A system and method to support and monitor one or more network functions

Abstract

The present invention relates to a system(108) for supporting and monitoring network functions in a wireless network The system(108) may comprise a memory(204) and one or more processors(202) configured to execute instructions stored in the memory(204) to receive a user request for monitoring and managing error codes, collect error code data of network functions from a distributed file system(220) via a data collection module(208), interpret and convert the collected error code data into a standardized format via a data conversion module(210), and analyze the standardized error code data based on the user request via a data analysis module(212). The system(108) may be configured to efficiently manage and analyze error codes in a wireless network environment, providing a centralized solution for monitoring and troubleshooting network functions.

Description

A SYSTEM AND METHOD TO SUPPORT AND MONITOR ONE OR MORE NETWORK FUNCTIONSRESERVATION 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 trade5 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 fully10 reserved by the owner.FIELD OF DISCLOSURE

[0002] The present invention, in general, relates to the field of wireless communication networks and more particularly, relates to supporting and monitoring network functions in a wireless network for effective error code15 management, analysis, and visualization.DEFINITIONS

[0003] "Network Functions" refers to various services, applications, or functionalities provided by a wireless communication network, such as voice services, data services, security services, and others.20

[0004] "Error Codes" refers to codes or messages generated by network functions to indicate errors, failures, or specific conditions encountered during operation.

[0005] Standardized Format" refers to a consistent and structured representation of error code data, typically including fields such as error code type,25 severity, timestamp, associated network function, and geographical information.

[0006] "Roll-up Operation" refers to the process of aggregating error code data from lower geographic levels to view the data at a higher geographic level, providing a broader overview of network performance.

[0007] Drill-down Operation" refers to the process of disaggregating error code data from higher geographic levels to view the data at a lower geographic level, enabling more granular analysis of specific geographic areas.

[0008] "Distributed File System" refers to a network file system that spans multiple servers or nodes, providing scalable and fault-tolerant storage for error code data and other related information.

[0009] Distributed Data Lake” refers to a scalable storage solution designed to store and manage large volumes of structured, semi-structured, and unstructured data, including processed and analyzed error code data.

[0010] “User Equipment” refers to the devices or computing systems used by users, such as network administrators, to interact with the system and send user requests.

[0011] “UI Server” is a server component responsible for handling user interface interactions and communicating with other components of the system.

[0012] “Load Balancer” is a component that distributes incoming user requests across multiple instances of the system to ensure optimal performance and scalability.

[0013] “vProbe Manager” stands for virtual probe manager, which is a central component responsible for coordinating the monitoring and management of error codes. It receives user requests and interacts with other components to process the requests for coordinating the monitoring and management of error codes.

[0014] “Computation Layer” is responsible for performing data filtering and geography-based network functions failure data computation. It retrieves raw errorcode data, applies filtering and aggregation operations based on user requests, and computes relevant metrics and insights.BACKGROUND OF DISCLOSURE

[0015] 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.

[0016] The rapid evolution of wireless communication networks, particularly with the advent of 5G technology, has brought about numerous advancements and opportunities. However, it has also introduced complex challenges in managing and monitoring the network functions effectively. One critical aspect of network management is the efficient handling of error codes generated by various network functions.

[0017] In the current 5G network infrastructure, there is a pressing need for a robust solution to support the computation, execution, and monitoring of network functions' failure error codes. The existing solutions face several limitations that hinder the ability of network administrators to diagnose and troubleshoot network issues promptly. These limitations lead to prolonged downtime and degraded network performance, which can have severe consequences for service providers and end-users alike.

[0018] One of the primary drawbacks of the current solutions is their inability to handle error codes in various formats of data representation. Network functions generate error codes in different formats, such as plain text, structured data, or proprietary encodings. The lack of a standardized format makes it challenging to interpret and analyze the error codes effectively, leading to increased complexity and inefficiency in the troubleshooting process.

[0019] Moreover, the existing solutions often lack essential features that are crucial for effective error code management. For instance, the absence of filtering capabilities makes it difficult for network administrators to focus on specific error codes or network functions of interest. Without the ability to filter out irrelevant data, administrators are overwhelmed with a vast amount of information, making it time-consuming to identify and isolate the root cause of network issues.

[0020] Another significant limitation is the lack of roll-up and drill-down options in the current solutions. Roll-up functionality allows administrators to aggregate error code data at higher levels of abstraction, providing a holistic view of the network's health. Drill-down capabilities, on the other hand, enable administrators to delve into specific details and analyze error codes at a granular level. The absence of these features restricts the ability to navigate through the error code data effectively, hindering the identification of patterns, trends, and correlations that could provide valuable insights into network performance.

[0021] Consequently, there is a pressing need for a comprehensive solution that tackles these limitations head-on, empowering network administrators with enhanced capabilities for error code management, analysis, and visualization. Such a solution should provide a standardized format for error code representation, robust filtering options, and intuitive roll-up and drill-down functionalities. By addressing these gaps, network administrators can effectively diagnose and troubleshoot network issues, reducing downtime, improving network performance, and ultimately enhancing the overall quality of service.

[0022] It is therefore an objective of the present invention to provide a comprehensive system and method for supporting and monitoring network functions in a wireless network, thereby overcoming the above-mentioned disadvantages in the field.SUMMARY

[0023] In an exemplary embodiment, a system for supporting and monitoring one or more network functions in a wireless network is described. The system comprises a memory and one or more processors configured to execute instructions stored in the memory. The one or more processors are configured to receive a user request via a user interface for monitoring and managing error code data of the one or more network functions. The processors collect, via a data collection module, the error code data of the one or more network functions from a distributed file system. The processors interpret and convert, via a data conversion module, the collected error code data into a standardized format. The processors then analyze, via a data analysis module, the standardized error code data based on the user request.

[0024] In some embodiments, the one or more processors are further configured to store, via a data storage module, the analyzed error code data in a distributed data lake.

[0025] In some embodiments, the one or more processors are further configured to display, via a user interface, the stored analyzed error code data along with navigation and filtering options, wherein the stored analyzed error code data is retrievable for future use.

[0026] In some embodiments, the user request includes at least one filter and a geography. The at least one filter includes one or more of error code type, severity, timestamp, and network function. The geography includes one or more of region, state, city, and network cell.

[0027] In some embodiments, the one or more processors are further configured to determine, by a request processing module, whether the user request is a fresh request or a follow-up request. When the user request is determined as the follow-up request, they determine whether the user request relates to a roll-up operation to view the analyzed error code data at a higher geographic level or a drill-down operation to view the analyzed error code data at a lower geographic level.

[0028] In some embodiments, when the request is for the roll-up operation, the one or more processors are further configured to add, by the request processing module, the higher geographic level in at least one filter and remove a previous lower geographic level along with previous filters.

[0029] In some embodiments, when the request is for the drill-down operation, the one or more processors are further configured to add, by the request processing module, the lower geographic level in the at least one filter along with previous filters.

[0030] In some embodiments, when the user request is a fresh request, the system performs data collection, filtering, and standardization operations on receiving the error code data of the one or more network functions and performs analysis of the standardized error code data based on the user request.

[0031] In some embodiments, the one or more processors are further configured to provide, via the user interface, real-time monitoring of the one or more network functions' failure error codes. They enable identification of issues based on the real-time monitoring and facilitate actions to minimize network disruptions based on the identified issues. The real-time monitoring is integrated with the display of the analyzed error code data and the navigation and filtering options.

[0032] In some embodiments, a user interface provides navigation and filtering options to allow users to navigate through the error code data, apply filters based on a criteria, and perform roll-up or drill-down operations to view relevant details for analysis. The roll-up operation allows the users to view the relevant details at a higher geographic level by aggregating data from lower geographic levels. The drill-down operation allows the users to view the relevant details at a lower geographic level by disaggregating data from higher geographic levels.

[0033] In another exemplary embodiment, a method for supporting and monitoring one or more network functions in a wireless network is described. The method comprises receiving a user request for monitoring and managing error code data of the one or more network functions. It includes collecting, via a data collection module, the error code data of the one or more network functions from a distributed file system. The method further comprises interpreting and converting, via a data conversion module, the collected error code data into a standardized format. It also includes analyzing, via a data analysis module, the standardized error code data based on the user request.

[0034] In some embodiments, the method further comprises storing, via a data storage module, the analyzed error code data in a distributed data lake.

[0035] In some embodiments, the method further comprises displaying, via a user interface, the stored analyzed error code data along with navigation and filtering options, wherein the stored analyzed error code data is retrievable for future use.

[0036] In some embodiments, the user request includes at least one filter and a geography. The at least one filter includes one or more of error code type, severity, timestamp, and network function. The geography includes one or more of region, state, city, and network cell.

[0037] In some embodiments, the method further comprises determining, by a request processing module, whether the user request is a fresh request or a follow-up request. When the user request is determined as the follow-up request, it determines whether the user request relates to a roll-up operation to view the analyzed error code data at a higher geographic level or a drill-down operation to view the analyzed error code data at a lower geographic level.

[0038] In some embodiments, when the request is for the roll-up operation, the method further comprises adding, by the request processing module, the higher geographic level in at least one filter and removing a previous lower geographic level along with previous filters.

[0039] In some embodiments, when the request is for the drill-down operation, the method further comprises adding, by the request processing module, the lower geographic level in the one or more filters along with previous filters.

[0040] In some embodiments, when the user request is a fresh request, the method further comprises performing data collection, filtering, and standardization operations on receiving the error code data of the one or more network functions and analyzing the standardized error code data based on the user request.

[0041] In some embodiments, the method further comprises providing, via the user interface, real-time monitoring of the one or more network functions' failure error codes. It enables identification of issues based on the real-time monitoring and facilitates actions to minimize network disruptions based on the identified issues. The real-time monitoring is integrated with the display of the analyzed error code data and the navigation and filtering options.

[0042] In some embodiments, a user interface provides navigation and filtering options to allow users to navigate through the error code data, apply filters based on criteria, and perform roll-up or drill-down operations to view relevant details for analysis. The roll-up operation allows the users to view the relevant details at a higher geographic level by aggregating error code data from lower geographic levels. The drill-down operation allows the users to view the relevant details at a lower geographic level by disaggregating error code data from higher geographic levels.

[0043] In yet another exemplary embodiment, a computer program product comprising a non-transitory computer-readable medium having instructions stored thereon is described. When executed by at least one processor, the instructions cause the at least one processor to perform operations. These operations comprise receiving, via a user interface, a user request for monitoring and managing error code data of one or more network functions in a wireless network. They include collecting, via a data collection module, the error code data of the network functions from a distributed file system. The operations further comprise interpreting and converting, via a data conversion module, the collected error code data into a standardized format. They also include analyzing, via a data analysis module, the standardized error code data based on the user request.

[0044] In a further exemplary embodiment, a user equipment communicatively coupled to a system through a network for supporting and monitoring one or more network functions is described. The user equipment is configured to send a user request for monitoring and managing error code data of the one or more network functions in the network. It receives analyzed error code data along with navigation and filtering options, wherein the analyzed error code data is obtained by a method for supporting and monitoring the one or more network functions in the network.

[0045] 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.OBJECTS OF THE PRESENT DISCLOSURE

[0046] Some of the objects of the present disclosure, which at least one embodiment herein satisfies, are as listed herein below.

[0047] One object of the present disclosure is to provide a comprehensive solution that offers enhanced capabilities for error code management, analysis, andvisualization at a User Interface (UI) level, enabling network administrators to effectively monitor and troubleshoot network functions in a wireless network.

[0048] Another object of the present disclosure is to handle error codes in various formats of data representation, allowing for the collection, interpretation, and conversion of error code data from diverse network functions into a standardized format, thereby facilitating efficient analysis and management.

[0049] A further object of the present disclosure is to provide essential features such as filtering and roll-up / drill-down options, empowering network administrators to identify and focus on specific error codes or network functions based on criteria such as error code type, severity, timestamp, and geography, enabling targeted investigations and analysis at different levels of granularity.

[0050] Yet another object of the present disclosure is to effectively diagnose and troubleshoot network issues by providing a user-friendly interface with realtime monitoring capabilities, advanced filtering options, and intuitive navigation, ultimately resulting in reduced downtime, improved network performance, and enhanced efficiency in managing wireless networks.BRIEF DESCRIPTION OF DRAWINGS

[0051] 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.

[0052] FIG. 1 illustrates an exemplary network architecture depicting the various components and their interactions within a system for supporting and monitoring network functions in a wireless network, in accordance with an embodiment of the present disclosure.

[0053] FIG. 2 illustrates a system architecture diagram showcasing the key modules and their relationships within the system for supporting and monitoring network functions in a wireless network, in accordance with an embodiment of the present disclosure.

[0054] FIG. 3 illustrates a flowchart representing a method steps, which enhances capabilities for error code management, analysis, and visualization at a User Interface (UI) level, in accordance with an embodiment of the present disclosure.

[0055] FIG. 4 depicts a process flow diagram that demonstrates steps of a method involved in error code management, analysis, and visualization at the UI level, in accordance with an embodiment of the present disclosure.

[0056] FIG. 5 illustrates an exemplary flow diagram of a method for supporting and monitoring network functions in a wireless network, in accordance with embodiments of the present disclosure.

[0057] FIG. 6 presents an exemplary block diagram of a computer system in which or with which embodiments of the present disclosure may be implemented, showcasing the hardware components and their interactions within the system.

[0058] The foregoing shall be more apparent from the following more detailed description of the disclosure.LIST OF REFERENCE NUMERALS100 - Network Architecture102 - User (s)104-1, 104-2. . . 104-N - User Equipment (s)106 -Network108 - System202 - One or more processor(s)204 - Memory206 - I / O Interfaces208 - Data collection module210 -Data conversion module212 - Data analysis module214 - Request processing module216 - Data storage module218 - Other Module (s)220- Distributed file system222- Database224- Distributed data lake300 - Method402 - UI server404 - Load balancer406 - vProbe manager408 - Computation layer510 - External Storage Device520 - Bus530 - Main Memory540 - Read Only Memory550 - Mass Storage Device560 - Communication Port570 - ProcessorDETAIL DESCRIPTION OF THE INVENTION

[0059] 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.

[0060] 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 thefunction and arrangement of elements without departing from the spirit and scope of the disclosure as set forth.

[0061] 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.

[0062] Also, it is noted that individual embodiments 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.

[0063] 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.

[0064] 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.

[0065] 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 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.

[0066] 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 function / 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.

[0067] 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 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 coding data processing, input / output processing, and / or any other functionality that enables the working of the system according to the present disclosure. More specifically, the processor is a hardware processor.

[0068] As portable electronic devices and wireless technologies continue to improve and grow in popularity, the advancing wireless technologies for data transfer are also expected to evolve and replace the older generations of technologies. In the field of wireless data communications, the dynamicadvancement of various generations of cellular technology are also seen. The development, in this respect, has been incremental in the order of second generation (2G), third generation (3G), fourth generation (4G), and now fifth generation (5G), and more such generations are expected to continue in the forthcoming time.

[0069] 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.

[0070] In the current landscape of wireless communication networks, network administrators face significant challenges in effectively managing and monitoring network functions, particularly in the context of 5G technology. The rapid evolution of network infrastructure and the increasing complexity of network functions have led to a pressing need for a comprehensive solution that enables efficient error code management, analysis, and visualization. The present disclosure addresses these challenges by providing a system and method for supporting and monitoring network functions in a wireless network, empowering network administrators with enhanced capabilities to diagnose and troubleshoot network issues promptly and effectively.

[0071] Error code and error code data has been interchangeably used in the present disclosure.

[0072] The present disclosure serves the purpose of streamlining the process of error code management and analysis in wireless networks, ultimately leading to improved network performance, reduced downtime, and enhanced user experience. By providing a standardized format for error code representation, advanced filteringoptions, and intuitive roll-up and drill-down functionalities, the present disclosure enables network administrators to navigate through vast amounts of error code data efficiently, identify patterns and trends, and pinpoint the root causes of network issues. This empowers network administrators to take proactive measures to prevent network disruptions, optimize network operations, and ensure the smooth functioning of the wireless network.

[0073] The present disclosure relates to a system and method for supporting and monitoring network functions in a wireless network. The system comprises a memory and one or more processors configured to execute instructions stored in the memory. The processors receive user requests for monitoring and managing error codes, collect error code data from network functions, interpret and convert the collected data into a standardized format, and analyze the standardized data based on user requests. The system provides a user interface with advanced navigation and filtering options, enabling users to perform roll-up and drill-down operations based on geography and other criteria. The method involves receiving user requests, collecting and standardizing error code data, analyzing the data, and presenting the results through the user interface, facilitating real-time monitoring and troubleshooting of network functions' failure error codes.

[0074] The various embodiments throughout the disclosure will be explained in more detail with reference to FIG. 1- FIG. 5.

[0075] FIG. 1 illustrates an exemplary network architecture 100 of a system 108 for supporting and monitoring network functions in a wireless network 106, in accordance with embodiments of the present disclosure.

[0076] Referring to FIG. 1, the network architecture 100 is implemented for enabling efficient management and analysis of error codes in the wireless network 106. In an embodiment, the system 108 is connected to the wireless network 106, which is further connected to at least one user equipment 104-1, 104-2, ... 104-N (collectively referred to as user equipment 104) associated with one or more users 102. In another embodiment the one or more user is network administrator. Theterms 'user,' 'network administrator,' and 'administrator' are used interchangeably throughout the description. The user equipment 104 may be smartphones, laptops, tablets, or any other devices capable of connecting to the wireless network 106. Further, the wireless network 106 can be configured with a distributed data lake 224 that stores error code data and other relevant information.

[0077] In an embodiment, the system 108 may receive user requests from the user equipment 104 for monitoring and managing error codes. A person of ordinary skill in the art will understand that the user equipment 104 may be individually referred to as user equipment 104 and collectively referred to as user equipment 104.

[0078] In an embodiment, the user equipment 104 may transmit the user requests over the wireless network 106 to the system 108 via I / O interfaces 206. The I / O interfaces and user interface may be the same and used interchangeably throughout the description.

[0079] In an embodiment, the system 108 may involve collection, analysis, and presentation of error code data received from network functions via the wireless network 106.

[0080] In an exemplary embodiment, the wireless network 106 may include, but not be limited to, 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 signals, packets, or messages. The wireless network 106 may include, but not be limited to, a cellular network, a satellite network, a Wi-Fi network, or some combination thereof.

[0081] In an embodiment, the user equipment 104 may communicate with the system 108 via the wireless network 106. The user equipment 104 may include, but not be limited to, smartphones, laptops, tablets, or any other devices capable of connecting to the wireless network 106.

[0082] A layout of the output end of the system 108 is described, as it may be implemented. The system 108 can be configured to enable efficient management and analysis of error codes in the wireless network 106, providing network administrators with enhanced capabilities for monitoring and troubleshooting network functions.

[0083] In an embodiment, the system 108 is connected to the wireless network 106, which is connected to the at least one user equipment 104, including smartphones, laptops, tablets, and other devices capable of connecting to the wireless network 106. When the user equipment 104 sends user requests for monitoring and managing error codes via the wireless network 106, the system 108 can process these requests and provide the necessary information and functionalities to the users 102.

[0084] In an embodiment, the wireless network 106 is further configured with a distributed data lake, where error code data and other relevant information related to the network functions are stored. This data can be retrieved by the system 108 whenever there is a need to process user requests or perform analysis.

[0085] In an embodiment, the user equipment 104 may transmit user requests over the wireless network 106 to the system 108 via I / O interfaces 206.

[0086] In an embodiment, the system 108 may involve collection, analysis, and presentation of error code data received from network functions via the wireless network 106.

[0087] 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.

[0088] FIG. 2 illustrates an exemplary system architecture of the system 108, comprising various modules and components such as memory 204 and one or more processor(s) 202, in accordance with embodiments of the present disclosure.

[0089] The disclosed system architecture ensures the efficient operation of the system 108 for supporting and monitoring network functions, facilitating the management and analysis of error codes in the wireless network 106.

[0090] FIG. 2, with reference to FIG. 1, illustrates an exemplary representation of the system 108 for supporting and monitoring network functions in a wireless network, in accordance with an embodiment of the present disclosure.

[0091] In an aspect, the system 108 may comprise 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 control the operation of the system 108. The memory 204 may comprise any non-transitory storage device including, for example, volatile memory such as Random Access Memory (RAM), or non-volatile memory such as Erasable Programmable Read- Only Memory (EPROM), flash memory, and the like.

[0092] Referring to FIG. 2, the system 108 may include I / O interfaces 206. The I / O interfaces 206 may comprise a variety of interfaces for data input and output devices, storage devices, and the like. The I / O interfaces 206 may facilitate communication to / from the system 108. The RO interfaces 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, data collection module 208, dataconversion module 210, data analysis module 212, request processing module 214, data storage module 216, and other modules 218.

[0093] In an embodiment, the modules 208, 210, 212, 214, 216, and 218 may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the respective modules. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the modules may be processor-executable instructions stored on a non-transitory machine-readable storage medium, and the hardware for the modules 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 modules 208, 210, 212, 214, 216, and 218. 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 modules may be implemented by electronic circuitry. The "other modules 218" may include, but are not limited to, data validation modules for ensuring data integrity, data compression modules for optimizing storage and transmission of error code data, and data encryption modules for securing sensitive information. These modules work in conjunction with the core modules to enhance the overall functionality, performance, and security of the system 108.

[0094] In an embodiment, the system 108 may include a distributed data lake 224, a distributed file system 220, and a database 222 that may be used to store error code data, user requests, and other relevant information. The distributed data lake 224, distributed file system 220, and database 222 may be separate from the system 108 but accessible to the system 108 and its components.

[0095] FIG. 2 illustrates an exemplary system architecture 200 of the system 108 for supporting and monitoring network functions in a wireless network. The system 108 may comprise one or more processors 202 and a memory 204. The one or more processors 202 may be configured to execute instructions stored in the memory 204 to perform various operations associated with managing and analyzing error codes in the wireless network.

[0096] In an embodiment, the system 108 may include I / O interfaces 206 that facilitate communication between the system 108 and other devices or components. The I / O interfaces 206 may comprise a variety of interfaces for data input and output, such as interfaces for input devices, output devices, storage devices, and communication networks. The I / O interfaces 206 may enable the system 108 to receive user requests for monitoring and managing error codes from user equipment 104 via the wireless network 106.

[0097] The system 108 may further comprise a data collection module 208, a data conversion module 210, a data analysis module 212, and a request processing module 214. These modules may be implemented as a combination of hardware and software components, working together to provide the functionalities of the system 108.

[0098] The data collection module 208 may be responsible for collecting error code data of network functions from various sources, such as a distributed file system 220. The error code data may be generated by different network functions and may be stored in the distributed file system 220 in various formats. The data collection module 208 may retrieve this error code data and provide it to other modules of the system 108 for further processing. "Error Codes" refers to codes or messages generated by network functions to indicate errors, failures, or specific conditions encountered during operation. Examples of error codes include: a. Hypertext Transfer Protocol (HTTP) Status Codes: Such as 404 (Not Found), 500 (Internal Server Error), or 403 (Forbidden), whichindicate issues with web services or Application Programming Interface (API) endpoints. b. Mobile Network Error Codes: For instance, 'CSOOOl' might indicate a general system failure in a cellular network, while 'CS0008' could represent an authentication failure. c. Network Equipment Error Codes: Such as 'ElOOl' potentially indicating a hardware failure in a network switch, or 'E2003' signaling a configuration error in a router. d. Protocol-Specific Error Codes: Like 'SIP 480' in Session Initiation Protocol indicating a temporarily unavailable endpoint, or 'ICMP Type 3 Code 1' indicating a host is unreachable in Internet Control Message Protocol. e. Application-Level Error Codes: Such as'ERR_CONN_TIMED_OUT' in web browsers indicating a connection timeout, or 'ORA-OOOOl' signaling a unique constraint violation in Oracle databases.

[0099] These error codes help network administrators and systems quickly identify the nature and location of issues within the network infrastructure, facilitating efficient troubleshooting and resolution.

[0100] The data conversion module 210 may receive the collected error code data from the data collection module 208 and interpret and convert the data into a standardized format. This standardization process may involve parsing the error code data, extracting relevant information, and transforming the data into a consistent format that can be easily analyzed and understood by other modules of the system 108. The standardized format may include fields such as error code type, severity, timestamp, associated network function, and geographical information.

[0101] The data analysis module 212 may analyze the standardized error code data based on the user request received via the I / O interfaces 206. The data analysis module 212 may apply various analytical techniques, algorithms, and models to the standardized error code data to derive insights, identify patterns, and generates meaningful reports or visualizations. The analysis may take into account the filters and geography specified in the user request, allowing users to focus on specific subsets of the error code data based on their requirements.

[0102] The request processing module 214 may handle the processing of user requests received by the system 108. The request processing module 214 may determine whether a user request is a fresh request or a follow-up request. In the case of a follow-up request, the request processing module 214 may further determine whether the request relates to a roll-up operation or a drill-down operation. A roll-up operation may involve viewing data at a higher geographic level by aggregating data from lower geographic levels, while a drill-down operation may involve viewing data at a lower geographic level by disaggregating data from higher geographic levels.

[0103] The system 108 may also include a data storage module 216 that stores the analyzed error code data in a distributed data lake 224. The distributed data lake 224 may serve as a centralized repository for storing the processed and analyzed error code data, along with any derived insights or reports. The data storage module 216 may ensure that the analyzed data may be persisted and can be retrieved efficiently when needed. The stored data may be presented to the user via a user interface, enabling them to access and review the error code analysis results.

[0104] The user interface provided by the system 108 may offer navigation and filtering options to facilitate easy exploration and analysis of the error code data. Users may navigate through the error codes, apply filters based on various criteria such as error code type, severity, timestamp, and network function, and perform roll-up or drill-down operations to view relevant details at different geographic levels. The user interface may present the analyzed error code dataalong with these navigation and filtering options, empowering the users to interactively investigate and gain insights from the data.

[0105] The system 108 is designed to handle two distinct types of user requests: fresh requests and follow-up requests. A fresh request is an initial query for error code data analysis, such as when a network administrator first logs in and asks to view all critical error codes from core network functions over the past 24 hours. In response to a fresh request, the system 108 initiates new data collection from network functions, applies initial filtering based on user parameters, standardizes the collected data, and then passes it to the data analysis module 212. In contrast, a follow-up request builds upon or refines a previous query within the same session. For instance, after viewing critical error codes, the administrator might request to see only authentication-related errors from the same dataset. For follow-up requests, the system 108 may reuse previously collected and processed data, apply additional filtering or aggregation, perform roll-up or drill-down operations as needed, and then conduct further analysis. This distinction in request types allows the system 108 to optimize data processing and improve response times, with fresh requests typically requiring more comprehensive data collection and processing, while follow-up requests often leverage existing datasets to focus on refining the analysis. By efficiently handling both types of requests, the system 108 provides a flexible and responsive tool for network administrators to investigate and manage error codes in various network scenarios.

[0106] The system 108 may handle both fresh requests and follow-up requests differently. When a user request is a fresh request, the system 108 may initiate the data collection, filtering, and standardization operations to gather the latest error code data from the network functions. The collected data may then be passed to the data analysis module 212 for analysis based on the specific requirements of the user request.

[0107] In another embodiment, when a user request is a follow-up request, the request processing module 214 may determine whether it is a roll-up operationor a drill-down operation. For a roll-up operation, the request processing module 214 may add a higher geographic level to the filter and remove the previous lower geographic level along with any previous filters. This allows users to view the error code data aggregated at a higher level, providing a broader overview of the network performance. Conversely, for a drill-down operation, the request processing module 214 may add a lower selected geographic level to the filter while retaining the previous filters. This enables users to delve into more granular details of the error code data at a specific geographic location.

[0108] The system 108 may provide real-time monitoring capabilities for network functions' failure error codes. By continuously collecting and analyzing error code data, the system 108 may enable proactive identification of issues and facilitate timely actions to minimize network disruptions. The user interface may present real-time updates and alerts, allowing network administrators to stay informed about the health and performance of the network functions.

[0109] The combination of real-time monitoring, advanced data analysis, and user-friendly navigation and filtering options provided by the system 108 may significantly enhance the efficiency and effectiveness of network administrators in managing and troubleshooting network functions. By leveraging the power of data analytics and providing intuitive tools for exploring and understanding error code data, the system 108 may empower network administrators to quickly identify and resolve issues, minimize downtime, and ensure the smooth operation of the wireless network.

[0110] In an embodiment, the system 108 may include a database 222 that stores various configuration settings, user preferences, and other relevant information required for the functioning of the system 108. The database 222 may be accessed by different modules of the system 108 to retrieve or store data as needed. For example, the request processing module 214 may access the database 222 to obtain user-specific settings or preferences related to error code analysis and visualization.

[0111] The system 108 may also incorporate other modules 218 that provide additional functionalities or support the core modules in performing their tasks. These other modules 218 may include, but are not limited to, security modules for authentication and authorization, logging modules for tracking system activities, and communication modules for facilitating data exchange between different components of the system 108 or with external systems.

[0112] In an embodiment, the distributed file system 220 may span across multiple servers or nodes, providing a scalable and fault-tolerant storage infrastructure for the error code data. The distributed file system 220 may ensure data availability and reliability by replicating data across multiple nodes and enabling parallel access to the data. This distributed architecture may allow the system 108 to handle large volumes of error code data efficiently and provide high performance for data retrieval and analysis operations.

[0113] The distributed data lake 224 may serve as a centralized repository for storing and managing the analyzed error code data, along with any derived insights, reports, or visualizations. The distributed data lake 224 may provide a scalable and flexible storage solution that can accommodate structured, semistructured, and unstructured data. It may enable the system 108 to store and process large amounts of error code data, support advanced analytics, and facilitate data sharing and collaboration among different stakeholders.

[0114] The system 108 may leverage various data processing and analysis techniques to extract meaningful insights from the error code data. These techniques may include statistical analysis, machine learning algorithms, pattern recognition, and data mining. By applying these techniques, the system 108 may identify trends, anomalies, and correlations in the error code data. For example, the system may detect a sudden increase in the frequency of a specific error code, indicating a potential hardware or software issue that requires attention. It may also identify correlations between certain error codes and network performance metrics, such as latency or throughput, enabling administrators to pinpoint the root cause ofperformance degradation. Additionally, the system may discover trends in error code occurrences over time, helping administrators anticipate and prevent future issues through proactive maintenance and optimization efforts. These insights enable proactive identification of potential issues and facilitate data-driven decision-making for effective network management.

[0115] The user interface of the system 108 may provide a range of visualization options to present the analyzed error code data in a clear and intuitive manner. These visualizations may include charts, graphs, heatmaps, and other graphical representations that help users quickly grasp the key insights and patterns in the data. The visualizations may be interactive, allowing users to drill down into specific details, filter the data based on various criteria, and explore different perspectives of the error code analysis results.

[0116] In an embodiment, the system 108 may generate alerts and notifications based on predefined thresholds or anomalies detected in the error code data. These alerts may be triggered when certain error codes exceed a specified frequency or severity level, indicating potential issues that require immediate attention. The alerts may be delivered to the relevant stakeholders via email, SMS, or other notification channels, enabling timely response and resolution of the identified problems.

[0117] The system 108 may also provide role-based access control and security measures to ensure that only authorized users can access and interact with the error code data and analysis results. Different user roles may be defined, such as network administrators, support engineers, and management personnel, each with specific permissions and access rights. The system 108 may authenticate and authorize users based on their assigned roles, ensuring data privacy, confidentiality, and compliance with organizational policies.

[0118] In an embodiment, the system 108 may integrate with other network management tools and systems to provide a holistic view of the network performance and health. The system 108 may exchange data with these externalsystems via APIs or other integration mechanisms, enabling seamless data flow and synchronization. This integration may allow network administrators to correlate error code data with other network metrics, alarms, and events, facilitating comprehensive analysis and troubleshooting.

[0119] The system 108 may continuously evolve and adapt to emerging technologies and changing requirements in the field of network management. The modular and extensible architecture of the system 108 may allow for easy integration of new data sources, analysis techniques, and visualization options. As new network functions and error codes are introduced, the system 108 may be updated to incorporate them seamlessly, ensuring that it remains relevant and effective in supporting the monitoring and management of network functions.

[0120] In another embodiment, the present subject matter relates to a computer program product comprising a non-transitory computer-readable medium having instructions stored thereon. When executed by at least one processor 202, these instructions cause the at least one processor 202 to perform operations comprising receiving, via a user interface, a user request for monitoring and managing error codes of network functions in a wireless network. The operations further include collecting error code data of the network functions from a distributed file system 220 via a data collection module 208, interpreting and converting the collected error code data into a standardized format via a data conversion module 210, and analyzing the standardized error code data based on the user request via a data analysis module 212. This computer program product aims to provide a comprehensive solution for efficiently monitoring, managing, and analyzing error codes associated with network functions in a wireless network environment.

[0121] FIG. 3 illustrates a flowchart representing a method 300 for supporting and monitoring network functions in a wireless network. The method 300 enhances capabilities for error code management, analysis, and visualization at a User Interface (UI) level, enabling network administrators to effectively monitor and troubleshoot network issues.

[0122] The method 300 may begin with receiving 302 a user request for monitoring and managing error codes. The user request may be initiated by a network administrator or other authorized personnel through a user interface provided by the system 108. The user request may include specific filters and geography to narrow down the scope of the error code analysis. The filters may include criteria such as error code type, severity, timestamp, and network function, while the geography may specify the region, state, city, or network cell of interest.

[0123] Upon receiving the user request, the method 300 may proceed to determine (304) whether the user request is a fresh request or a follow-up request. This determination may be performed by a request processing module 214 of the system 108. If the user request is a fresh request, the method 300 may initiate data collection, filtering, and standardization operations (306) to gather and process the relevant error code data.

[0124] The data collection operation (306) may involve collecting (316) error code data of network functions from a distributed data lake / file system 220. The distributed data lake / file system 220 may serve as a centralized repository for storing error code data generated by various network functions. The data collection module 208 of the system 108 may retrieve (316) the error code data from the distributed file system 220 based on the specified filters and geography in the user request.

[0125] After collecting the error code data, the method 300 may proceed to interpret and convert (306) the collected data into a standardized format. This operation may be performed by a data conversion module 210 of the system 108. The data conversion module 210 may parse the collected error code data, extract relevant information, and transform the data into a consistent and structured format. The standardized format may include fields such as error code type, severity, timestamp, associated network function, and geographical information.

[0126] Once the error code data is converted into a standardized format, the method 300 may analyze (308) the standardized error code data based on the userrequest. The data analysis module 212 of the system 108 may perform various analytical techniques, algorithms, and models to derive insights, identify patterns, and generate meaningful reports or visualizations from the standardized error code data. The analysis may take into account the filters and geography specified in the user request, allowing network administrators to focus on specific subsets of the error code data relevant to their needs.

[0127] The method 300 may further include storing (315) the analyzed error code data in a distributed data lake 224. The distributed data lake 224 may serve as a scalable and flexible storage solution for storing the processed and analyzed error code data, along with any derived insights or reports. The data storage module 216 of the system 108 may handle the storage operation, ensuring that the analyzed data may be persisted and can be easily retrieved when needed. The stored data may be presented to the user via the user interface, enabling them to access and review the error code analysis results.

[0128] In addition to storing the analyzed data, the method 300 may display the analyzed error code data along with navigation and filtering options via the user interface. The user interface may provide a user-friendly and intuitive way for network administrators to explore and interact with the error code analysis results. The navigation options may allow users to traverse through different levels of data granularity, while the filtering options may enable them to refine the displayed data based on specific criteria such as error code type, severity, timestamp, or network function.

[0129] If the user request is determined to be a follow-up request in step (304), the method 300 may further determine (310) whether the follow-up request relates to a roll-up operation or a drill-down operation. A roll-up operation may involve viewing the error code data at a higher geographic level by aggregating data from lower geographic levels. On the other hand, a drill-down operation may involve viewing the error code data at a lower geographic level by disaggregating data from higher geographic levels.

[0130] If the follow-up request is for a roll-up operation, the method 300 may proceed to add (312) a higher geographic level in the filter and remove the previous lower geographic level along with any previous filters. This operation may be performed by the request processing module 214 of the system 108. By adding a higher geographic level to the filter, the method 300 may enable network administrators to view the error code data aggregated at a broader level, providing a high-level overview of the network performance across a larger geographical area.

[0131] Conversely, if the follow-up request is for a drill-down operation, the method 300 may proceed to add (314) a lower selected geographic level in the filter along with the previous filters. This operation may also be performed by the request processing module 214. By adding a lower geographic level to the filter, the method 300 may allow network administrators to delve into more granular details of the error code data specific to a smaller geographical area, enabling them to identify and investigate localized network issues.

[0132] In the case of a fresh request, the method 300 may perform (306) data collection, filtering, and standardization operations while receiving network error code data of network functions. Network error code data encompasses information generated by network components when they encounter issues or anomalies, typically including error codes, timestamps, affected network elements, and contextual details. For instance, a single error entry might contain: "Timestamp: 2023-07-22 14:30:15, Error Code: NE5001, Severity: Critical, Network Function: Load Balancer, Description: Connection timeout, Affected IP: 192.168.1.100". The system retrieves this raw data from the distributed file system 220, which might involve collecting all error codes generated within a specified timeframe across all network functions. It then applies user-specified filters to narrow down the relevant data; for example, isolating only critical errors from load balancers if that's what the user requested. Finally, the system converts the filtered data into a standardized format, transforming diverse inputs into a uniform structure such as a JavaScript Object Notation (JSON) object with fields like "timestamp", "errorCode", "severity", "networkFunction", "description", and "affectedElement". Thisstandardized data is then passed to the data analysis module 212 for in-depth analysis based on the specific parameters of the user request. These operations may involve retrieving the error code data from the distributed file system 220, applying the specified filters to narrow down the relevant data, and converting the collected data into a standardized format. The standardized data may then be used by the data analysis module 212 for analyzing (308) the error code data based on the user request.

[0133] Throughout the method 300, the user interface may provide real-time monitoring of network functions' failure error codes. This real-time monitoring capability may enable network administrators to proactively identify issues and take timely actions to minimize network disruptions. The user interface may display live updates and alerts, allowing network administrators to stay informed about the health and performance of the network functions in real-time.

[0134] The user interface may also provide navigation and filtering options to facilitate efficient exploration and analysis of the error code data. Users may navigate through the error codes using various levels of granularity, such as region, state, city, or network cell. They may apply filters based on criteria like error code type, severity, timestamp, or network function to focus on specific subsets of the data. Additionally, users may perform roll-up or drill-down operations to view relevant details at different geographic levels, enabling them to analyze the error code data from both high-level and detailed perspectives.

[0135] The roll-up operation may allow users to view the error code data at a higher geographic level by aggregating data from lower geographic levels. For example, a user may start by analyzing error code data at the city level and then perform a roll-up operation to view the aggregated data at the state or region level. This operation may provide a broader overview of the network performance and help identify trends or patterns across larger geographical areas.

[0136] On the other hand, the drill-down operation may allow users to view the error code data at a lower geographic level by disaggregating data from highergeographic levels. For instance, a user may begin by analyzing error code data at the region level and then perform a drill-down operation to view the data at the state, city, or network cell level. This operation may enable users to investigate specific network issues or anomalies in more detail, facilitating targeted troubleshooting and resolution efforts.

[0137] The method 300 may leverage the power of data analytics and visualization to derive meaningful insights from the error code data. By applying advanced analytical techniques, such as statistical analysis, machine learning algorithms, or pattern recognition, the method 300 may uncover hidden patterns, correlations, and anomalies in the error code data. These insights may help network administrators identify potential issues, optimize network performance, and make data-driven decisions for network management and planning.

[0138] The method 300 may also incorporate data visualization techniques to present the analyzed error code data in a clear, concise, and visually appealing manner. The user interface may offer various visualizations, such as charts, graphs, heatmaps, or dashboards, to represent the error code data and analysis results. These visualizations may enable network administrators to quickly grasp the key insights, trends, and patterns in the data, facilitating rapid understanding and decisionmaking.

[0139] Furthermore, the method 300 may incorporate collaboration and sharing features, allowing network administrators to share their findings, insights, or reports with other team members or stakeholders. This collaborative approach may foster knowledge sharing, facilitate cross-functional communication, and enable coordinated efforts in resolving network issues and optimizing network performance.

[0140] In one embodiment, the present subject matter relates to a user equipment (104). The user equipment (104) may be communicatively coupled to a system (108) through a network for supporting and monitoring network functions in a wireless network. The user equipment (104) is configured to send a user requestfor monitoring and managing error codes of network functions in the network. It receives analyzed error code data along with navigation and filtering options from the system (108). The analyzed error code data is obtained by a method implemented by the system (108) that involves collecting error code data of the network functions from a distributed file system (220) via a data collection module (208), interpreting and converting the collected error code data into a standardized format via a data conversion module (210), and analyzing the standardized error code data based on the user request via a data analysis module (212). This allows the user equipment (104) to efficiently monitor, manage and analyze errors in the wireless network based on the processed error code data provided by the system (108).

[0141] FIG. 4 illustrates a process flow diagram depicting the execution of the system 108 for supporting and monitoring network functions in a wireless network. The process flow enhances capabilities for error code management, analysis, and visualization at the User Interface (UI) level, enabling network administrators to effectively diagnose and resolve network issues.

[0142] As illustrated in FIG. 4, a user request is initiated from a user equipment 104 at step 410 and passed via a UI server 402 to a load balancer 404 at step 412. The load balancer 404 is responsible for distributing the incoming user requests across multiple instances of the system 108 to ensure optimal performance and scalability. The load balancer 404 forwards the user request to a vProbe manager 406 at step 414, which acts as a central component for coordinating the monitoring and management of error codes.

[0143] The vProbe manager 406, a central component of the system, receives and processes user requests for network monitoring and analysis. These requests typically encompass two primary functions: real-time clearcodes monitoring and management (418) and geography-based roll-up or drill-down operations (420) for clearcodes.

[0144] Real-time clearcodes monitoring and management is an important feature of the system. In this context, "clearcodes" refer to standardized error codes that have been processed for clear interpretation and analysis. The vProbe manager 406 continuously receives streams of raw error code data from various network functions. It then processes these raw codes into clearcodes, which are more easily interpretable and analyzable. This real-time processing allows network administrators to monitor network health instantaneously, identify emerging issues, and respond promptly to critical situations.

[0145] The geography-based roll-up / drill-down for clearcodes provides network administrators with a powerful tool for spatial analysis of network performance. This feature enables users to view clearcode data at various levels of geographical granularity. In a roll-up operation, the system aggregates clearcode data from lower geographic levels (such as individual network cells) to higher levels (like cities, states, or regions). This provides a broad overview of network performance across larger areas. Conversely, in a drill-down operation, the system disaggregates data from higher geographic levels to lower ones, allowing for detailed analysis of specific localities.

[0146] Upon receiving a user request, the vProbe manager 406 interacts with the computation layer to perform data filtering and geography-based network functions failure data computation at step 416. The computation layer retrieves raw error code data from a distributed data lake and applies the necessary filtering and aggregation operations based on the user's specifications at step 422. This processed data is then stored back in the distributed data lake at step 424.

[0147] The vProbe manager 406 subsequently extracts the computed data from the data lake to facilitate real-time monitoring and management. It also establishes the requested geography-based view of the clearcodes. The resulting analysis, which includes geography-based clearcode data along with any relevant notifications at step 426, is then sent back through the load balancer at step 428 and UI server to be presented to the user at step 430.

[0148] This system architecture enables efficient handling of large volumes of network error data, provides real-time insights, and offers flexible geographical analysis capabilities. By combining these features, the system empowers network administrators to quickly identify, localize, and address network issues, thereby improving overall network performance and reliability. To process the user request and analyze the error code data, the vProbe manager 406 interacts with a computation layer 408. The computation layer 408 is responsible for performing data filtering and geography-based network functions failure data computation. It retrieves raw error code data from a distributed file system 220 and applies the necessary filtering and aggregation operations based on the specified geography and other criteria in the user request.

[0149] The computation layer 408 processes the raw error code data and computes relevant metrics, statistics, and insights related to network functions failures. It may utilize various data analysis techniques, such as statistical analysis, machine learning algorithms, or rule-based engines, to identify patterns, anomalies, and correlations in the raw error code data. The computed data is then stored in a distributed data lake 224, which serves as a centralized repository for storing and managing the processed error code data.

[0150] The vProbe manager 406 extracts the computed error code data from the distributed data lake 224 to perform real-time monitoring and management of network functions. It establishes a geography-based roll-up or drill-down view of the error codes, allowing network administrators to navigate through the data at different levels of geographical granularity. This enables administrators to gain insights into the overall network behavior at a high level and also drill down into specific regions or network cells for targeted troubleshooting.

[0151] The vProbe manager 406 prepares the geography-based error code data along with any relevant notifications or alerts and sends it back to the load balancer 404. The load balancer 404 then forwards the data via the UI server 402 tothe user equipment 104, where it is presented to the network administrator through the user interface.

[0152] By following the above-mentioned process flow steps, the system 108 significantly improves the effectiveness and efficiency of network administrators in diagnosing, troubleshooting, and resolving network issues. The real-time monitoring capabilities and geography-based error code analysis provided by the vProbe solution enable administrators to quickly identify and address network problems, leading to reduced downtime, enhanced network performance, and increased productivity in managing wireless network infrastructures.

[0153] The vProbe solution implemented by the system 108 has the capacity to handle error codes in various formats of data representation. This capability enables network administrators to accurately interpret and analyze error codes from different sources and formats, leading to more efficient troubleshooting and issue resolution. The vProbe solution implemented by the system 108 may offers advanced filtering options and roll-up or drill-down functionality, empowering administrators to focus on specific error codes or network functions and perform targeted investigations. Additionally, the roll-up feature allows administrators to view the overall network behavior at a higher level, facilitating effective troubleshooting and identifying broader trends or patterns.

[0154] The system 108 provides advanced network monitoring capabilities, enabling network administrators to track network functions' failure error codes in real-time. This real-time monitoring feature allows for quick identification of issues and proactive actions to prevent prolonged downtime and minimize network disruptions. With the system 108, network administrators have access to accurate and detailed error code management, analysis, and visualization through the user interface. The enhanced visibility and clarity provided by the system 108 enable administrators to diagnose network issues more precisely and accurately, leading to faster resolution and improved network performance.

[0155] Furthermore, by addressing the limitations of existing systems, the vProbe solution implemented by the system 108 contributes to enhanced network performance. The ability to efficiently compute, execute, and monitor network functions' failure error codes enables proactive measures to prevent issues and optimize network operations. This proactive approach results in reduced downtime and improved overall network performance, benefiting both network administrators and end-users.

[0156] FIG. 5 illustrates an exemplary flow diagram of a method (500) for supporting and monitoring one or more network functions in a wireless network, in accordance with embodiments of the present disclosure.

[0157] At step (502), the method (500) includes receiving a user request for monitoring and managing error code data of the one or more network functions. This step initiates the process of error code analysis and management. The user request typically contains specific parameters for filtering and analyzing the error code data, such as error code type, severity, timestamp, network function, and geographical information (e.g., region, state, city, or network cell). This granular specification enables targeted analysis of network issues across various geographical scales.

[0158] At step (504), the method (500) includes collecting, via a data collection module (208), the error code data of the one or more network functions from a distributed file system (220). This step involves retrieving raw error code data from various network components stored in the distributed file system (220). The distributed file system (220) ensures scalability and fault tolerance in data storage and retrieval, allowing the system to handle large volumes of error code data efficiently.

[0159] At step (506), the method (500) includes interpreting and converting, via a data conversion module (210), the collected error code data into a standardized format. This standardization process is crucial for ensuring consistent analysis across different types of network functions and error codes. It involves parsing theraw data, extracting relevant information, and transforming it into a uniform structure that can be easily processed and analyzed.

[0160] At step (508), the method (500) includes analysing, via a data analysis module (212), the standardized error code data based on the user request. This analysis step leverages the standardized data to derive insights, identify patterns, and generate meaningful reports or visualizations based on the specific requirements outlined in the user request.

[0161] The method further comprises storing the analysed error code data in a distributed data lake (224). This storage step ensures that the processed data is preserved for future retrieval and analysis. The distributed data lake provides a scalable and flexible storage solution for managing large volumes of analyzed error code data.

[0162] The method also includes displaying, via a user interface, the stored analysed error code data along with navigation and filtering options. This step enhances the usability of the system by providing an intuitive interface for users to interact with the analyzed data. The navigation and filtering options allow users to explore the data efficiently, applying various criteria to focus on specific aspects of the network performance.

[0163] The method is capable of handling different types of user requests, including fresh requests and follow-up requests. For follow-up requests, it can determine if the request relates to a roll-up operation (viewing data at a higher geographic level) or a drill-down operation (viewing data at a lower geographic level). This functionality allows for dynamic and flexible analysis of error code data across different geographical scales.

[0164] The method provides real-time monitoring of the one or more network functions' failure error codes via the user interface. This feature enables immediate identification of issues based on the real-time monitoring and facilitates actions to minimize network disruptions. The real-time monitoring is integratedwith the display of the analysed error code data and the navigation and filtering options, providing a comprehensive view of network performance.

[0165] The user interface provides advanced navigation and filtering options. The users can navigate through the error code data, apply filters based on various criteria, and perform roll-up or drill-down operations to view relevant details for analysis. The roll-up operation allows users to aggregate error code data from lower geographic levels to higher levels, providing a broader overview. Conversely, the drill-down operation enables users to disaggregate data from higher geographic levels to lower levels for more detailed analysis.

[0166] In another exemplary embodiment, a user equipment communicatively coupled to the system through a network for supporting and monitoring network functions is described. The user equipment is configured to send user requests for monitoring and managing error codes of network functions in the network and receive analysed error code data along with navigation and filtering options. This enables network administrators to access and interact with the error code analysis system using various devices, enhancing the system's accessibility and usability.

[0167] The present disclosure provides technical advancement related to network function monitoring and error code management in wireless networks. This advancement addresses the limitations of existing solutions by offering a comprehensive system for real-time error code analysis with geographic granularity. The disclosure involves standardized data processing, real-time monitoring, and flexible geographical analysis, which offer significant improvements in network performance diagnostics and issue resolution. By implementing advanced data collection, conversion, and analysis techniques, along with an intuitive user interface, the disclosed invention enhances network administrators' ability to quickly identify and resolve issues, resulting in improved network reliability and reduced downtime. The integration of real-time monitoringwith geographical analysis capabilities provides a powerful tool for maintaining optimal network performance in complex wireless environments.

[0168] FIG. 6 illustrates an exemplary computer system (600) in which or with which embodiments of the present disclosure may be implemented. 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 (660), and a processor (670). A person skilled in the art will appreciate that the computer system (600) may include more than one processor (670) and communication port (660). The processor (670) may include various modules associated with embodiments of the present disclosure. In an embodiment, the computer system (600) may be used to implement the system (108) described in FIG. 1 and FIG. 2, including the processors (202), memory (204), interfaces (206), modules, and database (222).

[0169] In an embodiment, the communication port (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 (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. In an embodiment, the communication port (660) may support wireless communication protocols, such as Wi-Fi, Bluetooth, or cellular networks (e.g., 4G, 5G), enabling the computer system (600) to connect to wireless networks and devices.

[0170] 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). In an embodiment, the main memory (630) and the read-onlymemory (640) may be part of the memory (204) in FIG. 2, storing instructions and data for the functioning of the system (108).

[0171] In an embodiment, the mass storage (650) may be any current or future mass storage solution, which may 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 Firewire interfaces), one or more optical discs, Redundant Array of Independent Disks (RAID) storage, e.g., an array of disks (e.g., SATA arrays). In an embodiment, the mass storage (650) may be used to implement the database (222) in FIG. 2, storing the data generated by the network (106) and processed by the system (108).

[0172] In an embodiment, the bus (620) communicatively couples 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 as a front side bus (FSB), which connects the processor (670) to the computer system (600). In an embodiment, the bus (620) may be used to implement the interfaces (206) in FIG. 2, providing communication pathways between the processors (202), modules, database (222), and other components of the system (108).

[0173] 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 (600). Other operator and administrative interfaces may be provided through network connections connected through the communication port (660).

[0174] The method and system of the present disclosure may be implemented in a number of ways. For example, the methods and systems of thepresent 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. The programs for executing the method according to the present disclosure can be recorded on various types of recording media, including, but not limited to, magnetic storage media (e.g., hard disks, floppy disks, magnetic tapes), optical storage media (e.g., CD-ROMs, DVDs, Blu-ray discs), solid-state storage media (e.g., USB flash drives, SD cards, solid-state drives), and any other non- transitory computer-readable storage media. These recording media can store the programs in the form of machine-readable instructions, which can be executed by a computer or other processing device to implement the methods described in the present disclosure.

[0175] 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 to be implemented merely as illustrative of the disclosure and not as limitation.ADVANTAGES OF THE PRESENT DISCLOSURE

[0176] The present disclosure provides a comprehensive solution to enhance capabilities for error code management, analysis, and visualization at aUser Interface (UI) level. This holistic approach enables network administrators to effectively handle and investigate error codes, leading to more efficient troubleshooting and issue resolution.

[0177] The present disclosure handles error codes in various formats of data representation. This flexibility ensures that the system can process and analyze error codes from different sources and formats, providing a unified and standardized view of the error code data. By accommodating diverse data formats, the present disclosure eliminates the need for manual data conversion and streamlines the error code management process.

[0178] The present disclosure provides essential features such as filtering and roll-up / drill-down options to identify and focus on specific error codes or network functions, allowing for targeted investigations. These features enable network administrators to quickly narrow down their analysis to the most relevant data points, facilitating efficient troubleshooting and root cause analysis.

[0179] The present disclosure effectively diagnoses and troubleshoots network issues, resulting in reduced downtime and improved network performance. The real-time monitoring capabilities and advanced analytics provided by the system enable proactive identification of potential problems and prompt resolution of network anomalies, contributing to enhanced network stability and reliability.

[0180] The present disclosure provides the system that significantly improves the effectiveness and efficiency of network administrators in diagnosing, troubleshooting, and resolving network issues. The intuitive user interface, along with the powerful error code management and analysis features, empowers administrators to quickly identify and address network problems, leading to reduced downtime, enhanced network performance, and increased productivity in managing network infrastructures.

Claims

We Claim:

1. A system (108) for supporting and monitoring one or more network functions, the system (108) comprising: a memory (204); and one or more processors (202) configured to execute instructions stored in the memory (204) to: receive a user request via a user interface (206) for monitoring and managing error code data of the one or more network function; collect, via a data collection module (208), the error code data of the one or more network functions from a distributed file system (220); interpret and convert, via a data conversion module (210), the collected error code data into a standardized format; and analyze, via a data analysis module (212), the standardized error code data based on the user request.

2. The system (108) as claimed in claim 1, wherein the one or more processors (202) are further configured to execute the instructions stored in the memory (204) to: store, via a data storage module (216), the analysed error code data in a distributed data lake (224) and; display, via the user interface, the stored analysed error code data along with navigation and filtering options.

3. The system (108) as claimed in claim 1, wherein the user request includes at least one filter and a geography, wherein the at least one filter includes one or more of error code type, severity, timestamp, and network function, and the geography includes one or more of region, state, city, and network cell.

4. The system (108) as claimed in claim 1, wherein the one or more processors (202) are further configured to execute the instructions stored in the memory (204) to: determine, by a request processing module (214), whether the user request is a fresh request or a follow-up request; and when the user request is determined as the follow-up request, determine, by the request processing module (214), whether the user request relates to a roll-up operation to view the analysed error code data at a higher geographic level or a drill-down operation to view the analysed error code data at a lower geographic level.

5. The system (108) as claimed in claim 4, wherein when the user request is for the roll-up operation, the one or more processors (202) are further configured to execute the instructions stored in the memory (204) to: add, by the request processing module (214), the higher geographic level in at least one filter and remove a previous lower geographic level along with previous filters.

6. The system (108) as claimed in claim 3, wherein when the user request is for the drill-down operation, the one or more processors (202) are further configured to execute instructions stored in the memory (204) to: add, by the request processing module (214), the lower geographic level in the at least one filter along with previous filters.

7. The system (108) as claimed in claim 1, wherein when the user request is a fresh request, the system (108) performs data collection, filtering, and standardization operations on receiving the error code data of the one or more network functions, and performs analysis of the standardized error code data based on the user request.

8. The system (108) as claimed in claim 1, wherein the one or more processors (202) are further configured to execute the instructions stored in the memory (204) to: enable, via the user interface, real-time monitoring of the one or more network functions' failure error codes; enable identification of issues based on the real-time monitoring; and facilitate actions to minimize network disruptions based on the identified issues, wherein the real-time monitoring is integrated with the display of the analysed error code data, navigation and filtering options.

9. The system (108) as claimed in claim 1, wherein the user interface provides navigation and filtering options to allow users to navigate through the error code data, apply filters based on a criteria, and perform roll-up or drill-down operations to view relevant details for analysis, wherein: roll-up operation allows the users to view the relevant details at a higher geographic level by aggregating data from lower geographic levels; and drill-down operation allows the users to view the relevant details at a lower geographic level by disaggregating data from higher geographic levels.

10. A method (500) for supporting and monitoring one or more network functions, the method (500) comprising: receiving (502), via a user interface (206), a user request for monitoring and managing error code data of the one or more network function; collecting (504), via a data collection module (208), the error code data of the one or more network functions from a distributed file system (220) based on the user request; interpreting and converting (506), via a data conversion module (210), the collected error code data into a standardized format; and analysing (508), via a data analysis module (212), the standardized error code data based on the user request.

11. The method (500) as claimed in claim 10, further comprising: storing , via a data storage module (216), the analysed error code data in a distributed data lake (224); and displaying, via the user interface, the stored analysed error code data along with navigation and filtering options, wherein the stored analysed error code data is retrievable for future use. .

12. The method (500) as claimed in claim 10, wherein the user request includes at least one filter and a geography, wherein the at least one filter includes one or more of error code type, severity, timestamp, and network function, and the geography includes one or more of region, state, city, and network cell.

13. The method (500) as claimed in claim 10, further comprising: determining , by a request processing module (214), whether the user request is a fresh request or a follow-up request; andwhen the user request is determined as the follow-up request, determining , by the request processing module (214), whether the user request relates to a roll-up operation to view the analysed error code data at a higher geographic level or a drill-down operation to view the analysed error code data at a lower geographic level.

14. The method (500) as claimed in claim 13, wherein when the user request is for the roll-up operation, the method further comprises: adding, by the request processing module (214), the higher geographic level in at least one filter and removing a previous lower geographic level along with previous filters.

15. The method (500) as claimed in claim 13, wherein when the request is for the drill-down operation, the method further comprises: adding, by the request processing module (214), the lower geographic level in the at least one filter along with previous filters.

16. The method (500) as claimed in claim 10, wherein when the user request is a fresh request, the method further comprises: performing data collection, filtering, and standardization operations on receiving the error code data of the one or more network functions; and analysing the standardized error code data based on the user request.

17. The method (500) as claimed in claim 10, further comprising: enabling, via the user interface, real-time monitoring of the one or more network functions' failure error codes; enabling identification of issues based on the real-time monitoring; andfacilitating actions to minimize network disruptions based on the identified issues, wherein the real-time monitoring is integrated with the display of the analysed error code data, navigation and filtering options.

18. The method (500) as claimed in claim 10, wherein the user interface provides navigation and filtering options to allow users to navigate through the error code data, apply filters based on criteria, and perform roll-up or drill-down operations to view relevant details for analysis, wherein: roll-up operation allows the users to view the relevant details at a higher geographic level by aggregating the error code data from lower geographic levels; and drill-down operation allows the users to view the relevant details at a lower geographic level by disaggregating the error code data from higher geographic levels.

19. A computer program product comprising a non-transitory computer- readable medium having instructions stored thereon that, when executed by at least one processor (202), cause the at least one processor (202) to perform operations comprising: receiving, via a user interface, a user request for monitoring and managing error code data of one or more network functions in a wireless network; collecting, via a data collection module (208), the error code data of the network functions a distributed file system (220) based on the user request; interpreting and converting, via a data conversion module (210), the collected error code data into a standardized format; andanalysing, via a data analysis module (212), the standardized error code data based on the user request.

20. A user equipment (104) communicatively coupled to a system (108) through a network for supporting and monitoring one or more network functions, the user equipment (104) is configured to send a user request for monitoring and managing error code data of the one or more network functions in the network; and receive analysed error code data along with navigation and filtering options, wherein the analysed error code data is obtained by a method for supporting and monitoring the one or more network functions in the network as claimed in claim 10.

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