CN110121190B - Data management method and device and computer readable storage medium - Google Patents
Data management method and device and computer readable storage medium Download PDFInfo
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- CN110121190B CN110121190B CN201810125285.XA CN201810125285A CN110121190B CN 110121190 B CN110121190 B CN 110121190B CN 201810125285 A CN201810125285 A CN 201810125285A CN 110121190 B CN110121190 B CN 110121190B
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Abstract
The embodiment of the invention provides a data management method, a data management device and a computer readable storage medium, wherein the method comprises the following steps: determining a monitoring period of control plane signaling data; slicing each user plane service data associated with the control plane signaling data in the monitoring period to obtain slices of each user plane service data; analyzing network characteristics within the monitoring period based on the slice and control plane signaling data within the monitoring period.
Description
Technical Field
The present invention relates to the field of mobile communications technologies, and in particular, to a data management method, an apparatus, and a computer-readable storage medium.
Background
For better network monitoring, optimization and maintenance, a data acquisition system (DPI) is introduced into the LTE network, and data acquisition is carried out on a plurality of interfaces of the LTE network, including interfaces of Uu/X2/S1-MME/S1-U/S6 a/S11/SGs. Based on the raw Data collected from these interfaces, DPI generates a record of user behavior in the user, cell dimensions, called External Data Representation (XDR) Data.
The UE _ MR and CELL _ MR interface XDR data based on the signaling plane can be subjected to network quality analysis; an analysis of the user business experience can be made based on the S1-U interface XDR data.
In the prior art, network monitoring and optimization and user service experience analysis are performed based on XDR data, and mainly based on single-interface data analysis, or analysis is performed by combining all interfaces after indexes are respectively counted. For example: the average downloading rate is counted based on the XDR data statistics index of the S1-U interface, the weak coverage and the overlapping coverage are counted based on the XDR data statistics index of the UE _ MR interface, and whether the average downloading rate of a certain cell is low, whether the cell is weakly covered or not and whether the cell is over-covered or not can be judged through the joint analysis of the two types of indexes of the certain cell. However, these two types of indicators do not have an absolutely necessary relationship, namely: the low rate cells are not necessarily weakly covered and the weakly covered cells are not necessarily low rate.
Disclosure of Invention
In view of the above, embodiments of the present invention are intended to provide a data management method, apparatus, and computer-readable storage medium.
In order to achieve the above purpose, the technical solution of the embodiment of the present invention is implemented as follows:
the embodiment of the invention provides a data management method, which comprises the following steps:
determining a monitoring period of control plane signaling data;
slicing each user plane service data associated with the control plane signaling data in the monitoring period to obtain slices of each user plane service data;
analyzing network characteristics within the monitoring period based on the slice and control plane signaling data within the monitoring period.
In this embodiment of the present invention, after determining the monitoring period of the control plane signaling data, the method further includes:
and associating the user plane service data with the control plane signaling data in the monitoring period based on the user identification and the cell identification of the control plane signaling data.
In this embodiment of the present invention, when associating the user plane service data with the control plane signaling data in the monitoring period, the method further includes:
when determining that the data associated with the control plane signaling data exists, performing subsequent slicing processing; otherwise, the current operation is ended.
Wherein, the determining the monitoring period of the control plane signaling data includes:
taking the generation time of the control plane signaling data as the end time of the monitoring period;
determining the starting time of the monitoring period based on a preset generation period of the control plane signaling data;
determining a monitoring period of the control plane signaling data based on a start time and an end time of the monitoring period.
In this embodiment of the present invention, the slicing processing of each piece of user plane service data associated with the control plane signaling data in the monitoring period includes:
acquiring the total duration of each user plane service data record;
determining the intersection duration of the total recorded duration and the monitoring period;
and determining the data slice of each piece of user plane service data in the monitoring period based on the ratio of the intersection duration to the total duration.
In this embodiment of the present invention, the determining, based on the slice and the control plane signaling data in the monitoring period, a network characteristic in the monitoring period includes:
and associating and analyzing the slice of each user plane service data and the control plane signaling data in the monitoring period, and determining the network characteristics in the monitoring period based on the relationship between the slices and the control plane signaling data.
In one embodiment, the method further comprises:
performing statistical analysis on network characteristics in a preset statistical period based on the slice and the control plane signaling data in the monitoring period;
the preset statistical period is greater than the monitoring period.
An embodiment of the present invention further provides a data management apparatus, where the apparatus includes:
the device comprises a determining module, a monitoring module and a processing module, wherein the determining module is used for determining a monitoring period of control plane signaling data;
a slicing module, configured to slice each piece of user plane service data associated with the control plane signaling data in the monitoring period to obtain a slice of each piece of user plane service data;
and the analysis module is used for analyzing the network characteristics in the monitoring period based on the slice and the control plane signaling data in the monitoring period.
An embodiment of the present invention further provides a data management apparatus, where the apparatus includes: a processor and a memory for storing a computer program capable of running on the processor,
wherein the processor is configured to perform the steps of the above method when running the computer program.
Embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps of the above-mentioned method.
The data management method, the data management device and the computer readable storage medium provided by the embodiment of the invention are used for determining the monitoring period of control plane signaling data; slicing each user plane service data associated with the control plane signaling data in the monitoring period to obtain slices of each user plane service data; analyzing network characteristics within the monitoring period based on the slice and control plane signaling data within the monitoring period. The embodiment of the invention carries out slicing processing on the user plane service data based on the periodic control plane signaling data, and correlates the slices with the control plane signaling data, thereby being convenient for analyzing the correlation between various services and signal quality, being capable of rapidly positioning network problems and greatly improving the analysis efficiency of the network signaling problems in the existing network; also, potential network performance, failures, etc. may be expected to be resolved based on the analysis results.
Drawings
Fig. 1 is a schematic flow chart of a data management method according to an embodiment of the present invention;
FIG. 2 is a first schematic structural diagram of a data management apparatus according to an embodiment of the present invention;
FIG. 3 is a second schematic structural diagram of a data management apparatus according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a time relationship between UE _ MR data and XDR-HTTP data of a user according to an embodiment of the present invention.
Detailed Description
The invention is described below with reference to the figures and examples.
An embodiment of the present invention provides a data management method, as shown in fig. 1, the method includes:
step 101: determining a monitoring period of control plane signaling data;
step 102: slicing each user plane service data associated with the control plane signaling data in the monitoring period to obtain slices of each user plane service data;
step 103: analyzing network characteristics within the monitoring period based on the slice and control plane signaling data within the monitoring period.
The embodiment of the invention carries out slicing processing on the user plane service data based on the periodic control plane signaling data, and correlates the slices with the control plane signaling data, thereby being convenient for analyzing the correlation between various services and signal quality, being capable of rapidly positioning network problems and greatly improving the analysis efficiency of the network signaling problems in the existing network; also, potential network performance, failures, etc. may be expected to be resolved based on the analysis results.
In this embodiment of the present invention, after determining the monitoring period of the control plane signaling data, the method further includes:
and associating the user plane service data with the control plane signaling data in the monitoring period based on the user identification and the cell identification of the control plane signaling data.
For example: based on the user identity (IMSI or IMEI or MSISDN) and the CELL identity (CELL _ ID) of the control plane signaling data (e.g. UE _ MR interface data), user plane traffic data (e.g. S1-U interface XDR data) for the user in the CELL within the time frame is associated.
Here, since the user plane service data associated with the control plane signaling data may include all types, the network optimizer can quickly analyze whether all indexes are abnormal or not, break through the limitation of selecting limited indexes to analyze and locate the network problem by relying on the past optimization experience, and comprehensively analyze the network condition and comprehensively optimize the network performance.
In this embodiment of the present invention, when associating the user plane service data with the control plane signaling data in the monitoring period, the method further includes:
when determining that the data associated with the control plane signaling data exists, performing subsequent slicing processing; otherwise, the current operation is ended.
In this embodiment of the present invention, the determining a monitoring period of control plane signaling data includes:
taking the generation time of the control plane signaling data as the end time of the monitoring period;
determining the starting time of the monitoring period based on a preset generation period of the control plane signaling data;
determining a monitoring period of the control plane signaling data based on a start time and an end time of the monitoring period.
For example: taking control plane signaling data UE _ MR data as an example, the generation time (time) is used as the end time of the UE _ MR data monitoring period, and the start time of the UE _ MR data monitoring period is traced back forward according to the period frequency (e.g. 5s) of the UE _ MR data, so as to determine the monitoring period of the UE _ MR data.
In this embodiment of the present invention, the slicing processing of each piece of user plane service data associated with the control plane signaling data in the monitoring period includes:
acquiring the total duration of each user plane service data record;
determining the intersection duration of the total recorded duration and the monitoring period;
and determining the data slice of each piece of user plane service data in the monitoring period based on the ratio of the intersection duration to the total duration.
In this embodiment of the present invention, the determining, based on the slice and the control plane signaling data in the monitoring period, a network characteristic in the monitoring period includes:
and correlating and analyzing the slice of each user plane service data with the control plane signaling data in the monitoring period, and determining the network characteristics in the monitoring period based on the relationship between the slice of each user plane service data and the control plane signaling data in the monitoring period.
Optionally, the method further includes:
performing statistical analysis on network characteristics in a preset statistical period based on the slice and the control plane signaling data in the monitoring period;
the predetermined statistical period (e.g., 5 minutes, 15 minutes, 1 hour) is greater than the monitoring period.
In order to implement the foregoing method embodiment, an embodiment of the present invention further provides a data management apparatus, as shown in fig. 2, where the apparatus includes:
a determining module 201, configured to determine a monitoring period of control plane signaling data;
a slicing module 202, configured to slice each piece of user plane service data associated with the control plane signaling data in the monitoring period to obtain a slice of each piece of user plane service data;
an analyzing module 203, configured to analyze network characteristics in the monitoring period based on the slice and the control plane signaling data in the monitoring period.
In the embodiment of the present invention, as shown in fig. 3, the apparatus further includes:
the associating module 204 is configured to associate, based on a user identifier and a cell identifier of the control plane signaling data, the user plane service data and the control plane signaling data in a monitoring period.
For example: based on the user identity (IMSI or IMEI or MSISDN) and the CELL identity (CELL _ ID) of the control plane signaling data (e.g. UE _ MR interface data), user plane traffic data (e.g. S1-U interface XDR data) for the user in the CELL within the time frame is associated.
In this embodiment of the present invention, the association module 204 is further configured to perform subsequent slicing processing when determining that data associated with the control plane signaling data exists; otherwise, the current operation is ended.
In this embodiment of the present invention, the determining module 201 determines a monitoring period of control plane signaling data, including:
taking the generation time of the control plane signaling data as the end time of the monitoring period;
determining the starting time of the monitoring period based on a preset generation period of the control plane signaling data;
determining a monitoring period of the control plane signaling data based on a start time and an end time of the monitoring period.
For example: taking control plane signaling data UE _ MR data as an example, the generation time (time) is used as the end time of the UE _ MR data monitoring period, and the start time of the UE _ MR data monitoring period is traced back forward according to the period frequency (e.g. 5s) of the UE _ MR data, so as to determine the monitoring period of the UE _ MR data.
In this embodiment of the present invention, the slicing module 202 slices each piece of user plane service data associated with the control plane signaling data in the monitoring period, including:
acquiring the total duration of each user plane service data record;
determining the intersection duration of the total recorded duration and the monitoring period;
and determining the data slice of each piece of user plane service data in the monitoring period based on the ratio of the intersection duration to the total duration.
In this embodiment of the present invention, the determining, by the analysis module 203, the network characteristics in the monitoring period based on the slice and the control plane signaling data in the monitoring period includes:
and correlating and analyzing the slice of each user plane service data with the control plane signaling data in the monitoring period, and determining the network characteristics in the monitoring period based on the relationship between the slice of each user plane service data and the control plane signaling data in the monitoring period.
Optionally, the analysis module 203 is further configured to perform statistical analysis on the network characteristics in a preset statistical period based on the slice and the control plane signaling data in the monitoring period;
the predetermined statistical period (e.g., 5 minutes, 15 minutes, 1 hour) is greater than the monitoring period.
An embodiment of the present invention further provides a data management apparatus, where the apparatus includes: a processor and a memory for storing a computer program capable of running on the processor,
wherein the processor is configured to execute, when running the computer program:
determining a monitoring period of control plane signaling data;
slicing each user plane service data associated with the control plane signaling data in the monitoring period to obtain slices of each user plane service data;
analyzing network characteristics within the monitoring period based on the slice and control plane signaling data within the monitoring period.
After determining the monitoring period of the control plane signaling data, the processor is further configured to, when running the computer program, perform:
and associating the user plane service data with the control plane signaling data in the monitoring period based on the user identification and the cell identification of the control plane signaling data.
When the user plane service data in the monitoring period is associated with the control plane signaling data, the processor is further configured to execute, when the computer program runs, the following steps:
when determining that the data associated with the control plane signaling data exists, performing subsequent slicing processing; otherwise, the current operation is ended.
When the monitoring period of the control plane signaling data is determined, the processor is further configured to execute, when the computer program is run:
taking the generation time of the control plane signaling data as the end time of the monitoring period;
determining the starting time of the monitoring period based on a preset generation period of the control plane signaling data;
determining a monitoring period of the control plane signaling data based on a start time and an end time of the monitoring period.
When the slicing processing is performed on each piece of user plane service data associated with the control plane signaling data in the monitoring period, the processor is further configured to execute, when the computer program runs, the following steps:
acquiring the total duration of each user plane service data record;
determining the intersection duration of the total recorded duration and the monitoring period;
and determining the data slice of each piece of user plane service data in the monitoring period based on the ratio of the intersection duration to the total duration.
When determining the network characteristics in the monitoring period based on the slice and the control plane signaling data in the monitoring period, the processor is further configured to execute, when running the computer program:
and correlating and analyzing the slice of each user plane service data with the control plane signaling data in the monitoring period, and determining the network characteristics in the monitoring period based on the relationship between the slice of each user plane service data and the control plane signaling data in the monitoring period.
The processor is further configured to, when executing the computer program, perform:
performing statistical analysis on network characteristics in a preset statistical period based on the slice and the control plane signaling data in the monitoring period;
the preset statistical period is greater than the monitoring period.
It should be noted that: in the above embodiment, when performing data management, the apparatus is only illustrated by dividing the program modules, and in practical applications, the above processing may be distributed and completed by different program modules according to needs, that is, the internal structure of the device is divided into different program modules to complete all or part of the above-described processing. In addition, the apparatus provided in the above embodiments and the corresponding method embodiments belong to the same concept, and specific implementation processes thereof are described in the method embodiments and are not described herein again.
In an exemplary embodiment, the embodiment of the present invention also provides a computer-readable storage medium, which may be a Memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface Memory, optical disc, or CD-ROM; or may be a variety of devices including one or any combination of the above memories, such as a mobile phone, computer, tablet device, personal digital assistant, etc.
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, performs:
determining a monitoring period of control plane signaling data;
slicing each piece of user plane service data associated with the control plane signaling data in the monitoring period to obtain slices of each piece of user plane service data;
analyzing network characteristics within the monitoring period based on the slice and control plane signaling data within the monitoring period.
After the determining the monitoring period of the control plane signaling data, the computer program, when executed by the processor, further performs:
and associating the user plane service data with the control plane signaling data in the monitoring period based on the user identification and the cell identification of the control plane signaling data.
When the user plane service data in the monitoring period is associated with the control plane signaling data, the computer program further executes, when executed by the processor:
when determining that the data associated with the control plane signaling data exists, performing subsequent slicing processing; otherwise, the current operation is ended.
When the monitoring period of the control plane signaling data is determined, the computer program is executed by the processor to further perform:
taking the generation time of the control plane signaling data as the end time of the monitoring period;
determining the starting time of the monitoring period based on a preset generation period of the control plane signaling data;
determining a monitoring period of the control plane signaling data based on a start time and an end time of the monitoring period.
When the slicing processing is performed on each piece of user plane traffic data associated with the control plane signaling data in the monitoring period, and the computer program is executed by a processor, the method further performs:
acquiring the total duration of each user plane service data record;
determining the intersection duration of the total recorded duration and the monitoring period;
and determining the data slice of each piece of user plane service data in the monitoring period based on the ratio of the intersection duration to the total duration.
When determining the network characteristics in the monitoring period based on the slice and the control plane signaling data in the monitoring period, the computer program, when executed by a processor, further performs:
and correlating and analyzing the slice of each user plane service data with the control plane signaling data in the monitoring period, and determining the network characteristics in the monitoring period based on the relationship between the slice of each user plane service data and the control plane signaling data in the monitoring period.
The computer program, when executed by the processor, further performs:
performing statistical analysis on network characteristics in a preset statistical period based on the slice and the control plane signaling data in the monitoring period;
the preset statistical period is greater than the monitoring period.
The invention is described below in conjunction with the scenario embodiments.
In order to reflect the real situation of the cell and the real experience of the user more accurately, the data (control plane signaling data) reflecting the network quality and the user plane service data can be associated and analyzed together. For example: the user service flow/time length and the average downloading rate of the same cell under different signal conditions are higher than the user service flow and the average downloading rate of the cell level.
It can be known that the mechanism for generating XDR data for different interfaces in DPI is different, such as: the CELL _ MR interface XDR data and part of the UE _ MR interface XDR data are generated according to a configured period (such as 5 seconds), and the time stamp of the XDR data is the data generation time; the XDR data of interfaces such as S1-U, UU, S1-MME and the like are generated according to the time point of signaling or service generation, and the time stamp of the XDR data comprises the starting time and the ending time of the signaling flow/service data generation.
Thus, the related methods and steps of the proposed embodiments of the invention are as follows:
example one
The control plane signaling data in this embodiment takes UE _ MR data as an example, and the user plane service data takes S1-U interface XDR data as an example:
the first step is as follows: taking the UE _ MR data as a slicing reference, taking the generation time (time) of the UE _ MR data as the end time of the UE _ MR monitoring period, and tracing the start time of the UE _ MR monitoring period forward according to the period frequency (such as 5s) of the UE _ MR;
the second step is that: associating the S1-U interface XDR data of the user under the CELL within the time range (monitoring period) based on the user identification (IMSI or IMEI or MSISDN) and the CELL identification (CELL _ ID) of the UE _ MR interface data; if so, performing subsequent slice calculation, and processing the associated S1-U interface XDR data one by one;
the third step: taking a piece of associated S1-U interface XDR data, taking a Time range from a starting Time (Procedure Start Time) to an ending Time (Procedure End Time) of a timestamp of the data, calculating intersection duration of the Time range and the UE _ MR data monitoring period, and further calculating the proportion of the duration of the intersection duration in the S1-U interface XDR record;
the fourth step: according to the ratio, relevant monitoring data of the XDR of the S1-U interface data, such as the number of downlink IP packets (dl _ IP _ packets), the uplink time length (ul _ duration) and the like, are distributed to the UE _ MR interface data of the user according to the ratio;
the fifth step: repeating the third step and the fourth step, and distributing the data of each S1-U interface associated with the UE _ MR interface data in the monitoring period to the corresponding UE _ MR interface data; relevant service analysis and statistics, such as classification relations between RSRP and traffic and the like, can be performed on each piece of UE _ MR data and some piece of monitoring data of a plurality of distributed S1-U interfaces, so that relevant labels are attached to relevant network quality and user services;
here, the labeling process may be based on traditional net optimization experience to determine the label, or may be based on the basic data after the second step of association to perform mining by a big data analysis method.
And a sixth step: after the XDR data of the S1-U interface is integrated based on the XDR data of the periodic UE _ MR interface, further analysis and statistics may be performed for a longer period of time (e.g. 5 minutes, 15 minutes, 1 hour), and a relevant label is attached to the correlation between the relevant network quality and the user service, for example, a user-level label is assembled based on the user identifier (IMSI or IMEI or MSISDN).
Example two
In this embodiment, it is assumed that UE _ MR data of a certain user and XDR-HTTP service data of an S1-U interface are already associated according to an association condition (e.g. UE identity and Cell identity), where UE _ MR is periodic measurement data.
Taking the data in fig. 4 as an example, the slice management method is specifically described:
the first step is as follows: taking 1 st 5s UE _ MR data, wherein 3 XDR-HTTP data and the intersection thereof are respectively XDR with three durations of 3s, 4s and 12s, and associating the 3 records;
the second step: assuming that the length of the time intersection of the XDR record of 3s and the UE _ MR data of the 1 st 5s is 2s, the time is 2/3 times the total time length of the XDR record; the XDR records of 4s are completely in the time range of the UE _ MR record of the 1 st 5s, the time intersection is 4s, and the time proportion is 1; and the length of the time intersection of the 12s XDR record and the 1 st 5s UE _ MR data is 3s, then the time is 3/12, i.e., 1/4, times of its total duration.
The third step: the information of interest is selected to be sliced and concentrated on the 1 st UE _ MR, for example, taking the uplink IP packet number (UL _ IP _ Package) as an example, the obtained slice values of the 1 st UE _ MR are as follows:
sections from the 3 second XDR were: 2/3 (number of upstream IP packets of XDR of duration 3 seconds);
sections from 4 seconds of XDR were: 1 x (number of upstream IP packets of XDR of duration 4 seconds),
sections from 12 seconds of XDR were: 1/4 (number of upstream IP packets of XDR of duration 12 seconds).
The fourth step: the values of the slices can be subjected to relevant statistics according to actual needs, such as summation and/or averaging, so as to obtain a statistical observation value under the UE _ MR data;
the fifth step: after the statistical observations of all UE _ MRs are obtained, the service quality, network quality of interest, and label tagging, such as RSRP and HTTP/Video traffic, may be further analyzed.
Here, if statistics of larger macro-particle size are required, data collection and statistics of large particle size time (e.g. 5 minutes, 15 minutes, etc.) can also be performed upwards based on the period data, and will not be described in detail here.
The embodiment of the invention carries out slicing processing on the user plane service data based on the periodic control plane signaling data, and correlates the slices with the control plane signaling data, thereby being convenient for analyzing the correlation between various services and signal quality, being capable of rapidly positioning network problems and greatly improving the analysis efficiency of the network signaling problems in the existing network; also, potential network performance, failures, etc. may be expected to be resolved based on the analysis results.
In the embodiment of the invention, because the user plane service data associated with the control plane signaling data can include all types, network optimization personnel can quickly analyze whether all indexes are abnormal or not, the limitation that limited indexes are selected to analyze and position network problems by relying on the previous optimization experience is broken through, and the network condition is comprehensively analyzed and the network performance is comprehensively optimized.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention.
Claims (8)
1. A method for managing data, the method comprising:
determining a monitoring period of control plane signaling data;
acquiring the total duration of each user plane service data record associated with the control plane signaling data, determining the intersection duration of the total duration and the monitoring period, and determining the slice of each user plane service data in the monitoring period based on the ratio of the intersection duration to the total duration;
and associating the slice with the control plane signaling data in the monitoring period, and analyzing the network characteristics in the monitoring period based on the relationship between the slice and the control plane signaling data in the monitoring period.
2. The method of claim 1, wherein after determining the monitoring period for the control plane signaling data, the method further comprises:
and associating the user plane service data with the control plane signaling data in the monitoring period based on the user identification and the cell identification of the control plane signaling data.
3. The method of claim 2, wherein when associating the user plane traffic data with the control plane signaling data in a monitoring period, the method further comprises:
when determining that the data associated with the control plane signaling data exists, performing subsequent slicing processing; otherwise, the current operation is ended.
4. The method of claim 1, wherein the determining the monitoring period of the control plane signaling data comprises:
taking the generation time of the control plane signaling data as the end time of the monitoring period;
determining the starting time of the monitoring period based on a preset generation period of the control plane signaling data;
determining a monitoring period of the control plane signaling data based on a start time and an end time of the monitoring period.
5. The method of claim 1, further comprising:
performing statistical analysis on network characteristics in a preset statistical period based on the slice and the control plane signaling data in the monitoring period;
the preset statistical period is greater than the monitoring period.
6. A data management apparatus, characterized in that the apparatus comprises:
the device comprises a determining module, a monitoring module and a processing module, wherein the determining module is used for determining a monitoring period of control plane signaling data;
a slicing module, configured to obtain a total duration of each user plane service data record associated with the control plane signaling data, determine an intersection duration of the total duration and the monitoring period, and determine a slice of each user plane service data in the monitoring period based on a ratio of the intersection duration to the total duration;
and the analysis module is used for correlating the slice with the control plane signaling data in the monitoring period and analyzing the network characteristics in the monitoring period based on the relationship between the slice and the control plane signaling data in the monitoring period.
7. A data management apparatus, characterized in that the apparatus comprises: a processor and a memory for storing a computer program capable of running on the processor,
wherein the processor is adapted to perform the steps of the method of any one of claims 1-5 when running the computer program.
8. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.
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