Method and system for communicating load information between network nodes

Abstract

The present disclosure provides a system (108) and a method (500) for communicating load information from a first cluster of network nodes (302-a), such as Network Repository Functions (NRFs), comprising a central network node (306) and one or more branch network nodes (304-a, 304-b), to a second network node (112), such as a Network Data Analytics Function (NWDAF). Each network node calculates load information based on transactions per second (TPS), number of registered NF profiles, and memory usage. A load notification thread is executed by each network node to identify subscription requests from the second network node (112). When a notification is due, the network node determines its deployment status. If it is a branch network node, it sends its load information to the central network node. If it is a central network node, it collects and aggregates load information from branch network nodes and sends it to the second network node.

Description

METHOD AND SYSTEM FOR COMMUNICATING LOAD INFORMATION BETWEEN NETWORK NODESRESERVATION OF RIGHTS

[0001] A portion of the disclosure of this patent document contains material, which is subject to intellectual property rights such as, but are not limited to, copyright, design, trademark, Integrated Circuit (IC) layout design, and / or trade dress protection, belonging to JIO PLATFORMS LIMITED or its affiliates (hereinafter referred as owner). The owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all rights whatsoever. All rights to such intellectual property are fully reserved by the owner.TECHNICAL FIELD

[0002] The present disclosure relates generally to the field of telecommunications. More particularly, the present disclosure relates to a method and a system for communicating load information from a cluster of first network nodes towards a second network node.DEFINITION

[0003] The term ‘Network Functions (NFs)’ used hereinafter in the specification refers to a functional entity within a telecommunications network, particularly within a 5G core architecture, that performs specific control or user plane operations. Network Functions (NFs) are typically software-based, cloud-native components such as an SMF (Session Management Function), a UPF (User Plane Function), an NRF (Network Repository Function), and an NWDAF (Network Data Analytics Function). Each NF registers its profile with the NRF and interacts with other NFs via service-based interfaces.

[0004] The term ‘Network Repository Function (NRF)’ used hereinafter in the specification refers to a key component in the 5G core network that is responsible for managing and distributing information about network functions (NFs) to other networkelements. The NRF acts as a central repository that stores and provides information regarding the availability, capabilities, and current status of various NFs within the network.

[0005] The term ‘Network Data Analytics Function (NWDAF)’ used hereinafter in the specification refers to a component within the 5G core network that is responsible for collecting, analyzing, and deriving insights from network data. NWDAF processes a variety of data sources, such as network performance metrics, user behavior patterns, and operational statistics gathered from different network functions (NFs).

[0006] The term ‘Dual-Tier NRF’ used hereinafter in the specification refers to an NRF architecture comprising at least one central NRF and one or more branch or mirrored NRFs, enabling hierarchical or federated management of NF profiles, service discovery, and load reporting across the network.

[0007] The term ‘Mirrored NRF’ used hereinafter in the specification refers to an NRF instance that maintains a synchronized copy of the NF profile and load-related data from one or more other NRFs, typically for redundancy, failover, or load distribution purposes within a multi-NRF deployment.

[0008] The term ‘Standalone NRF’ used hereinafter in the specification refers to a self-contained NRF instance operating independently without any interconnection to or synchronization with other NRFs in the network. It performs all repository and service discovery functions autonomously.

[0009] The term ‘Central NRF’ used hereinafter in the specification refers to a logically centralized NRF component in the dual-tier or distributed architecture that aggregates NF information, load data, and service discovery details from multiple Local or Mirrored NRFs to provide a unified network- wide view.

[0010] The term ‘Branch NRF’ used hereinafter in the specification refers to anNRF instance deployed in a distributed or regionalized network segment, typically under the control or coordination of the central NRF. The branch NRF is responsible for managing and storing NF profiles and service discovery within its assigned segment while optionally reporting load and status information to the central NRF for aggregation and network-wide visibility.

[0011] The term ‘TPS’ used hereinafter in the specification refers to a Transactions Per Second. The TPS is a metric indicating the rate at which a system, such as an NRF, is processing signaling or service discovery transactions, often used as an indicator of system load or performance.

[0012] The term ‘Subscription Request’ used hereinafter in the specification refers to message initiated by the NWDAF to an NRF to subscribe to specific events or information types, such as changes in NF profile status or load conditions.

[0013] These definitions are in addition to those expressed in the art.BACKGROUND

[0014] The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may 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 be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.

[0015] In a fifth-generation (5G) communication networks, a Network Repository Function (NRF) plays a crucial role in managing subscriptions and disseminating information about available network functions (NFs) to other network components, such as a Network Data Analytics Function (NWDAF). In a standalone NRF configuration, each NRF operates independently within its designated domain, managing subscriptions and providing pertinent data to NWDAF regarding the loadand capabilities of NFs under its jurisdiction. When the NWDAF subscribes for load notifications from a standalone NRF, the NRF proactively sends periodic updates detailing the load status of the network functions it oversees.

[0016] In a dual-tier deployment model, a central NRF is implemented to supervise multiple local NRF instances. In the dual-tier deployment model, the NWDAF subscribes to load notifications from the central NRF, consolidating and furnishing comprehensive load reports encompassing all local NRFs within its oversight. This architecture enhances network management efficiency and optimizes resource allocation across broader network domains. However, a significant challenge arises when the central NRF lacks direct access to load reports from its local NRFs. This limitation hampers the central NRF's ability to generate precise and comprehensive load reports. Consequently, the NWDAF may receive incomplete or inaccurate load notifications, which diminishes its capacity to make well-informed network resource allocation and optimization decisions.

[0017] There is, therefore, a need in the art to provide a method and a system that can mitigate the disadvantages of the prior art.SUMMARY OF THE DISCLOSURE

[0018] In an exemplary embodiment, a method for communicating load information from a first cluster of network nodes towards a second network node is described. The method includes calculating, by each network node of the first cluster, a load information representing a utilization associated with a corresponding network node by analyzing one or more parameters. The first cluster includes a central network node and one or more branch network nodes. The method further includes executing, by each network node of the first cluster, a load notification thread to determine a list of subscription requests for load information of at least one network node from the second network node after a predefined time interval. The method further includes determining, by the at least one network node, a deployment status of the at least onenetwork node, upon determining that a load notification to be sent is for the at least one network node based on the executed load notification thread. The deployment status is one of a branch network node and a central network node. The method includes collecting, by the central network node, the calculated load information from each of the one or more branch network nodes in responsive to the determined deployment status of the at least one network node, being the central network node. The method further includes communicating, by the central network node, the load notification to the second network node. The load notification includes load information of the central network node and each of the one or more branch network nodes.

[0019] In some embodiments, the method includes communicating, by the branch network node, the calculated load information associated with the branch network node to the central network node upon determining that the deployment status of the at least one network node is the branch network node.

[0020] In some embodiments, the network node of the first cluster is a NetworkRepository Function (NRF), and the second network node is a Network Data Analytics Function (NWDAF).

[0021] In some embodiments, the one or more parameters comprise a total current transaction per second (TPS), a number of registered profiles corresponding to each network node, and a total memory utilization.

[0022] In some embodiments, the method further includes storing, by the central network node, the load information corresponding to each of the one or more branch network nodes and the central network node of the first cluster in a database.

[0023] In some embodiments, the deployment status of the at least one network node is determined based on a set of information. The set of information includes information corresponding to the deployment status configured by a network operator for the at least one network node.

[0024] In some embodiments, the second network node is configured to subscribe for the load information from the at least network node of the first cluster by sending a subscription request to the at least one network node.

[0025] In another exemplary embodiment, a system for communicating load information from a first cluster of network nodes towards a second network node is described. The system comprises a processing unit and a communication unit. The processing unit is configured to calculate, by each network node of the first cluster, a load information representing a utilization associated with a corresponding network node by analyzing one or more parameters. The first cluster includes a central network node and one or more branch network nodes. The processing unit is configured to execute, by each network node of the first cluster, a load notification thread to determine a list of subscription requests for load information of at least one network node from the second network node after a predefined time interval. The processing unit is configured to determine, by the at least one network node, a deployment status of the at least one network node upon determining that a load notification to be sent is for the at least one network node based on the executed load notification thread. The deployment status is one of a branch network node and a central network node. The processing unit is configured to collect, by the central network node, the calculated load information from each of the one or more branch network nodes in responsive to the determined deployment status of the at least one network node, being the central network node. The communication unit is configured to communicate, by the central network node, a load notification to the second network node, wherein the load notification comprises load information of the central network node and each of the one or more branch network nodes.

[0026] In an exemplary embodiment, the present disclosure discloses a computer program product comprising a non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to perform a method for communicating load information from afirst cluster of network nodes towards a second network node is described. The method includes calculating, by each network node of the first cluster, a load information representing a utilization associated with a corresponding network node by analyzing one or more parameters. The first cluster includes a central network node and one or more branch network nodes. The method further includes executing, by each network node of the first cluster, a load notification thread to determine a list of subscription requests for load information of at least one network node from the second network node after a predefined time interval. The method further includes determining, by the at least one network node, a deployment status of the at least one network node, upon determining that a load notification to be sent is for the at least one network node based on the executed load notification thread. The deployment status is one of a branch network node and a central network node. The method includes collecting, by the central network node, the calculated load information from each of the one or more branch network nodes in responsive to the determined deployment status of the at least one network node, being the central network node. The method further includes communicating, by the central network node, the load notification to the second network node. The load notification includes load information of the central network node and each of the one or more branch network nodes.

[0027] The foregoing general description of the illustrative embodiments and the following detailed description thereof are merely exemplary aspects of the teachings of this disclosure, and are not restrictive.OBJECTIVES OF THE PRESENT DISCLOSURE

[0028] Some of the objectives of the present disclosure, which at least one embodiment herein satisfies, are as follows:

[0029] An objective of the present disclosure is to provide a system and a method for communicating load information from a cluster of first network nodes to a second network node.

[0030] Another objective of the present disclosure is to provide a system and a method that utilizes a central Network Resource Function (NRF) to aggregate load information from all branch NRFs and generate a more accurate and comprehensive load report for a Network Data Analytics Function (NWDAF). This process ensures improved network performance monitoring and analysis.

[0031] Another objective of the present disclosure is to provide a system and a method that utilizes centralized load data for more efficient management and optimization of network resources.

[0032] Another objective of the present disclosure is to provide a system and a method that enhances reliability as the NWDAF relies on timely and precise notifications regarding network load, ultimately leading to improved network reliability and stability.

[0033] Another objective of the present disclosure is to provide a system and a method that enhances scalability by collecting load information across multiple branch NRFs, supporting a scalable network architecture, and allowing for the addition of new local NRFs without compromising ability of the central NRF to monitor and report on network load effectively.

[0034] Another objective of the present disclosure is to provide a system and a method that standardizes a process of collecting and reporting load information across all NRFs, ensuring consistency in the data provided to NWDAF and facilitating improved data analysis and decision-making.

[0035] Another objective of the present disclosure is to provide a system and a method that improves service quality by allowing NWDAF to optimize service delivery and maintain high service quality, thereby benefiting end-users with more reliable and efficient network services.BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWING

[0036] 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; emphasis is instead being placed upon clearly illustrating the principles of the present disclosure. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that disclosure of such drawings includes disclosure of electrical components, electronic components, or circuitry commonly used to implement such components.

[0037] FIG. 1A illustrates an exemplary network architecture in which or with a system configured for communicating load information from a first cluster of network nodes towards a second network node may be implemented, in accordance with embodiments of the present disclosure.

[0038] FIG. IB illustrates another exemplary network architecture in which or with which the system configured for communicating load information from the first cluster of network nodes towards the second network node may be implemented, in accordance with embodiments of the present disclosure.

[0039] FIG. 2 illustrates a block diagram of the system configured for communicating load information from the first cluster of network nodes towards the second network node, in accordance with an embodiment of the present disclosure.

[0040] FIG. 3A illustrates an exemplary network architecture of the system for communicating load information in a mirroring deployment, in accordance with an embodiment of the present disclosure.

[0041] FIG. 3B illustrates another exemplary network architecture of the system in a dual-tier deployment, in accordance with an embodiment of the presentdisclosure.

[0042] FIG. 4 illustrates an exemplary flow chart illustrating a method of communicating load information from the first cluster of network nodes towards the second network node, in accordance with an embodiment of the present disclosure.

[0043] FIG. 5 illustrates an exemplary flow diagram of a method for communicating load information from the first cluster of network nodes towards the second network node, in accordance with an embodiment of the present disclosure.

[0044] FIG. 6 illustrates an exemplary computer system in which or with which the embodiments of the present disclosure may be implemented.

[0045] The foregoing shall be more apparent from the following more detailed description of the disclosure.LIST OF REFERENCE NUMERALS100 A - Network Architecture102 - User(s)104 - User Equipment (UEs)106 - Network108 - System110 - First Cluster110-a, 110-b, 110-c - One or more network nodes of a first cluster112 - Network Data Analytics Function (NWDAF)114-a, 114-b, 114c, 114-d - One or more network functions (NFs)202 - Processor(s)204 - Memory206 - Interfaces(s)208 - Processing Unit210 - Communication Unit212 - Database302-a, 302-b, 302-c - a plurality of Network Repository Functions (NRFs) clusters (NRF cluster 1, NRF cluster 2, NRF cluster n)304-a, 304-b, 304-c - One or more branch NRF306 - Central NRF400 - Flowchart500 - Method Flow Diagram600 - Computer System610 - External Storage Device620 - Bus630 - Main Memory640 - Read Only Memory650 - Mass Storage Device660 - Communication Port(S)670 - ProcessorDETAILED DESCRIPTION

[0046] 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 details. Several features described hereafter can 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. Some of the problems discussed above might not be fully addressed by any of the features described herein. Example embodiments of the present disclosure are described below, as illustrated in various drawings in which like reference numerals refer to the same parts throughout the different drawings.

[0047] 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 arrangement of elements without departing from the spirit and scope of the disclosure as set forth.

[0048] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments.

[0049] Also, it is noted that individual embodiments may be described as aprocess that is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can 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 included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.

[0050] 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 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 description or the claims, such terms are intended to be inclusive like the term “comprising” as an open transition word without precluding any additional or other elements.

[0051] Reference throughout this specification to “one embodiment” or “an embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0052] The terminology used herein is to describe particular embodiments onlyand is not intended to be limiting the disclosure. As used herein, the singular forms “a”, “an”, and “the” are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms “comprises” and / or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. As used herein, the term “and / or” includes any combinations of one or more of the associated listed items. It should be noted that the terms “mobile device”, “user equipment”, “user device”, “communication device”, “device” and similar terms are used interchangeably for the purpose of describing the invention. These terms are not intended to limit the scope of the invention or imply any specific functionality or limitations on the described embodiments. The use of these terms is solely for convenience and clarity of description. The invention is not limited to any particular type of device or equipment, and it should be understood that other equivalent terms or variations thereof may be used interchangeably without departing from the scope of the invention as defined herein.

[0053] While considerable emphasis has been placed herein on the components and component parts of the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiment as well as other embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the disclosure and not as a limitation.

[0054] In modem telecommunications, accurate load reporting is essential for effective network management. It enables operators to dynamically understand traffic patterns, identify bottlenecks, and allocate resources. Network Data Analytics Function (NWDAF) and Network Repository Function (NRF) are both key components in 5Gnetworks, each playing distinct roles in managing and utilizing network data. In a standalone NRF setup, when NWDAF subscribes for load notifications, the standalone NRF autonomously generates and transmits load notification reports to NWDAF at periodic intervals. The standalone NRF independently collects, aggregates, and analyzes load information pertaining to network functions and resources within its domain. Upon receiving a subscription request from NWDAF, the standalone NRF initiates the transmission of load notification reports according to predefined schedules or triggered by specific load thresholds or events. These reports encompass comprehensive data on the utilization, performance metrics, and operational statuses of network functions managed by the standalone NRF.

[0055] In a dual-tier deployment, a central NRF aggregates data from multiple local NRFs (branch NRFs). In the dual-tier deployment, the local NRFs gather detailed load information from their respective network segments and communicate this data to the central NRF. This hierarchical structure allows for more granular insights into network performance and facilitates informed decision-making. Despite the advantages, dual-tier NRF deployments face several challenges in network load reporting. As the network expands, the number of local NRFs increases, which can complicate load reporting processes and impact overall system performance. Additionally, ensuring the timely and accurate aggregation of load data from multiple local NRFs to the central NRF can be complex, especially in large-scale networks. Further, maintaining consistency in data reporting across different NRFs is crucial for reliable analysis and decision-making.

[0056] Accordingly, the present disclosure provides a solution to overcome the above challenges. The present disclosure provides a method and a system that are configured to report load information of NRFs connected in a multi-NRF deployment (dual-tier NRF deployment) or a mirroring deployment.

[0057] In the disclosed system, each NRF calculates its load based on currentutilization metrics such as Transaction per second (TPS) and number of registered profiles. If an NRF is identified as a branch NRF or a mirror NRF, then the NRF sends its calculated load information to a central NRF or another mirror NRF, which stores this data in its memory. In the disclosed system, the NWDAF subscribes to the load information of NRFs by initiating a subscribe request towards the central NRF. Periodically, each NRF checks for subscriptions to its load information. If a subscription is active, the NRF verifies the deployment mode. In scenarios where the deployment mode is multi-NRF / dual-tier, the NRF compiles load information from itself and other NRFs into a list of notifications intended for transmission to the NWDAF. The disclosed system ensures efficient reporting and monitoring the load information of the NRF in the multi-NRF deployment, facilitating effective resource management within 5G networks.

[0058] Hereinafter, exemplary embodiments of the present disclosure will be described with reference to the accompanying drawings.

[0059] FIG. 1A illustrates an exemplary network architecture (100 A) in which or with a system (108) configured for communicating load information from a first cluster of network nodes towards a second network node may be implemented, in accordance with embodiments of the present disclosure.

[0060] As illustrated in FIG. 1A, the network architecture (100 A) may include one or more User Equipments (UEs) (104-1, 104-2... 104-N) associated with one or more users (102-1, 102-2... 102-N) in an environment. A person of ordinary skill in the art will understand that one or more users (102-1, 102-2... 102-N) may be collectively referred to as the users (102). Similarly, a person of ordinary skill in the art will understand that one or more UEs (104-1, 104-2... 104-N) may be collectively referred to as the UE (104) or the UEs (104). Although only three UE 104 are depicted in FIG. 1 A, however, any number of the UE (104) may be included without departing from the scope of the ongoing description.

[0061] In an embodiment, the UE (104) may include smart devices operating in a smart environment, for example, an Internet of Things (loT) system. In such an embodiment, the UE (104) may include, but are not limited to, smartphones, smart watches, smart sensors (e.g., a mechanical, a thermal, an electrical, a magnetic, etc.), networked appliances, networked peripheral devices, networked lighting system, communication devices, networked vehicle accessories, networked vehicular devices, smart accessories, tablets, a smart television (TV), computers, a smart security system, a smart home system, other devices for monitoring or interacting with or for the users (102) and / or entities, or any combination thereof. A person of ordinary skill in the art will appreciate that the UE (104) may include, but not limited to, intelligent, multisensing, network- connected devices, that may integrate seamlessly with each other and / or with a central server or a cloud- computing system or any other device that is network-connected.

[0062] Additionally, in some embodiments, the UE (104) may include, but not limited to, a handheld wireless communication device (e.g., a mobile phone, a smartphone, a phablet device, and so on), a wearable computer device (e.g., a headmounted display computer device, a head-mounted camera device, a wristwatch computer device, and so on), a Global Positioning System (GPS) device, a laptop computer, a tablet computer, or another type of portable computer, a media playing device, a portable gaming system, and / or any other type of computer device with wireless communication capabilities, and the like. In an embodiment, the UE (104) may include, but are not limited to, any electrical, electronic, electromechanical, or equipment, or a combination of one or more of the above devices, such as virtual reality (VR) devices, augmented reality (AR) devices, a laptop, a general-purpose computer, a desktop, a personal digital assistant, a tablet computer, a mainframe computer, or any other computing device. Further, the UE (104) may include one or more in-built or externally coupled accessories including, but not limited to, a visual aid device such as a camera, an audio aid, a microphone, a keyboard, and input devices for receiving inputfrom the user (102) or an entity such as a touchpad, a touch-enabled screen, an electronic pen, and the like. A person of ordinary skill in the art will appreciate that the UE (104) may not be restricted to the mentioned devices, and various other devices may be used.

[0063] In FIG. 1A, the UE (104) may communicate with the system (108) through a network 106. In an embodiment, the network (106) may include at least one of a Fourth Generation (4G) network, a Fifth Generation (5G) network, a Sixth Generation (6G) network, or the like. The network 106 may enable the UE (104) to communicate with other devices in the network architecture 100 and / or with the system 108. The network (106) may include a wireless card or some other transceiver connection to facilitate this communication. In another embodiment, the network (106) may be implemented as, or include any of a variety of different communication technologies such as a wide area network (WAN), a local area network (LAN), a wireless network, a mobile network, a Virtual Private Network (VPN), the Internet, the Public Switched Telephone Network (PSTN), or the like.

[0064] In an embodiment, the network (106) may include, by way of example but not limitation, at least a portion of one or more networks having one or more nodes that transmit, receive, forward, generate, buffer, store, route, switch, process, or a combination thereof, etc. one or more messages, packets, signals, waves, voltage or current levels, some combination thereof, or so forth. The network (106) may also include, by way of example but not limitation, a wireless network, a wired network, an internet, an intranet, a public network, a private network, a packet-switched network, a circuit-switched network, an ad hoc network, an infrastructure network, a Public- Switched Telephone Network (PSTN), a cable network, a cellular network, a satellite network, a fiber optic network, or some combination thereof.

[0065] In an embodiment, the UE (104) is communicatively coupled with the network (106). The network (106) may receive a connection request from the UE (104).The network (106) may send an acknowledgment of the connection request to the UE (104). The UE (104) may transmit a plurality of signals in response to the connection request.

[0066] Although FIG. 1A shows exemplary components of the network architecture (100 A), in other embodiments, the network architecture (100A) may include fewer components, different components, differently arranged components, or additional functional components than depicted in FIG. 1A.

[0067] FIG. IB illustrates another exemplary network architecture (100B) in which or with which the system (108) configured for communicating load information from the first cluster of network nodes towards the second network node may be implemented, in accordance with embodiments of the present disclosure.

[0068] As shown in FIG. IB, the network architecture (100B) may include a first cluster of network nodes (110-a, 110-b, 110-c also referred to as “a first cluster 110”) and a second network node ( 112) . In an aspect, the cluster (110) may include one or more branch network nodes and a central network node. In an example, the first cluster of network nodes may be a network repository function (NRF). In an example, the second network node may be a Network Data Analytics Function (NWDAF).

[0069] The NRF is responsible for managing and providing information about the network functions available in the 5G core network. The NRF is a central repository that stores details about the different network functions, capabilities, and service profiles. When a network function (for example, NWDAF) needs to interact with other functions or requires information about available services, it queries the NRF. The NRF helps with service discovery, enabling network functions to find and interact with each other efficiently.

[0070] In an aspect, each network node of the first cluster (110-a, 110-b, 110- c) may be connected to one or more network functions (NFs) (114-a, 114-b, 114-c,114-d) (collectively known as “NFs 114”). The one or more NFs (114-a, 114-b, 114-c, 114-d) may include, such as the NRF, a Binding Support Function (BSF), or a Charging Function (CHF), an access and mobility management function (AMF), a session management function (SMF), a policy control function (PCF), a unified data management (UDM), a user plane function (UPF), an authentication server function (AUSF), an application function (AF), and / or a network slice selection function (NSSF), etc., but the example embodiments are not limited thereto.

[0071] In an aspect, each network node of the first cluster (110-a, 110-b, 110- c) may be configured to determine a load information representing a current utilization of itself.

[0072] In an aspect, each network node of the first cluster (110-a, 110-b, 110- c) may be configured to determine the utilization continuously or after a predefined time. For example, the predefined time may lie in a range of a few seconds to a few minutes. In an aspect, the current utilization may involve Transaction per second (TPS) associated with each network node. In an aspect, the TPS is used to measure current utilization, the number of transactions the network node handles per second. Transactions might include various types of operations, such as data processing requests, client interactions, or other activities that the node manages. High TPS indicates a higher workload, indicating that the node is actively processing many transactions. Another aspect of the current utilization involves counting the number of NF profiles registered with or managed by each network node. Each network node of the first cluster (110-a, 110-b, 110-c) is set up to monitor and report the TPS and the number of registered NF profiles. By continuously monitoring these aspects associated with the utilization, each network node of the first cluster (110-a, 110-b, 110-c) may be able to self-assess and provide data about its current operational status to the NWDAF (112). The cluster (110) may be configured to communicate the load information to the NWDAF (112). NWDAF (112) collects, processes, and analyzes the communicated load information in real-time. NWDAF (112) performs advancedanalytics to derive insights and make decisions based on the data received from the cluster (110). NWDAF (112) may use the load information from the NRFs to dynamically discover and interact with the one or more NFs (114-a, 114-b, 114-c, 114- d) to provide necessary data for analytics.

[0073] In an aspect, the one or more NFs (114) and / or the cluster (110) may be connected over the network 106. In an aspect, the UE (104) may be configured to connect with the one or more NFs (114) through the network 106.

[0074] In an aspect, the cluster (110) may be connected to the NWDAF (112) over the network 106, The detailed explanation and flow for communicating load information from a first cluster of network nodes towards a second network node are described further with reference to FIG. 2 to FIG. 5.

[0075] Although FIG. IB shows exemplary components of the network architecture (100B), in other embodiments, the network architecture (100B) may include fewer components, different components, differently arranged components, or additional functional components than depicted in FIG. IB.

[0076] FIG. 2 illustrates an exemplary block diagram (200) of the system (108) configured for communicating load information from the first cluster of network nodes (110) towards the second network node (112), in accordance with embodiments of the present disclosure. FIG. 2 is explained in conjunction with FIG. 1 A and IB.

[0077] In an embodiment, the system (108) may include one or more processor(s) (202). The one or more processor(s) (202) may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and / or any devices that process data based on operational instructions. Among other capabilities, the one or more processor(s) (202) may be configured to fetch and execute computer-readable instructions stored in a memory (204) of the system (108). The memory (204) may be configured to store oneor more computer-readable instructions or routines in a non-transitory computer readable storage medium, which may be fetched and executed to create or share data packets over a network service. The memory (204) may include any non-transitory storage device including, for example, volatile memory such as a Random-Access Memory (RAM), or a non-volatile memory such as an Erasable Programmable Read Only Memory (EPROM), a flash memory, and the like.

[0078] In an embodiment, the system (108) may include an interface(s) (206). The interface(s) (206) may include a variety of interfaces, for example, interfaces for data input and output devices (VO), storage devices, and the like. The interface(s) (206) may facilitate communication through the system (108). The interface(s) (206) may also provide a communication pathway for one or more components of the system (108). Examples of such components include, but are not limited to, a processing unit (208), a communication unit (210) and a database (212).

[0079] In an embodiment, the system (108) may include a processing unit (208) that may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing unit (208). In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing unit (208) may be processor-executable instructions stored on a non-transitory machine-readable storage medium, and the hardware for the processing unit (208) may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine- readable storage medium may store instructions that, when executed by the processing resource, implement the processing unit (208). In such examples, the system (108) may comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to the system (108) and the processing resource. In other examples, the processing unit (208) may be implemented byelectronic circuitry. In yet other examples, the processing unit (208) may be implemented by each network node of the first cluster. In an example, each network node of the first cluster is the Network Repository Function (NRF). In an aspect, the processing unit (208) is configured to cooperate with the communication unit (210).

[0080] In an embodiment, each network node of the first cluster (i.e. the processing unit (208)) is configured to calculate a load information representing a utilization associated with a corresponding network node by analyzing one or more parameters. The load information refers to a quantified and structured representation of the current utilization or performance state of the network node (such as the NRF). For example, the load information may indicate that the network node is operating at 72% utilization. The one or more parameters include a total current transaction per second (TPS), a number of registered profiles corresponding to each network node, and a total memory utilization. The total current TPS represents the real-time rate at which each network node of the first cluster processes incoming and outgoing service requests, such as network function (NF) registration, discovery, or update messages. Each network node of the first cluster may compute the total current TPS by maintaining a counter for processed transactions over a defined time interval and dividing it by the total duration (e.g., total transactions in the last 10 seconds divided by 10). The number of registered profiles corresponds to the total count of active NF profiles currently stored and managed by each network node of the first cluster. The registered profile refers to a structured representation of an NF instance that is successfully discovered and validated. Each registered profile typically contains metadata and operational parameters associated with the NF instance, such as the NF type, instance ID, status, priority, supported services, IP address, and available capacity. For example, the registered profile may correspond to an AMF (Access and Mobility Management Function) instance supporting registration, handover, and mobility events, an SMF (Session Management Function) profile indicating data session management capabilities, a PCF (Policy Control Function) instance profileincluding policy decision-making capacity and service access priorities, a UDM (Unified Data Management) profile containing user authentication and subscriber data management capabilities. Each network node maintains the current list of such active NF profiles as part of its local NF repository. In an example, each network node of the first cluster (i.e., the 110 (NRF)) may include all registered NFs and their associated service information in its internal database, such as the database (212). The memory utilization parameter reflects the total memory currently consumed by the processes executing at each network node, including memory allocated for service logic, cached NF data, and internal queues. Each network node may be configured to monitor the total memory utilization using monitoring tools. Together, these one or more parameters are periodically analyzed and compiled into a load report that represents the overall current utilization of each network node.

[0081] In order to calculate the load information, each network node may retrieve the total count of the registered profiles corresponding to network node directly from the internal database (212). Further, each network node may calculate the total current TPS by maintaining a time-based counter that increments with each incoming or outgoing service request (such as NF registration, discovery, or update requests) and dividing the accumulated transaction count by the duration of the predefined monitoring interval (e.g., 10 seconds). For example, if 500 transactions are recorded in the last 10 seconds, the TPS may be recorded as 50. This TPS value reflects the current processing load on each network node. Additionally, each network node may obtain the memory utilization parameter through internal monitoring mechanisms or tools that track the active memory consumed by running processes, which include memory allocated for service logic execution, NF data caching, and internal queuing operations. Once the one or more parameters are retrieved, calculated, and obtained, each network node may normalize and aggregate to derive a final load value also represented as an integer within the range of 0 to 100, indicating the current load percentage of the NF i.e., representing the overall utilization of each network node. Inan aspect, the normalized and aggregated value may be multiplied by 100 during computation to indicate the load information an integer percentage (such as 0-100%) for simplified processing and reporting.

[0082] In an aspect, each network node may be configured to periodically calculate the load information. For example, each network node may initiate the calculation of load information at regular intervals, such as every 10 seconds, 30 seconds, or one minute, based on system requirements or operator configuration. During each interval, the network node may collect the one or more parameters that reflect its current workload.

[0083] In an embodiment, each network node of the first cluster (110) is configured to execute a load notification thread to determine a list of subscription requests for load information of at least one network node from the second network node (112) after a predefined time interval. The load notification thread is a dedicated background process or scheduled task responsible for handling the load information to the second network node. In an embodiment, the second network node (112) is configured to subscribe for the load information from the at least network node of the first cluster (112) by sending a subscription request to the at least one network node. In an aspect, the second network node (112) is the Network Data Analytics Function (NWDAF). The subscription request refers to a structured communication message that expresses the second network node’s interest in receiving periodic updates related to the utilization or load status of each network node of the first cluster. The subscription request may include parameters such as the type of load information being requested (e.g., load data from a specific NRF instance), the preferred reporting interval or frequency, notification conditions (such as thresholds or change triggers), etc. In an aspect, the subscription request may be sent by the second network node (112) upon detecting one or more triggering conditions. The one or more triggering conditions may include a change in network topology, such as a registration or deregistration of a Network Function (NF), an initiation of a new service session or network slicedeployment that requires active monitoring of specific NFs, scheduled analytics collection intervals configured within the second network node, etc. Based on such conditions, the second network node (112) may generate and transmit the subscription request to the at least one network node, to subscribe to relevant NF state or load information in order to support adaptive analytics, prediction, and optimization of network behavior. In an aspect, the subscription request may be dynamically generated by the second network node (112) based on real-time network conditions and operational requirements. For example, the NWDAF may observe abnormal traffic patterns, increasing latency, or spikes in TPS for a particular NF type and, in response, dynamically initiate the subscription request to receive periodic load updates or state changes for those NFs.

[0084] In an aspect, upon receiving the subscription request, each network node of the first cluster (110) may store the subscription request in its internal database such as database (212). The purpose of the load notification thread is to periodically evaluate whether there is an active list of the subscription requests from the second network node (112) for accessing the load information of the at least one network node. Each subscription request in the list may include details such as the identity of the second network node (e.g., NWDAF instance ID), the type of load information being requested (e.g., for specific NFs such as NRF, BSF, CHF). The load notification thread is triggered after the predefined time interval, which may be set by the network operators based on network policy, for example, every 30 seconds or one minute. Upon execution of the load notification thread, each network node accesses the list of subscription requests previously received from the second network node (112).

[0085] In an embodiment, upon determining that a load notification to be sent is for the at least one network node based on the executed load notification thread, the at least one network node is configured to determine a deployment status of the at least one network node. The deployment status refers to an operational role or hierarchical position of the at least one network node within a distributed or multi-tiered clusterarchitecture. The deployment status may be configured by a network operator based on the deployment topology, policy settings, or operational requirements. In an aspect, the deployment status is one of a branch network node or a central network node. The central network node represents a node configured to aggregate load information from multiple branch network nodes and communicate with external entities such as the second network node (NWDAF). The branch network node represents a node configured to operate locally, calculate its own load information, and report it to the central network node. In an aspect, the deployment status of the at least one network node is determined based on a set of information. The set of information includes information corresponding to the deployment status configured by the network operator for the at least one network node. In an example, the at least one network node (NRF) among the first cluster may be deployed within a distributed architecture that includes multiple NRFs organized into a central and branch configuration. When the at least one network node determines that the load notification is to be sent for itself to the second network node (112), it first verifies its deployment status by referring to the deployment status configured by the network operator. This configuration may be stored locally in the NRF’s settings, loaded during initialization, or retrieved from a centralized configuration management system.

[0086] In an embodiment, in response to the determined deployment status of the at least one network node being the central network node, the central network node is configured to collect the calculated load information from each of the one or more branch network nodes. If the NRF finds that its deployment role is marked as the central network node in the configuration, it proceeds to collect load information for itself and from associated branch NRFs within the first cluster. In an example, the central network node may first calculate its own load information. For instance, the central network node may determine that its current TPS is 800 (with a maximum threshold of 1000), its memory utilization is 4096 MB out of 8192 MB, and it is managing 30,000 registered NF profiles out of a maximum capacity of 50,000. Similarly, each of the oneor more branch network nodes within the first cluster is independently configured to monitor, calculate, and normalize its own local performance parameters such as current TPS, memory usage, and number of registered NF profiles. For example, a branch node with current TPS of 400 (max 1000), memory usage of 2048 MB (max 8192 MB), and 10,000 profiles (max 50,000) may compute its corresponding composite load metric. Once calculated, each branch network node transmits its respective load metric to the central network node over a predefined load reporting interface. Further, the central network node may perform aggregation for each of these parameters alongside the load information received from the one or more branch network nodes to derive a final load value and stores the collected the load information corresponding to each of the one or more branch network nodes and the central network node of the first cluster in the database (212). For example, the collected load information may indicate that the central network node is operating at 800 TPS out of a maximum threshold of 1000, utilizing 4096 MB of memory out of 8192 MB, and managing 30,000 registered NF profiles out of a capacity of 50,000. Similarly, a branch node 1 may report 400 TPS out of 1000, memory usage of 2457 MB out of 8192 MB, and 10,000 registered profiles out of 50,000, a branch Node 2 may report 600 TPS, memory utilization of 3276 MB, and 25,000 registered profiles, while a branch Node 3 may report 300 TPS, 1638 MB of memory usage, and 5,000 registered profiles, respectively.

[0087] In an embodiment, the central network node is configured to communicate the load notification to the second network node (112). The load notification comprises load information of the central network node and each of the one or more branch network nodes. For example, if the at least one network node is determined as the central network node, the communication unit (210) embedded in the central network node (NRF) retrieves the collected load information from the database (212) and further, the communication unit (210) sends the load information to the second network node (NWDAF).

[0088] In an embodiment, upon determining that the deployment status of theat least one network node is the branch network node, the branch network node is configured to communicate the calculated load information associated with the branch network node to the central network node. In an example, if the deployment role of the NRF is configured as a branch network node by the network operator, then the communication unit 210 embedded in the NRF prepares and forwards its own load report to the central NRF. This approach ensures that each NRF performs its task according to its assigned function within the deployment, enabling accurate and organized load aggregation across the multi-NRF architecture. Further, the response is sent to the central network node if the first network node is determined as the branch network node.

[0089] FIG. 3A illustrates an exemplary network architecture (300A) of the system (108) for communicating load information in a mirroring deployment, in accordance with an embodiment of the present disclosure. FIG. 3A is explained in conjunction with FIGs. IB, and 2.

[0090] As shown, the architecture 300 A includes a plurality of NRF clusters, labeled as NRF cluster 1 (302-a), NRF cluster 2 (302-b), and NRF cluster n (302-c). As shown in FIG. 3 A, the plurality of clusters (NRF cluster 1, NRF cluster 2, NRF cluster n) (302-a, 302-b, 302-c) may be configured to communicate with each other to allow the exchange of load information. In an aspect, the structural and working aspects of the NRF cluster 1 (302-a), the NRF cluster 2 (302-b), and the NRF cluster n (302-c) may be same as the cluster (110). Each of these NRF clusters may include one or more network nodes (i.e., the NRFs) deployed either as the central network node or the one or more branch network nodes, depending on the configuration established by the network operator.

[0091] In an aspect, after determining the load information, each network node of the plurality of NRF clusters is configured to communicate the load information with the other network nodes within the cluster. In a further aspect, each cluster is furtherconfigured to update other clusters regarding the load information.

[0092] The second network node, (NWDAF) (112), is configured to receive aggregated or individual load notifications. In an embodiment, NWDAF (112) may subscribe to load information from multiple NRF clusters and receive structured load reports periodically or based on predefined conditions. As shown in FIG 3 A, any of the NRF clusters can serve as the aggregation point for collecting and communicating load information to NWDAF (112). For example, NRF cluster (302-a), acting as a central cluster, may collect load reports from (302-b) and (302-c), compile them into a consolidated notification, and transmit the report to NWDAF (112).

[0093] FIG. 3B illustrates another exemplary network architecture of the system in a dual-tier deployment, in accordance with an embodiment of the present disclosure. FIG. 3B is explained in conjunction with the FIGs.lB, 2 and 3 A

[0094] In the dual -tier deployment, the network architecture (300B) is divided into two layers or tiers (a client tier and a branch tier). Each layer is responsible for different aspects of the system’s functionality.

[0095] As shown in FIG. 3B, the network architecture (300B) may include the cluster of NRFs (302-a) and the NWDAF (112). In an aspect, the cluster of the NRFs (302-a) may include a central NRF (306) (acting as the client tier) and one or more branch NRFs (304-a, 304-b, 304-c) (acting as the branch tier).

[0096] Each NRF (306, 304-a, 304-b, 304-c) of the cluster of NRFs (302-a) may be configured to determine the load information representing its current utilization (load status). In an aspect, each of the one or more branch (local) NRFs (306, 304-a, 304-b, 304-c) may be configured to communicate the determined load information to the central NRF (306). The central NRF (306) may be configured to generate a list of determined load information corresponding to each branch NRF.

[0097] The central NRF (306) may be configured to receive a subscriptionrequest from the NWDAF (112). On receiving the subscription request, the central NRF (306) may be configured to communicate the generated list and the determined load to the NWDAF 112. In a summarized aspect, the central NRF (306) receives load information representing the utilizations from the one or more branch NRFs (306, 304- a, 304-b, 304-c). For example, if a branch NRF (304-a) reports the load information indicating a high load and a branch NRF (304-b) reports the load information indicating a normal load, then the central NRF (306) may aggregate these reported information(s) to generate the list. The list may thus include high load notification of the branch NRF (304-a) and normal load notification of the branch NRF (304-b), among potentially other notifications from additional branch NRFs. Subsequently, the central NRF (306) sends this comprehensive list to the NWDAF (112), allowing for a consolidated view of the network load distribution and facilitating more informed decision-making regarding resource allocation and management.

[0098] By adopting the dual-tier deployment, the system (108) introduces a capability where the central NRF (306) may collect load information from all branch network nodes (local NRFs). The present system (108) ensures that the central NRF (306) aggregates comprehensive load data across the entire network, providing the NWDAF (112) with accurate and holistic load reports, thereby improving network management, reliability, and performance.

[0099] FIG. 4 illustrates an exemplary process flow (400) for communicating load information from the first cluster of network nodes towards the second network node, in accordance with an embodiment of the present disclosure. FIG. 4 is explained in conjunction with the FIG. IB.

[0100] At step 402 of the process flow (400), the NRF (110-a, 110-b, 110-c) may be configured to compute its operational load. In an aspect, the NRF (110-a, 110- b, 110-c) computes the operational load by evaluating two key parameters: the Transactions Per Second (TPS) and the total number of Network Functions (NFs)currently registered with the NRF. The TPS metric reflects the volume of transactions the NRF handles within a given time frame, while the NF count represents the number of network functions that are interacting with or relying on the NRF for registration and service discovery.

[0101] At step 404, the NRF (110-a, 110-b, 110-c) may be configured to assess its operational role within the network architecture to determine if it is functioning as a branch NRF. In an aspect, this determination involves evaluating specific criteria or attributes associated with its configuration and role within the network.

[0102] At step 406, if the NRF (110-a, 110-b, 110-c) is the branch NRF, then the branch NRF is configured to communicate its current load information to the central NRF. In an example, this communication is carried out through a heartbeat request mechanism. The heartbeat request mechanism is a protocol or method employed by a network entity to periodically send status or health update messages to another network entity. In the context of the present disclosure, the heartbeat request mechanism facilitates regular communication between the NRFs to convey load information, operational status, or other relevant metrics. A heartbeat request serves as a periodic communication signal that includes the load information of the branch NRF. This load information may encompass metrics such as transactional processing load, resource utilization, or any other relevant performance indicators. The central NRF, upon receiving this heartbeat request, may then aggregate and analyze the load information from various branch NRFs to maintain an updated view of the network load distribution and ensure effective management of network resources.

[0103] At step 408, if it is determined that the NRF is not operating as a branch NRF, then the NRF considers itself as the central NRF and verifies whether there is an active subscription by the Network Data Analytics Function (NWDAF) (112) for receiving load information.

[0104] At step 410, if a subscription by the NWDAF (12) is found, the centralNRF may be configured to send a load notification that includes its own load information as well as load notifications from other branch NRFs to the NWDAF (112).

[0105] At step 412, if no active subscription is found, the NRF may be configured to monitor and manage its own load information continuously.

[0106] FIG. 5 illustrates another exemplary flow diagram of a method 500 for communicating load information from the first cluster of network nodes towards the second network node, in accordance with an embodiment of the present disclosure. FIG. 5 is explained in conjunction with FIGs 1 A, IB, 2, 3 A, and 3B. The network node of the first cluster is the Network Repository Function (NRF) (such as NRF cluster 1 302-a), and the second network node is a Network Data Analytics Function (NWDAF) (such as 112).

[0107] At step 502, the method (500) includes calculating, by each network node of the first cluster, a load information representing a utilization associated with a corresponding network node by analyzing one or more parameters. In an aspect, the one or more parameters comprise a total current transaction per second (TPS), a number of registered profiles corresponding to each network node, and a total memory utilization. The first cluster includes a central network node (such as central NRF 306) and one or more branch network nodes (such as local NRF 304-a, 304-b, and 304-c). In an aspect, the second network node (112) is configured to subscribe for the load information from the at least network node (such as central network node 306) of the first cluster by sending a subscription request to the at least one network node.

[0108] At step 504, the method (500) includes executing, by each network node of the first cluster, a load notification thread to determine a list of subscription requests for load information of at least one network node (306) from the second network node (112) after a predefined time interval. The load information includes the one or more parameters such as the total TPS processed by each network node, the number of currently registered NF profiles, and the total memory usage of each network node.These parameters collectively reflect the operational load and performance state of the network node. The list of subscription requests refers to a set of active requests received from the NWDAF, which indicate an interest in receiving load notifications. Each subscription request in the list may include details such as the type of load data requested, the identity of the target network node, the reporting interval or frequency, and the notification delivery endpoint.

[0109] At step 506, the method (500) includes determining, by the at least one network node, a deployment status of the at least one network node upon determining that a load notification to be sent is for the at least one network node based on the executed load notification thread. In an aspect, the deployment status is one of a branch network node and a central network node. In an aspect, the deployment status of the at least one network node is determined based on a set of information. The set of information includes information corresponding to the deployment status configured by a network operator for the at least one network node.

[0110] At step 508, the method (500) includes, in responsive to the determined deployment status of the at least one network node being the central network node (306), collecting, by the central network node (306), the calculated load information from each of the one or more branch network nodes (304-a, 304-b, 304-c). The method (500) further includes, storing, by the central network node (306), the load information corresponding to each of the one or more branch network nodes (304-a, 304-b, 304-c) and the central network node (306) of the first cluster in a database (212).

[0111] At step 510, the method (500) includes, communicating, by the central network node (306), the load notification to the second network node (112). The load notification includes load information of the central network node (306) and each of the one or more branch network nodes (304-a, 304-b, 304-c).

[0112] In an aspect, upon determining that the deployment status of the at least one network node is the branch network node, the method includes, communicating,by the branch network node (304-a, 304-b, 304-c), the calculated load information associated with the branch network node (304-a, 304-b, 304-c). to the central network node (306).

[0113] FIG. 6 illustrates an example computer system (600) in which or with which the embodiments of the present disclosure may be implemented.

[0114] As shown in FIG. 6, the computer system (600) may include an external storage device (610), a bus (620), a main memory (630), a read-only memory (640), a mass storage device (650), a communication port(s) (660), and a processor (670). A person skilled in the art will appreciate that the computer system (600) may include more than one processor and communication ports. The processor (670) may include various modules associated with embodiments of the present disclosure. The communication port(s) (660) may be any of an RS-232 port for use with a modembased dialup connection, a 10 / 100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or future ports. The communication ports(s) (660) may be chosen depending on a network, such as a Local Area Network (LAN), Wide Area Network (WAN), or any network to which the computer system (600) connects.

[0115] In an embodiment, the main memory (630) may be Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. The read-only memory (640) may be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chip for storing static information e.g., start-up or basic input / output system (BIOS) instructions for the processor (670). The mass storage device (650) may be any current or future mass storage solution, which can be used to store information and / or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives (internal or external, e.g., having Universal Serial Bus (USB) and / or Firewireinterfaces).

[0116] In an embodiment, the bus (620) may communicatively couple the processor(s) (670) with the other memory, storage, and communication blocks. The bus (620) may be, e.g. a Peripheral Component Interconnect PCI) / PCI Extended (PCI- X) bus, Small Computer System Interface (SCSI), Universal Serial Bus (USB), or the like, for connecting expansion cards, drives, and other subsystems as well as other buses, such a front side bus (FSB), which connects the processor (670) to the computer system (600).

[0117] In another embodiment, operator, and administrative interfaces, e.g., a display, keyboard, and cursor control device may also be coupled to the bus (620) to support direct operator interaction with the computer system (600). Other operator and administrative interfaces can be provided through network connections connected through the communication port(s) (660). Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system (600) limit the scope of the present disclosure.

[0118] In an exemplary embodiment, the present disclosure discloses a computer program product comprising a non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to perform a method for a method for communicating load information from a first cluster of network nodes towards a second network node is described. The method includes calculating, by each network node of the first cluster, a load information representing a utilization associated with a corresponding network node by analyzing one or more parameters. The first cluster includes a central network node and one or more branch network nodes. The method further includes executing, by each network node of the first cluster, a load notification thread to determine a list of subscription requests for load information of at least one network node from the second network node after a predefined time interval. The method further includes1 determining, by the at least one network node, a deployment status of the at least one network node, upon determining that a load notification to be sent is for the at least one network node based on the executed load notification thread. The deployment status is one of a branch network node and a central network node. The method further includes in response to the determined deployment status of the at least one network node, being the central network node, collecting, by the central network node, the calculated load information from each of the one or more branch network nodes The method further includes communicating, by the central network node, the load notification to the second network node. The load notification includes load information of the central network node and each of the one or more branch network nodes.

[0119] The present disclosure provides a technical advancement in the field of network analytics and management, particularly in multi-tier deployments involving distributed Network Repository Function (NRF) instances. By aggregating load information from all local NRFs, the central NRF is enabled to generate and transmit a more accurate and comprehensive load report to the Network Data Analytics Function (NWDAF). This ensures enhanced network performance monitoring and analysis by allowing NWDAF to operate based on a complete view of the network's operational state. The centralization of load data facilitates efficient management and optimization of network resources, enabling informed decision-making processes driven by real-time and system-wide utilization insights. Furthermore, the availability of timely and precise load notifications enhances the NWDAF ’s ability to detect, predict, and proactively respond to potential network issues, thereby contributing to improved network reliability, resilience, and overall stability. The disclosed approach also supports a scalable network architecture, where the addition of new local NRFs does not compromise the ability of the central NRF to aggregate and report load information, thus ensuring continued observability and control in growing deployments. Additionally, by standardizing the process of collecting and reporting load information across multiple NRF instances, the system ensures uniformity andconsistency in the data provided to NWDAF. This consistency is critical for enabling accurate data analysis, anomaly detection, and policy-based automation. As a result, NWDAF contributes to service optimization and maintains high-quality service delivery, ultimately benefiting end-users with more reliable, efficient, and responsive network services.

[0120] While the foregoing describes various embodiments of the invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.

[0121] The method and system of the present disclosure may be implemented in a number of ways. For example, the methods and systems of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order for the steps of the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above unless specifically stated otherwise. Further, in some embodiments, the present disclosure may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.

[0122] While considerable emphasis has been placed herein on the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiments ofthe disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter to be implemented merely as illustrative of the disclosure and not as limitation.ADVANCEMENTS OF THE PRESENT DISCLOSURE

[0123] The present disclosure described herein above has several technical advantages as follows:

[0124] The present disclosure facilitates a method for communicating load information from a first network node to a second network node.

[0125] The present disclosure ensures better network performance monitoring and analysis by utilizing a central Network Resource Function (NRF) to aggregate load information from all local NRFs and generate a more accurate and comprehensive load report for a Network Data Analytics Function (NWDAF).

[0126] The present disclosure improves network management by utilizing centralized load data. As the centralized load data allows for more efficient management and optimization of network resources, decisions can be based on a holistic view of the network's load status.

[0127] The present disclosure enhances reliability as the NWDAF relies on timely and precise notifications regarding network load, ultimately leading to improved network reliability and stability.

[0128] The present disclosure enhances scalability by collecting load information across multiple NRFs, supporting a scalable network architecture, and allowing for the addition of new local NRFs without compromising the central NRF's ability to monitor and report on network load effectively.

[0129] The present disclosure standardizes a process of collecting and reporting load information across all NRFs, ensuring consistency in the data providedto NWDAF and facilitating improved data analysis and decision-making.

[0130] The present disclosure improves service quality by allowing NWDAF to optimize service delivery and maintain high service quality, thereby benefiting endusers with more reliable and efficient network services.

Claims

CLAIMS1. A method (500) for communicating load information from a first cluster of network nodes (302-a) towards a second network node (112), the method (500) comprising: calculating (502), by each network node of the first cluster (302-a), a load information representing a utilization associated with a corresponding network node by analyzing one or more parameters, wherein the first cluster (302-a) comprises a central network node (306) and one or more branch network nodes (304-a, 304-b); executing (504), by each network node of the first cluster (302-a), a load notification thread to determine a list of subscription requests for load information of at least one network node from the second network node (112) after a predefined time interval; upon determining that a load notification to be sent is for the at least one network node based on the executed load notification thread, determining (506), by the at least one network node, a deployment status of the at least one network node, wherein the deployment status is one of a branch network node and a central network node; in responsive to the determined deployment status of the at least one network node being the central network node (306), collecting (508), by the central network node (306), the calculated load information from each of the one or more branch network nodes (304-a, 304-b); and communicating (510), by the central network node (306), the load notification to the second network node (112), wherein the load notificationcomprises load information of the central network node (306) and each of the one or more branch network nodes (304-a, 304-b).

2. The method (500) as claimed in claim 1, comprising: upon determining that the deployment status of the at least one network node is the branch network node (304-a or 304-b), communicating, by the branch network node (304-a or 304-b), the calculated load information associated with the branch network node (304-a or 304-b) to the central network node (306).

3. The method (500) as claimed in claim 1, wherein the network node of the first cluster is a Network Repository Function (NRF), and the second network node (112) is a Network Data Analytics Function (NWDAF).

4. The method (500) as claimed in claim 1, wherein the one or more parameters comprise a total current transaction per second (TPS), a number of registered profiles corresponding to each network node, and a total memory utilization.

5. The method (500) as claimed in claim 1, further comprising: storing, by the central network node, the load information corresponding to each of the one or more branch network nodes (304-a or 304-b) and the central network node (306) of the first cluster in a database (212).

6. The method (500) as claimed in claim 1, wherein the deployment status of the at least one network node is determined based on a set of information, wherein the set of information comprises information corresponding to the deployment status configured by a network operator for the at least one network node.

7. The method (500) as claimed in claim 1, wherein the second network node (112) is configured to subscribe for the load information from the at least network node of the first cluster by sending a subscription request to the at least one network node.

8. A system (108) for communicating load information from a first cluster of network nodes towards (302-a) a second network node (112), the system (108) comprising: a processing unit (208) configured to: calculate, by each network node of the first cluster (302-a), a load information representing a utilization associated with a corresponding network node by analyzing one or more parameters, wherein the first cluster comprises a central network node and one or more branch network nodes; execute, by each network node of the first cluster (302-a), a load notification thread to determine a list of subscription requests for load information of at least one network node from the second network node (112) after a predefined time interval; upon determining that a load notification to be sent is for the at least one network node based on the executed load notification thread, determine, by the at least one network node, a deployment status of the at least one network node, wherein the deployment status is one of a branch network node and a central network node; and in responsive to the determined deployment status of the at least one network node being the central network node (306), collect, by the central network node (306), the calculated load information from each of the one or more branch network nodes (304-a, 304-b); and a communication unit (210) configured to:communicate, by the central network node (306), a load notification to the second network node (112), wherein the load notification comprises load information of the central network node (306) and each of the one or more branch network nodes (304-a, 304- b).

9. The system (108) as claimed in claim 8, wherein upon determining that the deployment status of the at least one network node is the branch network node (304-a, 304-b), the communication unit (210) is configured to communicate, by the branch network node (304-a, 304-b), the calculated load information associated with the branch network node (304-a, 304-b) to the central network node (306).

10. The system (108) as claimed in claim 8, wherein the network node of the first cluster is a Network Repository Function (NRF), and the second network node (112) is a Network Data Analytics Function (NWDAF).

11. The system (108) as claimed in claim 8, wherein the one or more parameters comprises a total current transaction per second (TPS), a number of registered profiles corresponding to each network node, and a total memory utilization.

12. The system (108) as claimed in claim 8, wherein the processing unit is configured to store, by the central network node (306), the load information corresponding to each of the one or more branch network nodes (304-a, 304- b) and the central network node (306) of the first cluster in a database (212).

13. The system (108) as claimed in claim 8, wherein the deployment status of the corresponding network node is determined based on a set of information, wherein the set of information comprises information corresponding to the deployment status configured by a network operator for at least one network node.

14. The system (108) as claimed in claim 8, wherein the second network node (112) is configured to subscribe for the load information from at least one network node of the first cluster by sending a subscription request to the at least one network node.

15. A computer program product comprising a non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to perform a method for communicating load information from a first cluster of network nodes towards a second network node, the method comprising: calculating (502), by each network node of the first cluster (302-a), a load information representing a utilization associated with a corresponding network node by analyzing one or more parameters, wherein the first cluster comprises a central network node (306) and one or more branch network nodes (304-a, 304-b); executing (504), by each network node of the first cluster (302-a), a load notification thread to determine a list of subscription requests for load information of at least one network node from the second network node after a predefined time interval; upon determining that a load notification to be sent is for the at least one network node based on the executed load notification thread, determining (506), by the at least one network node, a deployment status of the at least one network node, wherein the deployment status is one of a branch network node and a central network node; in responsive to the determined deployment status of the at least one network node being the central network node (306), collecting (508), by thecentral network node (306), the calculated load information from each of the one or more branch network nodes (304-a, 304-b); and communicating (510), by the central network node (306), the load notification to the second network node (112), wherein the load notification comprises load information of the central network node (306) and each of the one or more branch network nodes (304-a, 304-b).

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