Method and system for sorting customer data in a network

Abstract

The present disclosure provides a system (108) and a method (500) for sorting customer data in a network. The method (500) includes receiving at least one request from a second network function (302). The at least one request include the customer data associated with a customer. The method (500) further includes extracting one or more parameters from the at least one received request. The method (500) includes determining a request type and a customer type based on the one or more extracted parameters. Further, the method (500) includes categorizing the customer data based, at least in part, on the determined request type and the customer type. The method (500) further includes storing the categorized customer data in two or more storage locations.

Description

METHOD AND SYSTEM FOR SORTING CUSTOMER DATA IN A NETWORKRESERVATION 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 (JPL) 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 to a field of telecommunications network. In particular, the present disclosure relates to a method and a system for sorting customer data in a network.DEFINITIONS

[0003] As used in the present disclosure, the following terms are generally intended to have the meaning as set forth below, except to the extent that the context in which they are used to indicate otherwise.

[0004] The term ‘Charging Function (CHF)’ as used herein in the specification refers to a network function that manage and process charging information within the 5G network architecture. The CHF is responsible for collecting, processing, and forwarding charging data related to user sessions and network resource usage, ensuring accurate billing and cost management.

[0005] The term ‘Charging Function-Broadband Network Gateway (CHF-BNG)’ used herein in the specification refers to a specialized component in a Fifth Generation (5G) network that integrates charging and policy management with broadband network gateway operations. The CHF-BNG manages the billing, policycontrol, and record-keeping functions necessary for handling customer data services.

[0006] The term ‘Session Management Function (SMF)’, as used herein in the specification refers to a core network component of the 5G network architecture. The SMF handles session-related functions in the 5G networks, such as session establishment, modification, and termination.

[0007] The term ‘Prepaid customer’, as used herein in the specification refers to a customer who pays in advance for telecommunication services, such as voice calls, data usage, or Short Message Service (SMS), before using them. In a prepaid model, the customer loads a specific amount of credit into their account, which is then deducted as they consume services.

[0008] The term ‘Postpaid customer’ as used herein in the specification refers to a customer who subscribes to telecommunications services (like calls, data, or SMS) and is billed after the customer have used the services. Unlike prepaid customers who pay in advance, postpaid customers consume services first and pay later based on their usage.

[0009] The term ‘Online service’ as used herein in the specification refers to a service that involves real-time interaction, communication, or data exchange, typically requiring an active and continuous connection to the network. In the context of charging and billing, ‘online service’ often relates to services that are monitored and charged in real-time, such as real-time data usage, instant communication services like Voice over Internet Protocol (VoIP), and video call.

[0010] The term ‘Offline service’ as used herein in the specification refers to a service where usage data and related transactions are not processed in real-time. Instead, the services are collected, stored, and billed later, typically in batch mode. Offline services do not require immediate monitoring or charging while the service is being used.

[0011] The term ‘Call Detail Records (CDRs)’ as used herein in the specification refers to a data record produced by a telecommunications system that documents the details of a telephone call or other communications transaction (such as SMS or data usage) that passes through that system. The CDR captures specific information needed for billing, analysis, and monitoring purposes.

[0012] The term ‘Online Charging System (OCS)’ as used herein in the specification refers to a billing system that handles real-time charging and billing for services such as voice calls, SMS, data usage, and other value-added services.

[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] Efficient and accurate charging mechanisms are critical for the financial operations of telecommunications networks. In 5G networks, a Charging Function (CHF) manages the financial operations, such as charging a customer based on the services used, along with policy control and record-keeping. The CHF works closely with a Session Management Function (SMF) to ensure that customer services are delivered according to the predefined policies based on their subscription and usage patterns. The CHF may store information about each session and transaction corresponding to the customers as Call Detail Records (CDRs) in a directory.

[0016] In a 5G network, customers are generally categorized into prepaid and postpaid types, reflecting their payment methods and billing structures. Prepaidcustomers pay in advance for their services, offering flexibility and control over expenses without long-term contracts. In contrast, postpaid customers are billed after usage, often benefiting from additional features or discounts and typically being tied to contracts. Services within the network are also classified into online and offline categories. Online services, such as streaming and cloud applications, require continuous internet access and are often data intensive. Offline services, including voice calls and Short Message Service (SMS), operate without a constant internet connection and rely on traditional cellular technologies.

[0017] The categorization of the customer and the services results in four distinct customer-service pairs: a prepaid customer with offline services (prepaid-offline), a prepaid customer with online services (prepaid-online), a postpaid customer with offline services (postpaid-offline), and a postpaid customer with online services (postpaid-online). Each customer-service pair involves different charging and policy mechanisms. For instance, for the prepaid-online customer, real-time charging is essential because the service must check the available balance before delivering the requested service to the customer. In contrast, the postpaid-offline pair involves billing based on usage records, after the service has been consumed by the customer.

[0018] In conventional techniques, the CDRs are saved collectively in a single directory, regardless of customer type or service type. As the volume of data grows, the practice introduces several inefficiencies. The storage of large volumes of data in a single folder can lead to performance degradation, making it difficult to manage, retrieve, and process the CDRs. The large size of the directory may slow down access time, affect backup and recovery processes, and increase the likelihood of file system errors or crashes.

[0019] 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

[0020] In an exemplary embodiment, a method for sorting customer data in a network is described. The method includes receiving at least one request from a second network function. The at least one request includes the customer data associated with a customer. The method further includes extracting one or more parameters from the at least one received request. The method includes determining a request type and a customer type based on the one or more extracted parameters. Further, the method includes categorizing the customer data based, at least in part, on the determined request type and the customer type. The method further includes storing the categorized customer data in two or more storage locations.

[0021] In an embodiment, the customer data is categorized using a sorting algorithm.

[0022] In another embodiment, the sorting algorithm includes determining a storage location among the two or more storage locations from a database based on the determined request type and the customer type. The sorting algorithm further includes accessing a storage location identifier (ID) corresponding to the determined storage location. The sorting algorithm includes assigning the storage location ID to the customer data.

[0023] In another embodiment, the method further comprising storing the customer data as a Call Detail Record (CDR) in a corresponding storage location associated with the assigned storage location ID in the database.

[0024] In another embodiment, the at least one request includes details of a data plan, and the details include a remaining data volume and a validity of the data plan.

[0025] In another embodiment, the two or more storage locations are created in the database based on one or more combinations of the request type and the customer type. The two or more storage locations include an online-prepaid customer storage location, an online-postpaid customer storage location, an offline-prepaid customer storage location and an offline-postpaid storage location. The storage location ID ismapped with each of the two or more storage locations, and the storage location ID mapped with each storage location is a unique storage location ID.

[0026] In another embodiment, the first network function is a Charging Function (CHF), and the second network function is a Session Management Function (SMF).

[0027] In another embodiment, the one or more parameters include a quota management indicator and a media access control (MAC) identifier (ID).

[0028] In another embodiment, the request type includes an online request and an offline request, and the customer type includes a pre-paid customer and a post-paid customer.

[0029] In another exemplary embodiment, a system for sorting customer data in a network is described. The system includes a receiving unit configured to receive at least one request from a second network function. The at least one request includes the customer data associated with a customer. The system further includes an extraction unit configured to extract one or more parameters from the at least one received request. Further, the system includes a determining unit configured to determine a request type and a customer type based on the one or more extracted parameters. The system further includes an execution unit configured to categorize the customer data based, at least in part, on the determined request type and the customer type. The execution unit is further configured to store the categorized customer data in two or more storage locations.

[0030] In yet another embodiment, a computer program product including a non- transitory computer-readable medium including instructions that, when executed by one or more processors, cause the one or more processors to execute a method for sorting customer data in a network is described. The method includes receiving at least one request from a second network function. The at least one request includes the customer data associated with a customer. The method further includes extracting one or more parameters from the at least one received request. The method includes determining a request type and a customer type based on the oneor more extracted parameters. Further, the method includes categorizing the customer data based, at least in part, on the determined request type and the customer type. The method further includes storing the categorized customer data in two or more storage locations.OBJECTIVES OF THE PRESENT DISCLOSURE

[0031] Some of the objectives of the present disclosure, which at least one embodiment herein satisfies, are as follows:

[0032] An objective of the present disclosure is to provide a method and a system to create separate folders for each type of customer-service pair (Prepaid-Offline, Prepaid-Online, Postpaid-Offline, and Postpaid-Online) to segregate Call Detail Records (CDRs) effectively.

[0033] Another objective of the present disclosure is to provide a method and a system to easily manage and retrieve information of the customers and associated services.

[0034] Another objective of the present disclosure is to provide a method and a system that segregates data to allow faster analysis and processing of the CDRs, optimizing overall system performance.

[0035] Another objective of the present disclosure is to reduce data corruption or loss by organizing the CDRs into dedicated folders based on customer categories.

[0036] Another objective of the present disclosure is to automate the process of separating the CDRs into distinct folders, reducing manual intervention and minimizing errors in record management.

[0037] Other objectives and advantages of the present disclosure will be more apparent from the following description, which is not intended to limit the scope of the present disclosure.BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS

[0038] 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 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 the disclosure of electrical components, electronic components or circuitry commonly used to implement such components.

[0039] FIG. 1 illustrates an exemplary network architecture of a system configured for sorting customer data in a network, in accordance with an embodiment of the present disclosure.

[0040] FIG. 2 illustrates an exemplary block diagram of the system configured for sorting the customer data in the network, in accordance with an embodiment of the present disclosure.

[0041] FIG. 3 illustrates an exemplary system architecture for sorting the customer data in the network, in accordance with an embodiment of the present disclosure.

[0042] FIG. 4 illustrates an exemplary flow diagram of a method for sorting the customer data in the network, in accordance with an embodiment of the present disclosure.

[0043] FIG. 5 illustrates another exemplary flow diagram of the method for sorting the customer data in the network, 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 detailed description of the disclosure.LIST OF REFERENCE NUMERALS100 - Network architecture102 - User(s)104 -User Equipments (UEs)106 - Network108 - System200 - Block diagram202 - Processor(s)204 - Memory206 -Interface(s)208 - Processing engine210 - Database212 - Receiving unit214 - Extraction unit216 - Determining unit218 - Execution unit300 - System Architecture302 - Session Management Function (SMF)304 - Charging Function (CHF)306 - Online Charging System (OCS)308 - Directory400 - Flow Diagram500 - Method600 - A computer system610 - External Storage Device620 - Bus630 - Main Memory640 - Read Only Memory650 - Mass Storage Device660 - Communication Port670 - 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 ofthe 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 embodiment may be described as a process 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 only and 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 forthe 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] As used herein, an “electronic device”, or “portable electronic device”, or “user device” or “communication device” or “user equipment” or “device” refers to any electrical, electronic, electromechanical, and computing device. The user device is capable of receiving and / or transmitting one or parameters, performing fimction / s, communicating with other user devices, and transmitting data to the other user devices. The user equipment may have a processor, a display, a memory, a battery, and an input-means such as a hard keypad and / or a soft keypad. The user equipment may be capable of operating on any radio access technology including but not limited to IP-enabled communication, Zig Bee, Bluetooth, Bluetooth Low Energy, Near Field Communication, Z-Wave, Wi-Fi, Wi-Fi direct, etc. For instance, the user equipment may include, but not limited to, a mobile phone, smartphone, virtual reality (VR) devices, augmented reality (AR) devices, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other device as may be obvious to a person skilled in the art for implementation of the features of the present disclosure.

[0054] Further, the user device may also comprise a “processor” or “processing unit” includes processing unit, wherein processor refers to any logic circuitry for processing instructions. The 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 Signalling Processing (DSP) core, a controller, a microcontroller, Application Specific Integrated Circuits, Field Programmable Gate Array circuits, any other type of integrated circuits, etc. The processor may perform signal codingdata 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 is a hardware processor.

[0055] 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.

[0056] Wireless communication technology has rapidly evolved over the past few decades. The first generation of wireless communication technology was analog, offering only voice services. Further, text messaging and data services became possible when the second-generation (2G) technology 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, improved network coverage, and security. Currently, fifth generation (5G) technology is being deployed, offering significantly faster data speeds, lower latency, and the ability to connect many devices simultaneously. These advancements represent a significant leap forward from previous generations, enabling enhanced mobile broadband, improved Internet of Things (loT) connectivity, and more efficient use of network resources. The sixth generation (6G) technology promises to build upon these advancements, pushing the boundaries of wireless communication even further. While the 5G technology is still being rolled out globally, research and development into the 6G are rapidly progressing, with the aim of revolutionizing the way to connect and interact with technology.

[0057] In 5G networks, effective management of customer charging and policy control is essential for delivering the services. A Charging Function (CHF) handles the charging operations by processing Call Detail Records (CDRs) based on customer data usage. Customers are classified into two primary categories, such as prepaid and postpaid, and the customers utilize services that may be online or offline, resulting in four customer-service combinations, such as Prepaid-Offline, Prepaid-Online, Postpaid-Offline, and Postpaid-Online. The Prepaid-Offline customers use services like voice calls and short message service (SMS), while Prepaid-Online customers access data-intensive services such as streaming and cloud applications with pre-paid plans. Postpaid-Offline customers are billed after using standard services, and Postpaid-Online customers enjoy postpaid billing for high-bandwidth online services.

[0058] Conventionally, the CDRs generated for each of the customer-service combinations are stored collectively in a single directory without distinguishing between the different customer-service categories. As the volume of CDRs increases, the conventional techniques may lead to several inefficiencies. The accumulation of large amounts of unsegregated CDRs within a single directory deteriorates system performance, making it difficult to access, retrieve, and analyse the CDRs. Moreover, the lack of organization of CDRs introduces operational complexities such as increased risk of errors, and ambiguities during data processing and analysis. This ultimately affects the accuracy of policy enforcement and degrades the quality of service delivered to customers.

[0059] There is, therefore, a need for a method and a system that sorts the CDRs based on each customer-service combination. The present disclosure provides an enhanced method and the system to create separate folders for each customerservice pair to store the CDRs associated with the corresponding customer-service pair.

[0060] The present disclosure introduces a method and a system to segregate the CDRs based on the customer type and service category. Instead of storing all CDRstogether in a single directory, the present disclosure automatically creates separate folders for each of the customer-service combinations such as, Prepaid-Offline, Prepaid-Online, Postpaid-Offline, and Postpaid-Online. The present disclosure ensures that the CDRs are categorized and stored efficiently, leading to improved data management, faster retrieval, and streamlined analysis.

[0061] By segregating the customer data, the present disclosure enhances performance and reduces the risk of errors and ambiguity in CDRs handling. Additionally, the present disclosure categorizes and stores the CDRs, which reduces manual intervention and operational overhead, leading to a more efficient and scalable system. The present disclosure optimizes the storage and management of the CDRs, ensuring more accurate and reliable charging operations while maintaining system integrity and performance.

[0062] Hereinafter, exemplary embodiments of the present disclosure will be described with reference to the accompanying drawings. The various embodiments throughout the disclosure will be explained in more detail with reference to FIG. 1 - FIG. 6.

[0063] FIG. 1 illustrates an exemplary network architecture 100 of a system 108 for sorting customer data in a network, in accordance with an embodiment of the present disclosure. As illustrated in FIG. 1, the network architecture 100 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, however, any number of the UE 104 may be included without departing from the scope of the ongoing description.

[0064] In an embodiment, the UE 104 may include smart devices operating in a smart environment, for example, Internet of Things (loT) system. In such anembodiment, 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, multi-sensing, network-connected devices, that may integrate seamlessly with each other and / or with a central server or a cloudcomputing system or any other device that is network-connected.

[0065] 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), awearable computer device (e.g., aheadmounted 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 input from 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.

[0066] In FIG. 1, the UE 104 may communicate with the system 108 through the network 106 for sending or receiving various types of data. In an embodiment, the network 106 may include at least one of a 5th Generation (5G) network, a 6th 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.

[0067] 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, one or more of, 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, the PSTN, a cable network, a cellular network, a satellite network, a fiber optic network, or some combination thereof.

[0068] 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.

[0069] In an embodiment, the system 108 may sort customer data in the network 106. The customers may be associated with the UE 104, such as user 102. Further, the customer data may include a CDR of the UE 104, indicating services availedand operations performed by the customer in the network 106. In an embodiment, the system 108 may include a first network function that receives at least one request from a second network function. The at least one request includes the customer data associated with the customer. The first network function may be a CHF, and the second network function may be a Session Management Function (SMF). Further, the at least one request may include details of a data plan, and the details of the data plan may include a remaining data volume and a validity of the data plan. The system 108 may extract one or more parameters from the at least one received request. The one or more parameters may include a quota management indicator and a Media Access Control (MAC) identifier (ID). Further, the system 108 may determine a request type and a customer type based on the one or more extracted parameters. The request type may include an online request and an offline request, and the customer type may include a pre-paid customer and a post-paid customer. Further, the system 108 may categorize the customer data based, at least in part, on the determined request type and the customer type. In an embodiment, the customer data may be categorized using a sorting algorithm. The sorting algorithm may determine a storage location among the two or more storage locations from a database based on the determined request type and the customer type. Further, the sorting algorithm may access a storage location identifier (ID) corresponding to the determined storage location. The sorting algorithm assigns the storage location ID to the customer data. The two or more storage locations are created in the database based on one or more combinations of the request type and the customer type. The two or more storage locations may include an online-prepaid customer storage location, an online-postpaid customer storage location, an offline- prepaid customer storage location and an offline-postpaid storage location. Further, the storage location ID is mapped to each of the two or more storage locations. The storage location ID mapped with each storage location is a unique storage location ID. Further, the system 108 may store the categorized customer data in the two or more storage locations. The system 108 stores the customer data as the CDR in a corresponding storage location associated with the assigned storage location ID in the database 210.

[0070] Conventionally, the system 108 may generate a combined document which may include the customer data corresponding to each of the at least one request. The combined document may then be parsed to retrieve the required customer data. In contrast, the system 108 sorts the customer data corresponding to each of the at least one request based on the request type and the customer type, effectively creating four categories of the customer data which may then be easily parsed to retrieve the required customer data. The sorting of the customer data may help in faster retrieval of the customer data, minimal resource utilization, and reducing the risk of data corruption or loss.

[0071] Although FIG. 1 shows exemplary components of the network architecture 100, in other embodiments, the network architecture 100 may include fewer components, different components, differently arranged components, or additional functional components than depicted in FIG. 1. Additionally, or alternatively, one or more components of the network architecture 100 may perform functions described as being performed by one or more other components of the network architecture 100.

[0072] FIG. 2 illustrates an exemplary block diagram 200 of the system 108 configured for sorting customer data in the network 106, in accordance with an embodiment of the disclosure.

[0073] 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 one or 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 anynon-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.

[0074] 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 (RO), 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 engine 208 and a database 210.

[0075] In an embodiment, the system 108 may include a processing engine 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 engine 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 engine 208 may be processorexecutable instructions stored on a non-transitory machine -readable storage medium and the hardware for the processing engine 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 engine 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 engine 208 may be implemented by electronic circuitry. In an embodiment, the processing engine 208 may include a receiving unit 212, an extraction unit 214, a determining unit 216, and an execution unit 218.

[0076] In an embodiment, the processing engine 208 is configured for sorting the customer data in the network 106. The receiving unit 212 of the processing engine 208 may be configured to receive at least one request from a second network function. In an example, the second network function is a SMF. The at least one request includes the customer data associated with a customer. The customer data may include a customer type, a service type, a service availed by the customer, a time duration of the service availed by the customer, a customer Internet Protocol (IP) address, etc. Further, the at least one request includes details of a data plan, and the details may include a remaining data volume and a validity of the data plan. In an example, the data plan defines the services which may be availed by the customer at a specific data rate (i.e., lOmbps, 2mbps, etc.) for a defined time period (i.e., 28 days, 84 days, etc.).

[0077] In an embodiment, the extraction unit 214 of the processing engine 208 may be configured to extract one or more parameters from the at least one received request. The one or more parameters may include a quota management indicator and a MAC ID. The MAC ID is a unique hardware address assigned to network interfaces. The MAC ID serve as a device-level identifier that helps associate customers with specific subscription types, such as prepaid or postpaid plans. The quota management indicator may be a flag which may be used to monitor, signal, or manage the usage of allocated data or service quotas for the customer.

[0078] In an embodiment, the determining unit 216 of the processing engine 208 may be configured to determine a request type and a customer type based on the one or more extracted parameters. The request type may include an online request and an offline request, and the customer type may include a pre-paid customer and the post-paid customer. The quota management indicator “quotaManagementlndicator” may include a value corresponding to the online service request or the offline service request. In an example, the CHF may extract the “quotaManagementlndicator” flag which may include a value “online” corresponding to the online request initiated by the customer. Further, when the customer’s UE 104 connects to the network 106, the MAC ID is used to retrievethe customer profile from the database 210. The customer profile may further include the type of subscription the customer is using, such as pre-paid or post-paid.

[0079] In an embodiment, the execution unit 218 of the processing engine 208 is configured to categorize the customer data based, at least in part, on the determined request type and the customer type. The execution unit 218 may effectively segregate the customer data into four customer-service pairs, such as the postpaid- online, the postpaid-offline, the prepaid-online, and the prepaid-offline. The execution unit 218 may categorize the customer data using a sorting algorithm. Further, the execution unit 218 may perform the sorting algorithm configured to determine a storage location among the two or more storage locations from the database 210 based on the determined request type and the customer type. Further, the execution unit 218 may perform the sorting algorithm configured to access a storage location identifier (ID) corresponding to the determined storage location. The storage location ID is a unique identifier corresponding to each of the two or more storage locations. The execution unit 210 may execute the sorting algorithm which is further configured to assign the storage location ID to the customer data. In an example, the sorting algorithm may assist the execution unit 218 in accessing the storage location ID that corresponds to the determined storage location. Once the storage location ID is retrieved, the storage location ID is assigned to the customer data, tagging the customer data with a pointer to its exact storage location. The storage location ID enables rapid lookup and retrieval in future operations and ensures that customer data management follows a consistent, organized pattern based on service type and the customer type.

[0080] In an exemplary embodiment, the CHF categorizes the incoming customer data by determining the request type (such as online request or offline request) and the customer type (such as prepaid customer or postpaid customer). When the customer data is received, the CHF identifies that the customer is, for example, the postpaid customer who made a transaction through an offline channel. Using the sorting algorithm, the execution unit 218 categorizes the customer data under the postpaid-offline service pair. Similarly in another example, if the customer datacorresponds to a prepaid customer who topped up online, the customer data may be categorized under the prepaid-online service pair. Upon categorizing the customer data, the sorting algorithm helps in identifying a specific storage location from the database 210. For example, there may be separate storage buckets / locations for "postpaid-online", "postpaid-offline", "prepaid-online", and "prepaid-offline" customer records. The CHF may retrieve a storage location ID, which acts as a unique pointer to the exact place where the customer’s call record should be stored. After retrieving the storage location ID, the CHF tags the customer data with the storage location ID, making it easier to rapidly retrieve the record for future billing, analysis, or customer service purposes.

[0081] Further, the execution unit 218 may be configured to store the categorized customer data in two or more storage locations. The two or more storage locations are created in the database 210 based on one or more combinations of the request type and the customer type. The two or more storage locations include an online- prepaid customer storage location, an online-postpaid customer storage location, an offline-prepaid customer storage location and an offline-postpaid customer storage location. The storage location ID is mapped with each of the two or more storage locations, and the storage location ID mapped with each storage location is a unique storage location ID.

[0082] In another embodiment, the execution unit 218 is further configured to store the customer data as a CDR in a corresponding storage location associated with the assigned storage location ID in the database 210. In some embodiments, the one or more storage locations may be the online -prepaid storage location corresponding to store the customer data of the online-prepaid customer service pair, the online- postpaid storage location corresponding to store the customer data of the online- postpaid customer service pair, the offline-prepaid storage location corresponding to store the customer data of the offline-prepaid customer service pair, and the offline-postpaid storage location corresponding to store the customer data of the offline-postpaid customer service pair.

[0083] In an exemplary embodiment, a telecommunications operator manages Call Detail Records (CDRs) for prepaid and postpaid customers, who use both real-time data (online) and monthly voice call (offline) services. The telecommunications operator may automatically segregate the CDRs into four distinct folders based on customer and service type such as Prepaid-Online, Prepaid-Offline, Postpaid- Online, and Postpaid-Offline. For example, when a prepaid customer “Priya” uses internet service, the SMF send a usage update to the CHF-BNG. The CHF-BNG identifies “Priya” as a prepaid customer with an online service. The CHF-BNG generates a CDR associated with the internet service, and stores it in the "Prepaid- Online" folder. Similarly, when a postpaid customer “Aqun” makes a voice call, the CHF-BNG saves the corresponding CDR in the "Postpaid-Offline" folder. During audit of “Priya’ s” CDR, the telecommunication operator’s team accesses the "Prepaid-Online" folder directly, retrieving Priya’s CDR for analysis, significantly speeding up the process. The automated segregation allows the telecommunication operator to quickly access specific CDRs for audits, accurate billing, and data management.

[0084] In an embodiment, the system 108 may include the database 210 that includes data (e.g., the customer type, the service type, the CDRs, the customer data etc.) that may be either stored or generated as a result of functionalities implemented by any of the components of the processor 202 or the processing engine 208.

[0085] FIG. 3 illustrates an exemplary system architecture 300 for sorting the customer data in the network 106, in accordance with an embodiment of the present disclosure. FIG. 3 is explained in conjunction with the FIGs. 1 and 2.

[0086] In FIG. 3, the system architecture 300 may include the SMF 302, the CHF 304, an Online Charging System (OCS) 306, and the directory 308. The SMF 302 may interact with the CHF 304 and vice versa. The CHF 304 may interact with the OCS 306 and vice versa. Further, the CHF 304 may interact with the directory 308. The SMF 302 may manage session policies and data usage for the customers. The SMF 302 may send update requests to the CHF 304 regarding the customer’s datausage. Further, based on the data usage reported by the SMF 302, the customer’s session policy is validated and updated.

[0087] In an embodiment, the CHF 304 handles the charging process for customers based on the data usage reported by the SMF 302. The CHF 304 applies charging policies based on the customer’s subscription type and usage. The CHF 304 may extract customer data from the request received from the SMF 302. The CHF 304 may also apply logical algorithms to segregate the customer data based on the one or more parameters associated with the customer. By a way of an example, the CHF 304 may extract a ‘quotaManagementlndicator’ to identify the online services and offline services availed by the customers. Further, the CHF 304 may extract a ‘Macld’ to identify if the customer is a postpaid customer or a prepaid customer. The CHF 304 may perform categorization (one or more operations) on the customer data to effectively segregate the customer data into four customer-service pairs, such as the postpaid-online, the postpaid-offline, the prepaid-online, and the prepaid-offline. Further, in an embodiment, the SMF 302 may receive a response from the CHF 304 corresponding to a successful reception of the received update request.

[0088] In an embodiment, the OCS 306 applies session policies in real-time, such as service limits or quotas for data usage. The OCS 306 complements?? the CHF 304 in segregating the online services and the offline services of the customers. The OCS 306 is typically used to track and manage charges for the network services complementary with the CHF 304.

[0089] In an embodiment, the directory 308 may store the customer data extracted by the CHF 304. The directory 308 may store the customer data in the form of the CDRs. The directory 308 may include one or more folders to store the extracted customer data. In examples, the directory 308 may include, for example, an OfflinePostpaidCDR folder for the postpaid-offline customer data, an OfflinePrepaidCDR for the prepaid-offline customer data, an OnlinePostpaidCDRfor the postpaid-online customer data, and an OnlinePrepaidCDR for the prepaid- online customer data.

[0090] FIG. 4 illustrates an exemplary flow diagram 400 of a method for sorting the customer data in the network, in accordance with an embodiment of the present disclosure. FIG. 4 is explained in conjunction with the FIGs. 1, 2, and 3. Each step of the method 400 may be performed by various units (e.g., the receiving unit 212, the extraction unit 214, the determining unit 216, and the execution unit 218) present within the processing engine 208 of the system 108. The elements and steps described in the figure are part of a process implemented within the CHF 304, which acts as a central system for receiving customer data, analysis, and decision-making.

[0091] At step 402, the process 400 is initiated. At step 404, a request is received from the SMF 302 for a customer to report usage of data to the CHF 304. The CHF 304 may then update the customer about the remaining data and validation policy. The request may include one or more parameters associated with the customer. The one or more parameters are associated with a customer type and a service type. The customer type includes a prepaid customer and a postpaid customer, and a service type includes an online service and an offline service. By a way of an example, the CHF 304 may extract the ‘quotaManagementlndicator’ to identify the online services and offline services availed by the customers. Further, the CHF 304 may extract a ‘Macld’ to identify the postpaid customers and the prepaid customers, effectively segregating the customer data into four customer-service pairs, such as the postpaid-online, the postpaid-offline, the prepaid-online, and the prepaid- offline.

[0092] At step 406, the request is determined as one of the online service requests or the offline service request. If the request is determined as the online service request, at step 408, the customertype is determined as one ofthe prepaid customers or the postpaid customer. In examples, the customer type may be identified by the CHF 304 by importing the policy from the SMF 302.

[0093] If the customer type is determined as the prepaid customer, at step 410, a folder is created for the CDRs associated with the prepaid-online combination of the request. The folder may be named as OnlinePrepaidCDR file. In examples, the folder may store the CDRs associated with the prepaid-online combination of the service.

[0094] If the customer type is determined as the postpaid customer, at step 412, a folder is created for the CDRs associated with the postpaid-online combination of the request. The folder may be named as OnlinePostpaidCDR file. In examples, the folder may store the CDRs associated with the postpaid-online combination of the service.

[0095] Further, if the request is determined as the offline service request, at step 414, the customer type is determined as one of the prepaid customers or the postpaid customer. If the customer type is determined as the prepaid customer, at step 416, a folder is created for the CDRs associated with the prepaid-offline combination of the request. The folder may be named as OfflinePrepaidCDR file. In examples, the folder may store the CDRs associated with the prepaid-offline combination of the service.

[0096] If the customer type is determined as the postpaid customer, at step 418, a folder is created for the CDRs associated with the postpaid-offline combination of the request. The folder may be named as OfflinePostpaidCDR file . In examples, the folder may store the CDRs associated with the postpaid-offline combination of the service. Further, at step 420, the process 400 is terminated.

[0097] The present disclosure automates dumping of the CDR files for customers into different folders, segregating the customer data for future analysis and audits based on customer type and request type. In an embodiment, an update request is received from the SMF 302 for a customer to report the usage of data and correspondingly, the customer is updated with remaining volume and the validating policy. In an embodiment, the customer may either prepaid or postpaid and similarly request may also be for two services offline or online. In one embodiment,each combination of customer type and service request is handled separately, with the request being processed based on predefined logical algorithms. In an embodiment, to maintain the logs of the manipulation, separate folders are created and the information in the form of the CDR files is dumped. In an embodiment, the folders are names as ‘OnlinePrepaidCDR’, and ‘OffhnePrepaidCDR’ for prepaid customers and ‘OffhnePostpaidCDR’, and ‘OnlinePostpaidCDR’ for postpaid customers.

[0098] FIG. 5 illustrates another exemplary flow diagram of the method 500 for sorting the customer data in the network 106, in accordance with an embodiment of the present disclosure. FIG. 5 is explained in conjunction with the FIGs. 1, 2, 3, and 4.

[0099] At step 502, at least one request from a second network function is received. The at least one request may include the customer data associated with a customer. The second network function is a Session Management Function (SMF). In some embodiments, the at least one request may include details of a data plan, and the details may further include a remaining data volume and a validity of the data plan.

[0100] At step 504, one or more parameters are extracted from the at least one received request. The one or more parameters may include a quota management indicator and a media access control (MAC) identifier (ID). In an embodiment, the quota management indicator parameter is used to signify whether the data usage for a session should be monitored or controlled based on a defined quota or policy. Further, the MAC ID is a unique hardware address associated with the UE 104 of the customer at a data link layer. The MAC ID enables identification and tracking of the UEs 104 across different parts of the network 106.

[0101] At step 506, a request type and a customer type are determined based on the one or more extracted parameters. The request type may include an online request and an offline request, and the customer type may include a pre-paid customer and a post-paid customer. The request type may categorize the nature of the operation being requested by the at least one request. The online request may refer to a real-time processing where immediate action or response is required such as balance checks or session initiation, and the offline request may involve deferred processing activities, such as billing reconciliation or batch updates. Further, the pre-paid customer may pay for services in advance and requires credit validation before service usage, and the post-paid customer uses services first and is billed afterward based on usage records.

[0102] At step 508, the customer data is categorized, based at least in part, on the determined request type and the customer type. The customer data is categorized using a sorting algorithm. The sorting algorithm may include determining a storage location among the two or more storage locations from a database based on the determined request type and the customer type. Further, the sorting algorithm may include accessing a storage location identifier (ID) corresponding to the determined storage location. Finally, the sorting algorithm may include assigning the storage location ID to the customer data. In an embodiment, the sorting algorithm operates by first determining an appropriate storage location from among multiple available storage locations in a database. The choice of storage location depends on the specific request type and customer type associated with the incoming data. Once the correct storage location is identified, the sorting algorithm accesses the corresponding storage location ID, which uniquely represents the storage area in the database where the customer data needs to be placed. The customer data is tagged or assigned with the storage location ID.

[0103] At step 510, the categorized customer data is stored in two or more storage locations. The two or more storage locations are created in the database based on one or more combinations of the request type and the customer type. The two or more storage locations may include an online-prepaid customer storage location, an online-postpaid customer storage location, an offline-prepaid customer storage location and an offline-postpaid storage location. Further, the storage location ID is mapped with each of the two or more storage locations, and the storage location ID mapped with each storage location is a unique storage location ID.

[0104] In an embodiment, the method 500 may further store the customer data as a CDR in a corresponding storage location associated with the assigned storage location ID in the database. After processing, each customer's CDR is associated with a specific storage location ID within the database based on the categorization of the customer data. The customer’s CDR may contain important communication- related data such as call duration, time, source and destination numbers, and service usage details. Further, the customer’s CDR is systematically stored in a predefined or dynamically assigned storage corresponding to the assigned storage location ID.

[0105] FIG. 6 illustrates an exemplary computer system 600 in which or with which embodiments of the present disclosure may be implemented. 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, 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 modem-based 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 port(s) 660 may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which the computer system 600 connects.

[0106] The main memory 630 may be a 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) chips 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 device 650 includes, but is not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives orsolid-state drives (internal or external, e.g., having Universal Serial Bus (USB) and / or Firewire interfaces), one or more optical discs, Redundant Array of Independent Disks (RAID) storage, e.g. an array of disks.

[0107] The bus 620 communicatively couples the processor 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.

[0108] Optionally, operator and administrative interfaces, e.g., a display, keyboard, joystick, and a cursor control device, may also be coupled to the bus 620 to support direct operator interaction with the computer system. 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.

[0109] In an embodiment, a computer program product including a non-transitory computer-readable medium including instructions that, when executed by one or more processors, cause the one or more processors to execute a method for sorting customer data in a network. The method includes receiving at least one request from a second network function. The at least one request includes the customer data associated with a customer. Further, the method includes extracting one or more parameters from the at least one received request. The method further includes determining a request type and a customer type based on the one or more extracted parameters. Further, the method includes categorizing the customer data based, at least in part, on the determined request type and the customer type. The method further includes storing the categorized customer data in two or more storage locations.

[0110] 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.[oni] 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.

[0112] 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 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 implemented merely as illustrative of the disclosure and not as a limitation.

[0113] The present disclosure provides a technical advancement related to a system and method for sorting customer data in a network. This advancement addresses the limitations of existing solutions by creating separate storage locations for each ofthe customer type and the service type combination pair of the customer data. The disclosure involves advanced sorting algorithms, intelligent rule-based classification, and real-time data processing mechanisms, which offer significant improvements in operational performance, data handling efficiency, and costeffectiveness. By implementing automated rule-driven sorting and contextual prioritization of customer data, the present disclosure enhances customer data management, policy enforcement, and service customization, resulting in faster response times, optimized resource utilization, and a superior user experience.TECHNICAL ADVANTAGES

[0114] Clarity and organization: The present disclosure allows segregation of Call Detail Records (CDRs) into separate folders based on customer type and service type, enhancing clarity and organization and making easier management, access, and retrieval of specific CDRs.

[0115] Improved processing efficiency: The present disclosure allows structured storage of the CDRs enabling faster data processing, analysis, and retrieval of specific records, optimizing system performance and saving resources.

[0116] Enhanced security: The present disclosure provides separate storage to each customer type and service type combination of the CDR, allowing for more targeted and effective security measures, reducing the risk of unauthorized access, and protecting sensitive customer information.

[0117] Better data integrity: The present disclosure provides dedicated folders for each customer type and service type combination, maintaining data integrity by minimizing risks of data corruption or loss due to large, unstructured data volumes.

[0118] Scalability and maintenance: The present disclosure provides a method and a system that is scalable and easier to maintain, as each CDR folder can be independently managed without impacting the overall data handling process.

[0119] Automated data management: The present disclosure provides automated segregation of the CDRs, reducing manual intervention, lowering operational overhead, and improving consistency in record storage and access.

Claims

CLAIMS1. A method (500) for sorting customer data in a network (106), the method (500) comprising: receiving (502), by a first network function (304), at least one request from a second network function (302), wherein the at least one request comprises the customer data associated with a customer; extracting (504), by the first network function (304), one or more parameters from the at least one received request; determining (506), by the first network function (304), a request type and a customer type based on the one or more extracted parameters; categorizing (508), by the first network function (304), the customer data based, at least in part, on the determined request type and the customer type; and storing (510), by the first network function (304), the categorized customer data in two or more storage locations.

2. The method (500) as claimed in claim 1, wherein the customer data is categorized using a sorting algorithm.

3. The method (500) as claimed in claim 2, wherein the sorting algorithm comprises: determining a storage location among the two or more storage locations from a database (210) based on the determined request type and the customer type; accessing a storage location identifier (ID) corresponding to the determined storage location; and assigning the storage location ID to the customer data.

4. The method (500) as claimed in claim 3, further comprising:storing, by the first network function (304), the customer data as a Call Detail Record (CDR) in a corresponding storage location associated with the assigned storage location ID in the database (210).

5. The method (500) as claimed in claim 1, wherein the at least one request comprises details of a data plan, and wherein the details comprise a remaining data volume and a validity of the data plan.

6. The method (500) as claimed in claim 3, wherein the two or more storage locations are created in the database (210) based on one or more combinations of the request type and the customer type, wherein the two or more storage locations comprise an online-prepaid customer storage location, an online -postpaid customer storage location, an offline-prepaid customer storage location and an offline- postpaid storage location, wherein the storage location ID is mapped with each of the two or more storage locations, and wherein the storage location ID mapped with each storage location is a unique storage location ID.

7. The method (500) as claimed in claim 1, wherein the first network function is a Charging Function (CHF) (304), and wherein the second network function is a Session Management Function (SMF) (302).

8. The method (500) as claimed in claim 1 , wherein the one or more parameters comprise a quota management indicator and a media access control (MAC) identifier (ID).

9. The method (500) as claimed in claim 1, wherein the request type comprises an online request and an offline request, and wherein the customer type comprises a pre-paid and post-paid.

10. A system (108) for sorting customer data in a network (106), the system (108) comprising a first network function (304), the first network function (304) comprising:a receiving unit (212) configured to receive at least one request from a second network function (302), wherein the at least one request comprises the customer data associated with a customer; an extraction unit (214) configured to extract one or more parameters from the at least one received request; a determining unit (216) configured to determine a request type and a customer type based on the one or more extracted parameters; and an execution unit (218) configured to: categorize the customer data based, at least in part, on the determined request type and the customer type; and store the categorized customer data in two or more storage locations.

11. The system (108) as claimed in claim 10, wherein the execution unit (218) is configured to categorize the customer data using a sorting algorithm.

12. The system (108) as claimed in claim 11, wherein the execution unit (218) is configured to perform the sorting algorithm comprising step of: determining a storage location among the two or more storage locations form a database (210) based on the determined request type and the customer type; accessing a storage location identifier (ID) corresponding to the determined storage location; and assigning the storage location ID to the customer data.

13. The system (108) as claimed in claim 12, wherein the execution unit (218) is further configured to store the customer data as a Call Detail Record (CDR) in a corresponding storage location associated with the assigned storage location ID in the database (210).

14. The system (108) as claimed in claim 10, wherein the at least one request comprises details of a data plan, and wherein the details comprise a remaining data volume and a validity of the data plan.

15. The system (108) as claimed in claim 12, wherein the two or more storage locations are created in the database (210) based on one or more combinations of the request type and the customer type, wherein the two or more storage locations comprise an online-prepaid customer storage location, an online -postpaid customer storage location, an offline-prepaid customer storage location and an offline- postpaid customer storage location, wherein the storage location ID is mapped with each of the two or more storage locations, and wherein the storage location ID mapped with each storage location is a unique storage location ID.

16. The system (108) as claimed in claim 10, wherein the first network function is a Charging Function (CHF) (304), and wherein the second network function is a Session Management Function (SMF) (302).

17. The system (108) as claimed in claim 10, wherein the one or more parameters comprise a quota management indicator and a media access control (MAC) identifier (ID).

18. The system (108) as claimed in claim 10, wherein the request type comprises an online request and an offline request, and wherein the customer type comprises a pre-paid and post-paid.

19. A computer program product comprising a non-transitory computer- readable medium comprising instructions that, when executed by one or more processors (202), cause the one or more processors (202) to execute a method (500) for sorting customer data in a network (106), the method (500) comprising: receiving (502), by a first network function (304), at least one request from a second network function (302), wherein the at least one request comprises the customer data associated with a customer;extracting (504), by the first network function (304), one or more parameters from the at least one received request; determining (506), by the first network function (304), a request type and a customer type based on the one or more extracted parameters; categorizing (508), by the first network function (304), the customer data based, at least in part, on the determined request type and the customer type; and storing (510), by the first network function (304), the categorized customer data in two or more storage locations.

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