FORM 2


PATENTS ACT, 1970 (39 of 1970) PATENTS RULES, 2003

COMPLETE SPECIFICATION
TITLE OF THE INVENTION
A SYSTEM AND METHOD TO SUPPORT AND MONITOR ONE OR MORE NETWORK
FUNCTIONS
APPLICANT
of Office-101, Saffron, Nr C JIO PLATFORMS LIM , Ambawadi, Ahmedabad -
380006, Gujarat, India; Nationality: India

following specification particularly describes the invention and the manner in which it is to be performed

RESERVATION OF RIGHTS
[0001] A portion of the disclosure of this patent document contains material,
which is subject to intellectual property rights such as, but are not limited to,
copyright, design, trademark, Integrated Circuit (IC) layout design, and/or trade
5 dress protection, belonging to Jio Platforms Limited (JPL) or its affiliates
(hereinafter referred as owner). The owner has no objection to the facsimile
reproduction by anyone of the patent document or the patent disclosure, as it
appears in the Patent and Trademark Office patent files or records, but otherwise
reserves all rights whatsoever. All rights to such intellectual property are fully
10 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 code
15 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.
2

[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
5 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.
10 [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
15 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
20 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.
25 [0014] “Computation Layer” is responsible for performing data filtering and
geography-based network functions failure data computation. It retrieves raw error

code 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
5 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.
10 [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
15 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
20 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
25 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.
4

[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
5 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
10 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.
15 [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
20 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
25 functions in a wireless network, thereby overcoming the above-mentioned
disadvantages in the field.
SUMMARY
5

[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
5 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
10 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.
15 [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
20 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
25 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.
6

[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.
5 [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
10 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
15 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.
20 [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
25 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.
7

[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
5 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.
10 [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
15 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.
20 [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
25 view the analyzed error code data at a lower geographic level.
8

[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.
5 [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
10 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
15 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
20 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
25 geographic levels.
9

[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
5 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
10 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
15 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.
20 [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
25 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, and
10

visualization 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,
5 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
10 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 real¬
time monitoring capabilities, advanced filtering options, and intuitive navigation,
15 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
20 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
25 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.
11

[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.
5 [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
10 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
15 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
20 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 NUMERALS
25 100 – Network Architecture
102 – User (s)
12

104-1, 104-2… 104-N - User Equipment (s)
106 -Network
108 - System
202 - One or more processor(s) 5 204 - Memory
206 - I/O Interfaces
208 - Data collection module
210 -Data conversion module
212 - Data analysis module 10 214 - Request processing module
216 - Data storage module
218 - Other Module (s)
220- Distributed file system
222– Database 15 224- Distributed data lake
300 - Method
402 - UI server
404 - Load balancer
406 - vProbe manager 20 408 - Computation layer
13

510 – External Storage Device 520 – Bus
530 – Main Memory
540 – Read Only Memory
5 550 – Mass Storage Device
560 – Communication Port 570 – Processor
DETAIL DESCRIPTION OF THE INVENTION
[0059] In the following description, for the purposes of explanation, various
10 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
15 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
20 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
25 embodiment. It should be understood that various changes may be made in the
14

function 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
5 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
10 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
15 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
20 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
25 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
15

“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,
5 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
10 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
15 “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
20 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
25 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.
16

[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
5 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,
10 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
15 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
20 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
25 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
30 technologies. In the field of wireless data communications, the dynamic
17

advancement 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.
5 [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
10 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,
15 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
20 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
25 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 filtering
18

options, 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
5 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
10 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
15 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
20 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
25 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. The
19

terms '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
5 224 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
10 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.
15 [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
20 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
25 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.
20

[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
5 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
10 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
15 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,
20 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
25 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.
21

[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
5 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.
10 [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)
15 202 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
20 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
25 output devices, storage devices, and the like. The I/O interfaces 206 may facilitate
communication to/from the system 108. The I/O 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, data
22

conversion 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,
5 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
10 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
15 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,
20 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
25 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.
23

[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
5 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
10 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,
15 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
20 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
25 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), which
24

indicate issues with web services or Application Programming Interface (API) endpoints.
b. Mobile Network Error Codes: For instance, 'CS0001' might indicate
a general system failure in a cellular network, while 'CS0008' could
5 represent an authentication failure.
c. Network Equipment Error Codes: Such as 'E1001' 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
10 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
15 connection timeout, or 'ORA-00001' 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.
20 [00100] 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
25 the system 108. The standardized format may include fields such as error code type,
severity, timestamp, associated network function, and geographical information.
25

[00101] 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
5 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.
[00102] The request processing module 214 may handle the processing of
user requests received by the system 108. The request processing module 214 may
10 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
15 operation may involve viewing data at a lower geographic level by disaggregating
data from higher geographic levels.
[00103] 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
20 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.
[00104] The user interface provided by the system 108 may offer navigation
25 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 data
26

along with these navigation and filtering options, empowering the users to interactively investigate and gain insights from the data.
[00105] 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
5 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.
10 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
15 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
20 108 provides a flexible and responsive tool for network administrators to investigate
and manage error codes in various network scenarios.
[00106] 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
25 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.
[00107] 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 operation
27

or 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
5 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.
[00108] The system 108 may provide real-time monitoring capabilities for
10 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.
15 [00109] 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
20 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.
[00110] In an embodiment, the system 108 may include a database 222 that
stores various configuration settings, user preferences, and other relevant
25 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.
28

[00111] 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,
5 and communication modules for facilitating data exchange between different
components of the system 108 or with external systems.
[00112] 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
10 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.
[00113] The distributed data lake 224 may serve as a centralized repository
15 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, semi-
structured, 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
20 sharing and collaboration among different stakeholders.
[00114] 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
25 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 of
29

performance 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
5 decision-making for effective network management.
[00115] 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
10 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.
[00116] In an embodiment, the system 108 may generate alerts and
notifications based on predefined thresholds or anomalies detected in the error code
15 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.
20 [00117] 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
25 authorize users based on their assigned roles, ensuring data privacy, confidentiality,
and compliance with organizational policies.
[00118] 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 external
30

systems 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.
5 [00119] 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
10 updated to incorporate them seamlessly, ensuring that it remains relevant and
effective in supporting the monitoring and management of network functions.
[00120] 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,
15 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
20 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.
25 [00121] 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.
31

[00122] 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
5 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.
[00123] 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.
10 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.
[00124] The data collection operation (306) may involve collecting (316)
15 error code data of network functions from a distributed file system 220. The
distributed 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.
20 [00125] 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.
25 The standardized format may include fields such as error code type, severity,
timestamp, associated network function, and geographical information.
[00126] 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 user request. The data analysis module 212 of the system 108 may perform various
32

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
5 error code data relevant to their needs.
[00127] 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
10 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.
[00128] In addition to storing the analyzed data, the method 300 may display
15 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
20 based on specific criteria such as error code type, severity, timestamp, or network
function.
[00129] 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
25 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.
33

[00130] 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
5 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.
[00131] 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
10 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.
15 [00132] 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,
20 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
25 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",
30 "severity", "networkFunction", "description", and "affectedElement". This
34

standardized 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
5 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.
[00133] Throughout the method 300, the user interface may provide real-time
monitoring of network functions' failure error codes. This real-time monitoring
10 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.
[00134] The user interface may also provide navigation and filtering options
15 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
20 relevant details at different geographic levels, enabling them to analyze the error
code data from both high-level and detailed perspectives.
[00135] 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
25 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.
[00136] 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 higher
35

geographic 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
5 troubleshooting and resolution efforts.
[00137] 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,
10 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.
[00138] The method 300 may also incorporate data visualization techniques
to present the analyzed error code data in a clear, concise, and visually appealing
15 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 decision-making.
20 [00139] 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
25 performance.
[00140] 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 request
36

for 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
5 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
10 wireless network based on the processed error code data provided by the system
(108).
[00141] 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,
15 analysis, and visualization at the User Interface (UI) level, enabling network
administrators to effectively diagnose and resolve network issues.
[00142] 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
20 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.
[00143] The vProbe manager 406, a central component of the system,
25 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 for clearcodes (420).
37

[00144] 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
5 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.
[00145] The geography-based roll-up / drill-down for clearcodes provides
10 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
15 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.
[00146] Upon receiving a user request, the vProbe manager 406 interacts
with the computation layer to perform data filtering and geography-based network
20 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.
[00147] The vProbe manager 406 subsequently extracts the computed data
25 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.
38

[00148] 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
5 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
10 necessary filtering and aggregation operations based on the specified geography
and other criteria in the user request.
[00149] 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,
15 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.
[00150] The vProbe manager 406 extracts the computed error code data from
20 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
25 specific regions or network cells for targeted troubleshooting.
[00151] 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 to
39

the user equipment 104, where it is presented to the network administrator through the user interface.
[00152] By following the above-mentioned process flow steps, the system
108 significantly improves the effectiveness and efficiency of network
5 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.
10 [00153] 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
15 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.
20 [00154] 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
25 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.
40

[00155] 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
5 optimize network operations. This proactive approach results in reduced downtime
and improved overall network performance, benefiting both network administrators and end-users.
[00156] 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
10 accordance with embodiments of the present disclosure.
[00157] 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
15 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.
[00158] At step (504), the method (500) includes collecting, via a data
20 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
25 data efficiently.
[00159] 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 the
41

raw data, extracting relevant information, and transforming it into a uniform structure that can be easily processed and analyzed.
[00160] At step (508), the method (500) includes analysing, via a data
analysis module (212), the standardized error code data based on the user request.
5 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.
[00161] 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
10 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.
[00162] The method also includes displaying, via a user interface, the stored
analysed error code data along with navigation and filtering options. This step
15 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.
[00163] The method is capable of handling different types of user requests,
20 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.
25 [00164] 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 integrated
42

with the display of the analysed error code data and the navigation and filtering options, providing a comprehensive view of network performance.
[00165] The user interface provides advanced navigation and filtering
options. The users can navigate through the error code data, apply filters based on
5 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.
10 [00166] 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
15 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.
[00167] The present disclosure provides technical advancement related to
network function monitoring and error code management in wireless networks. This
20 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
25 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 monitoring
43

with geographical analysis capabilities provides a powerful tool for maintaining optimal network performance in complex wireless environments.
[00168] FIG. 6 illustrates an exemplary computer system (600) in which or
with which embodiments of the present disclosure may be implemented. The
5 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
10 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).
[00169] In an embodiment, the communication port (660) may be any of an
15 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
20 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.
[00170] In an embodiment, the main memory (630) may be Random Access
Memory (RAM), or any other dynamic storage device commonly known in the art.
25 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-only
44

memory (640) may be part of the memory (204) in FIG. 2, storing instructions and data for the functioning of the system (108).
[00171] 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
5 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.,
10 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).
[00172] In an embodiment, the bus (620) communicatively couples the
processor(s) (670) with the other memory, storage, and communication blocks. The
15 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
20 implement the interfaces (206) in FIG. 2, providing communication pathways
between the processors (202), modules, database (222), and other components of the system (108).
[00173] Optionally, operator and administrative interfaces, e.g., a display,
keyboard, joystick, and a cursor control device, may also be coupled to the bus
25 (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).
[00174] The method and system of the present disclosure may be
implemented in a number of ways. For example, the methods and systems of the
45

present disclosure may be implemented by software, hardware, firmware, or any
combination of software, hardware, and firmware. The above-described order for
the steps of the method is for illustration only, and the steps of the method of the
present disclosure are not limited to the order specifically described above unless
5 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
10 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-
15 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.
[00175] While considerable emphasis has been placed herein on the preferred
20 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
25 descriptive matter to be implemented merely as illustrative of the disclosure and not
as limitation.
ADVANTAGES OF THE PRESENT DISCLOSURE
[00176] The present disclosure provides a comprehensive solution to
enhance capabilities for error code management, analysis, and visualization at a
46

User Interface (UI) level. This holistic approach enables network administrators to effectively handle and investigate error codes, leading to more efficient troubleshooting and issue resolution.
[00177] The present disclosure handles error codes in various formats of data
5 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.
10 [00178] 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.
15 [00179] 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.
20 [00180] 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
25 downtime, enhanced network performance, and increased productivity in managing
network infrastructures.
47

WE CLAIM:
1. A system (108) for supporting and monitoring one or more network
functions, the system (108) comprising:
5 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
10 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),
15 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
20 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.
48

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,
5 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
10 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
15 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
20 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)
25 to:
add, by the request processing module (214), the lower geographic level in the at least one filter along with previous filters.
49

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
5 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
10 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
15 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
20 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
25 drill-down operation allows the users to view the relevant details
at a lower geographic level by disaggregating data from higher geographic levels.
50

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
5 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
10 (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
15 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
20 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:
25 determining , 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,
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
5 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
10 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.
15 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.
20 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; and
52

facilitating 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
5 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
10 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.
15
19. 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
20
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.