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

SYSTEM AND METHOD FOR AUDITING AND RECOVERY OF MISSING KPI DATA WITHIN NETWORK MANAGEMENT SYSTEM
TECHNICAL FIELD
[0001] Embodiments of the present disclosure generally relate to network performance management system. More particularly, embodiments of the present disclosure relate to method and system for auditing and recovery of missing key performance indicator (KPI) data within network performance management systems (NMS).
BACKGROUND
[0002] The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.
[0003] Wireless communication technology has rapidly evolved over the past few decades, with each generation bringing significant improvements and advancements. The first generation of wireless communication technology was based on analog technology and offered only voice services. However, with the advent of the second-generation (2G) technology, digital communication and data services became possible, and text messaging was introduced. The third generation (3G) technology marked the introduction of high-speed internet access, mobile video calling, and location-based services. The fourth-generation (4G) technology revolutionized wireless communication with faster data speeds, better network coverage, and improved security. Currently, the fifth-generation (5G) technology is

being deployed, promising even faster data speeds, low latency, and the ability to connect multiple devices simultaneously. With each generation, wireless communication technology has become more advanced, sophisticated, and capable of delivering more services to its users.
[0004] In network management system (NMS), network key performance indicators (KPIs) are used to assess a network's performance. By tracking performance against KPIs, network managers can take pre-emptive action to ensure that determined service standards are met. The network professionals can make decisions concerning demand, performance, and infrastructure investment using KPIs as a concrete baseline. There is a chance of performance management (PM) data loss for any Network Element at any time interval due to network connectivity issue or hardware failure or some other fault at node end, which would lead to KPI data loss.
[0005] In the current existing solutions, missing KPIs and PM data hinder the ability to obtain a comprehensive view of network performance. Without complete data, it becomes challenging to identify and address performance issues effectively. This results in suboptimal network performance, reduced quality of service, and customer dissatisfaction. Also, KPIs and PM data provide valuable insights into network behavior, usage patterns, and performance trends. When certain data points are missing, it limits the depth of analysis and hampers the ability to gain a holistic understanding of the network's performance characteristics. This can impede decision-making and planning for network optimization and capacity upgrades.
[0006] In current existing solutions, KPIs and PM data play a vital role in network optimization activities, such as capacity planning, load balancing, and resource allocation. Incomplete data can lead to suboptimal decision-making, inefficient resource utilization, and decreased network efficiency. This can result in wasted resources, increased operational costs, and degraded network performance.

[0007] There is a direct need in the existing solutions to address the current limitations.
SUMMARY
[0008] This section is provided to introduce certain aspects of the present disclosure in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter.
[0009] An aspect of the present disclosure may relate to a method for auditing and recovery of missing Key Performance Indicator (KPI) data within a Network Management System (NMS). The method includes monitoring, by a KPI worker node, KPI data for a plurality of network nodes within the NMS. Next, the method includes identifying, by the KPI worker node, a set of log entries missing the KPI data. Next, the method includes storing, at the KPI worker node, a set of requests for the missed KPI data in an input-output (IO) Cache with a unique identifier for each of the set of log entries missing the KPI data. Next, the method includes fetching, by a KPI auditor, the set of requests for the set of log entries missing the KPI data. Next, the method includes transmitting, by the KPI auditor, the set of requests to the KPI worker node. Next, the method includes fetching, by KPI worker node, performance management (PM) data corresponding to the set of requests. Thereafter, the method includes determining, by the KPI auditor using the KPI worker node, the missed KPI data based on the fetched PM data and updating a database with the determined KPI data.
[0010] In an exemplary aspect of the present disclosure, the method further comprises storing, by the KPI worker node, the determined KPI data in the database.

[0011] In an exemplary aspect of the present disclosure, the method further comprises removing, by the KPI auditor, a log entry from the IO cache for which the missing KPI data is determined.
[0012] In an exemplary aspect of the present disclosure, the method further comprises validating, by the KPI auditor, whether any log entry of the set of log entries missing the KPI data is expired.
[0013] In an exemplary aspect of the present disclosure, the method further comprises the log entry is expired if the log entry exists in the IO cache for a predetermined time period.
[0014] In an exemplary aspect of the present disclosure, the method further comprises removing, by the KPI auditor, the expired log entry from the IO cache.
[0015] In an exemplary aspect of the present disclosure, the method further comprises retaining the set of log entries missing the KPI data in the IO Cache until expiry of the predetermined time period is reached, wherein if the KPI data is not received by the KPI worker node during subsequent audit before expiration of the predetermined time period, the set of log entries are automatically removed from the IO Cache.
[0016] Another aspect of the present disclosure may relate to a system for auditing and recovery of missing Key Performance Indicator (KPI) data within a Network Management System (NMS). The system comprises a KPI worker node configured to: monitor KPI data for a plurality of network nodes within the NMS; identify a set of log entries missing the KPI data; and store a set of requests for the missed KPI data in an input-output (IO) Cache with a unique identifier for each of the set of log entries missing the KPI data. The system also comprises a KPI auditor configured to: fetch the set of requests for the set of log entries missing the KPI

data; and transmit the set of requests to the KPI worker node; fetch performance management (PM) data corresponding to the set of requests. Also, the KPI auditor is configured to determine, using the KPI worker node, the missed KPI data based on the fetched PM data and updating the NMS with the determined KPI data.
[0017] Yet another aspect of the present disclosure may relate to a non-transitory computer readable storage medium storing instructions for auditing and recovery of missing Key Performance Indicator (KPI) data within a Network Management System (NMS), the instructions include executable code which, when executed by one or more units of a system, causes: monitoring, by a KPI worker node of the system, KPI data for a plurality of network nodes within the NMS; identifying, by the KPI worker node, a set of log entries missing the KPI data; storing, at the KPI worker node, a set of requests for the missed KPI data in an input-output (IO) Cache with a unique identifier for each of the set of log entries missing the KPI data; fetching, by a KPI auditor of the system, the set of requests for the set of log entries missing the KPI data; transmitting, by the KPI auditor, the set of requests to the KPI worker node; fetching, by KPI worker node, performance management (PM) data corresponding to the set of requests; and determining, by the KPI auditor using the KPI worker node, the missed KPI data based on the fetched PM data and updating a database with the determined KPI data.
[0018] Yet another aspect of the present disclosure may relate to a user equipment (UE) comprising a transceiver unit, configured to: transmit, a request to a system for receiving a missed Key Performance Indicator (KPI) data; and receive, the missed KPI data from the system in response to the request. The missed KPI data is generated by the system based on: monitoring, by a KPI worker node of the system, KPI data for a plurality of network nodes within a Network Management System (NMS); identifying, by the KPI worker node, a set of log entries missing the KPI data; storing, at the KPI worker node, a set of requests for the missed KPI data in an input-output (IO) Cache with a unique identifier for each of the set of log entries missing the KPI data; fetching, by a KPI auditor of the system, the set of

requests for the set of log entries missing the KPI data; transmitting, by the KPI
auditor, the set of requests to the KPI worker node; fetching, by KPI worker node,
performance management (PM) data corresponding to the set of requests; and
determining, by the KPI auditor using the KPI worker node, the missed KPI data
5 based on the fetched PM data and updating a database with the determined KPI
data.
OBJECTS OF THE DISCLOSURE
10 [0019] Some of the objects of the present disclosure, which at least one
embodiment disclosed herein satisfies are listed herein below.
[0020] It is an object of the present disclosure to provide a system and a method for
auditing of missing KPIs and performing calculation on restored performance
15 management (PM) data through PM auditor.
[0021] It is another object of the present disclosure to provide a solution to recover any lost KPI data that was caused by a network problem, hardware issue, network element failure, database failure, or network management system (NMS) error.
20
[0022] It is yet another object of the present disclosure to provide a system and method for network performance monitoring and auditing that is designed to minimize or eliminate data loss, thereby enhancing the integrity and completeness of the performance data collected.
25
[0023] Also, an object of the present disclosure is to provide a solution that allows for more accurate and reliable network performance monitoring and analysis.
7

[0024] It is yet another object of the present disclosure to provide a system and method for network performance monitoring and auditing that is developed such that to ensure that users are promptly notified about missing performance data.
5 [0025] It is yet another object of the present disclosure to provide a system and
method for network performance monitoring and auditing that streamlines and optimizes the procedure for identifying, requesting, and receiving missing data.
[0026] It is yet another object of the present disclosure to provide a solution to
10 utilize the distributed input-output (IO) cache to process each KPI data missed for
an interval and to make sure that all counter KPI data is obtained.
BRIEF DESCRIPTION OF THE DRAWINGS
15 [0027] The accompanying drawings, which are incorporated herein, and constitute
a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present
20 disclosure. Also, the embodiments shown in the figures are not to be construed as
limiting the disclosure, but the possible variants of the method and system according to the disclosure are illustrated herein to highlight the advantages of the disclosure. It will be appreciated by those skilled in the art that disclosure of such drawings includes disclosure of electrical components or circuitry commonly used
25 to implement such components.
[0028] FIG. 1 illustrates an exemplary block diagram of a computing device upon which the features of the present disclosure may be implemented in accordance with exemplary implementation of the present disclosure. 30
8

[0029] FIG. 2 illustrates an exemplary block diagram of a system for auditing and recovery of missing Key Performance Indicator (KPI) data within a Network Management System (NMS), in accordance with exemplary implementations of the present disclosure. 5
[0030] FIG. 3 illustrates a method flow diagram for auditing and recovery of missing Key Performance Indicator (KPI) data within a Network Management System (NMS), in accordance with exemplary implementations of the present disclosure.
10
[0031] FIG. 4 illustrates an exemplary block diagram of an exemplary system for auditing and recovery of missing Key Performance Indicator (KPI) data within a Network Management System (NMS), in accordance with exemplary implementations of the present disclosure.
15
[0032] FIG. 5 illustrates an exemplary process flow diagram for auditing and recovery of missing Key Performance Indicator (KPI) data within a Network Management System (NMS), in accordance with exemplary implementations of the present disclosure.
20
[0033] FIG. 6 illustrates an exemplary diagram depicting a user equipment connected to the system for auditing and recovery of missing Key Performance Indicator (KPI) data within a Network Management System (NMS), in accordance with exemplary implementations of the present disclosure.
25
[0034] The foregoing shall be more apparent from the following more detailed description of the disclosure.
DETAILED DESCRIPTION
30
9

[0035] In the following description, for the purposes of explanation, various
specific details are set forth in order to provide a thorough understanding of
embodiments of the present disclosure. It will be apparent, however, that
embodiments of the present disclosure may be practiced without these specific
5 details. Several features described hereafter may each be used independently of one
another or with any combination of other features. An individual feature may not address any of the problems discussed above or might address only some of the problems discussed above.
10 [0036] The ensuing description provides exemplary embodiments only, and is not
intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and
15 arrangement of elements without departing from the spirit and scope of the
disclosure as set forth.
[0037] Specific details are given in the following description to provide a thorough
understanding of the embodiments. However, it will be understood by one of
20 ordinary skill in the art that the embodiments may be practiced without these
specific details. For example, circuits, systems, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail.
25 [0038] Also, it is noted that individual embodiments may be described as a process
which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations may be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process
10

is terminated when its operations are completed but could have additional steps not included in a figure.
[0039] The word “exemplary” and/or “demonstrative” is used herein to mean
5 serving as an example, instance, or illustration. For the avoidance of doubt, the
subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques
10 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—in a manner similar to the term “comprising” as an open transition word—without precluding any additional or other elements.
15
[0040] As used herein, a “processing unit” or “processor” or “operating processor” includes one or more processors, wherein processor refers to any logic circuitry for processing instructions. A processor may be a general-purpose processor, a special purpose processor, a conventional processor, a digital signal processor, a plurality
20 of microprocessors, one or more microprocessors in association with a (Digital
Signal Processing) DSP core, a controller, a microcontroller, Application Specific Integrated Circuits, Field Programmable Gate Array circuits, any other type of integrated circuits, etc. The processor may perform signal 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 or
processing unit is a hardware processor.
[0041] As used herein, “a user equipment”, “a user device”, “a smart-user-device”,
“a smart-device”, “an electronic device”, “a mobile device”, “a handheld device”,
30 “a wireless communication device”, “a mobile communication device”, “a
11

communication device” may be any electrical, electronic and/or computing device
or equipment, capable of implementing the features of the present disclosure. The
user equipment/device may include, but is not limited to, a mobile phone, smart
phone, laptop, a general-purpose computer, desktop, personal digital assistant,
5 tablet computer, wearable device or any other computing device which is capable
of implementing the features of the present disclosure. Also, the user device may contain at least one input means configured to receive an input from unit(s) which are required to implement the features of the present disclosure.
10 [0042] As used herein, “storage unit” or “memory unit” refers to a machine or
computer-readable medium including any mechanism for storing information in a form readable by a computer or similar machine. For example, a computer-readable medium includes read-only memory (“ROM”), random access memory (“RAM”), magnetic disk storage media, optical storage media, flash memory devices or other
15 types of machine-accessible storage media. The storage unit stores at least the data
that may be required by one or more units of the system to perform their respective functions.
[0043] As used herein “interface” or “user interface refers to a shared boundary
20 across which two or more separate components of a system exchange information
or data. The interface may also be referred to a set of rules or protocols that define communication or interaction of one or more modules or one or more units with each other, which also includes the methods, functions, or procedures that may be called. 25
[0044] All modules, units, components used herein, unless explicitly excluded
herein, may be software modules or hardware processors, the processors being a
general-purpose processor, a special purpose processor, a conventional processor,
a digital signal processor (DSP), a plurality of microprocessors, one or more
30 microprocessors in association with a DSP core, a controller, a microcontroller,
12

Application Specific Integrated Circuits (ASIC), Field Programmable Gate Array circuits (FPGA), any other type of integrated circuits, etc.
[0045] As used herein the transceiver unit include at least one receiver and at least
5 one transmitter configured respectively for receiving and transmitting data, signals,
information, or a combination thereof between units/components within the system and/or connected with the system.
[0046] As used herein, log entries refer to the recorded data or documentation
10 entries generated by the Network Management System (NMS) that capture various
events, operations, and performance metrics of network elements. The log entries
facilitate in tracking the status, performance, and any issues within the network.
The log entries include timestamps, identifiers for specific network nodes, the type
of data or event being logged, and any pertinent details that describe the event or
15 metric. For example, log entries can include instances where Key Performance
Indicator (KPI) data is missing, enabling the system to identify, audit, and recover the lost data to ensure comprehensive performance assessment and management.
[0047] As discussed in the background section, the current known solutions for
20 auditing of missing KPIs and performing calculation on restored performance
management (PM) data have several shortcomings. Existing network performance
monitoring systems have a significant problem with performance data loss. This
loss could occur due to a variety of reasons, including network connectivity issues,
hardware failures, network element failures, database failures, and faults in the
25 network management system itself. The current disclosure overcomes this problem
by implementing an auditing solution to retrieve missing performance data,
ensuring more reliable and accurate data for analysis. Also, in the existing systems
lack of detailed tracking made it difficult to understand the flow and progress of
requests, as well as to identify and address issues when they arose. This disclosure
30 remedies this by using a distributed IO cache to track every counter reset request
13

with unique flow-ids. Further, earlier systems often fell short in notifying users
about missing performance data in a timely manner. This lack of communication
could lead to problems going unnoticed and unresolved for extended periods of
time. Furthermore, in the previous systems, handling missing performance data was
5 often inefficient and manual. They lacked a systematic approach to identify,
request, and receive missing data. The present disclosure aims to overcome the above-mentioned and other existing problems in this field of technology by providing method and system for auditing and recovery of missing Key Performance Indicator (KPI) data within a Network Management System (NMS).
10
[0048] FIG. 1 illustrates an exemplary block diagram of a computing device [100] [also referred to herein as a computer system [100]] upon which the features of the present disclosure may be implemented in accordance with exemplary implementation of the present disclosure. In an implementation, the computing
15 device [100] may implement a method for auditing and recovery of missing Key
Performance Indicator (KPI) data within a Network Management System (NMS) utilising the system [200]. In another implementation, the computing device [100] itself implements the method for auditing and recovery of missing Key Performance Indicator (KPI) data within a Network Management System (NMS) using one or
20 more units configured within the computing device [100], wherein said one or more
units are capable of implementing the features as disclosed in the present disclosure.
[0049] The computing device [100] may include a bus [102] or other communication mechanism for communicating information, and a hardware
25 processor [104] coupled with bus [102] for processing information. The hardware
processor [104] may be, for example, a general purpose microprocessor. The computing device [100] may also include a main memory [106], such as a random access memory (RAM), or other dynamic storage device, coupled to the bus [102] for storing information and instructions to be executed by the processor [104]. The
30 main memory [106] also may be used for storing temporary variables or other
14

intermediate information during execution of the instructions to be executed by the
processor [104]. Such instructions, when stored in non-transitory storage media
accessible to the processor [104], render the computing device [100] into a special-
purpose machine that is customized to perform the operations specified in the
5 instructions. The computing device [100] further includes a read only memory
(ROM) [108] or other static storage device coupled to the bus [102] for storing static information and instructions for the processor [104].
[0050] A storage device [110], such as a magnetic disk, optical disk, or solid-state
10 drive is provided and coupled to the bus [102] for storing information and
instructions. The computing device [100] may be coupled via the bus [102] to a
display [112], such as a cathode ray tube (CRT), Liquid crystal Display (LCD),
Light Emitting Diode (LED) display, Organic LED (OLED) display, etc. for
displaying information to a computer user. An input device [114], including
15 alphanumeric and other keys, touch screen input means, etc. may be coupled to the
bus [102] for communicating information and command selections to the processor
[104]. Another type of user input device may be a cursor controller [116], such as
a mouse, a trackball, or cursor direction keys, for communicating direction
information and command selections to the processor [104], and for controlling
20 cursor movement on the display [112]. This input device typically has two degrees
of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allow
the device to specify positions in a plane.
[0051] The computing device [100] may implement the techniques described
25 herein using customized hard-wired logic, one or more ASICs or FPGAs, firmware,
and/or program logic which in combination with the computing device [100] causes
or programs the computing device [100] to be a special-purpose machine.
According to one implementation, the techniques herein are performed by the
computing device [100] in response to the processor [104] executing one or more
30 sequences of one or more instructions contained in the main memory [106]. Such
15

instructions may be read into the main memory [106] from another storage medium,
such as the storage device [110]. Execution of the sequences of instructions
contained in the main memory [106] causes the processor [104] to perform the
process steps described herein. In alternative implementations of the present
5 disclosure, hard-wired circuitry may be used in place of or in combination with
software instructions.
[0052] The computing device [100] also may include a communication interface
[118] coupled to the bus [102]. The communication interface [118] provides a two-
10 way data communication coupling to a network link [120] that is connected to a
local network [122]. For example, the communication interface [118] may be an
integrated services digital network (ISDN) card, cable modem, satellite modem, or
a modem to provide a data communication connection to a corresponding type of
telephone line. As another example, the communication interface [118] may be a
15 local area network (LAN) card to provide a data communication connection to a
compatible LAN. Wireless links may also be implemented. In any such
implementation, the communication interface [118] sends and receives electrical,
electromagnetic, or optical signals that carry digital data streams representing
various types of information.
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[0053] The computing device [100] can send messages and receive data, including
program code, through the network(s), the network link [120] and the
communication interface [118]. In the Internet example, a server [130] might
transmit a requested code for an application program through the Internet [128], the
25 ISP [126], the local network [122], Host [124], and the communication interface
[118]. The received code may be executed by the processor [104] as it is received, and/or stored in the storage device [110], or other non-volatile storage for later execution.
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[0054] Referring to FIG. 2, an exemplary block diagram of a system [200] for
auditing and recovery of missing Key Performance Indicator (KPI) data within a
Network Management System (NMS), is shown, in accordance with the exemplary
implementations of the present disclosure. The system [200] comprises at least one
5 KPI worker node (WN) [202], at least one Input-output (IO) Cache [204], at least
one KPI auditor [206] and least one database [208]. Also, all of the components/
units of the system [200] are assumed to be connected to each other unless otherwise
indicated below. Also, in FIG. 2 only a few units are shown, however, the system
[200] may comprise multiple such units or the system [200] may comprise any such
10 numbers of said units, as required to implement the features of the present
disclosure. Further, in an implementation, the system [200] may reside in a server or a network entity.
[0055] The system [200] is configured for auditing and recovery of missing Key
15 Performance Indicator (KPI) data within a Network Management System (NMS),
with the help of the interconnection between the components/units of the system [200].
[0056] The system [200] comprises the KPI worker node (WN) [202]. The KPI WN
20 [202] is configured to: monitor KPI data for a plurality of network nodes within the
NMS; identify a set of log entries missing the KPI data; and store a set of requests
for the missed KPI data in the input-output (IO) Cache [204] with a unique identifier
for each of the set of log entries missing the KPI data. In an exemplary aspect, the
KPI worker node [202] may be such as, but not limited to, a processing unit or set
25 of instruction commands. The KPI WN [202] may monitor KPI data or indicators
associated with a plurality of network nodes within the NMS. The network nodes
may be such as, but not limited to, Access and Mobility Management Function
(AMF), Session Management Function (SMF), router, switch, and gateway. The
KPI WN [202] operates or runs repeatedly for a pre-configured time period by the
30 network administrator. In an exemplary aspect, time period may be in minutes or
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hours. In an exemplary aspect, the KPI WN [202] may monitor for a configured
time interval according to the types/categories of network nodes. The
types/categories may be based on service or location of the network nodes. The key
performance indicators (KPIs) are benchmarks that determine optimal network
5 performance. Tracking performance against KPIs enable network managers make
proactive decisions. The KPIs include availability, packet loss, call drop, throughput, latency, error rate and/or such indicators that are obvious to a person skilled in the art.
10 [0057] Further, the KPI WN [202] is configured to identify the set of log entries
missing the KPI data. The missing KPI data may occur due to any reasons such as network dis-connectivity or any software/hardware failure. The KPI WN [202] may store the set of requests for the missed KPI data in the input-output (IO) Cache [204] with a unique identifier for each of the set of log entries missing the KPI data. The
15 unique identifier (ID) may assign to identify set of missing the KPI data in log
entries for enabling proper identification and managing the KPI data. The IO cache [204] may be such as any suitable storage unit, database, or server, which stores the set of requests for the missed KPI data with associated unique ID. The KPI worker node [202] is configured to continuously monitor KPI data across the plurality of
20 network nodes. The KPI worker node [202] is further configured to compare the
expected KPI data against the received data. When a discrepancy is detected, such as a failure to receive the KPI data within a predefined time interval (such as an hour) or the presence of incomplete data, the worker node flags such instances. The process thus involves checking for anomalies or gaps in the KPI data, where the
25 absence of expected log entries or irregular log entries indicate missing KPI data.
[0058] Further, the system [200] comprises the KPI auditor [206]. The KPI auditor
[206] is configured to fetch the set of requests for the set of log entries missing the
KPI data; and transmit the set of requests to the KPI worker node [202]. Also,
30 thereafter the KPI worker node [202] is configured to fetch performance
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management (PM) data corresponding to the set of requests; and then the KPI
auditor [206] is configured to determine, using the KPI worker node [202], the
missed KPI data based on the fetched PM data and updates a database [208] with
the determined KPI data. In an exemplary aspect, the KPI auditor [206] may be
5 such as, but not limited to, a processing unit or instruction set commands. The KPI
auditor [206] may fetch the set of requests for the set of log entries missing the KPI
data. The KPI auditor [206] may run such as, but not limited to, every hour for
checking missed KPI data for configured network node type. The network
administrator may configure KPI auditor [206] run functioning based on pre-
10 defined time period and network node type. The KPI auditor [206] may fetch the
KPI entries from IO cache [204] for the configured node type. In an
implementation, if KPI auditor [206] detects no KPI entries in IO cache [204], it
represents the KPI data is received for all the requests. In another implementation,
if KPI auditor [206] detects request entries, it represents the KPI data for
15 performance management (PM) data is missing. Therefore, the KPI auditor [206]
may not calculate KPI data for those requests. In an implementation, the KPI auditor
[206] may remove a log entry from the IO Cache [204] for which the missing KPI
data is determined.
20 [0059] Further, the KPI auditor node [206] is configured to validate whether any
log entry of the set of log entries missing the KPI data is expired. The KPI Auditor [206] may perform requests validation, such that requests have not already expired (present more than for, for example 6 hrs or can be configured as per requirement) and if expired it removes the entries from IO Cache [204] without taking any
25 actions. The KPI auditor [206] may transmit the set of requests to the KPI worker
node [202] for the missed KPI data entry. In response to this, the KPI worker node [202] may fetch performance management (PM) data corresponding to the set of requests from a storage unit or database [208]. The database [208] may store performance monitoring data for the network nodes. In an exemplary aspect, the
19

system [200] comprises a collector unit (not shown), which collects performance management (PM) data and save into the database [208].
[0060] Further, the KPI auditor [206] may determine using the KPI worker node
5 [202] the missed KPI data based on the fetched PM data. Thereafter, the KPI auditor
[206] may update the database [208] with the determined KPI data. Further, the KPI worker node [202] may also store the determined KPI data in the database [208]. When log entries indicate that the KPI data is missing, the KPI auditor [206] initiates a request to the KPI worker node [202] to fetch relevant performance
10 management (PM) data that can help reconstruct the missing KPIs. For example, if
a network node did not report its latency metrics for a specific period, the KPI worker node [202] may retrieve related PM data such as latency reports from neighbouring nodes or historical latency data. Using the fetched PM data, the KPI auditor [206] analyses and calculates the approximate or exact values of the missing
15 KPI data. Once the KPI auditor [206] determines the accurate KPI data, it updates
this determined information into the database [208], ensuring that the Network Management System (NMS) maintains a complete and accurate set of performance metrics. This process not only helps in filling the gaps caused by data loss but also ensures the continuity and reliability of network performance assessments.
20
[0061] In an exemplary aspect, for all the missed KPI entries, the KPI Auditor [206] may run the KPI worker node [202] to calculate the missed KPI data. Once the PM data for missed KPI entries are received, the KPI auditor [206] may remove those request entries from IO Cache [204] and may upload the KPI data to stream for
25 further processing by the KPI worker node [202]. In an exemplary aspect, the log
entry is expired if the log entry exists in the IO Cache [204] for a predetermined time period. In an exemplary aspect, if the KPI data is again not received for audit requests raised by the KPI auditor [206], the entries may persist in IO Cache [204] till eventually their expiry time is reached. The KPI auditor [206] may remove the
30 expired entry from the IO Cache [204].
20

[0062] In an exemplary aspect, the KPI worker node [202] is configured to store
the determined KPI values in the database [208] or storage unit. The KPI worker
node [202] is further configured to retain the set of log entries missing the KPI data
5 in the IO Cache [204] until expiry of the predetermined time period is reached,
wherein if the KPI data is not received by the KPI worker node [202] during subsequent audit before expiration of the predetermined time period, the set of log entries are automatically removed from the IO Cache [204].
10 [0063] In an exemplary aspect, the KPI Auditor [206] may send audit requests to
the KPI worker node [202] for the missing KPI data entries. The KPI Auditor [206] operates repeatedly after a pre-configured time period. If the KPI Auditor [206] does not find any missing KPI entries, a confirmation is logged, indicating a complete reception of all data sets for that interval. At defined intervals, the KPI
15 Auditor [206] operates to check for missing KPI data for a predetermined node type.
This auditing process ensures comprehensive data collection and identifies any gaps in the collected data. Now, the KPI working node [202] is configured to retrieve the missing KPI data records from the IO Cache [204] upon receiving audit requests from the KPI Auditor [206]. Further, the system [200], is configured to validate
20 longevity of each missing data entry against a pre-set expiry time, determining if
further recovery actions are warranted. For audit requests where KPI data has not been received from the node, the system [200] persists the entries in the IO Cache [204]. These entries remain in the cache [204] until the expiry time is reached, providing opportunities for subsequent retrieval attempts.
25
[0064] Thereafter, the KPI auditor [206] is configured to remove the retrieved missing KPI records from the IO cache [204]. Also, entries that surpass the pre-configured expiry time are discarded from the IO Cache [204]. Upon successful receipt of KPI data during the audit, the corresponding request entries are removed
21

from the IO Cache [204]. The entries that surpass the pre-configured expiry time are discarded from the IO Cache [204].
[0065] The present disclosure also encompasses the KPI auditor [206], is
5 configured to generate feedback upon successful recovery of KPI data, the system
logs the recovery, and if the data remains unrecovered after a set number of attempts, an alert or notification is triggered to system administrators. The generated feedback enables comprehensive analysis and performance assessment.
10 [0066] In an example, a telecommunications company that operates a network
infrastructure consisting of multiple nodes, such as routers and switches. They use a Network Management System (NMS) to monitor and optimize the performance of their network. The company implements the described system for network performance monitoring and auditing. A distributed IO Cache system maintains
15 entries. These entries are associated with unique flow-ids. Every hour, a
Performance Management (PM) Auditor service operates to check for missing PM data for the configured node type, for e.g., routers. During the PM audit, the system tries to retrieve the counter reset request entries from the IO Cache for the routers. If the PM Auditor detects missing PM data for a specific router, it sends a request
20 to a Fault Management (FM) system to raise an alarm. If PM data is not received
for audit requests from a router, the entries for those requests persist in the IO Cache until the predefined expiry time, such as 6 hours, is reached. By implementing this system, the telecommunications company can ensure that the detected network performance data is continuously monitored and audited. If any missing data,
25 alarms are raised to promptly address the issue, the system [200] retries collecting
the missing data and ensures data integrity and reliability for further analysis and optimization of the network performance.
[0067] Referring to FIG. 3, an exemplary method flow diagram [300] for auditing
30 and recovery of missing Key Performance Indicator (KPI) data within a Network
22

Management System (NMS), in accordance with exemplary implementations of the
present disclosure is shown. In an implementation the method [300] is performed
by the system [200]. Further, in an implementation, the system [200] may be present
in a server device to implement the features of the present disclosure. Also, as
5 shown in FIG. 3, the method [300] starts at step [302].
[0068] At step [304], the method [300] as disclosed by the present disclosure comprises monitoring, by a KPI worker node [202], KPI data for a plurality of network nodes within the NMS. The method [300] implemented by the KPI worker
10 node (WN) [202] of the system [200] monitors the KPI data for a plurality of
network nodes within the network management system (NMS). In an exemplary aspect, the KPI worker node [202] may be such as, but not limited to, a processing unit or set of instruction commands. The KPI WN [202] may monitor KPI data or indicators associated with a plurality of network nodes within the NMS. The
15 network nodes may be such as, but not limited to, Access and Mobility Management
Function (AMF), Session Management Function (SMF), router, switch, and gateway. The KPI WN [202] operates or runs repeatedly for a pre-configured time period by the network administrator. In an exemplary aspect, time period may be in minutes or hours. In an exemplary aspect, the KPI WN [202] may monitor for a
20 configured time interval according to the types/categories of network nodes. The
types/categories may be based on service or location of the network nodes. The key performance indicators (KPIs) are benchmarks that determine optimal network performance. Tracking performance against KPIs enable network managers make proactive decisions. The KPIs include availability, throughput, latency, error rate
25 and/or such indicators that are obvious to a person skilled in the art.
[0069] Next, at step [306], the method [300] as disclosed by the present disclosure
comprises identifying, by the KPI worker node [202], a set of log entries missing
the KPI data. Therefore, the method [300] implemented by the KPI WN [202] of
30 the system [200] may identify the set of log entries missing the KPI data. The
23

missing KPI data may occur due to any reasons such as network dis-connectivity
or any software/hardware failure. The KPI worker node [202] is configured to
continuously monitor KPI data across the plurality of network nodes. The KPI
worker node [202] is further configured to compare the expected KPI data against
5 the received data. When a discrepancy is detected, such as a failure to receive the
KPI data within a predefined time interval (such as an hour) or the presence of incomplete data, the worker node flags such instances. The process thus involves checking for anomalies or gaps in the KPI data, where the absence of expected log entries or irregular log entries indicate missing KPI data.
10
[0070] Next, at step [308], the method [300] as disclosed by the present disclosure comprises storing, at the KPI worker node [202], a set of requests for the missed KPI data in an input-output (IO) Cache [204] with a unique identifier for each of the set of log entries missing the KPI data. The unique identifier (ID) may assign to
15 identify set of missing the KPI data in log entries for enabling proper identification
and managing the KPI data. The IO cache [204] may be such as any suitable storage unit, database, or server, which stores the set of requests for the missed KPI data with associated unique ID.
20 [0071] Next, at step [310], the method [300] as disclosed by the present disclosure
comprises fetching, by a KPI auditor [206], the set of requests for the set of log entries missing the KPI data. In an exemplary aspect, the KPI auditor [206] may be such as, but not limited to, a processing unit or instruction set commands. The KPI auditor [206] may fetch the set of requests for the set of log entries missing the KPI
25 data. The KPI auditor [206] may run such as, but not limited to, every hour for
checking missed KPI data for configured network node type. The network administrator may configure KPI auditor [206] run functioning based on pre-defined time period and network node type. The KPI auditor [206] may fetch the KPI entries from IO cache [204] for the configured node type. In an
30 implementation, if KPI auditor [206] detects no KPI entries in IO cache [204], it
24

represents the KPI data is received for all the requests. In another implementation,
if KPI auditor [206] detects request entries, it represents the KPI data for
performance management (PM) data is missing. Therefore, the KPI auditor [206]
may not calculate KPI data for those requests. In an implementation, the KPI auditor
5 [206] may remove a log entry from the IO Cache [204] for which the missing KPI
data is determined. Further, the KPI auditor node [206] is configured to validate
whether any log entry of the set of log entries missing the KPI data is expired. The
KPI Auditor [206] may perform requests validation, such that requests have not
already expired (present more than for example, for 6 hrs or can be configured as
10 per requirement) and if expired it removes the entries from IO Cache [204] without
taking any actions.
[0072] Next, at step [312], the method [300] as disclosed by the present disclosure comprises transmitting, by the KPI auditor [206], the set of requests to the KPI
15 worker node [202]. The method [300] implemented by the KPI auditor [206] of the
system [200] may transmit the set of requests to the KPI worker node [202] for the missed KPI data entry. In an exemplary aspect, for all the missed KPI entries, the KPI Auditor [206] may run the KPI worker node [202] to calculate the missed KPI data.
20
[0073] In an exemplary aspect, the KPI Auditor [206] may send audit requests to the KPI worker node [202] for the missing KPI data entries. The KPI Auditor [206] operates repeatedly after a pre-configured time period. If the KPI Auditor [206] does not find any missing KPI entries, a confirmation is logged, indicating a
25 complete reception of all data sets for that interval. At defined intervals, the KPI
Auditor [206] operates to check for missing KPI data for a predetermined node type. This auditing process ensures comprehensive data collection and identifies any gaps in the collected data.
25

[0074] Next, at step [314], the method [300] as disclosed by the present disclosure
comprises fetching, by KPI worker node [202], performance management (PM)
data corresponding to the set of requests. In response to the receiving the request
from the KPI auditor [206], the KPI worker node [202] may fetch performance
5 management (PM) data corresponding to the set of requests from a storage unit or
database [208]. The database [208] may store performance monitoring data for the network nodes. In an exemplary aspect, the system [200] comprises a collector unit (not shown), which collects performance management (PM) data and save into the database [208].
10
[0075] Once the PM data for missed KPI entries are received, the KPI auditor [206] may remove those request entries from IO Cache [204] and may upload the KPI data to stream for further processing by the KPI worker node [202]. In an exemplary aspect, the log entry is expired if the log entry exists in the IO Cache [204] for a
15 predetermined time period. In an exemplary aspect, if the KPI data is again not
received for audit requests raised by the KPI auditor [206], the entries may persist in IO Cache [204] till eventually their expiry time is reached. The KPI auditor [206] may remove the expired entry from the IO Cache [204].
20 [0076] In an exemplary aspect, the KPI worker node [202] is configured to store
the determined KPI values in the database [208] or storage unit. The KPI worker node [202] is further configured to retain the set of log entries missing the KPI data in the IO Cache [204] until expiry of the predetermined time period is reached, wherein if the KPI data is not received by the KPI worker node [202] during
25 subsequent audit before expiration of the predetermined time period, the set of log
entries are automatically removed from the IO Cache [204].
[0077] In an exemplary aspect, the KPI working node [202] may retrieve the
missing KPI data records from the IO Cache [204] upon receiving audit requests
30 from the KPI Auditor [206]. Further, the system [200], is configured to validate
26

longevity of each missing data entry against a pre-set expiry time, determining if
further recovery actions are warranted. For audit requests where KPI data has not
been received from the node, the system [200] persists the entries in the IO Cache
[204]. These entries remain in the cache [204] until the expiry time is reached,
5 providing opportunities for subsequent retrieval attempts.
[0078] Thereafter, the KPI auditor [206] is configured to remove the retrieved
missing KPI records from the IO cache [204]. Also, entries that surpass the pre-
configured expiry time are discarded from the IO Cache [204]. Upon successful
10 receipt of KPI data during the audit, the corresponding request entries are removed
from the IO Cache [204]. The entries that surpass the pre-configured expiry time are discarded from the IO Cache [204].
[0079] Also, at step [316], the method [300] as disclosed by the present disclosure
15 comprises determining, by the KPI auditor [206] using the KPI worker node [202],
the missed KPI data based on the fetched PM data and updating the NMS with the determined KPI data. Therefore, the KPI auditor [206] may determine using the KPI worker node [202] the missed KPI data based on the fetched PM data. Thereafter, the KPI auditor [206] may update a database [208] with the determined
20 KPI data. Further, the KPI worker node [202] may also store the determined KPI
data in the database [208]. When log entries indicate that the KPI data is missing, the KPI auditor [206] initiates a request to the KPI worker node [202] to fetch relevant performance management (PM) data that can help reconstruct the missing KPIs. For example, if a network node did not report its latency metrics for a specific
25 period, the KPI worker node [202] may retrieve related PM data such as latency
reports from neighbouring nodes or historical latency data. Using the fetched PM data, the KPI auditor [206] analyses and calculates the approximate or exact values of the missing KPI data. Once the KPI auditor [206] determines the accurate KPI data, it updates this determined information into the database [208], ensuring that
30 the Network Management System (NMS) maintains a complete and accurate set of
27

performance metrics. This process not only helps in filling the gaps caused by data loss but also ensures the continuity and reliability of network performance assessments.
5 [0080] The present disclosure also encompasses the KPI auditor [206], is
configured to generate feedback upon successful recovery of KPI data, the system logs the recovery, and if the data remains unrecovered after a set number of attempts, an alert or notification is triggered to system administrators. The generated feedback enables comprehensive analysis and performance assessment. 10
[0081] Thereafter, the method [300] terminates at step [318].
[0082] FIG. 4 illustrates an exemplary block diagram of an exemplary system [400] for auditing and recovery of missing Key Performance Indicator (KPI) data within
15 a Network Management System (NMS), in accordance with exemplary
implementations of the present disclosure. As shown in FIG. 4, the system [400] comprises at least one KPI system [402], at least one KPI Auditor module [406], at least one IO Cache system [404] and at least one database [408]. The KPI system [402] may be configured to fetch performance management (PM) data from the
20 database [408] and also, store calculated one or more KPI values. Next, the KPI
system [402] is configured to create one or more entries for missing KPI data. The KPI Auditor module [406] may audit missing KPI data for one or more configured nodes. Further, the KPI Auditor module [406] may fetch missing one or more records from the IO cache system [404]. Also, configurable interval may be set for
25 the KPI audit task and configurable expiry time for missed KPI entries.
[0083] Furthermore, an exemplary implementation of the present disclosure is shown below via the step-by-step procedure for auditing of missing PM data with the option to raise alarm for the same. 30
28

[0084] In the network management system (NMS), there is a component called the
collector or KPI worker node (WN) [202] that is responsible for collecting
performance data from various network nodes. As part of its operation, the collector
runs a counter reset scheduler. This scheduler is configured to run at specific
5 intervals, which are predetermined and can be customized based on the
requirements of the network. The purpose of the counter reset scheduler is to initiate the resetting of performance counters on the network nodes. Performance counters keep track of various metrics such as bandwidth usage, packet loss, or error rates. By resetting these counters at regular intervals, the collector ensures that accurate
10 and up-to-date performance data is collected. The configured interval determines
how frequently the counter reset scheduler runs. For example, it might be set to run every 24 hours, once a day, or any other time frame that suits the network's monitoring needs. This interval can be adjusted based on factors such as the desired granularity of data collection, the stability of the network, or the specific
15 requirements of the monitoring system.
[0085] In the network management system (NMS), the collector or KPI worker node (WN) [202] keeps track of every single request it sends to the network nodes for performance monitoring purposes. To accomplish this, the collector maintains
20 entries of these requests in a distributed Input/Output (IO) Cache system [204]. The
IO Cache [204] serves as a storage mechanism for the collector to store information related to the requests it sends. Each request is associated with a unique identifier called a flow-id. This flow-id acts as a means to distinguish and identify individual requests within the IO Cache [204]. By keeping entries of each request and
25 associating them with unique flow-ids, the collector or KPI worker WN [202] can
maintain a comprehensive record of its communications with the network nodes. This tracking mechanism enables the collector to precisely correlate the received data with the corresponding request. The use of a distributed IO Cache system [204] ensures that the entries are efficiently stored and accessible across the network. It
29

provides a centralized location where the collector can store and retrieve the request entries as needed.
[0086] In the network management system (NMS), the collector or KPI worker
5 node (WN) [202] sends requests to network nodes to retrieve performance counter
data. These requests are associated with unique flow-ids, which allow for precise tracking and identification of each request. When the collector receives the counter data from a network node, it uses the flow-id associated with that data to determine which request the data corresponds to. This flow-id serves as a key to link the
10 received data with the specific request that initiated its retrieval. Once the collector
successfully matches the flow-id of the received counter data with the corresponding request, it knows that the data has been received for that particular request. At this point, the collector removes the entry associated with that request from the IO Cache [204]. By removing the entry from the IO Cache [204], the
15 collector effectively manages the storage of request entries, keeping it up-to-date
and preventing unnecessary accumulation of data.
[0087] In the network management system (NMS), there is a component called the Performance Management (PM) Auditor service or KPI auditor [206]. This service
20 is designed to run at regular intervals, specifically every hour, to perform an audit
of the collected performance data for the configured node type. The purpose of the PM Auditor service is to check for any missed Performance Monitoring (PM) data. It verifies whether all the expected PM data for the configured node type has been received or if there are any gaps or missing data points. By running the PM Auditor
25 service every hour, the NMS ensures that the performance data collection is
regularly audited. This periodic check allows for the identification of any potential issues or inconsistencies in the collected data. The configured node type refers to the specific type of network nodes, such as routers or switches, for which the PM Auditor service is focused. The NMS can configure the PM Auditor to target
30 specific types of nodes based on their monitoring requirements.
30

[0088] In the network management system (NMS), the Performance Management
(PM) Auditor service or KPI auditor [206] aims to retrieve the counter reset request
entries from the Input/Output (IO) Cache [204] specifically for the configured node
5 type. During the PM audit process, the PM Auditor accesses the IO Cache [204]
and attempts to fetch the counter reset request entries that are associated with the configured node type. These entries represent the requests made by the collector to the network nodes for performance monitoring. By retrieving these entries from the IO Cache [204], the PM Auditor or KPI auditor [206] aims to examine and assess
10 the status of the counter reset requests for the configured node type. This retrieval
process allows the PM Auditor to determine whether all the requests have been successfully processed and corresponding data has been received, or if there are any missing or pending requests. The ability to fetch the counter reset request entries from the IO Cache [204] provides valuable information to the PM Auditor, aiding
15 in the analysis and identification of any gaps or discrepancies in the collected
performance data.
[0089] During the performance audit conducted by the Performance Management (PM) Auditor service in the network management system (NMS), if the PM Auditor
20 or KPI auditor [206] does not find any request entries in the Input/Output (IO)
Cache [204] for the configured node type, it indicates that Performance Monitoring (PM) data has been received for all the requests. The absence of request entries in the IO Cache [204] signifies that the network nodes have successfully provided the PM data corresponding to each of the counter reset requests made by the collector.
25 It suggests that the data collection process for the configured node type is complete,
and there are no missing or pending PM data points. This finding is an important indicator as it assures the NMS and network administrators that the PM data retrieval has been successful for all the requested metrics, providing a comprehensive and accurate overview of the network performance.
30
31

[0090] During the performance audit conducted by the Performance Management
(PM) Auditor service in the network management system (NMS), if the PM Auditor
finds request entries in the Input/Output (IO) Cache [204] for the configured node
type, it indicates that the corresponding network node has not sent the expected
5 Performance Monitoring (PM) data for those specific requests. The presence of
request entries in the IO Cache [204] implies that the collector has made counter reset requests to the node, but the node has not yet provided the requested PM data. This suggests a potential gap or delay in the data collection process for the configured node type. By identifying the request entries in the IO Cache [204], the
10 PM Auditor can determine which specific requests have not been fulfilled by the
node. This information is crucial for the subsequent steps, as it helps the PM Auditor track and address the missing PM data points. Once the PM Auditor identifies the request entries, further actions can be taken, such as raising alarms or initiating a reattempt to retrieve the missing PM data from the node.
15
[0091] During the performance audit conducted by the Performance Management (PM) Auditor service in the network management system (NMS), if the PM Auditor or KPI auditor [206] identifies counter reset requests for which the corresponding Performance Monitoring (PM) data is missing, it takes action to address this issue.
20 In such cases, the PM Auditor sends a request to the Fault Management (FM)
system, including the necessary alarm details. The purpose of this request is to raise an alarm within the FM system, notifying the relevant stakeholders, such as network administrators or operations teams, about the missing PM data. The alarm details included in the request provide essential information about the nature of the missing
25 data, such as the specific counter reset request, the affected node, and any other
relevant contextual information. These details help the FM system generate an accurate and informative alarm to draw attention to the missing PM data. By raising the alarm, the NMS ensures that the appropriate personnel are notified promptly and can take the necessary steps to investigate and resolve the issue. This proactive
32

approach helps maintain the integrity and reliability of the performance monitoring process.
[0092] During the performance audit conducted by the Performance Management
5 (PM) Auditor service in the network management system (NMS), when the PM
Auditor or KPI auditor [206] identifies counter reset requests for which the corresponding Performance Monitoring (PM) data is missing, it takes further action to address the issue. In this step, the PM Auditor adds these counters reset requests to a queue. The queue acts as a storage mechanism for holding the requests that
10 need to be resent to the respective node to retrieve the missing PM data. Once the
requests are added to the queue, the PM Auditor processes them in batches. The batch size is configured to determine the number of requests that are sent together as a group. For example, it could be configured to send 10 requests at a time. The PM Auditor or KPI auditor [206] ensures a systematic and controlled approach to
15 retrieve the missing PM data. This approach helps manage the network traffic and
allows the nodes to process the requests efficiently without overwhelming the system.
[0093] During the performance audit conducted by the Performance Management
20 (PM) Auditor service in the network management system (NMS), when the missing
PM data for the counter reset requests is finally received, the Collector or KPI
worker node (WN) [202], which is responsible for collecting and managing the
performance data, takes action to handle this data. Upon receiving the PM data, the
Collector identifies the corresponding request entries in the Input/Output (IO)
25 Cache [204]. These request entries were previously stored to track the progress and
status of the counter reset requests. The Collector or KPI worker node (WN) [202]
then removes the request entries associated with the received PM data from the IO
Cache [204]. This removal ensures that the IO Cache [204] remains up-to-date, and
only the relevant and pending requests are retained for further processing. After
30 removing the request entries, the Collector or KPI worker node [202] proceeds to
33

upload the received counter data to a stream. This stream serves as a data pipeline
or channel that feeds the performance data for further processing by the
Performance Management (PM) component of the system. By uploading the
counter data to the stream, the Collector enables the PM to access and analyse the
5 data in real-time or as per the defined processing schedule. The PM can perform
various operations on the data, such as generating reports, conducting analysis, or triggering further actions based on the insights gained from the received performance data.
10 [0094] Now, referring to FIG. 5 that illustrates an exemplary process flow diagram
for auditing and recovery of missing Key Performance Indicator (KPI) data within a Network Management System (NMS), in accordance with exemplary implementations of the present disclosure. The following is the step-by-step procedure for auditing of missing KPI data.
15
[0095] Firstly, at step S2, the KPI worker node [202] may run according to node type's configured interval, it may add entries for missed KPI values in distributed IO Cache system with unique flow-ids.
20 [0096] Further, at step S4 and S6, the KPI auditor [206] runs a KPI Auditor service
every hour for checking missed KPI data for configured node type and the KPI Auditor [206] may try to fetch audit KPI entries from IO Cache for the node type. In an event, if no KPI entries are found means KPI data may be received for all the requests. Now, in an event if the KPI Auditor [206] may find request entries that
25 means PM data is missing. Hence, it may not be able to calculate KPI data for those
requests.
[0097] Next, at step S8 and S10, the KPI Auditor [206] may validate if requests have not already expired, (for instance, presently more than 6 hrs or can be
34

configured as per requirement) and if expired it may remove the entries from IO Cache without taking any actions.
[0098] Further at step S12 and S14, for the all the missed KPI entries, KPI Auditor
5 [206] runs KPI worker [202] to calculate missed KPI data. Once PM data for missed
KPI entries are received, at least one of the KPI worker [202] and the KPI auditor
[206] may remove those request entries from IO Cache and upload KPI data to
stream for further processing by the KPI worker [202]. Also, if KPI data is again
not received for audit requests, the entries will persist in IO Cache till eventually
10 their expiry time is reached.
[0099] Thereafter, the process flow [500] terminates at step S16.
[0100] Further, referring to FIG. 6 that illustrates an exemplary diagram depicting
15 a user equipment [602] connected to the system [200] for auditing and recovery of
missing Key Performance Indicator (KPI) data within a Network Management System (NMS), in accordance with exemplary implementations of the present disclosure. The present disclosure discloses that the user equipment (UE) [602] comprises a transceiver unit [604], configured to: transmit, a request to a system
20 [200] for receiving a missed Key Performance Indicator (KPI) data; and receive,
the missed KPI data from the system [200] in response to the request. The missed KPI data is generated by the system [200] based on: monitoring, by a KPI worker node [202] of the system, KPI data for a plurality of network nodes within a Network Management System (NMS); identifying, by the KPI worker node [202],
25 a set of log entries missing the KPI data; storing, at the KPI worker node [202], a
set of requests for the missed KPI data in an input-output (IO) Cache [204] with a unique identifier for each of the set of log entries missing the KPI data; fetching, by a KPI auditor [206] of the system, the set of requests for the set of log entries missing the KPI data; transmitting, by the KPI auditor [206], the set of requests to
30 the KPI worker node [202]; fetching, by KPI worker node [202], performance
35

management (PM) data corresponding to the set of requests; and determining, by the KPI auditor [206] using the KPI worker node [202], the missed KPI data based on the fetched PM data and updating the NMS with the determined KPI data.
[0101] The present disclosure further discloses a non-transitory computer readable storage medium storing instructions for auditing and recovery of missing Key Performance Indicator (KPI) data within a Network Management System (NMS), the instructions include executable code which, when executed by one or more units of a system, causes: monitoring, by a KPI worker node [202] of the system, KPI data for a plurality of network nodes within the NMS; identifying, by the KPI worker node [202], a set of log entries missing the KPI data; storing, at the KPI worker node [202], a set of requests for the missed KPI data in an input-output (IO) Cache [204] with a unique identifier for each of the set of log entries missing the KPI data; fetching, by a KPI auditor [206] of the system, the set of requests for the set of log entries missing the KPI data; transmitting, by the KPI auditor [206], the set of requests to the KPI worker node [202]; fetching, by KPI worker node [202], performance management (PM) data corresponding to the set of requests; and determining, by the KPI auditor [206] using the KPI worker node [202], the missed KPI data based on the fetched PM data and updating the NMS with the determined KPI data.
[0102] Thereby, the present disclosure offers a technically advanced solution than the existing/ current solutions, especially by recovering any lost KPI data that was caused by a network problem, hardware issue, network element failure, database failure, or NMS error. Next, by utilizing the distribute IO cache to process each KPI data missed for an interval. Also, the auditor makes sure that all counter KPI data is obtained.
[0103] It would be appreciated by the person skilled in the art that the process of network performance monitoring and auditing, highlighting the mechanisms for

tracking, validation, alarm generation, queuing, and data retrieval ensures accurate and reliable performance data collection in the NMS.
[0104] Further, in accordance with the present disclosure, it is to be acknowledged that the functionality described for the various components/units can be implemented interchangeably. While specific embodiments may disclose a particular functionality of these units for clarity, it is recognized that various configurations and combinations thereof are within the scope of the disclosure. The functionality of specific units, as disclosed in the disclosure, should not be construed as limiting the scope of the present disclosure. Consequently, alternative arrangements and substitutions of units, provided they achieve the intended functionality described herein, are considered to be encompassed within the scope of the present disclosure.
[0105] While considerable emphasis has been placed herein on the
disclosed embodiments, it will be appreciated that many embodiments can be made and that many changes can be made to the embodiments without departing from the principles of the present disclosure. These and other changes in the embodiments of the present disclosure will be apparent to those skilled in the art, whereby it is to be understood that the foregoing descriptive matter to be implemented is illustrative and non-limiting.

I/We Claim:
1. A method for auditing and recovery of missing Key Performance Indicator
(KPI) data within a Network Management System (NMS), the method
comprising:
monitoring, by a KPI worker node [202], KPI data for a plurality of network nodes within the NMS;
identifying, by the KPI worker node [202], a set of log entries missing the KPI data;
storing, at the KPI worker node [202], a set of requests for the missed KPI data in an input-output (IO) Cache [204] with a unique identifier for each of the set of log entries missing the KPI data;
fetching, by a KPI auditor [206], the set of requests for the set of log entries missing the KPI data;
transmitting, by the KPI auditor [206], the set of requests to the KPI worker node [202];
fetching, by KPI worker node [202], performance management (PM) data corresponding to the set of requests; and
determining, by the KPI auditor [206] using the KPI worker node [202], the missed KPI data based on the fetched PM data and updating a database [208] with the determined KPI data.
2. The method as claimed in claim 1, wherein the method comprises storing, by the KPI worker node [202], the determined KPI data in the database [208].
3. The method as claimed in claim 1, wherein the method comprises removing, by the KPI auditor [206], a log entry from the IO Cache [204] for which the missing KPI data is determined.

4. The method as claimed in claim 1, wherein the method comprises validating, by the KPI auditor [206], whether any log entry of the set of log entries missing the KPI data is expired.
5. The method as claimed in claim 4, wherein the log entry is expired if the log entry exists in the IO Cache [204] for a predetermined time period.
6. The method as claimed in claim 4, wherein the method comprises removing, by the KPI auditor [206], an expired log entry from the IO Cache [204].
7. The method as claimed in claim 5, further comprising retaining the set of log entries missing the KPI data in the IO Cache [204] until expiry of the predetermined time period is reached, wherein if the KPI data is not received by the KPI worker node [202] during subsequent audit before expiration of the predetermined time period, the set of log entries are automatically removed from the IO Cache [204].
8. A system for auditing and recovery of missing Key Performance Indicator
(KPI) data within a Network Management System (NMS), the system
comprises:
a KPI worker node [202] configured to:
monitor KPI data for a plurality of network nodes within the NMS;
identify a set of log entries missing the KPI data;
store a set of requests for the missed KPI data in an input-output (IO) Cache [204] with a unique identifier for each of the set of log entries missing the KPI data; and a KPI auditor [206] configured to:
fetch the set of requests for the set of log entries missing the KPI data;

transmit the set of requests to the KPI worker node [202], wherein:
the KPI worker node [202] is configured to fetch performance management (PM) data corresponding to the set of requests; and
the KPI auditor [206] is configured to determine, using the KPI worker node [202], the missed KPI data based on the fetched PM data and updating a database [208] with the determined KPI data.
9. The system, as claimed in claim 8, wherein the KPI worker node [202] is further configured to store the determined KPI data in the database [208].
10. The system as claimed in claim 8, wherein the KPI auditor [206] is further configured to remove a log entry from the IO Cache [204] for which the missing KPI data is determined.
11. The system as claimed in claim 8, wherein the KPI auditor [206] is further configured to validate whether any log entry of the set of log entries missing the KPI data is expired.
12. The system as claimed in claim 11, wherein the log entry is expired if the log entry exists in the IO Cache [204] for a predetermined time period.
13. The system as claimed in claim 11, wherein the KPI auditor [206] is further configured to remove an expired log entry from the IO Cache [204].
14. The system as claimed in claim 12, wherein the KPI worker node [202] is further configured to retain the set of log entries missing the KPI data in the IO Cache [204] until expiry of the predetermined time period is reached, wherein if the KPI data is not received by the KPI worker node [202] during subsequent audit before expiration of the predetermined time period, the set of log entries are automatically removed from the IO Cache [204].

15. A user equipment (UE) [602] comprising: - a transceiver unit [604], configured to:
transmit, a request to a system [200] for receiving a missed Key
Performance Indicator (KPI) data, and
receive, the missed KPI data from the system [200] in response to
the request, wherein the missed KPI data is generated by the system
[200] based on:
monitoring, by a KPI worker node [202] of the system, KPI
data for a plurality of network nodes within a Network
Management System (NMS),
identifying, by the KPI worker node [202], a set of log entries
missing the KPI data,
storing, at the KPI worker node [202], a set of requests for
the missed KPI data in an input-output (IO) Cache [204] with
a unique identifier for each of the set of log entries missing
the KPI data,
fetching, by a KPI auditor [206] of the system, the set of
requests for the set of log entries missing the KPI data,
transmitting, by the KPI auditor [206], the set of requests to
the KPI worker node [202],
fetching, by KPI worker node [202], performance
management (PM) data corresponding to the set of requests,
and
determining, by the KPI auditor [206] using the KPI worker
node [202], the missed KPI data based on the fetched PM
data and updating a database [208] with the determined KPI
data.