Problem Mitigation in Subscriber Profile Management

Abstract

Systems, methods, apparatus, and computer program products for alleviating problems in subscriber profile management. A method may include creating a distribution of subscriber profile sizes. The method may also include collecting a distribution of subscriber profile sizes observed within a predefined interval of a network. The method may also include performing an analysis of the distribution. Additionally, the method may also include determining a corrective action based on the analysis. Furthermore, the method may include determining whether a corrective action is required. When it is determined that a corrective action is required, the method may include applying the corrective action to the network. When it is determined that a corrective action is not required, the method may include collecting another distribution of subscriber profile sizes.

Description

Technical Field

[0001] Some example embodiments may generally relate to mobile or wireless telecommunication systems, such as Long Term Evolution (LTE) or fifth generation (5G) radio access technology or new radio (NR) access technology, or other communication systems. For example, certain embodiments may relate to apparatus, systems and / or methods for alleviating problems in subscriber profile management. Background Art

[0002] Examples of mobile or wireless telecommunication systems may include the Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (UTRAN), Long Term Evolution (LTE) Evolved UTRAN (E-UTRAN), Advanced LTE (LTE-A), MulteFire, LTE-A Pro and / or fifth generation (5G) radio access technology or new radio (NR) access technology. The fifth generation (5G) wireless system refers to the next generation (NG) radio system and network architecture. 5G is primarily built on the New Radio (NR), but 5G (or NG) networks can also be built on the E-UTRAN radio. It is estimated that NR will provide bit rates on the order of 10-20Gbit / s or higher and will support at least enhanced mobile broadband (eMBB) and ultra-reliable low latency communications (URLLC) and massive machine type communications (mMTC). NR is expected to provide extreme broadband and ultra-robust low latency connectivity as well as large-scale networking to support the Internet of Things (IoT). As IoT and machine-to-machine (M2M) communications become more prevalent, there will be an increasing demand for networks that meet the requirements of low power consumption, low data rates, and long battery life. Note that in 5G, a node that can provide radio access functionality to user equipment (i.e., similar to a Node B in UTRAN or an eNB in ​​LTE) is called a gNB when built on an NR radio, and is called an NG-eNB when built on an E-UTRAN radio. Summary of the invention

[0003] Some example embodiments relate to a method. The method may include creating a distribution of subscriber profile sizes. Additionally, the method may include collecting a distribution of subscriber profile sizes observed within a predefined interval of a network. The method may also include performing an analysis of the distribution. The method may also include determining a corrective action based on the analysis. Additionally, the method may include determining whether a corrective action is required. When it is determined that a corrective action is required, the method may include applying the corrective action to the network. When it is determined that a corrective action is not required, the method may include collecting another distribution of subscriber profile sizes.

[0004] Other example embodiments may be directed to an apparatus. The apparatus may include at least one processor and at least one memory including computer program code. The at least one memory and the computer program code may be configured to, together with the at least one processor, cause the apparatus to at least create a distribution of subscriber profile sizes. In addition, the apparatus may be caused to collect a distribution of subscriber profile sizes observed within a predefined interval of a network. The apparatus may also be caused to perform an analysis of the distribution. The apparatus may also be caused to determine a corrective action based on the analysis. In addition, the apparatus may be caused to determine whether a corrective action is required. When it is determined that a corrective action is required, the apparatus may be caused to apply the corrective action to the network. When it is determined that a corrective action is not required, the apparatus may be caused to collect another distribution of subscriber profile sizes.

[0005] Other example embodiments may be directed to an apparatus. The apparatus may include components for creating a distribution of subscriber profile sizes. Additionally, the apparatus may include components for collecting a distribution of subscriber profile sizes observed within a predefined interval of a network. The apparatus may also include components for performing an analysis of the distribution. The apparatus may also include components for determining a corrective action based on the analysis. Additionally, the apparatus may include components for determining whether a corrective action is required. Upon determining that a corrective action is required, the apparatus may include components for applying the corrective action to the network. Upon determining that a corrective action is not required, the apparatus may include components for collecting another distribution of subscriber profile sizes.

[0006] According to other example embodiments, a non-transitory computer readable medium may be encoded with instructions that, when executed in hardware, may perform a method. The method may include creating a distribution of subscriber profile sizes. Additionally, the method may include collecting a distribution of subscriber profile sizes observed within a predefined interval of a network. The method may also include performing an analysis of the distribution. The method may also include determining a corrective action based on the analysis. Additionally, the method may include determining whether a corrective action is required. When it is determined that a corrective action is required, the method may include applying the corrective action to the network. When it is determined that a corrective action is not required, the method may include collecting another distribution of subscriber profile sizes.

[0007] Other example embodiments may be directed to a computer program product for performing a method. The method may include creating a distribution of subscriber profile sizes. Additionally, the method may include collecting a distribution of subscriber profile sizes observed within a predefined interval of a network. The method may also include performing an analysis of the distribution. The method may also include determining a corrective action based on the analysis. Additionally, the method may include determining whether a corrective action is required. When it is determined that a corrective action is required, the method may include applying the corrective action to the network. When it is determined that a corrective action is not required, the method may include collecting another distribution of subscriber profile sizes.

[0008] Other example embodiments may be directed to an apparatus that may include circuitry configured to create a distribution of subscriber profile sizes. Additionally, the apparatus may include circuitry configured to collect a distribution of subscriber profile sizes observed within a predefined interval of a network. The apparatus may also include circuitry configured to perform an analysis of the distribution. The apparatus may also include circuitry configured to determine a corrective action based on the analysis. Additionally, the apparatus may include circuitry configured to determine whether a corrective action is required. Upon determining that a corrective action is required, the apparatus may include circuitry configured to apply the corrective action to the network. Upon determining that a corrective action is not required, the apparatus may include circuitry configured to collect another distribution of subscriber profile sizes. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to properly understand the example embodiments, reference should be made to the accompanying drawings, in which:

[0010] Figure 1 a histogram showing the distribution of collected subscriber profile sizes according to certain example embodiments;

[0011] Figure 2A a histogram showing the distribution of collected subscriber profile sizes at time "X" in accordance with certain example embodiments;

[0012] Figure 2B showing a histogram of the distribution of collected subscriber profile sizes at time "Y" in accordance with certain example embodiments;

[0013] Figure 2C showing a histogram of the collected subscriber profile size distribution at time "Z" in accordance with certain example embodiments;

[0014] Figure 3 is a flow chart of a method according to certain example embodiments;

[0015] Figure 4 An Observe Oriented Decide to Act (OODA) control loop is shown in accordance with certain example embodiments;

[0016] Figure 5A An example block diagram showing an apparatus according to an embodiment; and

[0017] Figure 5B An example block diagram of another apparatus according to an example embodiment is shown. DETAILED DESCRIPTION

[0018] It will be readily appreciated that the components of certain example embodiments, as generally described and illustrated in the figures herein, may be arranged and designed in a variety of different configurations. The following detailed description of some example embodiments of systems, methods, apparatus, and computer program products may be used to alleviate problems in subscriber profile management. This is not intended to limit the scope of certain example embodiments, but rather to represent some example embodiments.

[0019] The features, structures, or characteristics of the example embodiments described throughout the specification may be combined in any suitable manner in one or more example embodiments. For example, throughout the specification, the use of the phrases "certain embodiments," "example embodiments," "some embodiments," or other similar language refers to the fact that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment. Thus, throughout the specification, the appearance of the phrases "in certain embodiments," "example embodiments," "in some embodiments," "in other embodiments," or other similar language does not necessarily all refer to the same set of embodiments, and in one or more example embodiments, the described features, structures, or characteristics may be combined in any suitable manner.

[0020] In addition, if necessary, the different functions or steps discussed below can be performed in different orders and / or concurrently with each other. In addition, if necessary, one or more of the described functions or steps can be optional or can be combined. Like this, the following description should be considered as only the principle of some example embodiments and the explanation of teaching, rather than limitation thereof.

[0021] When a user signs a contract with a network operator (eg, purchases a Subscriber Identity Module (SIM)), the network operator performs provisioning which creates a subscriber profile with data reflecting details of the SIM and associated services. A subscriber profile may include static and dynamic data.

[0022] Static data can be created during initial provisioning and can include various types of data. For example, static data can include International Mobile Subscriber Identity (IMSI), Mobile Station International Subscriber Directory Number, IP Multimedia Public Identity (IMPU), IP Multimedia Private Identity (IMPI), service profiles, billing information, static access point names (APNs), etc. On the other hand, dynamic data can be created during call processing and can include data such as repository data, dynamic APNs, notifications, monitoring events, communication modes, etc.

[0023] In some cases, the dynamic data in the subscriber profile may grow significantly over time. For example, a network function (NF) such as unified data management (UDM) may induce additional dynamic data due to roaming conditions (e.g., reflecting new repository data for supplementary services during roaming). In addition, the dynamic data may be expanded when reference configuration data (common data) is dereferenced. In addition, new dynamic data may be added when new features are enabled. For example, this may be due to the 3rd Generation Partnership Project (3GPP) evolution or vendor-specific implementation that introduces new containers in the service-based interface (SBI) message payload.

[0024] As described above, subscriber profiles may grow over time. The growth of subscriber profiles may result in the growth of corresponding protocol payloads, which may not usually be noticed until system performance is reduced (e.g., exceeding the planned system size) and service impacts are caused. In some cases, survey issues related to subscriber profile size and unoptimized profile plans may occur. For example, such issues may involve manually parsing a large number of positioning calculation application parts (PCAPs) and searching for Cx server assignment responses (SAA) messages of unexpected sizes. Therefore, this will increase maintainability costs and debugging complexity. In addition, similar scenarios may also affect SBI (e.g., eIMS SBI between a call session control function (CSCF) and a home subscriber server (HSS)). Therefore, certain example embodiments may solve the above situation in a standardized manner via automatic profile size monitoring.

[0025] Table 1 shows a summary of how the subscriber profile is organized. Specifically, Table 1 shows the dynamic and static parts of the subscriber profile, and the corresponding entities that can update the profile.

[0026] Table 1 - Organization of Subscriber Profiles

[0027] UE Profile Object Classes and Attributes property Entities that can update profiles IMPU, IMPI, MSISDN, IMSI Static Configure interfaces, such as CRM systems hssAliasRepData.data dynamic Application Server hssNotification dynamic Application Server globalFilterIds Runtime reference resolution Configure interfaces, such as CRM systems dynPdnInfo dynamic MME or AAA

[0028] In some cases, during a transaction, an NF may push data into a subscriber profile, also referred to as a user equipment (UE) profile. As a result, when a subscriber profile grows, another NF (including provisioning elements) that reads the profile may experience delays. Therefore, the unnoticed growth of subscription data (subscriber profile) may lead to message fragmentation, which in turn may lead to increased response times, ultimately affecting the service. In addition, an application server (AS) may intentionally or unintentionally (e.g., due to suboptimal implementation) push large amounts of data to a subscription, resulting in uncontrolled growth of the subscriber profile, leading to negative service impacts and network outages. Therefore, without an appropriate solution, the network may be vulnerable to malicious attacks, which may not be noticed until a network outage occurs.

[0029] In view of the problems that may occur due to the growth of subscriber profiles, certain example embodiments may provide a method for monitoring the dynamics of subscriber profile size at runtime and mitigating these problems before potential network-wide problems occur. For example, certain example embodiments may provide standardized performance management (PM) measurements that track the statistical distribution of subscriber profile sizes at the UDM. The observed distribution may be reported to analysis periodically, where trends may be derived and provided as insights to decision logic, where necessary corrective / mitigation actions may be identified. In certain example embodiments, the entire process may follow an observation-directed decision-behavior (OODA) control loop pattern. Therefore, according to certain example embodiments, PM measurements combined with analysis and corrective actions in UDM transactions or configurations may provide the solution needed to solve the subscriber profile size problem. Moreover, certain example embodiments may provide preventive mitigation of network outages, supply network operators with insights into subscriber profile dynamics, and achieve optimal planning of network resources such as network bandwidth, CPU, and memory.

[0030] Certain example embodiments may provide standardized performance measurements that focus on monitoring the statistical distribution (e.g., size) of service profiles stored by a unified data repository (UDR) and processed by the UDM. In addition, the statistical distribution of corresponding messages exchanged by the NF through a signaling interface may be monitored. In addition, certain example embodiments may generate a histogram representing the number of service profile sizes observed during a granularity period (GP) falling into a specific predefined interval. For example, a count of the service profile size observed within a certain interval may be captured as a bin value. In certain example embodiments, the histogram may be generated by a network data analysis function (NWDAF), a management function (MF), a management analysis function, a management system, a self-organizing network (SON) server, or a SON function. According to certain example embodiments, using this method, the level of detail necessary to understand the situation may be combined with effective data collection, in which only a brief summary may need to be collected and stored for future analysis.

[0031] Figure 1 A histogram of the size distribution of collected subscriber profiles according to certain example embodiments is shown. In certain example embodiments, the changes in the size distribution of collected subscriber profiles over time may also be observed. For example, Figure 2A A histogram of the size distribution of collected subscriber profiles at time "X" is shown in accordance with certain example embodiments. In addition, Figure 2B A histogram of the size distribution of collected subscriber profiles at time "Y" is shown in accordance with certain example embodiments. In addition, Figure 2CA histogram of the collected subscriber profile size distribution at time "Z" is shown according to certain example embodiments. In other example embodiments, a single-valued measure representing the average or median size of service profiles (and / or signaling messages) observed during a GP is also possible.

[0032] As described herein, subscriber profile sizes may be measured to provide a distribution of subscriber profile sizes in a UDM. For example, in certain example embodiments, the measurement may be obtained by determining the size of each subscriber profile. According to certain example embodiments, the subscriber profile sizes may be reported by a network function including, for example, the UDM as a performance measurement. In certain example embodiments, the network function may determine the size, and periodic reporting of the size(s) may be the responsibility of the network function itself or a management function responsible for the network function. Additionally, a bin having a range corresponding to the observed service profile size may be selected, and the value of a counter for the selected bin may be incremented by 1. For example, for an observed subscriber profile size of 3,300 bytes, a counter corresponding to bin "0-5000" may be incremented by 1.

[0033] According to certain example embodiments, each measurement may be an integer representing a count of service profiles whose sizes are within a range of bins. For example, the reported distribution may be represented as RM.SubscriberProfileSizesCount.Bin, where Bin represents a vendor-specific size range. In certain example embodiments, the Bin values ​​may be, for example: .0-5000=243, .5001-10000=1343, .10001-15000=3330, .15001-20000=3391, .20001-25000=1462, .25001-30000=215, or .30001-35000=16.

[0034] In certain example embodiments, message size may be measured. According to certain example embodiments, message size may be measured by a network function, including, for example, the UDM itself, an intermediate annotation (e.g., a router signaling gateway), or a probe monitoring signaling traffic. Message size may provide a distribution of message sizes in a UDM, such as UDMSubscriberDataManagement. For example, a measurement of a Diameter Extensible Authentication Protocol (EAP) Request (DER) may be n=1. The measurement may be obtained for each observed UDM_SubscriberDataManagement response or notification message (e.g., "SDM Get Response", "SDM Notification Notification", "SDM Information Response"), and its size may be determined. According to certain example embodiments, a bin having a range corresponding to the observed message size may be selected under a sub-counter corresponding to the message type, and each value of the counter for the selected bin may be incremented by 1. For example, for an observed "SDM Get Response" message of size 4,500 bytes, a counter corresponding to bin "0-5000" may be incremented by 1.

[0035] According to certain example embodiments, each measurement of a message may be an integer representing a count of service profiles having a size within a range of bins. For example, a Bin in RM.UdmSdm.GetResponseSize.Bin indicates a size range that may be vendor specific. Additionally, a Bin in RM.UdmSdm.NotificationSize.Bin may indicate a size range that may be vendor specific. Additionally, a Bin in RM.UdmSdm.InfoResponseSize.Bin may indicate a size range that may be vendor specific.

[0036] In certain example embodiments, once the size distribution of profiles and / or messages has been collected, an analysis of the periodically reported subscriber profile sizes and / or message size distributions may be performed. According to certain example embodiments, the analysis may identify trends or changes in the distributions. For example, FIG. 2A to FIG. 2C The distribution of subscriber profile size over time is shown according to the observation of steady growth at time "X", time "Y", and time "Z".

[0037] According to certain example embodiments, detected trends (e.g., analysis results) can be used to identify one or more possible corrective actions that may or may not be needed to mitigate the detected trends. In certain example embodiments, the corrective action may correspond to a change in the configuration of a particular application function. Another type of corrective action may include compressing (e.g., cleaning up) subscriber profiles, which can be applied to a certain number of subscriber profiles (e.g., based on predefined criteria such as profile size thresholds). Once (multiple) available corrective actions are identified, a decision can be made whether one or more corrective actions are needed. If it is determined that corrective actions are needed, one or more corrective actions can be applied to the network. After the corrective actions are completed, network behavior can continue to be observed, and the size and distribution of subscriber profiles can be periodically collected.

[0038] Figure 3 A flow chart of a method according to some example embodiments is shown. In some example embodiments, Figure 3 The flowchart of the method may be performed by a self-managing UDM (where the steps of the method may be performed by a management function integrated with the UDM), a management system, or multiple management functions that collaboratively perform individual steps (e.g., similar to Figure 5B 20) is performed. For example, at 300, the method may include a repeat execution point of the method, which occurs after determining that the operation continues at 345 and the method repeats again at 305. At 305, the method may include collecting a size distribution of profiles and / or messages. According to certain example embodiments, before collecting the size distribution, the method may include creating a distribution of subscriber profile sizes. Using the size distribution, the method may include analyzing the size distribution to identify any trends at 310. If no trends are identified, the method may proceed to a merge point 340, at which the method proceeds to 345. However, if one or more trends are identified, one or more potential corrective actions may be identified at 320. The method may also include determining whether any corrective action is required at 325. If no corrective action is required, the method may proceed to a merge point 335, at which point the method proceeds to 345. However, if it is determined that corrective action is required, at 330, the method may include applying one or more corrective actions to the network. According to certain example embodiments, the corrective action may include changing the configuration of a specific application function. At 345 , if it is determined that operation should continue, the method may return to 300 to continue observing network behavior.

[0039] In some example embodiments, a predefined threshold may be used at 325 to determine whether corrective action is needed. For example, in some example embodiments, the predefined threshold may correspond to whether the subscriber profile size or the message size exceeds the average size. However, in other example embodiments, detected trends (e.g., the size distribution shifts to the right or changes its shape) may also be used. In some example embodiments, the decision may be based on a prediction (e.g., based on linear regression or any other method), and the corrective action performed based on the prediction may include a preemptive action.

[0040] According to certain example embodiments, creating a distribution may include collecting single-value measurements of subscriber profile sizes, and reporting the number of subscriber profile sizes that fall within each of a plurality of predetermined size ranges. In certain example embodiments, creating a distribution may include collecting single-value measurements of subscriber profile sizes and calculating a mean or median of the subscriber profile sizes. According to other example embodiments, the method may further include creating a distribution of subscriber message sizes observed over a predefined interval of the network. In certain example embodiments, the analysis may include identifying trends in the distribution or anomalies in the distribution. In some example embodiments, determining whether corrective action is required may include identifying misbehaving application functions, identifying a need for subscriber profile optimization, or identifying a need for lifecycle management actions for application function instances and network slices. In other example embodiments, trends in the distribution may include changes in subscriber profile sizes or changes in counts of subscriber profiles. According to certain example embodiments, the corrective action may include reconfiguring application functions of the network, deleting unnecessary data from a subscriber profile, eliminating unused service information from a subscriber profile, dynamically compressing data in a subscriber profile, dynamically moving data to a shared profile, or performing lifecycle management actions at the application function or network slice level.

[0041] Figure 4 OODA control loop is shown according to certain example embodiments. Figure 4In the observation step shown, new subscriber profile size distribution measurements may be collected by the above method. According to certain example embodiments, the additional new measurements in this step may include message size distribution. In certain example embodiments, measurements may be for 5G related to UDM (e.g., Nudm_SubscriberDataManagement, Nudm_EventExposure, Nudm_ParameterProvision), HSS based on SBI (e.g., Nhss_SubscriberDataManagement), eIMS for HSS (e.g., Nhss_imsSubscriberDataManagement), and Nudr (e.g., Nudr_DataRepository data acquisition and data update, Nudr_GroupIDmap). In other example embodiments, measurements may be for legacy LTE / VoLTE of the HSS relating to various signaling interfaces, including, for example, Cx (e.g., Cx-SAA, Cx-PPR), Sh (e.g., Sh-UDR, PUR, SNR, Sh-PNR), S6a (e.g., S6a-ULR / ULA, S6a-IDR), and S6t (e.g., external group-related data for monitoring events / communication patterns when the group is extended for IoT).

[0042] like Figure 4 As further shown, the orientation step may include two different types of analysis. In some example embodiments, one analysis may include anomaly detection, which may include a non-zero value reported in a size bin that previously contained a zero value. In other example embodiments, the analysis may include detecting a trend of change, such as FIG. 2A to FIG. 2C As shown, the changing trends may include trends related to growth.

[0043] Figure 4 Further illustrated are decision steps that may include certain potential corrective decisions. For example, in certain example embodiments, the decision steps may include: identifying "misbehaving" NFs (e.g., application functions), identifying needs for subscriber profile optimization, and identifying needs for lifecycle management (LCM) actions (e.g., scale) for NF instances and network slices.

[0044] also, Figure 4Behavioral steps that may include potential corrective actions are shown. In certain example embodiments, the behavioral steps may include applying configuration changes to the identified NFs (e.g., reconfiguring application functions). In other example embodiments, the behavioral steps may include certain possible corrective actions, such as applying subscriber profile optimization, which may include deleting unnecessary data, eliminating unused service information, dynamically compressing data, and / or moving data to a shared profile. According to further example embodiments, the behavioral steps may include performing LCM actions at the NF level (e.g., scale-in / scaled-out) or at the network slice level (e.g., instantiating new NFs or modifying load balancing policies).

[0045] Figure 5A An apparatus 10 according to certain example embodiments is shown. In certain example embodiments, the apparatus 10 may be a node or element in a communication network or associated with such a network such as a UE, a mobile equipment (ME), a mobile station, a mobile device, a fixed device, an IoT device, or other device. As described herein, a UE may alternatively be referred to as, for example, a mobile station, a mobile equipment, a mobile unit, a mobile device, a user equipment, a subscriber station, a wireless terminal, a tablet computer, a smart phone, an IoT device, a sensor, or a NB-IoT device, etc. As an example, the apparatus 10 may be implemented, for example, in a wireless handheld device, a wireless plug-in accessory, etc.

[0046] In certain example embodiments, the apparatus 10 may include one or more processors, one or more computer-readable storage media (e.g., memory, storage, etc.), one or more radio access components (e.g., modems, transceivers, etc.), and / or a user interface. In some example embodiments, the apparatus 10 may be configured to operate using one or more radio access technologies, such as GSM, LTE, LTE-A, NR, 5G, WLAN, WiFi, NB-IoT, Bluetooth, NFC, MulteFire, and / or any other radio access technology. It should be noted that one of ordinary skill in the art will appreciate that the apparatus 10 may include Figure 5A Components or features not shown.

[0047] like Figure 5A As shown in the example of , the device 10 may include or be coupled to a processor 12 for processing information and executing instructions or operations. The processor 12 may be any type of general or special purpose processor. Specifically, for example, the processor 12 may include one or more of a general purpose computer, a special purpose computer, a microprocessor, a digital signal processor (DSP), a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), and a processor based on a multi-core processor architecture. Although in Figure 5AA single processor 12 is shown in FIG. 1 , but multiple processors may be utilized according to other example embodiments. For example, it should be understood that in some example embodiments, the apparatus 10 may include two or more processors that may form a multiprocessor system that may support multiprocessing (e.g., in which case the processor 12 may represent a multiprocessor). According to some example embodiments, the multiprocessor system may be tightly coupled or loosely coupled (e.g., to form a computer cluster).

[0048] Processor 12 may perform functions associated with the operation of device 10, including, as some examples, precoding of antenna gain / phase parameters, encoding and decoding of individual bits forming communication messages, formatting of information, and overall control of device 10, including Figure 1 system Figure 4 The process shown.

[0049] The device 10 may also include or be coupled to a memory 14 (internal or external) for storing information and instructions that can be executed by the processor 12, and the memory 14 may be coupled to the processor 12. The memory 14 may be one or more memories and of any type suitable for the local application environment, and may be implemented using any suitable volatile or non-volatile data storage technology, such as semiconductor-based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory, and / or removable memory. For example, the memory 14 may include any combination of random access memory (RAM), read-only memory (ROM), static memory such as a magnetic disk or optical disk, a hard disk drive (HDD), or any other type of non-transitory machine or computer readable medium. The instructions stored in the memory 14 may include program instructions or computer program code that, when executed by the processor 12, enables the device 10 to perform the tasks described herein.

[0050] In certain example embodiments, in one embodiment, the apparatus 10 may also include or be coupled to a (internal or external) drive or port configured to accept and read an external computer-readable storage medium, such as an optical disk, a USB drive, a flash drive, or any other storage medium. For example, the external computer-readable storage medium may store programs for execution by the processor 12 and / or the apparatus 10 to perform Figures 1 to 4 A computer program or software comprising any of the methods described.

[0051] In certain example embodiments, the apparatus 10 may also include or be coupled to one or more antennas 15 for receiving downlink signals and transmitting from the apparatus 10 via an uplink. The apparatus 10 may also include a transceiver 18 configured to send and receive information. The transceiver 18 may also include a radio interface (e.g., a modem) coupled to the antenna 15. The radio interface may correspond to a variety of radio access technologies, including one or more of GSM, LTE, LTE-A, 5G, NR, WLAN, NB-IoT, Bluetooth, BT-LE, NFC, RFID, UWB, etc. The radio interface may include other components, such as filters, converters (e.g., digital-to-analog converters, etc.), symbol demappers, signal shaping components, inverse fast Fourier transform (IFFT) modules, etc., to process symbols such as OFDMA symbols carried by the downlink or uplink.

[0052] For example, the transceiver 18 may be configured to modulate information onto a carrier waveform for transmission by the antenna(s) 15, and to demodulate information received via the antenna(s) 15 for further processing by other elements of the apparatus 10. In other example embodiments, the transceiver 18 may be capable of directly sending and receiving signals or data. Additionally or alternatively, in certain example embodiments, the apparatus 10 may include input and / or output devices (I / O devices). In certain example embodiments, the apparatus 10 may also include a user interface, such as a graphical user interface or a touch screen.

[0053] In certain example embodiments, memory 14 stores software modules that provide functionality when executed by processor 12. For example, a module may include an operating system that provides operating system functionality for device 10. Memory may also store one or more functional modules, such as applications or programs, for providing additional functionality for device 10. The components of device 10 may be implemented in hardware or any suitable combination of hardware and software. According to certain example embodiments, device 10 may optionally be configured to communicate with device 20 via a wireless or wired communication link 70 according to any radio access technology such as NR.

[0054] According to some example embodiments, processor 12 and memory 14 may be included in a processing circuit system or a control circuit system, or may form a part of a processing circuit system or a control circuit system. In addition, in some embodiments, transceiver 18 may be included in a transceiver circuit system, or may form a part of a transceiver circuit system.

[0055] Figure 5BAn apparatus 20 is shown according to certain example embodiments. In an example embodiment, the apparatus 20 may be a network element, node, host, or server in a communication network or serving such a network. For example, the apparatus 20 may be a base station, a Node B, an evolved Node B (eNB), a 5G Node B or access point, a next generation Node B (NG-NB or gNB), an AMF, an SMF, a PCF, a NEF, an AF, a UDM, a WLAN access point, and / or a collection of any combination of such elements associated with a radio access network (RAN) such as an LTE network, 5G or NR. It should be noted that a person of ordinary skill in the art will understand that the apparatus 20 may include Figure 5B Components or features not shown.

[0056] As in Figure 5B As shown in the example of , the device 20 may include a processor 22 for processing information and executing instructions or operations. The processor 22 may be any type of general or special purpose processor. For example, as an example, the processor 22 may include one or more of a general purpose computer, a special purpose computer, a microprocessor, a digital signal processor (DSP), a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), and a processor based on a multi-core processor architecture. Although in Figure 5B A single processor 22 is shown in FIG. 1 , but multiple processors may be utilized according to other embodiments. For example, it should be understood that in some example embodiments, apparatus 20 may include two or more processors that may form a multiprocessor system that may support multiprocessing (e.g., in which case processor 22 may represent a multiprocessor). In some example embodiments, the multiprocessor system may be tightly coupled or loosely coupled (e.g., to form a computer cluster).

[0057] According to certain example embodiments, processor 22 may perform functions associated with the operation of device 20, which may include, for example, precoding of antenna gain / phase parameters, encoding and decoding of individual bits forming communication messages, formatting of information, and overall control of device 20, including Figures 1 to 4 The process shown.

[0058] The device 20 may also include or be coupled to a memory 24 (internal or external) for storing information and instructions that can be executed by the processor 22, and the memory 24 may be coupled to the processor 22. The memory 24 may be one or more memories and of any type suitable for the local application environment, and may be implemented using any suitable volatile or non-volatile data storage technology, such as semiconductor-based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory, and / or removable memory. For example, the memory 24 may include any combination of random access memory (RAM), read-only memory (ROM), static memory such as a magnetic disk or optical disk, a hard disk drive (HDD), or any other type of non-transient machine or computer readable medium. The instructions stored in the memory 24 may include program instructions or computer program codes that, when executed by the processor 22, enable the device 20 to perform the tasks described herein.

[0059] In certain example embodiments, the apparatus 20 may also include or be coupled to a (internal or external) drive or port configured to accept and read an external computer-readable storage medium, such as an optical disk, a USB drive, a flash drive, or any other storage medium. For example, the external computer-readable storage medium may store programs for execution by the processor 22 and / or the apparatus 20 to perform Figures 1 to 4 A computer program or software for the method shown.

[0060] In certain example embodiments, the apparatus 20 may also include or be coupled to one or more antennas 25 for sending and receiving signals and / or data to and from the apparatus 20. The apparatus 20 may also include or be coupled to a transceiver 28 configured to send and receive information. The transceiver 28 may include, for example, a plurality of radio interfaces that may be coupled to the antenna(s) 25. The radio interfaces may correspond to a variety of radio access technologies, including one or more of GSM, NB-IoT, LTE, 5G, WLAN, Bluetooth, BT-LE, NFC, Radio Frequency Identifier (RFID), Ultra-Wideband (UWB), MulteFire, etc. The radio interfaces may include components such as filters, converters (e.g., digital-to-analog converters, etc.), mappers, Fast Fourier Transform (FFT) modules to generate symbols for transmission via one or more downlinks and receive symbols (e.g., via an uplink).

[0061] Thus, the transceiver 28 may be configured to modulate information onto a carrier waveform for transmission by the antenna(s) 25, and to demodulate information received via the antenna(s) 25 for further processing by other elements of the apparatus 20. In other example embodiments, the transceiver 28 may be capable of directly sending and receiving signals or data. Additionally or alternatively, in certain example embodiments, the apparatus 20 may include input and / or output devices (I / O devices).

[0062] In certain example embodiments, memory 24 may store software modules that provide functionality when executed by processor 22. These modules may include, for example, an operating system that provides operating system functionality for apparatus 20. Memory may also store one or more functional modules, such as applications or programs, for providing additional functionality for apparatus 20. The components of apparatus 20 may be implemented in hardware or any suitable combination of hardware and software.

[0063] According to some example embodiments, processor 22 and memory 24 may be included in a processing circuit system or a control circuit system, or may form a part of a processing circuit system or a control circuit system. In addition, in some example embodiments, transceiver 28 may be included in a transceiver circuit system, or may form a part of a transceiver circuit system.

[0064] As used herein, the term "circuitry" may refer to a hardware circuitry implementation only (e.g., analog and / or digital circuitry), a combination of hardware circuitry and software, a combination of analog and / or digital hardware circuitry and software / firmware, any portion of a hardware processor(s) (including a digital signal processor) with software that works together to enable a device (e.g., devices 10 and 20) to perform various functions, and / or hardware circuit(s) and / or processor(s), or portions thereof, which operate using software, but which may not be present when the software is not required for operation. As another example, as used herein, the term "circuitry" may also cover an implementation of a hardware circuit or processor only (or multiple processors), or a portion of a hardware circuit or processor, and its accompanying software and / or firmware. The term circuitry may also cover, for example, a baseband integrated circuit in a server, a cellular network node or device, or other computing or network device.

[0065] As described above, in certain example embodiments, the device 20 may be a network element, node, host, or server in a communication network or serving such a network. For example, the device 20 may be a base station, a node B, an evolved node B (eNB), a 5G node B or access point, a next generation node B (NG-NB or gNB), an AMF, a SMF, a PCF, a NEF, an AF, a WLAN access point, and / or a collection of any combination of such elements associated with a radio access network (RAN) such as an LTE network, 5G, or NR. According to certain embodiments, the device 20 may be controlled by the memory 24 and the processor 22 to perform functions associated with any embodiment described herein.

[0066] For example, in certain example embodiments, the apparatus 20 may be controlled by the memory 24 and the processor 22 to collect a distribution of subscriber profile sizes observed within a predefined interval of the network. The apparatus 20 may also be controlled by the memory 24 and the processor 22 to perform an analysis of the distribution. The apparatus 20 may also be controlled by the memory 24 and the processor 22 to determine a corrective action based on the analysis. In addition, the apparatus 20 may be controlled by the memory 24 and the processor 22 to determine whether a corrective action is required. When it is determined that a corrective action is required, the apparatus 20 may be controlled by the memory 24 and the processor 22 to apply the corrective action to the network. When it is determined that a corrective action is not required, the apparatus 20 may be controlled by the memory 24 and the processor 22 to collect another distribution of subscriber profile sizes.

[0067] Additional example embodiments may provide components for performing any function, step, or process described herein. For example, certain example embodiments may relate to an apparatus comprising components for collecting a distribution of subscriber profile sizes observed within a predefined interval of a network. The apparatus may also include components for performing an analysis of the distribution. The apparatus may also include components for determining corrective action based on the analysis. In addition, the apparatus may include components for determining whether corrective action is required. When it is determined that corrective action is required, the apparatus may include components for applying the corrective action to the network. When it is determined that corrective action is not required, the apparatus may include components for collecting another distribution of subscriber profile sizes.

[0068] Certain example embodiments described herein provide several technical improvements, enhancements and / or advantages over prior art processes and constitute at least an improvement in the art that can alleviate problems in subscriber profile management. In some example embodiments, subscriber profile size dynamics can be monitored at runtime and potential network-wide problems can be mitigated before they occur. The statistical distribution of subscriber profile sizes can also be tracked at the UDM. In addition, the observed distribution can be periodically reported to analysis, where trends can be derived and provided as insights to decision logic, where necessary corrective / mitigation actions are identified. According to other example embodiments, insights into subscriber profile dynamics can be provided to network operators, and optimal planning of network resources such as network bandwidth, CPU, and memory can be achieved.

[0069] A computer program product may include one or more computer executable components that, when the program is run, are configured to perform some of the various example embodiments described herein. The one or more computer executable components may be at least one software code or part thereof. Modifications and configurations required to implement the functionality of the example embodiments may be performed as (multiple) routines, which may be implemented as added or updated (multiple) software routines. (Multiple) software routines may be downloaded to a device.

[0070] As an example, the software or computer program code or part thereof may be in source code form, object code form or some intermediate form and may be stored in some carrier, distribution medium or computer readable medium, which may be any entity or device capable of carrying the program. Such carriers may include, for example, recording media, computer memory, read-only memory, optoelectronic and / or electrical carrier signals, telecommunication signals and software distribution packages. Depending on the processing power required, the computer program may be executed in a single electronic digital computer or distributed among multiple computers. The computer readable medium or computer readable storage medium may be a non-transient medium.

[0071] In other example embodiments, the functionality may be performed by hardware or circuitry included in the device, such as by using an application specific integrated circuit (ASIC), a programmable gate array (PGA), a field programmable gate array (FPGA), or any other combination of hardware and software. In yet another embodiment, the functionality may be implemented as a signal, an intangible means that may be carried by an electromagnetic signal downloaded from the Internet or other network.

[0072] According to an example embodiment, an apparatus such as a node, a device or a corresponding component may be configured as a circuit system, a computer or a microprocessor (such as a single-chip computer element) or a chipset, including at least a memory for providing storage capacity for arithmetic operations and an operation processor for performing arithmetic operations.

[0073] Those of ordinary skill in the art will readily appreciate that the example embodiments described above may be practiced with steps in a different order and / or with hardware elements in a configuration different from that disclosed. Thus, although some embodiments have been described based on these preferred example embodiments, it will be clear to those skilled in the art that certain modifications, variations, and alternative constructions will be apparent without departing from the spirit and scope of the example embodiments. Therefore, in order to determine the boundaries and limits of the example embodiments, reference should be made to the appended claims.

[0074] Partial Glossary

[0075] 5GS 5G System

[0076] 5SI 5G Synchronization Identifier

[0077] AMF Access and Mobility Function

[0078] BS Base Station

[0079] eIMS Enhanced IMS

[0080] eNB Enhanced Node B

[0081] gNB 5G or NR base station

[0082] HSS Home Subscriber Server

[0083] IMS IP Multimedia Subsystem

[0084] LTE Long Term Evolution

[0085] NEF Network Exposure Function

[0086] NF Network Function

[0087] NR New Radio

[0088] NWDAF network data analysis function

[0089] OODA Observation Oriented Determination of Behavior

[0090] PDU Protocol Data Unit

[0091] SDM Subscriber Data Management

[0092] SMF session management functions

[0093] UDICOM user data intercommunication, coexistence and migration

[0094] UDM Unified Data Management

[0095] UDR Unified Data Repository

[0096] UE User Equipment

[0097] UECM UE Context Management

[0098] URLCC Ultra-Reliable Low-Latency Communications

Claims

1. A device for communication, comprising: means for determining a size of a subscriber profile associated with a plurality of subscribers; means for creating a first distribution of said sizes of said subscriber profiles based on said determining; means for performing an analysis based on a plurality of distributions of the size of the subscriber profile, the plurality of distributions including the first distribution, each of the plurality of distributions identifying one or more bins and respective values ​​associated with a respective bin of the one or more bins, the respective bin of the one or more bins of each distribution being associated with a respective range of the size of the subscriber profile; means for determining corrective action based on said analysis; means for determining that corrective action is required; as well as Means for applying the corrective action to the network, wherein applying the corrective action comprises at least one of: reconfiguring application functions of the network; deleting data from a subscriber profile in said subscriber profile; eliminating unused service information from said subscriber profile; dynamically compressing data in the subscriber profile; dynamically moving data in the subscriber profile to a shared profile; or Perform lifecycle management actions at the network slice level.

2. The apparatus of claim 1 , wherein the means for creating the first distribution comprises: Means for incrementing, for each respective subscriber of the plurality of subscribers, a value of a first counter of a bin of the one or more bins corresponding to a respective size of the respective subscriber profile for the respective subscriber.

3. The apparatus according to claim 1 or 2, wherein the means for creating the distribution comprises: means for collecting a single-valued measure of said size of said subscriber profile; and means for reporting a number of said sizes of said subscriber profiles falling within each of a plurality of predetermined size ranges.

4. The apparatus according to claim 1 or 2, wherein the means for creating the distribution comprises: means for collecting a single-valued measure of said size of said subscriber profile; and means for calculating an average or median value of said sizes of said subscriber profiles.

5. The apparatus of claim 2, wherein the means for determining whether the corrective action is required comprises: Components for identifying misbehaving application features; means for identifying a need for optimization for said subscriber profile; Or a component used to identify requirements for lifecycle management actions for a network slice.

6. A method of communication, comprising: determining a size of a subscriber profile associated with a plurality of subscribers; creating a first distribution of the sizes of the subscriber profiles based on the determining; performing an analysis based on a plurality of distributions of the size of the subscriber profile, the plurality of distributions including the first distribution, each of the plurality of distributions identifying one or more bins and respective values ​​associated with a respective bin of the one or more bins, a respective bin of the one or more bins of each distribution being associated with a respective range of the size of the subscriber profile; determining corrective action based on the analysis; determining that corrective action is required; and Applying the corrective action to the network, wherein applying the corrective action comprises at least one of: reconfiguring application functions of the network; deleting data from a subscriber profile in said subscriber profile; eliminating unused service information from said subscriber profile; dynamically compressing data in the subscriber profile; dynamically moving data in the subscriber profile to a shared profile; or Perform lifecycle management actions at the network slice level.

7. A machine-readable medium comprising program instructions for causing an apparatus to at least perform the following: determining a size of a subscriber profile associated with a plurality of subscribers; creating a first distribution of the sizes of the subscriber profiles based on the determining; performing an analysis based on a plurality of distributions of the size of the subscriber profile, the plurality of distributions including the first distribution, each of the plurality of distributions identifying one or more bins and respective values ​​associated with a respective bin of the one or more bins, a respective bin of the one or more bins of each distribution being associated with a respective range of the size of the subscriber profile; determining corrective action based on the analysis; determining that corrective action is required; and Applying the corrective action to the network, wherein applying the corrective action comprises at least one of: reconfiguring application functions of the network; deleting data from a subscriber profile in said subscriber profile; eliminating unused service information from said subscriber profile; dynamically compressing data in the subscriber profile; dynamically moving data in the subscriber profile to a shared profile; or Perform lifecycle management actions at the network slice level.

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