FORM 2
THE PATENTS ACT, 1970 (39 OF 1970) & THE PATENT RULES, 2003
COMPLETE SPECIFICATION
(See section 10 and rule 13)
“METHOD AND SYSTEM FOR MONITORING A NETWORK LOAD ASSOCIATED WITH ONE OR MORE NETWORK
FUNCTIONS”
We, Jio Platforms Limited, an Indian National, of Office - 101, Saffron, Nr. Centre Point, Panchwati 5 Rasta, Ambawadi, Ahmedabad - 380006, Gujarat, India.
The following specification particularly describes the invention and the manner in which it is to be performed.

METHOD AND SYSTEM FOR MONITORING A NETWORK LOAD ASSOCIATED WITH ONE OR MORE NETWORK FUNCTIONS
TECHNICAL FIELD
5
[0001] Embodiments of the present disclosure generally relate to network performance management systems. More particularly, embodiments of the present disclosure relate to methods and systems for monitoring a network load associated with one or more Network Functions (NFs). 10
BACKGROUND
[0002] The following description of the related art is intended to provide
background information pertaining to the field of the disclosure. This section may
15 include certain aspects of the art that may be related to various features of the
present disclosure. However, it should be appreciated that this section is used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of the prior art.
20 [0003] Wireless communication technology has rapidly evolved over the past few
decades, with each generation bringing significant improvements and advancements. The first generation of wireless communication technology was based on analog technology and offered only voice services. However, with the advent of the second-generation (2G) technology, digital communication and data
25 services became possible, and text messaging was introduced. The third generation
(3G) technology marked the introduction of high-speed internet access, mobile video calling, and location-based services. The fourth generation (4G) technology revolutionized wireless communication with faster data speeds, better network coverage, and improved security. Currently, the fifth generation (5G) technology is
30 being deployed, promising even faster data speeds, low latency, and the ability to
connect multiple devices simultaneously. With each generation, wireless
2

communication technology has become more advanced, sophisticated, and capable of delivering more services to its users.
[0004] The 5G Core network architecture includes a plurality of network functions
5 (NFs) and network elements, which serve specific roles in facilitating a
communication between two or more user devices, applications and alike. The NFs
are building blocks of the network architecture which are associated with one or
more interfaces and have a functional behaviour. Some examples of the NFs are an
Access and Mobility Management Function (AMF), an Authentication Server
10 Function (AUSF), a Unified Data Management (UDM), a Session Management
Function (SMF), an Application Function (AF), and a Policy Control Function (PCF).
[0005] In network structures like 5G, the operation and coordination of multiple
15 individual NFs and their instances pose a significant challenge. Ensuring a proper
functioning of each NF instance is crucial for the overall performance of the network. However, the sheer number of instances makes their monitoring and management a complex and extensive task. Moreover, existing approaches often lack an efficient means of handling the load associated with these NFs.
20
[0006] Further, over the period of time various solutions have been developed to improve the performance of communication devices and to provide service-based load analytics in the network. However, there are certain challenges with existing solutions. The existing approaches for monitoring and managing Network
25 Functions (NFs) in the network structures like 5G face several limitations. The
sheer number of NF instances makes their monitoring and management complex and extensive, resulting in inefficiencies and potential performance issues. These prior solutions often lack an efficient means of handling the load associated with NFs, leading to suboptimal load distribution and potential overloading of certain
30 NF instances. This can negatively impact the overall network performance and user
experience.
3

[0007] Thus, there exists an imperative need in the art to provide an enhanced solution for monitoring a network load associated with one or more Network Functions (NFs). 5
SUMMARY
[0008] This section is provided to introduce certain aspects of the present disclosure
in a simplified form that are further described below in the detailed description.
10 This summary is not intended to identify the key features or the scope of the claimed
subject matter.
[0009] An aspect of the present disclosure may relate to a method for monitoring a network load associated with one or more Network Functions (NFs). The method
15 comprises receiving, by a transceiver unit at a Network Data Analytic Function
(NWDAF) in a network from a user, a load analytics request associated with the one or more network functions (NFs) of the network. The method further comprises fetching, by a processing unit at the NWDAF, a set of instance based data associated with the one or more NFs based on the load analytics request. The method further
20 comprises determining, by the processing unit at the NWDAF, a set of service based
data associated with the one or more NFs based on the set of instance based data. The method further comprises receiving, by the transceiver unit at the NWDAF, a real time network data associated with the one or more NFs. The method further comprises generating, by the processing unit at the NWDAF, a set of analysed
25 service based data associated with the one or more NFs based on at least one of the
set of service based data and the real time network data. The method further comprises transmitting, by the transceiver unit from the NWDAF to a NWDAF UI, the set of analysed service based data. The method further comprises monitoring, by the processing unit, the network load associated with the one or more Network
30 functions (NFs) based on the set of analysed service based data.
4

[0010] In an exemplary aspect of the present disclosure, the set of instance based data associated with the one or more NFs is fetched from one or more predefined instance data sources.
5 [0011] In an exemplary aspect of the present disclosure, the present disclosure
further comprises storing, by the processing unit in a database, the set of service based data associated with the one or more NFs.
[0012] In an exemplary aspect of the present disclosure, the set of analysed service
10 based data is generated in a predefined format.
[0013] In an exemplary aspect of the present disclosure, the set of analysed service based data is generated based on the set of service based data stored in the database and the real time network data associated with the one or more NFs.
15
[0014] Another aspect of the present disclosure may relate to a system for monitoring a network load associated with one or more Network Functions (NFs). The system comprises a transceiver unit configured to receive, at a Network Data Analytic Function (NWDAF) in a network from a user, a load analytics request
20 associated with the one or more network functions (NFs) of the network. The
system further comprises a processing unit connected to at least the transceiver unit and configured to fetch, by at the NWDAF, a set of instance based data associated with the one or more NFs based on the load analytics request. The processing unit is further configured to determine, at the NWDAF, a set of service based data
25 associated with the one or more NFs based on the set of instance based data. The
transceiver unit is further configured to receive, at the NWDAF, a real time network data associated with the one or more NFs. The processing unit is further configured to generate, at the NWDAF, a set of analysed service based data associated with the one or more NFs based on at least one of the set of service based data and the real
30 time network data. The transceiver unit is further configured to transmit, by from
the NWDAF to the NWDAF UI, the set of analysed service based data. The
5

processing unit is further configured to monitor, the network load associated with the one or more Network Functions (NFs) based on the set of analysed service based data.
5 [0015] Another aspect of the present disclosure may relate to a User Equipment
(UE) for monitoring a network load associated with one or more Network Functions (NFs). The UE comprises a memory, a processor connected to with the memory, wherein the processor is configured to monitor a network load associated with one or more Network Function (NFs) via a system. The monitoring of the network load
10 is based on receiving, by a transceiver unit of the system, at a Network Data
Analytic Function (NWDAF) in a network from a user, a load analytics request associated with the one or more network functions (NFs) of the network. The monitoring of the network load is further based on fetching, by a processing unit of the system, at the NWDAF, a set of instance based data associated with the one or
15 more NFs based on the load analytics request. The monitoring of the network load
is further based on determining, by the processing unit of the system, at the NWDAF, a set of service based data associated with the one or more NFs based on the set of instance based data. The monitoring of the network load is further based on receiving, by the transceiver unit of the system, at the NWDAF, a real time
20 network data associated with the one or more NFs. The monitoring of the network
load is further based on generating, by the processing unit of the system, at the NWDAF, a set of analysed service based data associated with the one or more NFs based on at least one of the set of service based data and the real time network data. The monitoring of the network load is further based on transmitting, by the
25 transceiver unit of the system, from the NWDAF to a NWDAF UI, the set of
analysed service based data. The monitoring of the network load is further based on monitoring, by the processing unit of the system, the network load associated with the one or more Network functions (NFs) based on the set of analysed service based data.
30
6

[0016] Yet another aspect of the present disclosure may relate to a non-transitory
computer readable storage medium storing one or more instructions for monitoring
a network load associated with one or more Network Functions (NFs), the one or
more instructions include executable code which, when executed by one or more
5 units of a system, causes a transceiver unit of the system to receive, at a Network
Data Analytic Function (NWDAF) in a network from a user, a load analytics request associated with the one or more network functions (NFs) of the network. Further, the executable code when executed causes a processing unit of the system to fetch, by at the NWDAF, a set of instance based data associated with the one or more NFs
10 based on the load analytics request. Further, the executable code when executed
causes the processing unit of the system to determine, at the NWDAF, a set of service based data associated with the one or more NFs based on the set of instance based data. Further, the executable code when executed causes the transceiver unit to receive, at the NWDAF, a real time network data associated with the one or more
15 NFs. Further, the executable code when executed causes the processing unit to
generate, at the NWDAF, a set of analysed service based data associated with the one or more NFs based on at least one of the set of service based data and the real time network data. Further, the executable code when executed causes the transceiver unit to transmit, by from the NWDAF to the NWDAF UI, the set of
20 analysed service based data. Further, the executable code when executed causes the
processing unit to monitor, the network load associated with the one or more Network Functions (NFs) based on the set of analysed service based data.
OBJECTS OF THE DISCLOSURE
25
[0017] Some of the objects of the present disclosure, which at least one embodiment disclosed herein satisfies are listed herein below.
[0018] It is an object of the present disclosure to provide a solution for monitoring
30 a network load associated with one or more network functions.
7

[0019] It is another object of the present disclosure to provide a solution for determining a set of service based data associated with each network function from the one or more NFs based on a set of instance based data associated with each network function from the one or more NFs. 5
[0020] It is another object of the present disclosure to provide a solution for receiving a real time network data associated with each network function from the one or more NFs.
10 [0021] It is another object of the present disclosure to provide a solution for
generating a set of analysed service based data associated with each network function from the one or more NFs based on at least one of the set of service based data and the real time network data.
15 [0022] It is another object of the present disclosure to provide a solution for service
based load analytics in a network.
[0023] It is another object of the present disclosure to provide a solution that receives a service based data based on the load analytics request from the user. 20
[0024] It is yet another object of the present disclosure to provide a solution to generate an analysed service based data based on the service based data.
BRIEF DESCRIPTION OF THE DRAWINGS
25
[0025] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale,
30 emphasis instead being placed upon clearly illustrating the principles of the present
disclosure. Also, the embodiments shown in the figures are not to be construed as
8

limiting the disclosure, but the possible variants of the method and system
according to the disclosure are illustrated herein to highlight the advantages of the
disclosure. It will be appreciated by those skilled in the art that disclosure of such
drawings includes disclosure of electrical components or circuitry commonly used
5 to implement such components.
[0026] FIG. 1 illustrates an exemplary block diagram representation of 5th generation core (5GC) network architecture.
10 [0027] FIG. 2 illustrates an exemplary block diagram of a computing device upon
which the features of the present disclosure may be implemented in accordance with exemplary implementation of the present disclosure.
[0028] FIG. 3 illustrates an exemplary block diagram of a system for monitoring a
15 network load associated with one or more Network Functions (NFs), in accordance
with exemplary implementations of the present disclosure.
[0029] FIG. 4 illustrates a flow diagram of a method for monitoring a network load
associated with one or more Network Functions (NFs) in accordance with
20 exemplary implementations of the present disclosure.
[0030] FIG. 5 illustrates a flow diagram of an exemplary method for monitoring a network load associated with one or more Network Functions (NFs), in accordance with exemplary implementations of the present disclosure. 25
[0031] FIG. 6 illustrates another flow diagram of an exemplary method for monitoring a network load associated with one or more Network Functions (NFs), in accordance with exemplary implementations of the present disclosure.
30
9

[0032] The foregoing shall be more apparent from the following more detailed description of the disclosure.
DETAILED DESCRIPTION
5
[0033] In the following description, for the purposes of explanation, various
specific details are set forth in order to provide a thorough understanding of
embodiments of the present disclosure. It will be apparent, however, that
embodiments of the present disclosure may be practiced without these specific
10 details. Several features described hereafter may each be used independently of one
another or with any combination of other features. An individual feature may not address any of the problems discussed above or might address only some of the problems discussed above.
15 [0034] The ensuing description provides exemplary embodiments only, and is not
intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and
20 arrangement of elements without departing from the spirit and scope of the
disclosure as set forth.
[0035] Specific details are given in the following description to provide a thorough
understanding of the embodiments. However, it will be understood by one of
25 ordinary skill in the art that the embodiments may be practiced without these
specific details. For example, circuits, systems, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail.
30 [0036] Also, it is noted that individual embodiments may be described as a process
which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure
10

diagram, or a block diagram. Although a flowchart may describe the operations as
a sequential process, many of the operations may be performed in parallel or
concurrently. In addition, the order of the operations may be re-arranged. A process
is terminated when its operations are completed but could have additional steps not
5 included in a figure.
[0037] The word “exemplary” and/or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any
10 aspect or design described herein as “exemplary” and/or “demonstrative” is not
necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed
15 description or the claims, such terms are intended to be inclusive—in a manner
similar to the term “comprising” as an open transition word—without precluding any additional or other elements.
[0038] As used herein, a “processing unit” or “processor” or “operating processor”
20 includes one or more processors, wherein processor refers to any logic circuitry for
processing instructions. A processor may be a general-purpose processor, a special
purpose processor, a conventional processor, a digital signal processor, a plurality
of microprocessors, one or more microprocessors in association with a Digital
Signal Processing (DSP) core, a controller, a microcontroller, Application Specific
25 Integrated Circuits, Field Programmable Gate Array circuits, any other type of
integrated circuits, etc. The processor may perform signal coding data processing,
input/output processing, and/or any other functionality that enables the working of
the system according to the present disclosure. More specifically, the processor or
processing unit is a hardware processor.
30
11

[0039] As used herein, “a user equipment”, “a user device”, “a smart-user-device”,
“a smart-device”, “an electronic device”, “a mobile device”, “a handheld device”,
“a wireless communication device”, “a mobile communication device”, “a
communication device” may be any electrical, electronic and/or computing device
5 or equipment, capable of implementing the features of the present disclosure. The
user equipment/device may include, but is not limited to, a mobile phone, smart
phone, laptop, a general-purpose computer, desktop, personal digital assistant,
tablet computer, wearable device or any other computing device which is capable
of implementing the features of the present disclosure. Also, the user device may
10 contain at least one input means configured to receive an input from unit(s) which
are required to implement the features of the present disclosure.
[0040] As used herein, “storage unit” or “memory unit” refers to a machine or computer-readable medium including any mechanism for storing information in a
15 form readable by a computer or similar machine. For example, a computer-readable
medium includes read-only memory (“ROM”), random access memory (“RAM”), magnetic disk storage media, optical storage media, flash memory devices or other types of machine-accessible storage media. The storage unit stores at least the data that may be required by one or more units of the system to perform their respective
20 functions.
[0041] As used herein “interface” or “user interface refers to a shared boundary
across which two or more separate components of a system exchange information
or data. The interface may also be referred to a set of rules or protocols that define
25 communication or interaction of one or more modules or one or more units with
each other, which also includes the methods, functions, or procedures that may be called.
[0042] All modules, units, components used herein, unless explicitly excluded
30 herein, may be software modules or hardware processors, the processors being a
general-purpose processor, a special purpose processor, a conventional processor, a
12

digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASIC), Field Programmable Gate Array circuits (FPGA), any other type of integrated circuits, etc. 5
[0043] As used herein the transceiver unit include at least one receiver and at least one transmitter configured respectively for receiving and transmitting data, signals, information or a combination thereof between units/components within the system and/or connected with the system.
10
[0044] As discussed in the background section, the current known solutions for monitoring a network load associated with one or more network functions and for service based load analytics in the network have several shortcomings such as the sheer number of network function (NF) instances complicates their monitoring and
15 management processes, resulting in increased complexity and resource
requirements. Secondly, these solutions lack an efficient mechanism for handling the load associated with NFs, leading to suboptimal load distribution and potential performance bottlenecks. Additionally, the current approaches fail to effectively address the service-based load of NFs, which limits their ability to dynamically
20 allocate resources and optimize network performance. As a result, the overall
network efficiency and user experience are compromised.
[0045] Therefore, the present disclosure aims to overcome the above-mentioned and other existing problems in this field of technology by disclosing a novel
25 solution for monitoring and managing individual instances in an ecosystem,
particularly in the context of network functions (NFs). The novel solution involves the receiving a Network Data Analytic Function (NWDAF) in a network from a user, a load analytics request which is associated with the network functions (NFs) of the network. Further, a set of instance based data associated with the NFs are
30 fetched. Thereafter a set of service based data associated with the NFs are
determined based on the set of instance based data. Furthermore, a real time
13

network data associated with the NFs is received, and a set of analysed service
based data associated with the NFs is generated based on the set of service based
data and the real time network data. Thereafter, the set of analysed service based
data is transmitted from the NWDAF to a NWDAF user interface (UI), and then the
5 NFs are monitored based on the set of analysed service based data.
[0046] FIG. 1 illustrates an exemplary block diagram representation of 5th generation core (5GC) network architecture, in accordance with exemplary implementation of the present disclosure. As shown in fig. 1, the 5GC network
10 architecture [100] includes a user equipment (UE) [102], a radio access network
(RAN) [104], an access and mobility management function (AMF) [106], a Session Management Function (SMF) [108], a Service Communication Proxy (SCP) [110], an Authentication Server Function (AUSF) [112], a Network Slice Specific Authentication and Authorization Function (NSSAAF) [114], a Network Slice
15 Selection Function (NSSF) [116], a Network Exposure Function (NEF) [118], a
Network Repository Function (NRF) [120], a Policy Control Function (PCF) [122], a Unified Data Management (UDM) [124], an application function (AF) [126], a User Plane Function (UPF) [128], and a data network (DN) [130], wherein all the components are assumed to be connected to each other in a manner as obvious to
20 the person skilled in the art for implementing features of the present disclosure.
[0047] Radio Access Network (RAN) [104] is a part of a mobile
telecommunications system that connects user equipment (UE) [102] to the core
network (CN) and provides access to different types of networks (e.g., 5G network).
25 It consists of radio base stations and the radio access technologies that enable
wireless communication.
[0048] Access and Mobility Management Function (AMF) [106] is a 5G core
network function responsible for managing access and mobility aspects, such as UE
30 registration, connection, and reachability. It also handles mobility management
procedures like handovers and paging.
14

[0049] Session Management Function (SMF) [108] is a 5G core network function
responsible for managing session-related aspects, such as establishing, modifying,
and releasing sessions. It coordinates with the User Plane Function (UPF) for data
5 forwarding and handles IP address allocation and QoS enforcement.
[0050] Service Communication Proxy (SCP) [110] is a network function in the 5G
core network that facilitates communication between other network functions by
providing a secure and efficient messaging service. It acts as a mediator for service-
10 based interfaces.
[0051] Authentication Server Function (AUSF) [112] is a network function in the 5G core responsible for authenticating UEs during registration and providing security services. It generates and verifies authentication vectors and tokens.
15
[0052] Network Slice Specific Authentication and Authorization Function (NSSAAF) [114] is a network function that provides authentication and authorization services specific to network slices. It ensures that UEs can access only the slices for which they are authorized.
20
[0053] Network Slice Selection Function (NSSF) [116] is a network function responsible for selecting the appropriate network slice for a UE based on factors such as subscription, requested services, and network policies.
25 [0054] Network Exposure Function (NEF) [118] is a network function that exposes
capabilities and services of the 5G network to external applications, enabling integration with third-party services and applications.
[0055] Network Repository Function (NRF) [120] is a network function that acts
30 as a central repository for information about available network functions and
services. It facilitates the discovery and dynamic registration of network functions.
15

[0056] Policy Control Function (PCF) [122] is a network function responsible for policy control decisions, such as QoS, charging, and access control, based on subscriber information and network policies. 5
[0057] Unified Data Management (UDM) [124] is a network function that centralizes the management of subscriber data, including authentication, authorization, and subscription information.
10 [0058] Application Function (AF) [126] is a network function that represents
external applications interfacing with the 5G core network to access network capabilities and services.
[0059] User Plane Function (UPF) [128] is a network function responsible for
15 handling user data traffic, including packet routing, forwarding, and QoS
enforcement.
[0060] Data Network (DN) [130] refers to a network that provides data services to
user equipment (UE) in a telecommunications system. The data services may
20 include but are not limited to Internet services, private data network related services.
[0061] FIG. 2 illustrates an exemplary block diagram of a computing device [200] upon which the features of the present disclosure may be implemented in accordance with exemplary implementation of the present disclosure. In an
25 implementation, the computing device [200] may also implement a method for
monitoring a network load associated with one or more Network Functions (NFs) utilising the system [300]. In another implementation, the computing device [200] itself implements the method for monitoring the network load associated with the one or more Network Functions (NFs) using one or more units configured within
30 the computing device [200], wherein said one or more units are capable of
implementing the features as disclosed in the present disclosure.
16

[0062] The computing device [200] may include a bus [202] or other
communication mechanism for communicating information, and a processor [204]
coupled with the bus [202] for processing information. The processor [204] may
5 be, for example, a general-purpose microprocessor. The computing device [200]
may also include a main memory [206], such as a random-access memory (RAM), or other dynamic storage device, coupled to the bus [202] for storing information and instructions to be executed by the processor [204]. The main memory [206] also may be used for storing temporary variables or other intermediate information
10 during execution of the instructions to be executed by the processor [204]. Such
instructions, when stored in non-transitory storage media accessible to the processor [204], render the computing device [200] into a special-purpose machine that is customized to perform the operations specified in the instructions. The computing device [200] further includes a read only memory (ROM) [208] or other static
15 storage device coupled to the bus [202] for storing static information and
instructions for the processor [204].
[0063] A storage device [210], such as a magnetic disk, optical disk, or solid-state drive is provided and coupled to the bus [202] for storing information and
20 instructions. The computing device [200] may be coupled via the bus [202] to a
display [212], such as a cathode ray tube (CRT), Liquid crystal Display (LCD), Light Emitting Diode (LED) display, Organic LED (OLED) display, etc. for displaying information to a computer user. An input device [214], including alphanumeric and other keys, touch screen input means, etc. may be coupled to the
25 bus [202] for communicating information and command selections to the processor
[204]. Another type of user input device may be a cursor controller [216], such as a mouse, a trackball, or cursor direction keys, for communicating direction information and command selections to the processor [204], and for controlling cursor movement on the display [212]. The input device typically has two degrees
30 of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allow
the device to specify positions in a plane.
17

[0064] The computing device [200] may implement the techniques described
herein using customized hard-wired logic, one or more ASICs or FPGAs, firmware
and/or program logic which in combination with the computing device [200] causes
5 or programs the computing device [200] to be a special-purpose machine.
According to one implementation, the techniques herein are performed by the computing device [200] in response to the processor [204] executing one or more sequences of one or more instructions contained in the main memory [206]. Such instructions may be read into the main memory [206] from another storage medium,
10 such as the storage device [210]. Execution of the sequences of instructions
contained in the main memory [206] causes the processor [204] to perform the process steps described herein. In alternative implementations of the present disclosure, hard-wired circuitry may be used in place of or in combination with software instructions.
15
[0065] The computing device [200] also may include a communication interface [218] coupled to the bus [202]. The communication interface [218] provides a two-way data communication coupling to a network link [220] that is connected to a local network [222]. For example, the communication interface [218] may be an
20 integrated services digital network (ISDN) card, cable modem, satellite modem, or
a modem to provide a data communication connection to a corresponding type of telephone line. As another example, the communication interface [218] may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links may also be implemented. In any such
25 implementation, the communication interface [218] sends and receives electrical,
electromagnetic or optical signals that carry digital data streams representing various types of information.
[0066] The computing device [200] can send messages and receive data, including
30 program code, through the network(s), the network link [220] and the
communication interface [218]. In the Internet example, a server [230] might
18

transmit a requested code for an application program through the Internet [228], the
ISP [226], the local network [222], the host [224] and the communication interface
[218]. The received code may be executed by the processor [204] as it is received,
and/or stored in the storage device [210], or other non-volatile storage for later
5 execution.
[0067] Referring to FIG. 3, an exemplary block diagram of a system [300] for monitoring a network load associated with one or more Network Functions (NFs), is shown, in accordance with the exemplary implementations of the present
10 disclosure. The system [300] comprises at least one transceiver unit [304], at least
one processing unit [306] and at least one database [310]. Also, all of the components/ units of the system [300] are assumed to be connected to each other unless otherwise indicated below. As shown in the figures all units shown within the system [300] should also be assumed to be connected to each other. Also, in Fig.
15 3 only a few units are shown, however, the system [300] may comprise multiple
such units or the system [300] may comprise any such numbers of said units, as required to implement the features of the present disclosure. Further, in an implementation, the system [300] may be present in a user device/ user equipment [102] to implement the features of the present disclosure. The system [300] may be
20 a part of the user device [102]/ or may be independent of but in communication
with the user device [102] (may also referred herein as a UE). In another implementation, the system [300] may reside in a server or a network entity. In yet another implementation, the system [300] may reside partly in the server/ network entity and partly in the user device.
25
[0068] The system [300] is configured for monitoring the network load associated with the one or more Network Functions (NFs), with the help of the interconnection between the components/units of the system [300].
30 [0069] In order to monitor the network load associated with one or more Network
Functions (NFs), the transceiver unit [304] is configured to receive, at a Network
19

Data Analytic Function (NWDAF) [302] in a network from a user, a load analytics request associated with the one or more network functions (NFs) of the network.
[0070] As used herein, the “Network Data Analytic Function (NWDAF) [302]”
5 incorporates one or more standard interfaces from a service -based architecture to
collect a data by a subscription or request model from one or more network functions (NFs) and similar procedures. The NWDAF [302] is configured to deliver one or more analytics functions in the network for automation of one or more tasks such as reporting, solving interface or format challenges. 10
[0071] The present disclosure encompasses that the load analytics request refers to a message sent from the user to the NWDAF [302] for performing the load analytics of the one or more NFs of the network.
15 [0072] Further, the load analytics refers to examination of one or more parameters
associated with the one or more NFs. The one or more parameters may include, but are not limited to, a traffic pattern, a user behaviour, a network resource utilization for analysing one or more aspects such as a peak load time, a traffic distribution, a resource allocation, etc. The traffic pattern includes an information about
20 communication between multiple nodes in the network. The user behaviour refers
to one or more activities done by the user while interacting with the network. The network resource utilization refers to an amount or a percentage of available network capacity that is currently being used for the one or more activities done by the user while interacting with the network. Also, the network resource utilization
25 is the proportion of the current network traffic with respect to a maximum amount
of traffic that can be handled by each of the one or more NFs. The network utilization indicates a bandwidth consumption in the network.
[0073] As used herein, “network function” refers to a virtualized network
30 component that performs a specific procedure (such as a handover procedure, a
messaging procedure, a call establishment procedure, etc.) in the network such as
20

an access and mobility management function (AMF) [106], a Session Management Function (SMF) [108], etc.
[0074] Further, the processing unit [306] is connected to at least the transceiver unit
5 [304]. The processing unit [306] is configured to fetch, at the NWDAF [302], a set
of instance based data associated with the one or more NFs based on the load analytics request.
[0075] The present disclosure encompasses that the set of instance based data refers
10 to one or more specific data instances or measurements which are associated with
the NFs within the network. For example, the set of instance based data may include, but not limited to, a current bandwidth usage associated with a particular NF, a latency metric associated with the particular NF, or an error rate associated with the particular NF. 15
[0076] The current bandwidth usage refers to a maximum rate of data transfer
across the network. The latency metric refers to a time delay between sending a
request and receiving a response associated with the request. The error rate indicates
a frequency of errors encountered during the data transmission or processing within
20 the network.
[0077] The present disclosure encompasses that the processing unit [306] may fetch
the set of instance based data via one or more data fetching techniques such as a
GraphQL data fetching technique, a cases enabled data fetching technique, or any
25 other such similar technique that may be appreciated by a person skilled in the art
to implement the solution of the present disclosure. The one or more data fetching techniques may be stored in the database [310] and/or pre-defined by an administrator.
21

[0078] The present disclosure encompasses that the set of instance based data associated with the one or more NFs is fetched from one or more predefined instance data sources.
5 [0079] The present disclosure encompasses that the one or more predefined
instance data sources may include the one or more NFs like the access and mobility management function (AMF) [106], the Session Management Function (SMF) [108], an Operations, Administration, and Maintenance (OAM) systems, an Application Functions (AFs), etc.
10
[0080] The present disclosure encompasses that the one or more predefined instance data sources may include but not limited to one or more monitoring systems, one or more network devices, one or more management systems or any other network entity associated with the network that may be appreciated by a
15 person skilled in the art to implement the solution of the present disclosure. The one
or more monitoring system refers to a dedicated system or a platform for collecting and storing a network performance data such as the OAM systems. The one or more network devices may include a routers, a switch which may generate an operational data related to their respective functions. The one or more management systems
20 refer to a centralized system that collect the data from multiple network components
for analysis and reporting.
[0081] The processing unit [306] is further configured to determine, at the NWDAF
[302], a set of service based data associated with the one or more NFs based on the
25 set of instance based data.
[0082] The present disclosure encompasses that the set of service based data refers
to a collection of data related to one or more services provided by the one or more
NFs. The set of service based data may relate to one or more services provided by
30 the one or more NFs such as a network function (NF) service discovery, a NF
service authorization, a communication service, a location service and like.
22

[0083] The NF service discovery refers to a service rendered by a control plane
network function within the network. The NF service discovery enables the control
5 plane network function or the Service Communication Proxy (SCP) for discovering
one or more NF instances which provides one or more expected NF services such as a Nnrf_NF management service (i.e., a service allowing Network Functions (NFs) in the network to register, update, and deregister NF Profiles at the Network Repository Function (NRF)), an NRF status subscribing service, etc. 10
[0084] The NF service authorization ensures that a NF service consumer is authorized to access the NF service provided by a NF service provider.
[0085] The communication service enables the NF service consumer to
15 communicate with the UE via the access and Mobility Management Function
(AMF) [106].
[0086] The location service enables the NF consumer to request a location information for a target UE.
20
[0087] For example, the AMF [106] provide a plurality of services such as a registration management, a connection management, a reachability management, a mobility management and an access authentication. Hence, the set of service based data of the AMF [106] (i.e., network function) may include an information/data
25 related to the one or services provided by the AMF [106]. Also, the set of service
based data may be a historical data associated with the set of services of the NF (for e.g., past one month data, last year data).
[0088] The present disclosure encompasses that the processing unit [306] may
30 utilize one or more data processing or one or more data fetching techniques for
determining the set of service based data associated with the one or more NFs based
23

on the set of instance based data such as an edge computing technique, and any other such similar technique that may be appreciated by a person skilled in the art to implement the solution of the present disclosure. The one or more data processing techniques may be stored in database [310] and/or pre-defined by an administrator. 5
[0089] The present disclosure encompasses that the processing unit [306] is further configured to store in a database [310], the set of service based data associated with the one or more NFs.
10 [0090] The transceiver unit [304] is further configured to receive, at the NWDAF
[302], a real time network data associated with the one or more NFs.
[0091] The present disclosure encompasses that the real time network data may refer to a data that is generated and transmitted immediately after occurrence of an
15 event such as a data transmission, within the network. The real time network data
may include a current bandwidth usage, a current error rate, a current latency metric, etc. Further, the real time network data may provide one or more insights into an operational status and a performance of the one or more network functions at a given instance of time.
20
[0092] For example, the AMF [106] provides the plurality of services such as S1, S2 and S3. If the processing unit [306] fetches/determines the set of the service data related to the service S1, then the processing unit may further fetch the real time network data related to the service S1 from the AMF [106].
25
[0093] The processing unit [306] is further configured to generate, at the NWDAF [302], a set of analysed service based data associated with the one or more NFs based on at least one of the set of service based data and the real time network data.
30 [0094] The present disclosure encompasses that the processing unit [306] may
analyse the set of service based data and the real time network data to obtain the set
24

of analysed service based data. The processing unit [306] may compare the set of
service based data with the real time network data to obtain the set of analysed
service based data. Moreover, the processing unit [306] may utilize one or more
data analysis techniques to process the set of service based data and the real time
5 network data for obtaining the set of analysed service based data. Further, the one
or more data analysis techniques may be an edge analytics technique and any other such similar technique that may be appreciated by a person skilled in the art to implement the solution of the present disclosure.
10 [0095] For example, the processing unit may retrieve the set of instance based data
of the one or more NFs (such as NF (A), NF (B)), Further, the processing unit may determine the set of service based data (S1, S2, S3) which is associated with the one or more NFs based on the set of instance based data. The set of service based data that may be a historical service based data over a period of a predefined time
15 such as last one month, last six months, last year, etc. Thereafter, the processing unit
receive the real time network data associated with the one or more NFs (i.e., NF (A), NF (B)). Further, the processing unit [306] may compare the set of service based data (i.e., historical set of service data) with the real time network data to obtain the set of analysed service based data. Further, in an implementation, the
20 processing unit [306] may analyse a network data associated with particular service
associated with the network by comparing the historical set of service data (e.g., previous month's call records, SMS logs, and data usage patterns) with the real-time network data (e.g., current call volumes, message traffic, and data transmission rates) to determine the set of analysed service based data. For example, the set of
25 analysed service based data may indicate a 20% increase in call volumes during
peak hours, a 15% rise in SMS traffic among subscribers in a specific region, and a 30% surge in data usage due to a popular new mobile application. Additionally, the analysis may identify trends like a higher call failure rate in a specific area, a spike in data usage during special events, and any other such like trend.
30
25

[0096] The transceiver unit [304] is further configured to transmit, from the NWDAF to the NWDAF user interface (UI) [308], the set of analysed service based data.
5 [0097] The present disclosure encompasses that the NWDAF UI [308] refers to a
user interface that may be a visual interface or a graphical user interface which allows the user to interact with the NWDAF [302]. The user may include the administrator, an operator or an analyst.
10 [0098] The present disclosure encompasses that the set of analysed service based
data is generated in a predefined format.
[0099] The present disclosure encompasses that the predefined format refers to a
pre-determined structure or a pre-define layout or a pre-defined schema for ensuring
15 consistency and compatibility of the data such as tables, graphs, charts, trends, and
any other such similar predefined format that may be appreciated by a person skilled in the art to implement the solution of the present disclosure.
[0100] The present disclosure encompasses that the set of analysed service based
20 data is generated based on the set of service based data stored in the database [310]
and the real time network data associated with the one or more NFs.
[0101] The processing unit [306] is further configured to monitor, the network load
associated with the one or more Network Functions (NFs) based on the set of
25 analysed service based data.
[0102] The present disclosure encompasses that the monitoring of the network load
refers to a continuous observation, measurement, and analysis of network load
associated with one or more Network Functions (NFs) based on the set of analysed
30 service based data. The monitoring of the network load helps to ensure an optimal
performance, identify one or more potential issues for maintain or enhancing the
26

service quality of the network. Further, the monitoring of the network load may facilitate in identifying one or more insights, one or more patterns, one or more trends, and one or more anomalies.
5 [0103] The present disclosure encompasses that the processing unit [306] may
observe, track, analyse the network load associated with the one or more Network
Functions (NFs) based on the set of analysed service based data. Further, in an
implementation of the present disclosure, the processing unit [306] may recommend
one or more enhancement steps such a load balancing step, an NF addition step, an
10 NF deletion step, etc. based on the observation, the tracking, performing the
analysis of the network load associated with the one or more Network Functions (NFs).
[0104] Referring to FIG. 4, wherein a flow diagram of a method [400] for
15 monitoring a network load associated with one or more Network Functions (NFs),
in accordance with exemplary implementations of the present disclosure is shown.
In an implementation the method [400] is performed by the system [300]. Further,
in an implementation, the system [300] may be present in a server device to
implement the features of the present disclosure. Also, as shown in Fig. 4, the
20 method [400] starts at step [402].
[0105] At step [404], the method [400] comprises receiving, by a transceiver unit
[304] at a Network Data Analytic Function (NWDAF) [302] in a network from a
user, a load analytics request associated with the one or more network functions
25 (NFs) of the network.
[0106] As used herein, the “Network Data Analytic Function (NWDAF) [302]”
incorporates one or more standard interfaces from a service -based architecture to
collect a data by a subscription or request model from one or more network
30 functions (NFs) and similar procedures. The NWDAF [302] is configured to deliver
27

one or more analytics functions in the network for automation of one or more tasks such as reporting, solving interface or format challenges.
[0107] The present disclosure encompasses that the load analytics request refers to
5 a message sent from the user to the NWDAF [302] for performing the load analytics
of the one or more NFs of the network.
[0108] Further, the load analytics refers to examination of one or more parameters associated with the one or more NFs. The one or more parameters may include but
10 are not limited to a traffic pattern, a user behaviour, a network resource utilization
for analysing one or more aspects such as a peak load time, a traffic distribution, a resource allocation, etc. The traffic pattern includes an information about communication between multiple nodes in the network. The user behaviour refers to one or more activities done by the user while interacting with the network. The
15 network resource utilization refers to an amount or a percentage of available
network capacity that is currently being used for the one or more activities done by the user while interacting with the network. Also, the network resource utilization is the proportion of the current network traffic with respect to maximum amount of traffic that can be handled by each of the one or more NFs. The network utilization
20 indicates a bandwidth consumption in the network.
[0109] As used herein, “network function” refers to a virtualized network
component that performs a specific procedure (such as a handover procedure, a
message procedure, a call establishment procedure, etc.) function in the network
25 such as an access and mobility management function (AMF) [106], a Session
Management Function (SMF) [108], etc.
[0110] At step [406], the method [400] comprises fetching, by a processing unit
[306] at the NWDAF [302], a set of instance based data associated with the one or
30 more NFs based on the load analytics request.
28

[0111] The present disclosure encompasses that the set of instance based data refers
to one or more specific data instances or measurements which are associated with
the NFs within the network. For example, the set of instance based data may include
but not limited to a current bandwidth usage associated with a particular NF, a
5 latency metric associated with the particular NF, or an error rate associated with the
particular NF.
[0112] The current bandwidth usage refers to a maximum rate of data transfer
across the network. The latency metric refers to a time delay between sending a
10 request and receiving a response associated with the request. The error rate indicates
a frequency of errors encountered during the data transmission or processing within the network.
[0113] The present disclosure encompasses that the processing unit [306] may fetch
15 the set of instance based data via one or more data fetching techniques such as a
GraphQL data fetching technique, a cases enabled data fetching technique, or any
other such similar technique that may be appreciated by a person skilled in the art
to implement the solution of the present disclosure. The one or more data fetching
techniques may be stored in the database [310] and/or pre-defined by an
20 administrator.
[0114] The present disclosure encompasses that the set of instance based data associated with the one or more NFs is fetched from one or more predefined instance data sources.
25
[0115] The present disclosure encompasses that the one or more predefined instance data sources may include the one or more NFs like the access and mobility management function (AMF) [106], the Session Management Function (SMF) [108], an Operations, Administration, and Maintenance (OAM) systems, an
30 Application Functions (AFs), etc.
29

[0116] The present disclosure encompasses that the one or more predefined
instance data sources may include but not limited to one or more monitoring
systems, one or more network devices, one or more management systems or any
other network entity associated with the network that may be appreciated by a
5 person skilled in the art to implement the solution of the present disclosure system
or database [310]. The one or more monitoring system refers to a dedicated system
or a platform for collecting and storing a network performance data. The one or
more network devices may include a routers, a switch which may generate an
operational data related to their respective functions. The one or more management
10 systems refers to a centralized system that collect the data from multiple network
components for analysis and reporting.
[0117] At step [408], the method [400] comprises determining, by the processing
unit [306] at the NWDAF [302], a set of service based data associated with the one
15 or more NFs based on the set of instance based data.
[0118] The present disclosure encompasses that the set of service based data refers
to a collection of data related to one or more services provided by the one or more
NFS. The set of service based data may relate to one or more services provided by
20 the one or more NFs such as a network function (NF) service discovery, a NF
service authorization, a communication service, a location service and like.
[0119] The NF service discovery refers to a service rendered by a control plane network function within the network. The NF service discovery enables the control
25 plane network function or the Service Communication Proxy (SCP) for discovering
one or more NF instances which provides one or more expected NF services such as a Nnrf_NF management service (i.e., a service allowing Network Functions (NFs) in the network to register, update, and deregister NF Profiles at the Network Repository Function (NRF)), an NRF status subscribing service, etc.
30
30

[0120] The NF service authorization ensures that a NF service consumer is authorized to access the NF service provided by a NF service provider.
[0121] The communication service enables the NF service consumer to
5 communicate with the UE via the access and Mobility Management Function
(AMF) [106].
[0122] The location service enables the NF consumer to request a location information for a target UE.
10
[0123] For example, the AMF [106] provide a plurality of services such as a registration management, a connection management, a reachability management, a mobility management and an access authentication. Hence, the set of service based data of the AMF [106] (i.e., network function) may include an information/data
15 related to the one or services provided by the AMF [106]. Also, the set of service
based data may be a historical data associated with the set of services of the NF (for e.g., past one month data, last year data).
[0124] The present disclosure encompasses that the processing unit [306] may
20 utilize one or more data processing or one or more data fetching techniques for
determining the set of service based data associated with the one or more NFs based
on the set of instance based data such as an edge computing technique, and any
other such similar technique that may be appreciated by a person skilled in the art
to implement the solution of the present disclosure. The one or more data processing
25 techniques may be stored in the database [310] and/or pre-defined by an
administrator.
[0125] The present disclosure encompasses that the method further comprises
storing, by the processing unit [306] in a database [310], the set of service based
30 data associated with the one or more NFs.
31

[0126] At step [410], the method [400] comprises receiving, by the transceiver unit [304] at the NWDAF [302], a real time network data associated with the one or more NFs.
5 [0127] The present disclosure encompasses that the real time network data may
refer to a data that is generated and transmitted immediately after occurrence of an
event such as a data transmission, within the network. The real time network data
may include a current bandwidth usage, a current error rate, a current latency metric
and etc. Further, the real time network data may provide one or more insights into
10 an operational status and a performance of the one or more network components
functions at a given instance of time.
[0128] For example, the AMF [106] provides the plurality of services such as S1,
S2 and S3. If the processing unit [306] fetches/determines the set of the service data
15 related to the service S1, then the processing unit may further fetch the real time
network data related to the service S1 from the AMF [106].
[0129] At step [412], the method [400] comprises generating, by the processing
unit [306] at the NWDAF [302], a set of analysed service based data associated
20 with the one or more NFs based on at least one of the set of service based data and
the real time network data.
[0130] The present disclosure encompasses that the processing unit [306] may analyse the set of service based data and the real time network data to obtain the set
25 of analysed service based data. The processing unit [306] may compare the set of
service based data with the real time network data to obtain the set of analysed service based data. Moreover, the processing unit [306] may utilize one or more data analysis techniques to process the set of service based data and the real time network data for obtaining the set of analysed service based data. Further, the one
30 or more data analysis techniques may be an edge analytics technique and any other
32

such similar technique that may be appreciated by a person skilled in the art to implement the solution of the present disclosure.
[0131] For example, the processing unit may retrieve the set of instance based data
5 of the one or more NFs (such as NF (A), NF (B)), Further, the processing unit may
determine the set of service based data (S1, S2, S3) which is associated with the one or more NFs based on the set of instance based data. The set of service based data that may be a historical service based data over a period of a predefined time such as last one month, last six months, last year, etc. Thereafter, the processing unit
10 receive the real time network data associated with the one or more NFs (i.e., NF
(A), NF (B)). Further, the processing unit may compare the set of service based data (i.e., historical set of service data) with the real time network data to obtain the set of analysed service based data. Further, in an implementation, the processing unit [306] may analyse a network data associated with particular service associated with
15 the network by comparing the historical set of service data (e.g., previous month's
call records, SMS logs, and data usage patterns) with the real-time network data (e.g., current call volumes, message traffic, and data transmission rates) to determine the set of analysed service based data. For example, the set of analysed service based data may indicate a 20% increase in call volumes during peak hours,
20 a 15% rise in SMS traffic among subscribers in a specific region, and a 30% surge
in data usage due to a popular new mobile application. Additionally, the analysis may identify trends like a higher call failure rate in a specific area, a spike in data usage during special events, and any other such like trend.
25 [0132] At step [414], the method [400] comprises transmitting, the transceiver unit
[304] from the NWDAF [302] to a NWDAF UI [308], the set of analysed service based data.
[0133] The present disclosure encompasses that the NWDAF UI [308] refers to a
30 user interface that may be a visual interface or a graphical user interface which
33

allows the user to interact with the NWDAF [302]. The user may include the administrator, an operator or an analyst.
[0134] The present disclosure encompasses that the NWDAF UI [308] refer to a
5 user interface that may a visual interface or a graphical interface which allows the
user to interact with the NWDAF [302]. The user may include the administrator, an operator or an analyst.
[0135] The present disclosure encompasses that the set of analysed service based
10 data is generated in a predefined format.
[0136] The present disclosure encompasses that the predefine format refers to a
pre-determined structure or a pre-define layout or a pre-defined schema for ensuring
consistency and compatibility of the data such as tables, graphs, charts, trends, and
15 any other such similar predefined format that may be appreciated by a person skilled
in the art to implement the solution of the present disclosure.
[0137] The present disclosure encompasses that the set of analysed service based
data is generated based on the set of service based data stored in the database [310]
20 and the real time network data associated with the one or more NFs.
[0138] At step [416], the method [400] comprises monitoring, by the processing unit [306], the network load associated with the one or more Network functions (NFs) based on the set of analysed service based data.
25
[0139] The present disclosure encompasses that the monitoring of the network load refers to a continuous observation, measurement, and analysis of network load associated with one or more Network Functions (NFs) based on the set of analysed service based data. The monitoring of the network load helps to ensure an optimal
30 performance, identify one or more potential issues for maintain or enhancing the
service quality of the network. Further, the monitoring of the network load may
34

facilitate in identifying one or more insights, one or more patterns, one or more trends, and one or more anomalies.
[0140] The present disclosure encompasses that the processing unit [306] may
5 observe, track, analyse the network load associated with the one or more Network
Functions (NFs) based on the set of analysed service-based data. Further, in an
implementation of the present disclosure, the processing unit [306] may recommend
one or more enhancement steps such a load balancing step, an NF addition step, an
NF deletion step, etc based on the observation, the tracking, performing the analysis
10 of the network load associated with the one or more Network Functions (NFs).
[0141] Thereafter, the method [400] terminates at step [418].
[0142] Referring to FIG. 5, a flow diagram of an exemplary method [500] for
15 monitoring a network load associated with one or more Network Functions (NFs),
in accordance with exemplary implementations of the present disclosure is shown. In an implementation, the method [500] is performed by the system [300]. The flow diagram depicted in [500] in an exemplary illustration only, and is not intended to limit the scope, applicability, or configuration of the disclosure. 20
[0143] Also, as shown in FIG.5, the method [500] starts at step S1.
[0144] At step S2, a user request (i.e. the load analytics request) is received at a
user interface for a load analytics data. The user interface may be a Network Data
25 Analytic Function user interface (NWDAF UI) [308].
[0145] Upon receiving, the request for the load analytics, a set of instance based
data is fetched. The set of instance based data is related to the one or more NFs such
as an access and mobility management function (AMF) [106], a Session
30 Management Function (SMF) [108] and alike. Thereafter, a service based data (such
as S1, S2, S3) is received based on the load analytics request from a source (like
35

the one or more NFs). Further, the service based data is associated with the one or more NFs based on a set of instance based data. Thereafter, a real time network data corresponding to the one or more NFs is received at the NWDAF [302].
5 [0146] At step S3, a Network Data Analytic Function (NWDAF) [302] perform an
analysis on the service based data collected from the source. In step S3, the
NWDAF [302] compares the real time network data with the service based data.
For example, an NF such as the AMF [106], provides one or more services S1, S2,
S3 and S4. The service data relating to service S1 is fetched, wherein the service-
10 based data is historical data (i.e., historical service data) and the real time network
data of the service S1 is fetched. Thereafter, the real time network data of the service
S1 is compared with the historical service data i.e., the service-based data to obtain
an analysed service-based data.
15 [0147] At step S4, a data i.e., the analysed service based data, obtained based on
the analysis performed at step S3 (i.e., comparing the real time network data of the service S1 with the historical service data), is provided to the user on the user interface i.e., the NWDAF UI [308]. The result of the comparison (i.e. the analysed service based data) is displayed onto the user interface at step S4. Moreover, the
20 result may be displayed in a pre-defined format. The set of analysed service based
data may indicate the network load associated with the one or more Network Functions (NFs). For instance, the set of analysed service based data may indicate a pattern and/or trend through which the network load may be determined. For example, the processing unit may retrieve the set of instance based data of the one
25 or more NFs (such as NF (A), NF (B)), Further, the processing unit may determine
the set of service based data (S1, S2, S3) which is associated with the one or more NFs based on the set of instance based data. The set of service based data that may be a historical service based data over a period of a predefined time such as last one month, last six months, last year, etc. Thereafter, the processing unit receive the real
30 time network data associated with the one or more NFs (i.e., NF (A), NF (B)).
Further, the processing unit may compare the set of service based data (i.e.,
36

historical set of service data) with the real time network data to obtain the set of analysed service based data.
[0148] The method [500] terminates at step S5. 5
[0149] Referring to FIG. 6, a flow diagram of an exemplary method [600] for monitoring a network load associated with one or more Network Functions (NFs), in accordance with exemplary implementations of the present disclosure is shown.
10 [0150] In an implementation the method [600] is performed by the system [300]. It
will be appreciated by a person skilled in the art that the method [600] as depicted is an exemplary illustration only, and is not intended to limit the scope, applicability, or configuration of the disclosure.
15 [0151] Initially, a Network Data Analytic Function (NWDAF) [302] in a network
receives a load analytics request (such as a monitoring request of network function(s) (NFs) based on a service-based load) from a user associated with a network on a NWDAF user interface (UI) (i.e., NWDAF UI) [308]. Further, the Network Data Analytic Function (NWDAF) [302] may comprise a Network Data
20 Analytic Function Back End (NWDAF BE) to receive the load analytics request in
conjunction with the NWDAF UI [308].
[0152] At step S1, a Network Repository Function (NRF) [602] collects one or
more instances/one or more services based load data from the NFs. For example,
25 the NRF [602] collects the load data of the one or more services (such as S1, S2,
S3) of the one or more instances such as an access and mobility management function (AMF) [106], a Session Management Function (SMF) [108], etc.
[0153] Also, the NRF [602] collects a historical service data i.e., the service based
30 data of a predefined time period, related to one or more services (S1, S2 and S3)
37

and a real time network data for the corresponding the one or more services (S1, S2 and S3).
[0154] At step S2, the collected one or more instances/one or more services based
5 load data (i.e., the historical service based data and the real time network based
data) is transmitted to the NWDAF backend (NWDAF BE). Thereafter, the historical service data and the real time network data are compared/matched with each other to obtain an analysed set of service data.
10 [0155] Further, the analysed set of service data is passed to the NWDAF UI [308].
The NWDAF UI [308] displays the analysed set of service data for the NFs.
[0156] At step S3, one or more data consumers access the displayed data (i.e. analysed set of service data) and in case of a high data traffic, a closed-loop
15 reporting is utilized for informing the one or more data consumers. The closed-loop
reporting is a process of sharing one or more insights or a feedback about the high data traffic to the one or more data consumers. The closed-loop reporting may help to manage a condition of high data traffic by providing timely feedback related to high traffic to the one or more data consumers. Further, with the help of feedback,
20 the one or more data consumers may manage one or more operations accordingly
such as resource utilization, performance optimization.
[0157] Thereafter, the method [600] terminates.
25 [0158] The present disclosure further discloses a User Equipment (UE) [102] for
monitoring a network load associated with one or more Network Functions (NFs). The UE [102] comprises a memory, a processor connected to with the memory, wherein the processor is configured to monitor a network load associated with one or more Network Function (NFs) via a system [300]. The monitoring of the network
30 load is based on receiving, by a transceiver unit [304] of the system [300], at a
Network Data Analytic Function (NWDAF) [302] in a network from a user, a load
38

analytics request associated with the one or more network functions (NFs) of the
network. The monitoring of the network load is further based on fetching, by a
processing unit [306] of the system [300], at the NWDAF [302], a set of instance
based data associated with the one or more NFs based on the load analytics request.
5 The monitoring of the network load is further based on determining, by the
processing unit [306] of the system, at the NWDAF [302], a set of service based data associated with the one or more NFs based on the set of instance based data. The monitoring of the network load is further based on receiving, by the transceiver unit [304] of the system [300], at the NWDAF [302], a real time network data
10 associated with the one or more NFs. The monitoring of the network load is further
based on generating, by the processing unit [306] of the system [300], at the NWDAF [302], a set of analysed service based data associated with the one or more NFs based on at least one of the set of service based data and the real time network data. The monitoring of the network load is further based on transmitting, by the
15 transceiver unit [304] of the system [300], from the NWDAF [302] to a NWDAF
UI [308], the set of analysed service based data. The monitoring of the network load is further based on monitoring, by the processing unit [306] of the system [300], the network load associated with the one or more Network functions (NFs) based on the set of analysed service based data.
20
[0159] The present disclosure further discloses a non-transitory computer readable storage medium storing one or more instructions for monitoring a network load associated with one or more Network Functions (NFs), the one or more instructions include executable code which, when executed by one or more units of a system
25 [300], causes a transceiver unit [304] of the system to receive, at a Network Data
Analytic Function (NWDAF) [302] in a network from a user, a load analytics request associated with the one or more network functions (NFs) of the network. Further, the executable code when executed may cause a processing unit [306] of the system [300] to fetch, by at the NWDAF [302], a set of instance based data
30 associated with the one or more NFs based on the load analytics request. Further,
the executable code when executed may causes the processing unit [306] of the
39

system [300] to determine, at the NWDAF [302], a set of service based data
associated with the one or more NFs based on the set of instance based data. Further,
the executable code when executed may causes the transceiver unit [304] of the
system [300] to receive, at the NWDAF [302], a real time network data associated
5 with the one or more NFs. Further, the executable code when executed may causes
the processing unit [306] of the system [300] is further configured to generate, at the NWDAF [302], a set of analysed service based data associated with the one or more NFs based on at least one of the set of service based data and the real time network data. Further, the executable code when executed may causes the
10 transceiver unit [304] of the system [300] to transmit, by from the NWDAF [302]
to the NWDAF UI [308], the set of analysed service based data. Further, the executable code when executed may causes the processing unit [306] of the system [300] to monitor, the network load associated with the one or more Network Functions (NFs) based on the set of analysed service based data.
15
[0160] As is evident from the above, the present disclosure provides a technically advanced solution for monitoring a network load associated with one or more Network Functions (NFs). The present solution offers a notable technical advantage for managing network functions (NFs) by leveraging the Network Data Analytics
20 Function (NWDAF) to perform analysis based on service-based load. The present
solution provides a technical edge by enabling deeper analysis of the actual load of each NF instance by considering service-based load as opposed to general instance load, the present solution achieves increased granularity, which, in turn, leads to more effective load management. The present solution provides an enhanced level
25 of analysis allows for a more precise understanding of the load distribution and
performance of NFs, facilitating proactive load balancing, resource allocation, and optimization strategies. Consequently, the technical advantage of the present solution improves an overall efficiency and a reliability of a NF ecosystem, resulting in an optimized service delivery and a better user experience.
30
40

[0161] While considerable emphasis has been placed herein on the disclosed
implementations, it will be appreciated that many implementations can be made and
that many changes can be made to the implementations without departing from the
principles of the present disclosure. These and other changes in the implementations
5 of the present disclosure will be apparent to those skilled in the art, whereby it is to
be understood that the foregoing descriptive matter to be implemented is illustrative and non-limiting.
[0162] Further, in accordance with the present disclosure, it is to be acknowledged
10 that the functionality described for the various components/units can be
implemented interchangeably. While specific embodiments may disclose a
particular functionality of these units for clarity, it is recognized that various
configurations and combinations thereof are within the scope of the disclosure. The
functionality of specific units as disclosed in the disclosure should not be construed
15 as limiting the scope of the present disclosure. Consequently, alternative
arrangements and substitutions of units, provided they achieve the intended functionality described herein, are considered to be encompassed within the scope of the present disclosure.
41

We Claim:
1. A method for monitoring a network load associated with one or more
Network Functions (NFs), the method comprising:
5 o receiving, by a transceiver unit [304] at a Network Data Analytic
Function (NWDAF) [302] in a network from a user, a load analytics
request associated with the one or more network functions (NFs) of the
network;
o fetching, by a processing unit [306] at the NWDAF [302], a set of
10 instance based data associated with the one or more NFs based on the
load analytics request;
o determining, by the processing unit [306] at the NWDAF [302], a set
of service based data associated with the one or more NFs based on the
set of instance based data;
15 o receiving, by the transceiver unit [304] at the NWDAF [302], a real
time network data associated with the one or more NFs;
o generating, by the processing unit [306] at the NWDAF [302], a set of
analysed service based data associated with the one or more NFs based
on at least one of the set of service based data and the real time network
20 data;
o transmitting, by the transceiver unit [304] from the NWDAF [302] to
a NWDAF UI [308], the set of analysed service based data; and
o monitoring, by the processing unit [306], the network load associated
with the one or more Network functions (NFs) based on the set of
25 analysed service based data.
2. The method as claimed in claim 1, wherein the set of instance based data
associated with the one or more NFs is fetched from one or more
predefined instance data sources.
3. The method as claimed in claim 1, further comprises storing, by the
30 processing unit [306] in a database [310], the set of service based data
associated with the one or more NFs.
42

4. The method as claimed in claim 1, wherein the set of analysed service based data is generated in a predefined format.
5. The method as claimed in claim 3, wherein the set of analysed service based data is generated based on the set of service based data stored in the
5 database [310] and the real time network data associated with the one or
more NFs.
6. A system [300] for monitoring a network load associated with one or more
Network Functions (NFs), the system comprises:
- a transceiver unit [304], wherein the transceiver unit [304] is
10 configured to:
o receive, at a Network Data Analytic Function (NWDAF) [302] in a network from a user, a load analytics request associated with one or more network functions (NFs) of the network; and
- a processing unit [306] connected to at least the transceiver unit
15 [304], wherein the processing unit [306] is configured to:
o fetch, by at the NWDAF [302], a set of instance based data associated with the one or more NFs based on the load analytics request, and
o determine, at the NWDAF [302], a set of service based data
20 associated with the one or more NFs based on the set of instance
based data;
- wherein the transceiver unit [304] is further configured to:
o receive, at the NWDAF [302], a real time network data
associated with the one or more NFs;
25 - wherein the processing unit [306] is further configured to:
o generate, at the NWDAF [302], a set of analysed service based data associated with the one or more NFs based on at least one of the set of service based data and the real time network data;
- wherein the transceiver unit [304] is further configured to:
30 o transmit, by from the NWDAF [302] to a NWDAF UI [308], the
set of analysed service based data; and
43

- wherein the processing unit [306] is further configured to:
o monitor, the network load associated with the one or more
Network Functions (NFs) based on the set of analysed service
based data.
5 7. The system as claimed in claim 6, wherein the set of instance based data
associated with the one or more NFs is fetched from one or more
predefined instance data sources.
8. The system as claimed in claim 6, wherein the processing unit [306] is
further configured to store in a database [310] the set of service based data
10 associated with the one or more NFs.
9. The system as claimed in claim 6, wherein the set of analysed service based data is generated in a predefined format.
10. The system as claimed in claim 8, wherein the set of analysed service based data is generated based on the set of service based data stored in the
15 database [310] and the real time network data associated with the one or
more NFs.
11. A user equipment (UE) for monitoring a network load associated with one
or more Network Functions (NFs), the UE comprises:
a memory; and
20 o a processor connected to with the memory, wherein the processor is
configured to monitor a network load associated with one or more
Network Function (NFs) via a system [300], wherein the monitoring
of the network load is based on:
o receiving, by a transceiver unit [304] of the system [300], at a
25 Network Data Analytic Function (NWD AF) [302] in a network from
a user, a load analytics request associated with one or more network
functions (NFs) of the network; o fetching, by a processing unit [306] of the system [300], at the
NWDAF [302], a set of instance based data associated with the one
30 or more NFs based on the load analytics request;
44

o determining, by the processing unit [306] of the system [300], at the NWDAF [302], a set of service based data associated with the one or more NFs based on the set of instance based data;
o receiving, by the transceiver unit [304] of the system [300], at the
5 NWDAF [302], a real time network data associated with the one or
more NFs;
o generating, by the processing unit [306] of the system [300], at the
NWDAF [302], a set of analysed service based data associated with
the one or more NFs based on at least one of the set of service based
10 data and the real time network data;
o transmitting, by the transceiver unit [304] of the system [300], from the NWDAF [302] to a NWDAF UI [308], the set of analysed service based data; and
o monitoring, by the processing unit [306] of the system [300], the
15 network load associated with the one or more Network functions
(NFs) based on the set of analysed service based data.