proceed to step S306; if not, proceed to step S314.

[0176] See the previous explanation of Rule A1.

[0177] Step S306: Determine whether the counter statistical value meets the threshold rule. If so, proceed to step S307; if not, proceed to step S315.

[0178] See the previous explanation of Rule A2.

[0179] Step S307: Determine whether the counter statistical value satisfies the rationality rule of being equal to 0. If so, proceed to step S308; if not, proceed to step S315.

[0180] See the previous explanation of Rule B1.

[0181] Step S308: Determine whether the statistical value of the counter satisfies the association rule. If so, proceed to step S316; if not, proceed to step S315.

[0182] See the previous explanation of Rule B2.

[0183] Step S309: Determine whether some cycles are completely missing. If so, proceed to step S311; if not, proceed to step S310.

[0184] Step S310: Determine whether the entire cycle is missing, if so, proceed to step S312, if not, proceed to step S313.

[0185] Step S311: Determine whether the partial period all missing rule is satisfied, if so, proceed to step S317, if not, proceed to step S318.

[0186] For the rules of partial and complete missing periods, please refer to Table 3 above.

[0187] Step S312: Determine whether the full cycle missing rule is met. If so, proceed to step S317; if not, proceed to step S318.

[0188] The full-cycle missing rules can be found in Table 2 above.

[0189] Step S313: Determine whether the individual counter individual cycle missing rule is satisfied, if so, proceed to step S317, if not, proceed to step S318.

[0190] For the rules of missing individual cycles of individual counters, please refer to Table 1 above.

[0191] Step S314: Determine whether the counter report meets the invalid reporting rule. If so, proceed to step S306; if not, proceed to step S315.

[0192] See the previous explanation of Rule A3.

[0193] Step S315: It is considered to be an abnormal report and the specific verification results are output.

[0194] Specifically, it can output which counters have abnormal reports and the specific period of abnormal reports.

[0195] Step S316: It is considered to be a normal report.

[0196] Step S317: The missing data is considered normal.

[0197] Step S318: Output the missing counter list.

[0198] As can be seen, based on the above steps S301-S318, it is possible to verify the range and rationality of the counter statistics of base stations of different versions and cell standards, as well as the rationality of the correlation between different statistical values, and determine whether the situation of missing or invalid statistical values ​​is reasonable, thereby completing the automated verification of counter statistical values. This can reduce the workload of manual verification, ensure comprehensive verification content and reduce the risk of errors, and minimize the problem of missing field counters.

[0199] Furthermore, when network elements report performance data statistics to network element management devices, the same network element in a live network may be connected to both the network element platform and the local maintenance tool. In this case, the network element is simultaneously connected to two network element management tools, or two network element management devices. Currently, if two network element management devices are configured to report KPI-related performance data statistics for the network element, the network element can only report performance data to the first connected network element management device. The later connected network element management device will not receive the performance data reported by the network element device. This means that performance file reporting conflicts exist for different network element management devices.

[0200] In the current application scenario, when a network element is connected to both the network element management platform and the local maintenance tool, the network element reports performance files as follows:

[0201] 1. Performance files can only be reported to the first connected NE management device. Performance tasks of the later connected NE management device cannot be reported.

[0202] 2. The network element device cannot distinguish between different network element management devices and only reports according to the latest performance data reporting task.

[0203] Specifically, the aggregation of counter statistics by the network element device is performed by the counter subsystem, and the counter subsystem obtains the counter statistics according to the given statistical parameters. The counter subsystem can be understood as a module within the network element device that aggregates the statistical values ​​of counters within a specific range. Therefore, when there is a running performance data reporting task within the network element device, if the network element device receives a new performance data reporting task, the statistical parameters used by the counter subsystem will be modified based on the new performance data reporting task, and the counter subsystem will subsequently aggregate the counter statistics based on the new statistical parameters, resulting in a conflict between the two performance data reporting tasks.

[0204] In view of this, the embodiment of the present invention also provides a conflict resolution method for performance data reporting tasks, which can be implemented by adding a conflict processing module in the network element device. Figure 4 The conflict resolution process for performance data reporting tasks includes the following steps:

[0205] Step S401: receiving a first performance data reporting task issued by a first network element management device.

[0206] Specifically, after the network element device and the network element management device are normally connected and communicated, the network element device can normally receive the performance data reporting task issued by the network element management device with which it has a communication connection.

[0207] Furthermore, the first performance data reporting task may carry statistical parameters that are required to be applied when instructing the network element device to aggregate counter statistical values.

[0208] Step S402: Determine a target statistical parameter based on a first statistical parameter of a first performance data reporting task and a second statistical parameter of a second performance data reporting task; wherein the second performance data reporting task is a performance data reporting task currently running in a network element device.

[0209] In an embodiment of the present invention, when a network element device receives a performance data reporting task, it can first determine whether the ongoing tasks within itself include an existing performance data reporting task (the embodiment of the present invention refers to it as a second performance data reporting task). If not, there is no conflict between the performance data reporting tasks, and the network element device can perform the performance data reporting task process according to the existing process; if so, before the network element device executes the subsequent performance file reporting, it is necessary to first determine the target statistical parameters to be actually applied based on the first statistical parameters and the second statistical parameters.

[0210] It should be understood that if the first statistical parameter is consistent with the second statistical parameter, then the performance data required to characterize the first performance data reporting task is consistent with the performance data required for the second performance data reporting task and there is no conflict between them. In this case, the target statistical parameter can be maintained as the statistical parameter of the original performance data reporting task (i.e., the second statistical parameter).

[0211] If the first statistical parameter is inconsistent with the second statistical parameter, it indicates that the performance data required for the first performance data reporting task and the performance data required for the second performance data reporting task are inconsistent and conflict with each other. In this case, it is necessary to combine the first statistical parameter and the second statistical parameter to determine the target statistical parameter.

[0212] Specifically, the counter subsystem must ensure that the data it can obtain when aggregating counter statistics based on the target statistical parameters covers both the data required for the first performance data reporting task and the data required for the second performance data reporting task. In other words, if the first statistical parameter indicates that the data required for the first performance data reporting task is specifically set M, and the second statistical parameter indicates that the data required for the second performance data reporting task is specifically set N, and the data that can be obtained when aggregating counter statistics based on the target statistical parameters is represented as set K, then it must be ensured that set K is sufficient to derive both set M and set N.

[0213] Specifically, the statistical parameters carried by the performance data reporting task issued by the network element management device usually include a statistical period and a specific counter set. Therefore, in an embodiment of the present invention, the target statistical period can be determined based on the first statistical period in the first statistical parameter and the second statistical period in the second statistical parameter, and the target counter set can be determined based on the fourth counter set in the first statistical parameter and the fifth counter set in the second statistical parameter to obtain the target statistical parameters.

[0214] In one possible implementation, the smaller value of the first statistical period and the second statistical period can be used as the target statistical period. After obtaining the counter statistical value based on the target statistical period, the statistical value corresponding to the larger statistical period can be determined based on the numerical relationship between the first statistical period and the second statistical period. In other words, in order to ensure that the obtained data can accurately cover the requirements of the first performance data statistical task and the second performance data statistical task, the common divisor of the first statistical period and the second statistical period can be used as the target statistical period. For example, if the first statistical period is 5 minutes and the second statistical period is 15 minutes, 5 minutes can be used as the target statistical period.

[0215] Regarding the target counter set, the union of the fourth counter set and the fifth counter set can be used as the target counter set. For example, if the fourth counter set includes counters with counter IDs 0-19 and the fifth counter set includes counter IDs 20-39, then the target counter set specifically includes counters with counter IDs 0-39.

[0216] Step S403: Perform statistics on performance data based on target statistical parameters to obtain target statistical results.

[0217] After determining the target statistical parameters, the counter subsystem aggregates the counter statistical values ​​based on the target statistical parameters to obtain the target statistical results. Specifically, if the target statistical parameters include a target statistical period and a target counter set, the counter subsystem will obtain the statistical value corresponding to each counter in the target counter set during each statistical period of the data extraction period.

[0218] Step S404: Based on the target statistical result, a first statistical result that meets the first statistical parameter and a second statistical result that meets the second statistical parameter are generated.

[0219] After obtaining the target statistical result, a first statistical result that meets the first statistical parameter and a second statistical result that meets the second statistical parameter can be generated according to the first statistical parameter and the second statistical parameter.

[0220] Specifically, if the first statistical parameter is consistent with the second statistical parameter, the first statistical result and the second statistical result are actually two identical files; if the first statistical parameter is inconsistent with the second statistical parameter, the first statistical result and the second statistical result are two different files.

[0221] Continuing with the previous example, if the counter subsystem uses 5 minutes as the target statistical period and counters with IDs 0-39 as the target counter set, after obtaining the target statistical result, it can generate a statistical result that meets the first statistical parameter based on the statistical values ​​corresponding to counters with IDs 0-19. Furthermore, for each counter with IDs 20-39, by integrating the statistical values ​​corresponding to three 5-minute statistical periods, it can derive the statistical value corresponding to that counter in a single 15-minute statistical period, thereby generating a second statistical result that meets the second statistical parameter.

[0222] Step S405: reporting the first statistical result to the first network element management device, and reporting the second statistical result to the second network element management device that issues the second performance data reporting task.

[0223] After obtaining the first statistical result and the second statistical result, the network element device can report the two statistical results to the corresponding network element management device respectively, so as to achieve conflict resolution between different performance data reporting tasks.

[0224] In an embodiment of the present invention, when a performance data reporting task newly received by a network element device conflicts with an existing performance reporting task within the network element device, the new performance data reporting task will not directly overwrite the existing performance reporting task. Instead, the statistical parameters corresponding to the two performance data reporting tasks will be combined to determine the target statistical parameters, and the performance data will be aggregated based on the target statistical parameters to generate the target statistical results. Subsequently, two statistical results that meet the respective requirements of the two performance data reporting tasks can be generated based on the target statistical results, thereby effectively resolving the conflict problem between the performance data reporting tasks.

[0225] Figure 5 The embodiment of the present invention provides a flow chart of conflict handling for performance data reporting tasks. Figure 5 Further explanation of the conflict handling process. Figure 5 This process can be implemented by a new module in the network element device, including the following steps:

[0226] Step S501: Receive a performance counter reporting task.

[0227] Before step S501 , the network element device needs to establish a normal connection and communication with the network element management device.

[0228] The received task information of the reporting task includes: the network element management device to which the task is to be reported, the counter range, and the statistical period.

[0229] Step S502: Determine whether there is a reporting task currently. If so, proceed to step S503; if not, proceed to step S510.

[0230] The task information of the existing task specifically includes: the network element management device to which the task is to be reported, the counter range, and the statistical period.

[0231] Step S503: Determine whether the statistical period of the new reporting task is consistent with that of the existing reporting task. If so, proceed to step S504; if not, proceed to step S507.

[0232] Step S504: the statistical period of the counter subsystem remains unchanged.

[0233] Remaining unchanged specifically means that the statistical period remains the statistical period indicated by the existing reporting tasks.

[0234] Step S505: Determine whether the counter group of the new reported task is consistent with the counter group of the existing reported task statistics. If so, proceed to step S506; if not, proceed to step S508.

[0235] Step S506: The generated identical performance files are reported to two network element management devices respectively.

[0236] Step S507: the counter subsystem performs statistics according to a small statistical period.

[0237] Alternatively, statistics can be conducted based on the common denominator of the two statistical periods.

[0238] Step S508: The counter subsystem performs statistics according to the complete set of performance task counters of the two network element management devices.

[0239] Step S509: The generated different performance files are reported to two network element management devices respectively.

[0240] Specifically, the two performance files should respectively meet the counter range and statistical period indicated by the corresponding reporting task.

[0241] Step S510: Process according to the original process.

[0242] It means that the processing flow in the prior art can be followed. For details, please refer to the above description.

[0243] It can be seen that by adding a new module inside the network element device, the new module will issue tasks inside the network element device based on the above steps S501-S510 and summarize and report statistical results, which can avoid conflicts between reporting tasks issued by different network element management devices and report statistical results for different reporting tasks at the same time.

[0244] In addition, after obtaining the performance data statistics, in order to implement performance analysis, it is currently necessary to manually sort out and analyze the performance indicators of each base station and each cell, which makes it impossible to quickly analyze the situation of poor quality cells in the network.

[0245] In view of this, the embodiment of the present invention further provides an automated analysis mechanism for poor quality cells, which can be implemented by adding a new tool or integrated into a network element device or a network element management device. Figure 6 , this process specifically includes the following steps:

[0246] Step S601: According to the calculation formula of the performance indicator to be analyzed, various statistical data based on the performance indicator are obtained from the performance data statistical results.

[0247] Specifically, the performance indicators involved in analyzing poor quality cells can generally be divided into access control indicators, VONR (Voice over New Radio) indicators, network quality indicators, and coverage indicators. The specific content of each indicator can refer to the relevant technology. For example, access control indicators can specifically include the following:

[0248] Table 7

[0249]

[0250]

[0251] In addition, each performance indicator to be analyzed has a corresponding calculation formula. Generally speaking, the calculation formula of the performance indicator is in the form of a fraction, with the numerator and denominator corresponding to different counter statistical values.

[0252] For example, for the RRC access success rate indicator, the calculation formula of the indicator can be specifically expressed as follows:

[0253] RRC access success rate = number of successful RRC connection establishments / number of RRC connection establishment requests * 100%

[0254] The number of RRC connection establishment requests can be specifically counted by cause based on the cause value carried in the EstablishmentCause field of the RRC Connection Request sent by the UE (User Equipment) and received by the gNB (next generation Node B). The cause value may be one of the following fields: emergency; highPriorityAccess; mt-Access; mo-Signalling; mo-Data; mo-VoiceCall; mo-VideoCall; mo-SMS; mps-PriorityAccess; mcs-PriorityAccess.

[0255] The number of successful RRC connection establishments can be counted by cause during the RRC connection establishment process, after the base station sends the RRCSetup message and receives the RRCSetupComplete message from the UE. The cause value carried in the EstablishmentCause field is used to calculate the number of successful RRC connection establishments. For more information about the cause value, refer to the description of the number of RRC connection establishment requests.

[0256] Therefore, if you need to analyze the RRC access success rate, you need to query the specific values ​​of the number of successful RRC connection establishments and the number of RRC connection establishment requests in the performance data statistics.

[0257] Step S602: Determine the index value of the performance index of each cell of the base station based on various statistical data.

[0258] For the performance indicator to be analyzed, based on the known calculation formula of the performance indicator, the indicator value of the performance indicator can be obtained by looking up the specific value of the statistical value contained in the calculation formula in the performance data statistical results, and then substituting the specific value back into the calculation formula.

[0259] In an embodiment of the present invention, for a base station that needs to perform performance analysis, it is necessary to obtain the statistical value corresponding to each cell of the base station based on a calculation formula and calculate the index value of the performance index corresponding to the cell, thereby obtaining the index value of each cell in the base station.

[0260] Step S603: Compare the index value with the first quality difference judgment threshold to determine the poor quality cell among the cells.

[0261] For the performance metrics to be analyzed, after obtaining the metric values corresponding to each cell of the base station, compare the metric value corresponding to each cell with the first quality difference judgment threshold, and the quality difference cells in each cell of the base station can be determined.

[0262] Specifically, in combination with the characteristics of each performance metric to be analyzed, a first quality difference judgment threshold for each performance metric to be analyzed can be set respectively for that metric.

[0263] Taking the RRC access success rate as an example, the first quality difference judgment threshold can be set to 95%. In this case, if the metric value of the RRC access success rate corresponding to a certain cell satisfies: 0 < RRC access success rate < 95%, it is considered that the metric value corresponding to this cell satisfies the first quality difference judgment threshold, and this cell can be determined as a quality difference cell.

[0264] After determining the quality difference cells in the base station, the quality difference cell determination result can be output for targeted processing by the relevant responsible personnel. The quality difference cell determination result can include: the cells determined as quality difference cells, which specific performance metrics of each quality difference cell do not meet the standard, the metric values of the performance metrics of each quality difference cell, and other relevant information.

[0265] In the embodiment of the present invention, when analyzing quality difference cells, for the performance metrics to be analyzed, the metric value of the performance metric corresponding to each cell can be calculated by combining the calculation formula of the metric and the performance data statistical results. By comparing the metric value corresponding to each cell with the first quality difference judgment threshold, the quality difference cells can be determined. It can automatically perform analysis and calculation for performance metrics and accurately determine quality difference cells in combination with the first quality difference judgment threshold.

[0266] In an embodiment of the present invention, in order to ensure the accuracy of the quality difference cell determination result, specifically, the quality difference cells included in each cell of the base station can be determined based on the following steps:

[0267] Step 21: According to the statistical data of each item, for each cell, determine the metric values corresponding to each sub-period within the preset judgment period of this cell.

[0268] As described above, the performance data statistical results specifically include the statistical values corresponding to each statistical cycle within the statistical period. Therefore, in the embodiment of the present invention, the size of the sub-period and the size of the corresponding preset judgment period can be set, and taking the sub-period as the granularity, calculate the metric values of the performance metrics corresponding to each cell in each sub-period.

[0269] For example, the sub-period can be set to one day, and the preset decision period can be set to one week. In this case, the statistical value corresponding to each cell of the base station on each day can be calculated based on the performance data statistics. Based on this, the index value of the performance indicator corresponding to each cell on each day can be calculated to obtain the index value of the daily performance indicator of each cell of the base station.

[0270] Step 22: For each cell, compare the indicator value corresponding to each sub-period of the cell with the first poor quality decision threshold to determine the poor quality sub-period of the cell within the preset decision period.

[0271] After obtaining the index value corresponding to each cell of the base station in each sub-time period, for each cell, the index value corresponding to the cell in each sub-time period is compared with the first quality difference judgment threshold to determine the quality difference sub-time period in each sub-time period corresponding to the cell.

[0272] Continuing with the previous example, after obtaining the daily performance indicator values ​​for each cell of the base station, for each cell, the indicator values ​​corresponding to the cell on each day are compared with the first poor quality judgment threshold to determine the poor quality days corresponding to the cell. Taking the RRC access success rate as an example, if the RRC access success rate indicator values ​​for a cell are greater than 95% for 3 days out of 7 days, which does not meet the first poor quality judgment threshold, these 3 days are not poor quality days; if the RRC access success rate indicator values ​​for 4 days are less than 95%, which meets the first poor quality judgment threshold, then these 4 days are determined to be poor quality days.

[0273] Step 23: Compare the number of poor-quality sub-periods corresponding to each cell with the second poor-quality decision threshold to determine the poor-quality cells among the cells.

[0274] It should be understood that if a cell contains a larger number of poor quality sub-periods within a specific time period, it indicates that the cell is more likely to have poor network quality issues. Therefore, if the number of poor quality sub-periods corresponding to a cell is greater than the second quality difference satisfaction threshold, the cell can be determined to be a poor quality cell.

[0275] Continuing with the previous example, if the index value of the RRC access success rate of a cell meets the first poor quality judgment threshold for 4 days out of 7 days and is a poor quality day, and does not meet the first poor quality judgment threshold for 3 days, and the second poor quality judgment threshold is set to 3 days, the number of poor quality days is greater than 3, and the cell is judged to be a poor quality cell.

[0276] In this embodiment of the present invention, for each cell to be analyzed, the performance indicator values ​​corresponding to each sub-period are calculated at a sub-period granularity, and the corresponding poor-quality sub-period for each cell is determined. A cell is determined as a poor-quality cell only if the number of poor-quality sub-periods corresponding to the cell within a preset decision period exceeds a second poor-quality decision threshold. This stricter decision logic for determining a cell as a poor-quality cell avoids misjudgments of poor-quality cells and improves the accuracy of determining a base station's poor-quality cell.

[0277] It should be understood that when calculating performance indicators based on calculation formulas, if the number of statistical values ​​used is insufficient, it may cause the reference value of the calculated performance indicators to be low. If it is directly judged on this basis that a cell has a quality problem in a certain sub-time period, it may subsequently lead to misjudgment of poor quality cells.

[0278] Taking this into consideration, in one embodiment of the present invention, for each cell of the base station, after determining the sub-periods that meet the first poor quality decision threshold in each sub-period corresponding to the cell based on the above step 22, the sub-periods that meet the first poor quality decision threshold are not directly determined as poor quality sub-periods. Instead, the following further processing may be performed:

[0279] For each determined sub-period, determine whether the denominator value in the calculation formula corresponding to the cell performance indicator in the sub-period is not less than the traffic volume decision threshold. If so, determine the sub-period as a poor quality sub-period.

[0280] Specifically, for a base station cell, for a sub-period corresponding to the cell that meets the first poor quality decision threshold, it can be determined whether the denominator value in the calculation formula of the performance indicator corresponding to the sub-period is sufficiently large, that is, whether the denominator value is not less than the preset traffic volume decision threshold. If so, the indicator value calculated for the sub-period is considered to be of reference value, and the sub-period is determined to be a poor quality sub-period. Otherwise, the indicator value calculated for the sub-period is considered to be of no reference value, and the sub-period does not need to be determined as a poor quality sub-period.

[0281] Continuing with the previous example, taking the RRC access success rate as an example, the denominator in the calculation formula for this performance indicator is specifically the number of RRC connection establishment requests. Assuming the traffic volume decision threshold is 100, for a sub-period corresponding to a cell, if the RRC access success rate corresponding to that sub-period is less than 95% and the number of RRC connection establishment requests corresponding to that sub-period is greater than 100, the sub-period can be determined as a poor-quality sub-period. Otherwise, the sub-period does not need to be determined as a poor-quality sub-period.

[0282] In specific applications, a unified traffic volume decision index can be set for various performance indicators, or a corresponding traffic volume decision index can be set for each performance indicator, depending on specific needs.

[0283] In an embodiment of the present invention, for each cell to be analyzed, if the index value corresponding to the cell in a certain sub-period satisfies the first poor quality judgment threshold and it is determined that the cell may have a poor quality problem in the sub-period, a determination will be made as to whether the denominator of the index value in the calculation formula is greater than the traffic volume judgment index. If the judgment result is yes, the index value based on this time is considered to have reference value and the sub-period is determined to be a poor quality sub-period. This can avoid misjudgment of poor quality cells in the subsequent determination of poor quality cells and improve the accuracy of determining the poor quality cells of base stations.

[0284] Figure 7 For a flow chart of automatic analysis of performance indicators provided by an embodiment of the present invention, see Figure 7 , this process specifically includes the following steps:

[0285] Step S701: Input the indicators and statistical formulas to be analyzed.

[0286] Before the above step S701 , the base station and the network element management device need to establish a normal connection communication first.

[0287] Step S702: Obtain performance data of counters related to the statistical formula and calculate indicators.

[0288] Specifically, it is necessary to calculate the daily performance index of each cell of each base station to be analyzed.

[0289] Step S703: Determine whether the index value meets the first poor quality judgment threshold. If so, proceed to step S704; if not, proceed to step S708.

[0290] Step S704: Determine whether the denominator of the daily statistical result that meets the first poor quality judgment threshold is greater than the traffic judgment indicator. If so, proceed to step S705; if not, proceed to step S708.

[0291] Step S705: The number of days of poor quality of the cell of the station is increased by 1.

[0292] Step S706: Determine whether the number of days with poor quality meets the second poor quality judgment threshold. If so, proceed to step S707; if not, proceed to step S708.

[0293] Step S707: Output the poor quality cells, poor quality days and detailed information.

[0294] Step S708: Obtain the index values ​​of other time periods of the cell or other cell index values, and return to step S703.

[0295] Specifically, when the number of days with poor quality corresponding to the current cell is not greater than the traffic volume judgment index, if the corresponding indicators of the cell on other days in the preset judgment period have not been judged, it is still necessary to analyze the corresponding indicators of the cell on other days. If the analysis of the corresponding indicators of the cell on each day has been completed, further analysis can be performed on the indicators of other cells to be analyzed.

[0296] It can be seen that after obtaining the performance data reported by the base station (i.e., the performance data statistical results referred to above), by applying the above steps S701-S708, it is possible to realize automatic analysis of KPI indicators, quickly obtain the situation of poor quality cells in the network, and reduce labor costs and error rates.

[0297] Based on the same inventive concept, the embodiment of the present invention further provides a device for checking the statistical value of a counter, see Figure 8 , the device comprises:

[0298] The acquisition module 801 is configured to acquire a performance data statistical result determined by a network element device; the performance data statistical result includes a statistical value of a counter managed by the network element device;

[0299] A first determining module 802 is configured to determine whether a second counter set is missing from the performance data statistical result by verifying whether the performance data statistical result completely includes statistical values ​​of the first counter set; the first counter set is predetermined;

[0300] The second determination module 803 is used to determine whether the missing statistical results corresponding to the second counter set meet the pre-set rationality missing rules, and determine whether the corresponding statistical result missing belongs to the third counter set of irrational missing; the rationality missing rules are used to describe the reasons for the rationality missing of the performance data statistical results and the counters targeted by the reasons.

[0301] The counter statistical value verification device provided in an embodiment of the present invention predetermines a first counter set corresponding to the statistical values ​​that a network element device should ideally report. Thus, for performance data statistical results obtained by the network element device, this first counter set can be used to locate data missing from the performance data statistical results. Furthermore, the embodiment of the present invention configures rationality loss rules based on the cause of rationality loss in the performance data statistical results and the counters targeted by the cause. For data missing from the performance data statistical results, the rationality loss rules can be used to effectively filter the rationality loss contained therein, thereby obtaining a third counter set whose corresponding statistical results are abnormally missing. This allows for targeted, accurate, and automated verification of abnormal missing results that may exist in the performance data statistical results. This eliminates the need for relevant personnel to manually verify the contents of the performance data statistical results one by one to check for missing statistical results, reducing the workload of manual verification and making it less prone to errors. It also effectively prevents the problem of missing some counter statistical values ​​during manual verification.

[0302] In one embodiment of the present invention, the apparatus further comprises:

[0303] a third determination module, configured to determine statistical values ​​in the performance data statistical results that are non-abnormal values ​​by determining whether the statistical values ​​contained in the performance data statistical results satisfy pre-set rationality rules; wherein the rationality rules include: numerical rationality rules for the values ​​of the statistical values, and / or rationality constraint rules between different statistical values ​​having correlations;

[0304] The analysis module is used to perform performance analysis on the network element device based on the statistical values ​​that are non-abnormal values ​​in the performance data statistical results.

[0305] In one embodiment of the present invention, the second determining module 803 is specifically configured to:

[0306] Determining, based on the attributes of the missing statistical values ​​in the performance data statistical results, the missing scenario to which the statistical results corresponding to the second counter set are missing; a plurality of missing scenarios are predefined, and the rationality missing rule includes a sub-scenario missing rule corresponding to each missing scenario; the attributes of the statistical value include: the counter corresponding to the statistical value, and / or the statistical period corresponding to the statistical value;

[0307] The third counter set is determined by judging whether the missing of the statistical result corresponding to the second counter set satisfies the scenario-specific missing rule corresponding to the missing scenario.

[0308] In one embodiment of the present invention, the missing scenarios include: missing of individual periods of individual counters, missing of the entire period, and missing of all partial periods; the missing of individual periods of individual counters is characterized by: missing statistical values ​​corresponding to some statistical periods of some counters of the network element device within the statistical period; the missing of the entire period is characterized by: missing statistical values ​​corresponding to all statistical periods of some counters of the network element device within the statistical period; the missing of all partial periods is characterized by: missing statistical values ​​corresponding to one or more statistical periods of all counters of the network element device, or missing statistical values ​​corresponding to one or more statistical periods of all counters of the base station cell.

[0309] In one embodiment of the present invention, the scenario-specific missing rules corresponding to the missing of individual counters of individual periods include one or more of the following: in the cell deactivation scenario, the statistical values ​​of some counters of the network element equipment are missing, the statistical values ​​of counters without statistical objects are missing, the RRU of the base station is not connected or not in place, and the RRU is in a non-energy-saving state, and the statistical value of the RRU transmit power counter is missing; the scenario-specific missing rules corresponding to the missing of the entire period include one or more of the following: the statistical values ​​of counters to be delivered are missing, in the cell deactivation scenario, the statistical values ​​of some counters of the network element equipment are missing, the statistical values ​​of counters without statistical objects are missing, the RRU of the base station is not connected or not in place, and the RRU is in a non-energy-saving state, and the statistical value of the RRU transmit power counter is missing; the scenario-specific missing rules corresponding to the missing of all partial periods include one or more of the following: the base station is in any state of upgrading, resetting, cutover, and hosting.

[0310] In one embodiment of the present invention, the numerical rationality rules include: the statistical value is a non-invalid value, and / or the statistical value is within a preset range, and / or the statistical value is an invalid value, and the invalid value reporting for the statistical value meets the preset invalid value reporting conditions.

[0311] In one embodiment of the present invention, two statistical values ​​with correlation satisfy the rationality constraint rule, indicating that the two statistical values ​​satisfy the corresponding preset association condition, and the preset association condition is: if the first statistical value is not 0, then the second statistical value is not 0, or, the two statistical values ​​satisfy a specific size relationship.

[0312] In one embodiment of the present invention, the apparatus is applied to a network element device, and the apparatus further includes:

[0313] A receiving module, configured to receive a first performance data reporting task issued by a first network element management device;

[0314] a fourth determining module, configured to determine a target statistical parameter based on the first statistical parameter of the first performance data reporting task and the second statistical parameter of the second performance data reporting task; wherein the second performance data reporting task is a performance data reporting task running in the network element device;

[0315] A statistics module, configured to perform statistics on performance data based on the target statistical parameters to obtain target statistical results;

[0316] a generating module, configured to generate, based on the target statistical result, a first statistical result that meets the first statistical parameter and a second statistical result that meets the second statistical parameter;

[0317] The reporting module is used to report the first statistical result to the first network element management device, and report the second statistical result to the second network element management device that issues the second performance data reporting task.

[0318] In one embodiment of the present invention, the first statistical parameter includes a first statistical period and a fourth counter set, the second statistical parameter includes a second statistical period and a fifth counter set, and the target statistical parameter includes a target statistical period and a target counter set; the target statistical period is determined based on the first statistical period and the second statistical period, and the target counter set covers the union of the fourth counter set and the fifth counter set.

[0319] In one embodiment of the present invention, the apparatus further comprises:

[0320] An acquisition module, configured to obtain various statistical data based on the performance indicator to be analyzed from the performance data statistical results according to a calculation formula of the performance indicator to be analyzed;

[0321] a fifth determining module, configured to determine an indicator value of the performance indicator of each cell of the base station based on the statistical data;

[0322] The sixth determination module is used to compare the indicator value with the first quality difference judgment threshold to determine the poor quality cell among the cells.

[0323] In one embodiment of the present invention, the fifth determining module is specifically configured to:

[0324] Determining, for each cell, an indicator value corresponding to each sub-period within a preset decision period based on the statistical data;

[0325] The sixth determination module is specifically configured to:

[0326] For each of the cells, comparing the indicator values ​​corresponding to the cell in each sub-time period with the first poor quality decision threshold, and determining the poor quality sub-time period of the cell within the preset decision time period;

[0327] The number of poor-quality sub-periods corresponding to each of the cells is compared with a second poor-quality decision threshold to determine a poor-quality cell among the cells.

[0328] In one embodiment of the present invention, when the calculation formula is in fractional form, the fifth determination module determines the quality-poor sub-period corresponding to each cell based on the following method:

[0329] For each of the cells, determining a sub-period in which the indicator value corresponding to the cell within the preset decision period meets the first poor quality decision threshold;

[0330] For each determined sub-period, determine whether the denominator value in the calculation formula corresponding to the performance indicator of the cell in the sub-period is not less than the traffic volume decision threshold. If so, determine the sub-period as a poor quality sub-period.

[0331] The embodiment of the present invention further provides an electronic device, such as Figure 9 As shown, it includes a memory 901, a transceiver 902, and a processor 903:

[0332] The memory 901 is used to store computer programs; the transceiver 902 is used to send and receive data under the control of the processor; the processor 903 is used to read the computer program in the memory and perform the following operations:

[0333] Obtaining performance data statistics determined by the network element device; the performance data statistics include statistical values ​​of counters managed by the network element device;

[0334] Determining whether a second counter set has missing statistical results in the performance data statistical results by checking whether the performance data statistical results completely include statistical values ​​of the first counter set; the first counter set is predetermined;

[0335] By judging whether the missing statistical results corresponding to the second counter set meet the pre-set rationality missing rules, it is determined that the corresponding statistical result missing belongs to the third counter set of irrational missing; the rationality missing rules are used to describe the reasons for the rationality missing of the performance data statistical results and the counters targeted by the reasons.

[0336] Among them, Figure 9In the embodiment, the bus architecture may include any number of interconnected buses and bridges, specifically linking together various circuits of one or more processors represented by processor 903 and memory represented by memory 901. The bus architecture may also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are all well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 902 may be a plurality of components, i.e., a transmitter and a receiver, providing a unit for communicating with various other devices on a transmission medium, such as a wireless channel, a wired channel, an optical cable, and the like. The processor 903 is responsible for managing the bus architecture and general processing, and the memory 901 may store data used by the processor 903 when performing operations.

[0337] The processor 903 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or a complex programmable logic device (CPLD). The processor may also adopt a multi-core architecture.

[0338] The electronic device for counter statistics provided in an embodiment of the present invention predetermines a first set of counters corresponding to the statistical values ​​that a network element device should ideally report. Thus, for performance data statistical results obtained by the network element device, the first set of counters can be combined with the first set of counters to locate missing data in the performance data statistical results. Furthermore, the embodiment of the present invention configures a rationality loss rule based on the cause of the rationality loss in the performance data statistical results and the counters targeted by the cause. For data missing in the performance data statistical results, the rationality loss rule can be combined to effectively filter the rationality loss contained therein, resulting in a third set of counters whose corresponding statistical results are abnormally missing. This allows for targeted, accurate, and automated verification of possible abnormal missing results in the performance data statistical results. Consequently, relevant personnel do not need to manually verify the contents of the performance data statistical results one by one to check for missing statistical results, reducing the workload of manual verification and making it less prone to errors. It can also effectively prevent the problem of missing some counter statistical values ​​in manual verification.

[0339] In one embodiment of the present invention, the processor 903 is further configured to read the computer program in the memory and perform the following operations:

[0340] Determining statistical values ​​in the performance data statistical results that are non-abnormal values ​​by judging whether the statistical values ​​included in the performance data statistical results satisfy pre-set rationality rules; wherein the rationality rules include: numerical rationality rules for the values ​​of the statistical values, and / or rationality constraint rules between different statistical values ​​with correlation;

[0341] Based on the statistical values ​​that are non-abnormal values ​​in the performance data statistical results, performance analysis is performed on the network element device.

[0342] In one embodiment of the present invention, determining whether the missing statistical results corresponding to the second set of counters satisfy a preset rationality missing rule, and determining that the missing statistical results belong to the third set of counters that are irrational missing, includes:

[0343] Determining, based on the attributes of the missing statistical values ​​in the performance data statistical results, the missing scenario to which the statistical results corresponding to the second counter set are missing; a plurality of missing scenarios are predefined, and the rationality missing rule includes a sub-scenario missing rule corresponding to each missing scenario; the attributes of the statistical value include: the counter corresponding to the statistical value, and / or the statistical period corresponding to the statistical value;

[0344] The third counter set is determined by judging whether the missing of the statistical result corresponding to the second counter set satisfies the scenario-specific missing rule corresponding to the missing scenario.

[0345] In one embodiment of the present invention, the missing scenarios include: missing of individual periods of individual counters, missing of the entire period, and missing of all partial periods; the missing of individual periods of individual counters is characterized by: missing statistical values ​​corresponding to some statistical periods of some counters of the network element device within the statistical period; the missing of the entire period is characterized by: missing statistical values ​​corresponding to all statistical periods of some counters of the network element device within the statistical period; the missing of all partial periods is characterized by: missing statistical values ​​corresponding to one or more statistical periods of all counters of the network element device, or missing statistical values ​​corresponding to one or more statistical periods of all counters of the base station cell.

[0346] In one embodiment of the present invention, the missing scenarios include one or more of the following: in the cell deactivation scenario, the statistical values ​​of some counters of the network element device are missing, the statistical values ​​of counters without statistical objects are missing, the RRU of the base station is not connected or not in place, and the RRU is in a non-energy-saving state, and the statistical value of the RRU transmit power counter is missing; the sub-scenario missing rules corresponding to the full-cycle missing include one or more of the following: the statistical values ​​of the counters to be delivered are missing, in the cell deactivation scenario, the statistical values ​​of some counters of the network element device are missing, the statistical values ​​of counters without statistical objects are missing, the RRU of the base station is not connected or not in place, and the RRU is in a non-energy-saving state, and the statistical value of the RRU transmit power counter is missing; the sub-scenario missing rules corresponding to the partial cycle missing include one or more of the following: the base station is in any state of upgrading, resetting, cutover, and hosting.

[0347] In one embodiment of the present invention, two statistical values ​​with correlation satisfy the rationality constraint rule, indicating that the two statistical values ​​satisfy the corresponding preset association condition, and the preset association condition is: if the first statistical value is not 0, then the second statistical value is not 0, or, the two statistical values ​​satisfy a specific size relationship.

[0348] In one embodiment of the present invention, the electronic device is a network element device, and the processor 903 is further configured to read the computer program in the memory and perform the following operations:

[0349] receiving a first performance data reporting task issued by a first network element management device;

[0350] Determining a target statistical parameter based on a first statistical parameter of the first performance data reporting task and a second statistical parameter of the second performance data reporting task; wherein the second performance data reporting task is a performance data reporting task currently running in the network element device;

[0351] Performing statistics on the performance data based on the target statistical parameters to obtain target statistical results;

[0352] generating, based on the target statistical result, a first statistical result that meets the first statistical parameter and a second statistical result that meets the second statistical parameter;

[0353] The first statistical result is reported to the first network element management device, and the second statistical result is reported to the second network element management device that issues the second performance data reporting task.

[0354] In one embodiment of the present invention, the first statistical parameter includes a first statistical period and a fourth counter set, the second statistical parameter includes a second statistical period and a fifth counter set, and the target statistical parameter includes a target statistical period and a target counter set; the target statistical period is determined based on the first statistical period and the second statistical period, and the target counter set covers the union of the fourth counter set and the fifth counter set.

[0355] In one embodiment of the present invention, the electronic device is a network element device, and the processor 903 is further configured to read the computer program in the memory and perform the following operations:

[0356] According to the calculation formula of the performance indicator to be analyzed, various statistical data based on the performance indicator are obtained from the performance data statistical results;

[0357] Determining, based on the statistical data, an indicator value of the performance indicator of each cell of the base station;

[0358] The indicator value is compared with a first quality-poor decision threshold to determine a poor-quality cell among the cells.

[0359] In one embodiment of the present invention, determining the index value of the performance index of each cell of the base station according to the statistical data includes:

[0360] Determining, for each cell, an indicator value corresponding to each sub-period within a preset decision period based on the statistical data;

[0361] The comparing the indicator value with the first poor quality decision threshold to determine the poor quality cell among the cells includes:

[0362] For each of the cells, comparing the indicator values ​​corresponding to the cell in each sub-time period with the first poor quality decision threshold, and determining the poor quality sub-time period of the cell within the preset decision time period;

[0363] The number of poor-quality sub-periods corresponding to each of the cells is compared with a second poor-quality decision threshold to determine a poor-quality cell among the cells.

[0364] In one embodiment of the present invention, when the calculation formula adopts a fractional form, the quality-poor sub-period corresponding to each cell is determined based on the following method:

[0365] For each of the cells, determining a sub-period in which the indicator value corresponding to the cell within the preset decision period meets the first poor quality decision threshold;

[0366] For each determined sub-period, determine whether the denominator value in the calculation formula corresponding to the performance indicator of the cell in the sub-period is not less than the traffic volume decision threshold. If so, determine the sub-period as a poor quality sub-period.

[0367] In another embodiment of the present invention, a computer-readable storage medium is provided, which stores a computer program. When the computer program is executed by a processor, the steps of the above-mentioned method for checking the statistical value of any counter are implemented.

[0368] In another embodiment of the present invention, a computer program product including instructions is provided. When the computer program product is run on a computer, the computer executes the method for checking the statistical value of any counter in the above embodiments.

[0369] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0370] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0371] Each embodiment in this specification is described in a related manner. Similar portions between the various embodiments can be referenced to each other. Each embodiment focuses on the differences between the other embodiments. In particular, the embodiments of the device for verifying counter statistics, electronic device, computer storage medium, and computer program product are generally similar to the method embodiments, so their description is relatively simple. For relevant portions, reference can be made to the description of the method embodiments.

[0372] The above description is only a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention are included in the scope of protection of the present invention.

Claims

1. A method for checking counter statistical values, characterized in that: include: Obtain performance data statistics determined by network element devices; The performance data statistical result includes the statistical value of the counter managed by the network element device; determining whether a second counter set including missing statistical results exists in the performance data statistical result by checking whether the performance data statistical result completely includes statistical values ​​of the first counter set; the first counter set is predetermined; By judging whether the missing statistical results corresponding to the second counter set meet the pre-set rationality missing rules, it is determined that the corresponding missing statistical results belong to the third counter set of irrational missing; the rationality missing rules are used to describe the reasons for the rationality missing of the performance data statistical results and the counters targeted by the reasons.

2. The method according to claim 1, characterized in that Also includes: Determining statistical values ​​in the performance data statistical results that are non-abnormal values ​​by judging whether the statistical values ​​included in the performance data statistical results satisfy pre-set rationality rules; wherein the rationality rules include: numerical rationality rules for the values ​​of the statistical values, and / or rationality constraint rules between different statistical values ​​with correlation; Based on the statistical values ​​that are non-abnormal values ​​in the performance data statistical results, performance analysis is performed on the network element device.

3. The method according to claim 1, characterized in that The determining whether the missing statistical results corresponding to the second counter set satisfy a preset rationality missing rule and determining that the missing statistical results belong to the third counter set of irrational missing includes: Determining, based on the attributes of the missing statistical values ​​in the performance data statistical results, the missing scenario to which the statistical results corresponding to the second counter set are missing; a plurality of missing scenarios are predefined, and the rationality missing rule includes a sub-scenario missing rule corresponding to each missing scenario; the attributes of the statistical value include: the counter corresponding to the statistical value, and / or the statistical period corresponding to the statistical value; The third counter set is determined by judging whether the missing of the statistical result corresponding to the second counter set satisfies the scenario-specific missing rule corresponding to the missing scenario.

4. The method according to claim 3, characterized in that The missing scenarios include: missing of individual periods of individual counters, missing of the entire period, and missing of all periods; the missing of individual periods of individual counters is characterized by: missing statistical values ​​corresponding to some statistical periods of some counters of the network element device within the statistical period; missing of the entire period is characterized by: missing statistical values ​​corresponding to all statistical periods of some counters of the network element device within the statistical period; missing of all periods is characterized by: missing statistical values ​​corresponding to one or more statistical periods of all counters of the network element device, or missing statistical values ​​corresponding to one or more statistical periods of all counters of the base station cell.

5. The method according to claim 4, characterized in that The scenario-specific missing rules corresponding to the missing of individual periods of the individual counters include one or more of the following: in a cell deactivation scenario, the statistical values ​​of some counters of the network element equipment are missing, the statistical values ​​of counters without statistical objects are missing, the RRU of the base station is not connected or is not in place, and the RRU is in a non-energy-saving state, and the statistical value of the RRU transmit power counter is missing; The scenario-specific missing rules corresponding to the full-cycle missing include one or more of the following: missing statistical values ​​of counters to be delivered, missing statistical values ​​of some counters of the network element device in the cell deactivation scenario, missing statistical values ​​of counters without statistical objects, the RRU of the base station is not connected or is not in place, and the RRU is in a non-energy-saving state, and the statistical value of the RRU transmit power counter is missing; The scenario-specific missing rules corresponding to the complete missing of some periods include: the base station is in any state of upgrading, resetting, cutover, and trusteeship.

6. The method according to claim 2, characterized in that The numerical rationality rules include: the statistical value is a non-invalid value, and / or the statistical value is within a preset range, and / or the statistical value is an invalid value, and reporting an invalid value for the statistical value meets the preset invalid value reporting conditions.

7. The method according to claim 2, characterized in that The two statistical values ​​with correlation satisfy the rationality constraint rule, indicating that the two statistical values ​​satisfy the corresponding preset association condition, and the preset association condition is: if the first statistical value is not 0, then the second statistical value is not 0, or the two statistical values ​​satisfy a specific size relationship.

8. The method according to claim 1, characterized in that The method is applied to a network element device, and the method further includes: receiving a first performance data reporting task issued by a first network element management device; Determining a target statistical parameter based on a first statistical parameter of the first performance data reporting task and a second statistical parameter of the second performance data reporting task; wherein the second performance data reporting task is a performance data reporting task currently running in the network element device; Performing statistics on the performance data based on the target statistical parameters to obtain target statistical results; generating, based on the target statistical result, a first statistical result that meets the first statistical parameter and a second statistical result that meets the second statistical parameter; The first statistical result is reported to the first network element management device, and the second statistical result is reported to the second network element management device that issues the second performance data reporting task.

9. The method according to claim 8, characterized in that The first statistical parameter includes a first statistical period and a fourth counter set, the second statistical parameter includes a second statistical period and a fifth counter set, and the target statistical parameter includes a target statistical period and a target counter set; the target statistical period is determined based on the first statistical period and the second statistical period, and the target counter set covers the union of the fourth counter set and the fifth counter set.

10. The method according to claim 1, characterized in that Also includes: According to the calculation formula of the performance indicator to be analyzed, various statistical data based on the performance indicator are obtained from the performance data statistical results; Determining, based on the statistical data, an indicator value of the performance indicator of each cell of the base station; The indicator value is compared with a first quality-poor decision threshold to determine a poor-quality cell among the cells.

11. The method according to claim 10, characterized in that The determining, based on the statistical data, the index value of the performance index of each cell of the base station includes: Determining, for each cell, an indicator value corresponding to each sub-period within a preset decision period based on the statistical data; The comparing the indicator value with the first poor quality decision threshold to determine the poor quality cell among the cells includes: For each of the cells, comparing the indicator values ​​corresponding to the cell in each sub-time period with the first poor quality decision threshold, and determining the poor quality sub-time period of the cell within the preset decision time period; The number of poor-quality sub-periods corresponding to each of the cells is compared with a second poor-quality decision threshold to determine a poor-quality cell among the cells.

12. The method according to claim 11, characterized in that When the calculation formula adopts a fractional form, the quality-poor sub-period corresponding to each cell is determined based on the following method: For each of the cells, determining a sub-period in which the indicator value corresponding to the cell within the preset decision period meets the first poor quality decision threshold; For each determined sub-period, determine whether the denominator value in the calculation formula corresponding to the performance indicator of the cell in the sub-period is not less than the traffic volume decision threshold. If so, determine the sub-period as a poor quality sub-period.

13. A device for checking counter statistical values, characterized in that: include: An acquisition module is used to obtain performance data statistics determined by the network element device; The performance data statistical result includes the statistical value of the counter managed by the network element device; a first determining module, configured to determine whether a second counter set including missing statistical values ​​exists in the performance data statistical result by verifying whether the performance data statistical result completely includes statistical values ​​of a first counter set; wherein the first counter set is predetermined; The second determination module is used to determine whether the missing statistical results corresponding to the second counter set meet the pre-set rationality missing rules, and determine whether the corresponding statistical result missing belongs to the third counter set of irrational missing; the rationality missing rules are used to describe the reasons for the rationality missing of the performance data statistical results and the counters targeted by the reasons.

14. An electronic device, characterized in that: Including memory, transceiver, processor: a memory for storing computer programs; a transceiver for transmitting and receiving data under the control of the processor; A processor is configured to read the computer program in the memory and perform the following operations: Obtaining a performance data statistical result determined by a network element device; the performance data statistical result includes a statistical value of a counter managed by the network element device; determining whether a second counter set including missing statistical results exists in the performance data statistical result by checking whether the performance data statistical result completely includes statistical values ​​of the first counter set; the first counter set is predetermined; By judging whether the missing statistical results corresponding to the second counter set meet the pre-set rationality missing rules, it is determined that the corresponding missing statistical results belong to the third counter set of irrational missing; the rationality missing rules are used to describe the reasons for the rationality missing of the performance data statistical results and the counters targeted by the reasons.

15. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method steps of any one of claims 1 to 12 are implemented.

16. A computer program product comprising computer instructions, characterized in that When the calculator instruction is executed by a processor, the method steps described in any one of claims 1 to 12 are implemented.

Images