FORM 2
THE PATENTS ACT, 1970 (39 OF 1970) & THE PATENT RULES, 2003
COMPLETE SPECIFICATION
(See section 10 and rule 13)
“METHOD AND SYSTEM FOR PARSING COUNTER DATA FROM NETWORK NODES IN A COMMUNICATION
NETWORK”
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.

METHOD AND SYSTEM FOR PARSING COUNTER DATA FROM NETWORK NODES IN A COMMUNICATION NETWORK
FIELD OF INVENTION
[0001] Implementations of the present disclosure generally relate to parsing of counters. More particularly, implementations of the present disclosure relate to methods and systems for parsing a counter data from a plurality of network nodes in a communication network.
BACKGROUND
[0002] The following description of the 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 is used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of the prior art.
[0003] In the 5G wireless communication system, multiple network elements which are termed as ‘gNB’ or ‘gNodeB’, cater for providing 5G cellular communication services between multiple User Equipment (UEs). An Element Management System (EMS) collects all the Network statistics periodically, alert messages and configuration parameters from various network elements. Depending upon the hardware and software capabilities, the number of network elements connected to EMS varies and hence multiple Element Management Systems will be installed for serving the network having millions of nodes.
[0004] Network elements periodically send the performance counter data to the Element Management System (EMS) and EMS combines all the data of the network nodes category wise and generates a tar file which is fetched by Operation Support

System (OSS) for further processing and generating meaningful Key performance metrics.
[0005] Therefore, in any Telecom network deployment, each of the (Original Equipment Manufacturers) OEMs have an Element Management System (EMS) which periodically collects Performance Management statistics in the form of raw counters from all the Network Nodes. These raw counters are then grouped together based on the procedures or events which they follow for establishment of voice or data session known as counter categories. Performance Counters are grouped category wise for all the nodes connected to the Element Management System (EMS) and individual PM statistics files are created for each of the category and all category files are grouped to make a tar file or zip file at EMS end.
[0006] Different Original Equipment Manufacturers (OEMs) adopt different file format for providing performance statistics as it is not standardized by 3GPP. Traditional methods assume that each counter provides only one value per time interval. This assumption works fine when dealing with OEMs that follow this pattern. However, some OEMs provide multiple values for a single counter within a given time interval, such as 15 minutes. These conventional methods are not designed to handle multiple values for one counter, which can lead to erroneous data interpretation. When a counter sends multiple values within a single time interval, parsing becomes a more complicated task. Each of these values needs to be correctly interpreted and processed to provide meaningful performance statistics. Traditional methods may not have the ability to break down and understand these multiple values correctly, causing a potential misrepresentation of the actual performance data. A common issue is the inadequate segregation of various performance metrics. For instance, if multiple values related to different services like voice and data are bundled and sent in the same counter, conventional systems may struggle to correctly attribute these values to their respective services. This can affect the accuracy of the performance metrics and hinder optimization efforts. If new Quality of Service (QoS) indicators are introduced in the future, traditional

methods may not be able to accommodate these changes without significant development efforts. This lack of flexibility and scalability can slow down the process of integrating these new metrics into the performance analysis.
[0007] Therefore, in the light of the foregoing discussion, there exists a need to overcome the aforementioned drawbacks and to provide a method and a system for parsing counters with multiple values in single Report Output Period (ROP), which the present disclosure aims to address.
OBJECTS OF THE DISCLOSURE
[0008] Some of the objects of the present disclosure, which at least one implementation disclosed herein satisfies are listed herein below.
[0009] It is an object of the present disclosure to provide a system and a method for parsing counters with multiple values in single Report Output Period (ROP).
[0010] It is another object of the present disclosure to provide a system and a method for parsing counters with multiple values in single ROP that is capable of processing and interpreting multiple values from a single counter within a given time interval. The system aims to accommodate different OEM methodologies and their unique ways of providing performance statistics.
[0011] It is another object of the present disclosure to provide a system and a method for parsing counters with multiple values in single Report Output Period (ROP) that can handle the complexity of parsing multiple counter values effectively. The system aims to parse these multiple values correctly, regardless of whether they are presented in a compressed or non-compressed types of counters.

[0012] It is another object of the present disclosure to provide a means of representing multiple performance metrics that come from the same counter but relate to different services.
[0013] It is another object of the present disclosure to provide a system and a method for parsing counters with multiple values in single ROP that can adapt to future updates, specifically in accommodating new quality of service indicators. This design aims to make the process of integrating new metrics into performance analysis seamless and efficient, minimizing the need for substantial development efforts.
[0014] It is yet another object of the present disclosure to provide a system and a method for parsing counters with multiple values in single ROP that not only interprets data accurately but also translates it into meaningful insights that are relevant to business decisions. The system intends to parse the values and assign them to individual counters in a way that the interpreted data can support strategic decisions and optimize network performance.
SUMMARY OF THE DISCLOSURE
[0015] 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.
[0016] A first aspect of the present disclosure is related to a method for parsing a set of counter data from a plurality of network nodes in a communication network, said method comprising: receiving, by a receiving unit, the set of counter data periodically from the plurality of network nodes, wherein each counter data of the set of counter data comprises a plurality of values within a single Report Output Period (ROP). Further, the method comprising parsing, by the parsing unit, the

received counter data based on a parsing procedure for processing the plurality of values in at least one format. Furthermore, the method comprises segregating, by an analysis unit, the plurality of parsed values into one or more sub-counters based on a set of service-related parameters; and displaying, by a display unit, a User Interface (UI) for defining a set of Key Performance Indicators (KPIs) utilizing the one or more sub-counters.
[0017] Another aspect of the present disclosure relates to a system for parsing a set of counter data from a plurality of network nodes in a communication network, the system comprises a receiving unit, a parsing unit, an analysis unit, and a display unit connected to each other. The receiving unit is configured to receive the set of counter data periodically from the plurality of network nodes, wherein each counter data of the set of counter data comprises a plurality of values within a single Report Output Period (ROP). The parsing unit is configured to parse the received set of counter data based on a parsing procedure for processing the plurality of values in at least one format. Further, the analysis unit is configured to segregate the parsed plurality of values into one or more sub-counters based on a set of service-related parameters. The display unit is configured to display a user interface (UI) for defining Key Performance Indicators (KPIs) utilizing the one or more sub-counters.
[0018] As per another aspect of the present disclosure, the counter data comprises one or more non-zero values of each of the set of service-related parameters.
[0019] As per another aspect of the present disclosure, the at least one format comprises at least one of a compressed format and a non-compressed format.
[0020] As per another aspect of the present disclosure, the at least one format is identified based on a compression attribute, wherein the compression attribute comprises one of a true flag and a false flag, wherein in an event the compression attribute is a true flag, the at least one format is identified as the compressed format,

and in an event the compression attribute is a false flag, the at least one format is identified as the non-compressed format.
[0021] As per another aspect of the present disclosure, the segregation of the plurality of parsed values into the one or more sub-counters is further based on one or more size attributes of the received set of counter data.
[0022] As per another aspect of the present disclosure, the plurality of network nodes comprises one or more components selected from a group consisting of a base station, a router, a switch, and any other hardware that assists in managing network traffic in the communication network.
[0023] As per another aspect of the present disclosure, the set of counter data corresponds to one or more performance metrics reflecting aspects comprising a latency, a throughput, a dropped call, and a signal strength.
[0024] As per another aspect of the present disclosure, the set of counter data is received from a plurality of original equipment manufacturers (OEMs).
[0025] Further, an aspect of the present disclosure relates to a non-transitory computer readable storage medium storing instruction for parsing a set of counter data from a plurality of network nodes in a communication network. The instructions include executable code which, when executed by a one or more units of a system, causes: a receiving unit of the system to receive the set of counter data periodically from the plurality of network nodes, wherein each counter data of the set of counter data comprises a plurality of values within a single Report Output Period (ROP). Further, the instructions include executable code, which when executed causes a parsing unit of the system to parse the received counter data based on a parsing procedure for processing the plurality of values in at least one format. Further, the instructions include executable code, which when executed causes an analysis unit of the system to segregate the plurality of parsed values into one or

more sub-counters based on a set of service-related parameters. Further, the instructions include executable code, which when executed causes a display unit of the system to display a User Interface (UI) for defining a set of Key Performance Indicators (KPIs) utilizing the one or more sub-counters. 5
BRIEF DESCRIPTION OF THE DRAWINGS
[0026] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary implementations of the disclosed
10 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. Also, the implementations shown in the figures are not to be construed as limiting the disclosure, but the possible variants of the method and
15 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 to implement such components.
20 [0027] FIG. 1 illustrates an exemplary block diagram representation of 5th
generation core (5GC) network architecture.
[0028] FIG.1A illustrates an exemplary block diagram of a system [100A] for
parsing a set of counter data from a plurality of network nodes in a communication
25 network, in accordance with exemplary implementations of the present disclosure.
[0029] FIG.2 illustrates an exemplary method flow diagram indicating the process
[200] for parsing a set of counter data from a plurality of network nodes in a
communication network, in accordance with exemplary implementations of the
30 present disclosure.
8

[0030] FIG. 3 illustrates an exemplary diagram depicting the representation at a user interface for utilising the set of counter data with the plurality of values in the key performance indicators (KPI), in accordance with exemplary implementations of the present disclosure. 5
[0031] FIG. 4 illustrates an exemplary diagram depicting a raw counter data file format of the set of counter data, in accordance with exemplary implementations of the present disclosure.
10 [0032] FIG. 5 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.
[0033] The foregoing shall be more apparent from the following more detailed
15 description of the disclosure.
DETAILED DESCRIPTION
[0034] In the following description, for the purposes of explanation, various
20 specific details are set forth in order to provide a thorough understanding of
implementations of the present disclosure. It will be apparent, however, that
implementations of the present disclosure may be practiced without these specific
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
25 address any of the problems discussed above or might address only some of the
problems discussed above.
[0035] The ensuing description provides exemplary implementations only, and is
not intended to limit the scope, applicability, or configuration of the disclosure.
30 Rather, the ensuing description of the exemplary implementations will provide
those skilled in the art with an enabling description for implementing an exemplary
9

implementation. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the disclosure as set forth.
5 [0036] Specific details are given in the following description to provide a thorough
understanding of the implementations. However, it will be understood by one of
ordinary skill in the art that the implementations 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
10 implementations in unnecessary detail.
[0037] Also, it is noted that individual implementations 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
15 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 is terminated when its operations are completed but could have additional steps not included in a figure.
20 [0038] The word “exemplary” and/or “demonstrative” is used herein to mean
serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or
25 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 in a manner similar to the term “comprising” as an open transition word without precluding any
30 additional or other elements.
10

[0039] 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
5 of microprocessors, one or more microprocessors in association with a DSP core, a
controller, a microcontroller, Application Specific Integrated Circuits, Field
Programmable Gate Array circuits, any other type of integrated circuits, etc. The
processor may perform signal coding data processing, input/output processing,
and/or any other functionality that enables the working of the system according to
10 the present disclosure. More specifically, the processor or processing unit is a
hardware processor.
[0040] 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”,
15 “a wireless communication device”, “a mobile communication device”, “a
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,
20 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 at least one of a receiver unit, an analysis unit, a storage unit, a display unit, a parsing unit and any other such unit(s) which are required to implement the features of the present
25 disclosure.
[0041] 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
30 medium includes read-only memory (“ROM”), random access memory (“RAM”),
magnetic disk storage media, optical storage media, flash memory devices or other
11

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.
5 [0042] As disclosed in the background section, different Original Equipment
Manufacturers (OEMs) often have their unique methods for providing performance statistics. This can vary significantly from one manufacturer to another, leading to discrepancies in data interpretation and processing. Traditional methods assume that each counter considered for providing performance statistics provides only one
10 value per time interval. This assumption works fine when dealing with OEMs that
follow this pattern. However, some OEMs provide multiple values for a single counter within a given time interval, such as 15 minutes. These conventional methods aren't designed to handle multiple values from one counter, which can lead to inaccuracies in data interpretation and further processing. When a counter sends
15 multiple values within a single time interval, parsing becomes a more complicated
task. Each of these values needs to be correctly interpreted and processed to provide meaningful performance statistics. Traditional methods may not have the ability to break down and understand these multiple values correctly, causing a potential misrepresentation of the actual performance data. A common issue is the inadequate
20 segregation of various performance metrics. For instance, if multiple values related
to different services like voice and data are bundled and sent in the same counter, conventional systems may not be able to handle correctly and assign properly these values to their respective services. This can affect the accuracy of the performance metrics and hinder optimization efforts. If new Quality of Service (QoS) indicators
25 are introduced in the future, traditional methods may not be able to accommodate
these changes without significant development effort. This lack of flexibility and scalability can slow down the process of integrating these new metrics into the performance analysis.
30 [0043] Thus, there exists an imperative need in the art to provide a method and a
system for parsing counters with multiple values in single Report Output Period
12

(ROP), which the present disclosure aims to address. The proposed solution
addresses these problems by offering a flexible and adaptive approach to handle
performance statistics, specifically capable of parsing counters with multiple values
and effectively managing both compressed and non-compressed modes. By doing
5 so, it enhances the efficiency and accuracy of performance data interpretation and
can easily adapt to future updates.
[0044] Implementations of the present disclosure generally relate to parsing counters. Particularly, the present disclosure provides a technical solution for
10 parsing counters with multiple values in single reporting period (ROP). The
solution encompasses receiving counter data sent periodically from network nodes, wherein the counter data includes multiple values sent within a single time interval. The received counter data is then parsed based on a parsing procedure, which can handle multiple values for a single counter in both compressed and non-compressed
15 formats. Further, the solution encompasses segregating the parsed values into
corresponding sub-counters based on their specific service-related parameters, thus enabling accurate representation of individual performance metrics. Also, a user interface is then provided for defining Key Performance Indicators (KPIs) using these sub-counters, thereby offering relevant insights derived from the parsed
20 counter data. The present disclosure also provides an adaptive solution to
accommodate new quality of service indicators by utilizing the flexible parsing procedure. Thus, the technical solution as disclosed in the present disclosure ensures the method for parsing remains relevant and effective in response to future updates in network node performance statistics.
25
[0045] Hereinafter, exemplary implementations of the present disclosure will be described with reference to the accompanying drawings.
[0046] FIG. 1 illustrates an exemplary block diagram representation of 5th
30 generation core (5GC) network architecture, in accordance with exemplary
implementation of the present disclosure. As shown in FIG. 1, the 5GC network
13

architecture [100] includes a user equipment (UE) [102], a radio access network
(RAN) [104], an access and mobility management function (AMF) [106], a Session
Management Function (SMF) [108], a Service Communication Proxy (SCP) [110],
an Authentication Server Function (AUSF) [112], a Network Slice Specific
5 Authentication and Authorization Function (NSSAAF) [114], a Network Slice
Selection Function (NSSF) [116], a Network Exposure Function (NEF) [118], a
Network Repository Function (NRF) [120], a Policy Control Function (PCF) [122],
a Unified Data Management (UDM) [124], an application function (AF) [126], a
User Plane Function (UPF) [128], a data network (DN) [130], wherein all the
10 components are assumed to be connected to each other in a manner as obvious to
the person skilled in the art for implementing features of the present disclosure.
[0047] The User Equipment (UE) [102] interfaces with the network via the Radio Access Network (RAN) [104]; the Access and Mobility Management Function
15 (AMF) [106] manages connectivity and mobility, while the Session Management
Function (SMF) [108] administers session control; the service communication proxy (SCP) [110] routes and manages communication between network services, enhancing efficiency and security, and the Authentication Server Function (AUSF) [112] handles user authentication; the Network Slice Specific Authentication and
20 Authorization Function (NSSAAF) [114] for integrating the 5G core network with
existing 4G LTE networks i.e., to enable Non-Standalone (NSA) 5G deployments, the Network Slice Selection Function (NSSF) [116], Network Exposure Function (NEF) [118], and Network Repository Function (NRF) [120] enable network customization, secure interfacing with external applications, and maintain network
25 function registries respectively; the Policy Control Function (PCF) [122] develops
operational policies, and the Unified Data Management (UDM) [124] manages subscriber data; the Application Function (AF) [126] enables application interaction, the User Plane Function (UPF) [128] processes and forwards user data, and the Data Network (DN) [130] connects to external internet resources;
30 collectively, these components are designed to enhance mobile broadband, ensure
14

low-latency communication, and support massive machine-type communication, solidifying the 5GC as the infrastructure for next-generation mobile networks.
[0048] Radio Access Network (RAN) [104] is the part of a mobile
5 telecommunications system that connects user equipment (UE) [102] to the core
network (CN) and provides access to different types of networks (e.g., 5G network). It consists of radio base stations and the radio access technologies that enable wireless communication.
10 [0049] Access and Mobility Management Function (AMF) [106] is a 5G core
network function responsible for managing access and mobility aspects, such as UE registration, connection, and reachability. It also handles mobility management procedures like handovers and paging.
15 [0050] Session Management Function (SMF) [108] is a 5G core network function
responsible for managing session-related aspects, such as establishing, modifying, and releasing sessions. It coordinates with the User Plane Function (UPF) for data forwarding and handles IP address allocation and QoS enforcement.
20 [0051] Service Communication Proxy (SCP) [110] is a network function in the
5G core network that facilitates communication between other network functions by providing a secure and efficient messaging service. It acts as a mediator for service-based interfaces.
25 [0052] Authentication Server Function (AUSF) [112] is a network function in
the 5G core responsible for authenticating UEs during registration and providing security services. It generates and verifies authentication vectors and tokens.
[0053] Network Slice Specific Authentication and Authorization Function
30 (NSSAAF) [114] is a network function that provides authentication and
15

authorization services specific to network slices. It ensures that UEs can access only the slices for which they are authorized.
[0054] Network Slice Selection Function (NSSF) [116] is a network function
5 responsible for selecting the appropriate network slice for a UE based on factors
such as subscription, requested services, and network policies.
[0055] Network Exposure Function (NEF) [118] is a network function that
exposes capabilities and services of the 5G network to external applications,
10 enabling integration with third-party services and applications.
[0056] Network Repository Function (NRF) [120] is a network function that acts as a central repository for information about available network functions and services. It facilitates the discovery and dynamic registration of network functions. 15
[0057] Policy Control Function (PCF) [122] is a network function responsible for policy control decisions, such as QoS, charging, and access control, based on subscriber information and network policies.
20 [0058] Unified Data Management (UDM) [124] is a network function that
centralizes the management of subscriber data, including authentication, authorization, and subscription information.
[0059] Application Function (AF) [126] is a network function that represents
25 external applications interfacing with the 5G core network to access network
capabilities and services.
[0060] User Plane Function (UPF) [128] is a network function responsible for
handling user data traffic, including packet routing, forwarding, and QoS
30 enforcement.
16

[0061] Data Network (DN) [130] refers to a network that provides data services to user equipment (UE) in a telecommunications system. The data services may include but are not limited to Internet services, private data network related services.
5 [0062] Referring to FIG. 1A, an exemplary block diagram of a system [100A] for
parsing a set of counter data from one or more network nodes in a communication network is shown, in accordance with the exemplary implementations of the present disclosure. The system [100A] comprises a receiving unit [102A], a parsing unit [104A], an analysis unit [106A], and a display unit [108A] connected to each other.
10 The receiving unit [102A] may be a unit capable of receiving data. The parsing unit
[104A] may be a unit capable of parsing data, and may also be a processor capable of processing data for parsing. The analysis unit [106A] may be a unit capable of performing analysis of the data, and may also be a processor capable of processing data and performing analysis based on processing of the data. The display unit
15 [108A] may be a unit capable of displaying data visually. Also, all of the
components/ units of the system [100A] are assumed to be connected to each other unless otherwise indicated below.
[0063] Also, in FIG. 1A only a few units are shown, however, the system [100A]
20 may comprise multiple such units or the system [100A] may comprise any such
numbers of said units, as required to implement the features of the present
disclosure. Further, in an implementation, the system [100A] may be present in a
user device that is in communication with the communication network to implement
the features of the present disclosure. The system [100A] may be a part of the user
25 device / or may be independent of but in communication with the user device. In
another implementation, the system [100A] may reside in a server or at the
communication network end. In yet another implementation, the system [100A]
may reside partly in the at the communication network end and partly in the user
device.
30
17

[0064] The system [100A] is configured for parsing a set of counter data from a
plurality of network nodes in a communication network, with the help of the
interconnection between the components/units of the system [100A]. The plurality
of network nodes may comprise two or more components which may be such as a
5 base station, a router, a switch, and any other network unit that assists in managing
network traffic in the communication network. The network unit assisting in management of network traffic may be, for example, a user plane function (UPF), an access and mobility management function (AMF), a session management function (SMF), etc.
10
[0065] Particularly, for parsing the set of counter data from the plurality of network nodes in the communication network, initially the receiving unit [102A] of the system [100A] is configured to receive the set of counter data periodically from the plurality of network nodes, wherein each counter data of the set of counter data
15 comprises a plurality of values within a single Report Output Period (ROP). The set
of counter data may comprise one or more non-zero values of each of a set of service-related parameters. The set of counter data is received in the form of a raw counter data file. The set of counter data and the plurality of values may also correspond to one or more performance metrics which can reflect certain aspects of
20 network performance. The one or more performance metrics may be at least one
from among a latency, a throughput, a dropped call, and a signal strength. The set of counter data may be received from a plurality of Original Equipment Manufacturers (OEMs) in one implementation of the present disclosure. The single ROP may be referred to as a period timeframe for data or information collection,
25 and presentation in a report. As an example, the single ROP may be 15 minutes.
The period may be dynamic and is configurable based on change in needs and purposes. The plurality of values of the counter data within the single ROP is the data present in the number of values present in each counter data.
30 [0066] The set of service-related parameters may comprise an Allocation and
Retention Priority (ARP), Reflective QoS Attribute (RQA), Notification Control,
18

Flow Bit Rates, Aggregate Bit Rates, Default values, Maximum Packet Loss Rate.
Further, the service-related parameters may be associated with services such as
voice- related services, video- related services, gaming services, non-conservational
video streaming services, mission critical push to talk voice services, non-mission
5 critical push to talk voice services, etc. In an exemplary implementation, service-
related parameters may comprise services like voice and data separately. Like in
case of 5G, voice related statistics are captured under 5QI1 (5G Quality of Service
Indicator-1) and Data related statistics are captured under 5QI9 (5G Quality of
Service Indicator-9) even though values for both is available in same counter from
10 the an OEM EMS raw data.
[0067] In a 5G/6G network, the devices or stations that perform the functions necessary for network communication are the plurality of network nodes. Now, to monitor and evaluate the performance of these network nodes, they are configured
15 to send performance statistics or performance metrics, also known as counters (or
the set of counter data, as may be used interchangeably), to a centralized system or an Element Management System (EMS), which provides a powerful user interface for centralized management of network nodes. This set of counter data is sent at regular intervals, often every 15 minutes. This set of counter data carries various
20 types of information regarding network performance such as latency, throughput,
dropped calls, signal strength, etc. In certain cases, instead of sending a single value representing a single performance metric (PM), a counter data from the set of counter data may send multiple values within a single time interval or ROP. This could be because a single performance metric could have different values at
25 different instances within that 15-minute interval, and all these values are relevant
for a comprehensive understanding of that performance metric.
[0068] Further, in an implementation, the present disclosure further provides that
along with the set of counter data, a compression attribute may also be received by
30 the receiving unit [102A]. The compression attribute indicates whether the set of
counter data is compressed or non-compressed. This compression attribute can be
19

then used for identification of the at least one format. The compression attribute
may comprise a true flag or a false flag. The true flag may indicate that the set of
counter data is in a compressed format, i.e., in an event the compression attribute is
a true flag, the at least one format is identified as the compressed format. The false
5 flag may indicate that the set of counter data is in a non-compressed format, i.e., in
an event the compression attribute is a false flag, the at least one format is identified as the non-compressed format.
[0069] Further, the parsing unit [104A] is configured to parse the received raw
10 counter data file based on a parsing procedure for processing the plurality of values
in at least one format. The at least one format may be a compressed format and/or a non-compressed format. For identification of the at least one format the compression attribute may be analysed based on a true flag or a false flag.
15 [0070] The received counter data is parsed based on a specific parsing procedure.
This parsing procedure is capable of handling multiple values for a single counter in different modes, be it compressed or non-compressed. This is a crucial step as the complexity of the data increases with the presence of multiple values in a single counter. The parsing procedure comprises identifying whether the incoming data is
20 in a compressed or non-compressed format based on the compression attribute, and
appropriately parse it based on the identified format.
[0071] Parsing refers to the process of analysing a string of symbols or data, according to certain rules. The parsing procedure may be predefined, meaning that
25 it has been established in advance how to analyse the incoming counter data. In
essence, parsing the received counter data involves examining and interpreting the multiple values received from each counter, irrespective of their format, so they can be correctly processed and utilized for performance monitoring. Furthermore, the parsing procedure may be dynamically configured/updated based on change in the
30 set of counter data. The parsing procedure is capable of handling multiple values
for a single counter. As mentioned before, a single counter can send multiple data
20

values within one Report Output Period (ROP). The parsing procedure handles the
set of counter data in a flexible manner. The parsing procedure should be able to
cater to the services which may be either activated or not activated. In the parsing
procedure the values that are zero indicate that the service is not activated currently,
5 but when these services are activated or provisioned, then the counter would
indicate the performance of such services. There may be additions or subtractions
in the number of services provided by a particular network node, and the set of
counter data may change accordingly based on the number of services provided.
However, the present disclosure is able to provide a solution for parsing the set of
10 counter data without requiring any significant development efforts for the same by
providing a flexible solution that can adjust the parsing procedure to be used based on the set of counter data.
[0072] The parsing procedure has to take these multiple counter values, analyse
15 what each of them represents, and allocate them appropriately for further analysis.
These multiple values from a single counter can come in both compressed and non-
compressed formats. The parsing procedure analyses the compression attribute to
identify the format of the counter values. And then analysis of the plurality of values
is further done based on parsing the set of counter data using the parsing procedure,
20 and segregation of the plurality of parsed values based on the set of service-related
parameters that is further described below.
[0073] Furthermore, the analysis unit [106A] is configured to segregate the
plurality of parsed values into one or more sub-counters based on the set of service-
25 related parameters. In an implementation of the present disclosure, the segregation
of the plurality of parsed values into the one or more sub-counters may be based on
one or more size attributes of the received set of counter data.
[0074] With the segregated sub-counters, a user interface is provided where users
30 can define Key Performance Indicators (KPIs) using these sub-counters. This step
enables the transformation of parsed and segregated data into meaningful and
21

business-relevant insights. Users can define and customize their KPIs based on the
specific needs of their network management and optimization tasks. The usage of
sub-counters for providing information associated with service-related parameters
such as Allocation and Retention Priority (ARP), Reflective QoS Attribute (RQA),
5 Notification Control, Flow Bit Rates, Aggregate Bit Rates, Default values,
Maximum Packet Loss are mere exemplary implementations of the present disclosure, and shall not be construed to be limiting in nature, and may be used for providing information associated with other similar parameters as may be known to a person skilled in the art.
10
[0075] After the parsing and segregation of the counter data, the next logical step is to use that data effectively. This is where KPIs come into play. KPIs are measurable values that show the performance of specific aspects of a business, in this case, the network's operation. Examples of KPIs in a network context might
15 include data transmission rate, network latency, the number of successful
connections, etc. The user interface provided would allow users, who may be network administrators or analysts, to define these KPIs based on the sub-counter data. This could involve setting a specific threshold for a certain performance metric, or combining several metrics to create a composite KPI. The purpose of
20 defining KPIs is to derive business-relevant insights from the counter data. For
instance, by tracking a KPI related to data transmission rate, a network operator could identify potential bottlenecks in their network and take action to rectify them, thereby improving the service for end-users. Thus, by creating a user interface for defining KPIs using these sub-counters, the system allows users to convert the raw,
25 parsed counter data into meaningful, actionable insights that can help to optimize
the network's operation and ultimately deliver better service to the users.
[0076] In an exemplary aspect, the parsing procedure and parsing logic is described
here as disclosed by the present disclosure. The parsing procedure describes a
30 parsing logic which first identifies whether the incoming data is in a compressed or
non-compressed format, and then accordingly parse it. For compressed data, the
22

parsing logic should identify the value of the compressed attribute. For a
compressed format, the compressed attribute will be set as true. For non-
compressed data, the parsing procedure would directly segregate the parsed values
to the appropriate sub-counters. The parsing logic, further checks the value of the
5 first digit in the received raw counter data file. This first digit is called a size
attribute and indicates the number of distinct values which can be there for any counter. Since, the nature of counters is of compressed type, the parsing logic parses the counter data with the logic applicable for compressed counters. The first digit in case of compressed counter always represents the number of non-zero values
10 which are accumulated in the counter. Then the remaining values are given in
parameter-value pairs. The first pair would comprise a first parameter at second digit and a corresponding first value at third digit. The second pair would comprise a second parameter at fourth position and a corresponding second value at fifth position. Similarly, for the remaining pairs of parameter-value. Thereafter, each pair
15 is analysed for segregating into one or more sub-counters based on the set of
service-related parameters. which can then be further used for KPI estimation. For example, if a raw counter data file for Counter ‘A’ for a node, as received is represented as '4-1-22-2-16-5-39-9-109', then the logic to parse this file is to read the first digit to identify the number of non-zero values for the Counter ‘A’. In the
20 above representation, the first digit is 4, which means there are four non-zero values
for sub-counters defined at positions 1, 2, 5 and 9. The parsing logic will create split counters at these positions mapped to the corresponding counter value. This is shown as an exemplary representation below: A5QI1 ->22
25 A5QI2 ->16
A5QI5 ->39 A5QI9 ->109
[0077] In case of non-compressed format of the set of counter data, the first digit
30 or the size attribute in the raw counter data file indicates the number of values for
the counter separated by a dash symbol “-”. For example, consider a counter ‘A’ for
23

which the size attribute is 16. Then, the raw counter data file for counter ‘A’ will
have 16 values separated by “-”. A sample raw counter data file for a node for
counter ‘A’ may be represented as “1372-274805-75466-7634-694-30-0-0-0-0-0-0-
0-0-0-0”. The parsing logic to parse the raw counter data file for Counter ‘A’, will
5 create a number of split counters which is equal to the value specified in the size
attribute. Each of these split counters will represent one value in the same order as they appear in the raw counter data file. Then these parsed values are segregated based on their positions and the one or more sub-counters are created based on segregation. The one or more sub-counters pertain to the set of service-related
10 parameters. The value within the sub-counter indicates the performance of the
network node regarding the particular service. For example, the value 1372 of the sub-counter may indicate the performance of the voice-related services. Each sub-counter provides QoS for different KPIs. For example, the split counters created such as, sub-counter A.Bin[0] may indicate a QoS/KPI for a voice - related service
15 and its value 1372 may indicate that the QoS indicator for such case would be 1372.
In this exemplary case, after segregating, the one or more split counters or sub-counters as created are shown below. Each of these sub-counters will represent one value in the same order of the name.
20 A.Bin0 → 1372
A.Bin1 → 274805
A.Bin2 → 75466
A.Bin3 → 7634
A.Bin4 → 694
25 A.Bin5 → 30
A.Bin6 → 0
A.Bin7 → 0
A.Bin8 → 0
A.Bin9 → 0
30 A.Bin10 → 0
A.Bin11 → 0
24

5

A.Bin12 → 0
A.Bin13 → 0
A.Bin14 → 0
A.Bin15 → 0
[0078] As disclosed above, each of the split counters or sub-counters, A.Bin() provides the QoS Indicators for each service parameter. These QoS indicators may indicate different services based on a customized rules or dynamic rules which may be determined by the network operators or service providers.

10
[0079] The present disclosure encompasses that once the plurality of parsed values
is segregated into one or more sub-counters, the display unit [108A] is configured
to display a user interface (UI) for defining a set of key performance indicators
(KPIs) utilizing the one or more sub-counters. Now, based on the one or more sub-
15 counters and the plurality of values, the KPIs associated with the particular service
is displayed on the user interface. For example, if the QoS indicator for voice-
related service is 1372, it will be displayed on the user interface. The representation
may be graphical representation such as graphs, diagrams, etc., and may also be
textual representation such as in a tabular format.
20
[0080] Also, a storage unit in communication with the system [100A] or configured within the system [100A] is configured to store the values and data for implementation of the features of the present disclosure. For example, the parsing values, split counters, etc. are stored in the storage unit at each stage of the process.
25
[0081] Referring to FIG. 2 an exemplary method flow diagram [200], for parsing a
set of counter data from a plurality of network nodes in a communication network,
in accordance with exemplary implementation of the present disclosure is shown.
In an implementation, the method [200] is performed by the system [100A]. As
30 shown in Figure 2, the method [200] starts at step [202].
25

[0082] At step [204], the method [200] as disclosed by the present disclosure
comprises receiving, by a receiving unit [102A], a set of counter data periodically
from the plurality of network nodes, wherein each counter data of the set of counter
data, comprises a plurality of values within a single Report Output Period (ROP).
5 The set of counter data may comprise one or more non-zero values of each of a set
of service-related parameters. The set of counter data and the plurality of values may also correspond to one or more performance metrics reflecting certain aspects. The set of counter data may be received in the form of a raw counter data file. The one or more performance metrics may be at least one from among a latency, a
10 throughput, a dropped call, and a signal strength. Further, the set of counter data
may be received from a plurality of Original Equipment Manufacturers (OEMs) in one implementation of the present disclosure. The single ROP may be referred as a period with the timeframe for data or information collection, and presentation in a report. As an example, the single ROP may be 15 minutes. The period may be
15 dynamic and is able to be changed based on change in needs and purposes. The
plurality of values of the counter data within the single ROP is the data present in the number of values present in each counter data.
[0083] The set of service-related parameters may comprise an Allocation and
20 Retention Priority (ARP), Reflective QoS Attribute (RQA), Notification Control,
Flow Bit Rates, Aggregate Bit Rates, Default values, Maximum Packet Loss Rate.
Further, the service-related parameters may be associated with services such as
voice- related services, video- related services, gaming services, non-conservational
video streaming services, mission critical push to talk voice services, non-mission
25 critical push to talk voice services, etc. In an exemplary implementation, service-
related parameters may comprise services like voice and data separately. Like in
case of 5G, voice related statistics are captured under 5QI1 (5G Quality of Service
Indicator-1) and Data related statistics are captured under 5QI9 (5G Quality of
Service Indicator-9) even though values for both is available in same counter from
30 the OEM EMS raw data.
26

[0084] Also, the plurality of network nodes comprise components selected from a
group consisting of base stations, routers, switches, or any other network unit that
assists in managing network traffic in the communication network such as a 5G/6G
network. The network unit assisting in management of network traffic may be, for
5 example, a user plane function (UPF), an access and mobility management function
(AMF), a session management function (SMF) etc.
[0085] In a 5G/6G network, the devices or stations that perform the functions necessary for network communication are the plurality of network nodes. Now, to
10 monitor and evaluate the performance of these network nodes, they are configured
to send performance statistics or performance metrics, also known as counters (or the set of counter data, as may be used interchangeably), to a centralized system or an Element Management System (EMS), which provides a powerful user interface for centralized management of network nodes. This set of counter data is sent at
15 regular intervals, often every 15 minutes. This set of counter data carries various
types of information regarding network performance such as latency, throughput, dropped calls, signal strength, etc. Now, in some cases, instead of sending a single value representing a single performance metric, a counter data from the set of counter data may send multiple values within a single time interval or ROP. This
20 could be because a single performance metric could have different values at
different instances within that 15-minute interval, and all these values are relevant for a comprehensive understanding of that performance metric. So, the process of receiving counter data sent periodically from network nodes, wherein the counter data includes multiple values sent within a single time interval, is essentially the
25 process of collecting detailed performance metrics from the network nodes for
further analysis and performance monitoring.
[0086] Further, in an implementation, the present disclosure provides that along
with the set of counter data, a compression attribute may also be received by the
30 receiving unit [102A]. The compression attribute indicates whether the set of
counter data is compressed or non-compressed. This compression attribute can be
27

then used for identification of the at least one format. The compression attribute
may comprise a true flag or a false flag. The true flag may indicate that the set of
counter data is in a compressed format, i.e., in an event the compression attribute is
a true flag, the at least one format is identified as the compressed format. The false
5 flag may indicate that the set of counter data is in a non-compressed format, i.e., in
an event the compression attribute is a false flag, the at least one format is identified as the non-compressed format.
[0087] Next, at step [206], the method [200] as disclosed by the present disclosure
10 comprises parsing, by the parsing unit [104A], the received counter data based on
a parsing procedure capable of processing the multiple values in both compressed format and non-compressed format. For identification of the at least one format the compression attribute may be analysed based on a true flag or a false flag.
15 [0088] The received counter data is parsed based on a specific parsing procedure.
This parsing procedure is capable of handling multiple values for a single counter in different modes, be it compressed or non-compressed. This is a crucial step as the complexity of the data increases with the presence of multiple values in a single counter. The parsing procedure comprises identifying whether the incoming data is
20 in a compressed or non-compressed format based on the compression attribute, and
appropriately parse it based on the identified format.
[0089] Parsing refers to the process of analysing a string of symbols or data, according to certain rules. The parsing procedure here is predefined, meaning that
25 it has been established in advance how to analyse the incoming counter data.
However, the parsing procedure may be dynamically configured/updated based on change in the set of counter data. The parsing procedure needs to handle multiple values for a single counter. As mentioned before, a single counter can send multiple data values within one Report Output Period (ROP). The parsing procedure handles
30 the set of counter data in a flexible manner. The parsing procedure should be able
to cater to the services which may be either activated or not activated. In the parsing
28

procedure the values that are zero indicate that the service is not activated currently,
but when these services are activated or provisioned, then the counter would
indicate the performance of such services. There may be additions or subtractions
in the number of services provided by a particular network node, and the set of
5 counter data may change accordingly based on the number of services provided.
However, the present disclosure is able to provide a solution for parsing the set of
counter data without requiring any significant development efforts for the same by
providing a flexible solution that can adjust the parsing procedure to be used based
on the set of counter data.
10
[0090] The parsing procedure has to take these multiple counter values, analyse
what each of them represents, and allocate them appropriately for further analysis. These multiple values from a single counter can come in both compressed and non-compressed formats. A compressed format implies that the data has been reduced
15 in size to save space or speed up transmission. The parsing procedure analyses the
compression attribute to identify the format of the counter values. And then analysis of the plurality of values is further done based on parsing the set of counter data using the parsing procedure, and segregation of the plurality of parsed values based on the set of service-related parameters that is further described below.
20
[0091] Next, at step [208], the method [200] as disclosed by the present disclosure comprises segregating, by the analysis unit [106A], the plurality of parsed values into one or more sub-counters based on the set of service-related parameters. After the parsing of the counter data, the parsed values are segregated into corresponding
25 sub-counters. The segregation of the plurality of parsed values into the one or more
sub-counters may be based on one or more size attributes of the received set of counter data. The one or more size attributes are the attributes for the size of the data based on the plurality of values.
30 [0092] Once the counter data has been parsed, the multitude of values from each
counter need to be appropriately allocated. They are segregated into what we call
29

'sub-counters.' Each sub-counter corresponds to a specific performance metric
related to a specific aspect or service of the network. For example, there could be
sub-counters for metrics like Bin wise measurement of Channel Quality Indicators,
Modulation samples distribution, etc. The process of segregation is based on
5 service-related parameters. This means that each value is assigned to a sub-counter
depending on what aspect or service of the network it represents. For example, if a counter sends multiple values related to various services assigned with different Quality of Service Identifiers (QoS) within a single Report Output Period (ROP), each of these values would be assigned to the sub-counter specifically for voice call
10 quality. This segregation is crucial for an accurate representation of individual
performance metrics. By allocating each value to its corresponding sub-counter, each performance metric can be analysed separately. This leads to a more detailed, granular understanding of network performance, as we can see exactly how each aspect of the network is performing for different services. This would not be
15 possible if all the values from a counter were lumped together without segregation
into sub-counters. Thus, segregating the parsed values into corresponding sub-counters is a critical step in the process of parsing counter data, as it facilitates a more detailed and accurate representation and analysis of network performance.
20 [0093] Next, at step [210], the method [200] as disclosed by the present disclosure
comprises displaying, by the display unit [108A] a user interface (UI) for defining Key Performance Indicators (KPIs) utilizing the sub-counters. With the segregated sub-counters, a user interface is provided where users can define and view Key Performance Indicators (KPIs) using these sub-counters. This step enables the
25 transformation of parsed and segregated data into meaningful and business-relevant
insights. Users can define and customize their KPIs based on the specific needs of their network management and optimization tasks. The usage of sub-counters for providing information associated with service-related parameters such as Allocation and Retention Priority (ARP), Reflective QoS Attribute (RQA),
30 Notification Control, Flow Bit Rates, Aggregate Bit Rates, Default values,
Maximum Packet Loss are mere exemplary implementations of the present
30

disclosure, and shall not be construed to be limiting in nature, and may be used for providing information associated with other similar parameters as may be known to a person skilled in the art.
5 [0094] After the parsing and segregation of the counter data, the next logical step
is to use that data effectively. This is where KPIs come into play. KPIs are measurable values that show the performance of specific aspects of a business, in this case, the network's operation. Examples of KPIs in a network context might include data transmission rate, network latency, the number of successful
10 connections, etc. The user interface provided would allow users, who may be
network administrators or analysts, to define these KPIs based on the sub-counter data. This could involve setting a specific threshold for a certain performance metric, or combining several metrics to create a composite KPI. The purpose of defining KPIs is to derive business-relevant insights from the counter data. For
15 instance, by tracking a KPI related to data transmission rate, a network operator
could identify potential bottlenecks in their network and take action to rectify them, thereby improving the service for end-users. Thus, by creating a user interface for defining KPIs using these sub-counters, the system allows users to convert the raw, parsed counter data into meaningful, actionable insights that can help to optimize
20 the network's operation and ultimately deliver better service to the users.
[0095] In an exemplary aspect, the parsing procedure and parsing logic is described here as disclosed by the present disclosure. The parsing procedure describes a parsing logic which first identifies whether the incoming data is in a compressed or
25 non-compressed format, and accordingly parse it. For compressed data, the
procedure should identify the value of the compressed attribute. For a compressed format, the compressed attribute will set as true. For non-compressed data, the parsing procedure would directly segregate the parsed values to the appropriate sub-counters. The parsing logic for a counter data, further checks the value of the first
30 digit in the received counter data. This first digit is called as a size attribute and
indicates the number of distinct values which can be there for any counter. Since,
31

the nature of counters is of compressed type, the parsing logic parses the counter
data with the logic applicable for compressed counters. The first digit in case of
compressed counter always represents the number of non-zero values which are
accumulated in the counter. Then the remaining values are given in parameter-value
5 pairs. The first pair would comprise a first parameter at second digit and a
corresponding first value at third digit. The second pair would comprise a second
parameter at fourth position and a corresponding second value at fifth position.
Similarly, for the remaining pairs of parameter-value. Thereafter, each pair is
analysed for segregating into one or more sub-counters based on the set of service-
10 related parameters. which can then be further used for KPI estimation. For example,
if a raw counter data file for Counter ‘A’ for a node, as received is represented as
'4-1-22-2-16-5-39-9-109', then the logic to parse this file is to read the first digit to
identify the number of non-zero values for the Counter ‘A’. In the above
representation, the first digit is 4, which means there are four non-zero values for
15 sub-counters defined at positions 1, 2, 5 and 9. The parsing logic will create split
counters at these positions mapped to the corresponding counter value. This is
shown as an exemplary representation below:
A5QI1 ->22
A5QI2 ->16
20 A5QI5 ->39
A5QI9 ->109
[0096] In case of non-compressed format of the set of counter data, the first digit or the size attribute in the raw counter data file indicates the number of values for
25 the counter separated by a dash symbol “-”. For example, consider a counter ‘A’ for
which the size attribute is 37. Then, the raw counter data file for counter ‘A’ will have 37 values separated by “-”. A sample raw counter data file for a node for counter ‘A’ may be represented as “1372-274805-75466-7634-694-30-0-0-0-0-0-0-0-0-0-0”. The parsing logic to parse the raw counter data file for Counter ‘A’, will
30 create a number of split counters which is equal to the value specified in the size
attribute. Each of these split counters will represent one value in the same order as
32

they appear in the raw data file. Then these parsed values are then segregated based
on their positions and the one or more sub-counters are created based on
segregation. The one or more sub-counters pertain to the set of service-related
parameters. The value within the sub-counter indicates the performance of the
5 network node regarding the particular service. For example, the value 1372 of the
sub-counter may indicate the performance of the voice-related services. Each sub-
counter provides QoS for different KPIs. For example, the sub-counter Bin[0] may
indicate a QoS/KPI for a voice - related service and its value 1372 may indicate that
the QoS indicator for such case would be 1372. In this exemplary case, after
10 segregating, the one or more sub-counters are created. Each of these sub-counters
will represent one value in the same order of the name.
A.Bin0 → 1372
A.Bin1 → 274805
A.Bin2 → 75466
15 A.Bin3 → 7634
A.Bin4 → 694
A.Bin5 → 30
A.Bin6 → 0
A.Bin7 → 0
20 A.Bin8 → 0
A.Bin9 → 0
A.Bin10 → 0
A.Bin11 → 0
A.Bin12 → 0
25 A.Bin13 → 0
A.Bin14 → 0
A.Bin15 → 0
[0097] As disclosed above, each of the split counter or sub-counter, A.Bin()
30 provides the QoS Indicators for each services provided. These QoS indicators may
33

indicate different services based on a customized rules or dynamic rules which may be determined by the network operators or service providers.
[0098] The present disclosure encompasses that once the plurality of parsed values
5 is segregated into one or more sub-counters, the display unit [108A] is configured
to display a user interface (UI) for defining a set of key performance indicators
(KPIs) utilizing the one or more sub-counters. Now, based on the one or more sub-
counters and the plurality of values, the KPIs associated with the particular service
is displayed on the user interface. For example, if the QoS indicator for voice-
10 related service is 1372, it will be displayed on the user interface. The representation
may be graphical representation such as graphs, diagrams, etc., and may also be
textual representation such as in a tabular format.
[0099] The method [200] as disclosed by the present disclosure comprises adapting
15 to accommodate new quality of service indicators: A significant feature of this
method is its ability to adapt and accommodate new quality of service indicators.
As networks evolve and new quality of service indicators are introduced, the
flexible parsing procedure can handle these new metrics. This ensures the method
remains relevant and effective in processing future updates in network node
20 performance statistics without the need for substantial development efforts.
[0100] As technology advances and network infrastructure evolves, new parameters or quality of service indicators may be introduced to monitor and measure different aspects of network performance. Traditional, hard-coded parsing
25 methods may not be able to adapt to these changes effectively, necessitating
significant redevelopment or adjustment. However, the technical solution as disclosed in the present disclosure incorporates a flexible parsing procedure, capable of accommodating such changes. For instance, if a new service is introduced in the network that uses a new quality of service indicator, this parsing
30 procedure can handle it without any additional development effort. The flexibility
stems from the way the system handles multiple values from a single counter, either
34

in compressed or non-compressed formats, and segregates them into the
corresponding sub-counters. This adaptability ensures the longevity and continued
relevance of the method. Instead of needing constant updates or redevelopment in
response to changes in network node performance statistics, the system can
5 continue to provide accurate and useful data analysis. As a result, network
administrators can depend on this method to continue offering valuable, business-relevant insights into network performance, irrespective of how network technologies evolve in the future.
10 [0101] Thereafter, the method terminates at step [212].
[0102] Referring to FIG. 3, an exemplary representation [300] at the user interface
of utilising the set of counter data in key performance indicators (KPI) is provided
in accordance with exemplary implementation of the present disclosure. The
15 exemplary representation shows an illustration of a user interface showing the set
of counter data received (such as for a Counter ‘A’), along with the one or more
sub-counters (such as A.Bin0, A.Bin1, A.Bin2, A.Bin3, A.Bin4) illustrating the
performance of the one or more network nodes and each of the Key Performance
Indicators.
20
[0103] Referring to FIG. 4, an exemplary raw counter data file format of the set of
counter data is illustrated, in accordance with the exemplary implementations of the
present disclosure. The receiving unit [102A] receives the set of counter data with
multiple values in a compressed format. These set of counters data have different
25 logic for interpretation and need to be handled in different manner. The parsing
logic and interpretation of values in these set of counter data is depicted in FIG. 4.
This parsing logic and interpretation is further explained using an exemplary data
as shown below.
30 [0104] For example, the set of counter data (for example Y) which may be received
from the one or more network nodes, is:
35

Y= 4-1-22-2-16-5-38-9-130
[0105] The plurality of values in this example may be analysed as follows:
5 [0106] The first digit, in case the set of counter data is compressed, represents the
number of non-zero values which are pegged in the set of counter data. In this
example it is 4. It means out of available plurality of values, only 4 values are having
non-zero values. Next in this implementation, the receiving unit [102A] is
configured to give remaining values in 5QIs-Value for particular 5QI pairs.
10 Continuing with above example, remaining all values are given in 5QIs-Value for
particular 5QI pairs. i.e. the remaining values except the value at first position are divided into pairs. For example:
[1-22]-[2-16]-[5-38]-[9-130]
15 [0107] Here, the first pair would indicate the one or more sub-counters (for 5G
Quality of Service Indicators) as 5QI1 → 22, 5QI2→ 16, 5QI5→ 38 & 5QI9→130.
[0108] It would be appreciated by the person skilled in the art that the present
disclosure presents a flexible, adaptive, and efficient approach to process and
20 interpret performance statistics from network nodes, particularly for cases where
multiple values are present within a single counter data for a specific time interval.
[0109] FIG. 5 illustrates an exemplary block diagram of a computing device [500] upon which the features of the present disclosure may be implemented in
25 accordance with exemplary implementation of the present disclosure. In an
implementation, the computing device [500] may also implement a method [200] for parsing a set of counter data from a plurality of network nodes in a communication network by utilising the system [50]. In another implementation, the computing device [500] itself implements the method [200] for parsing a set of
30 counter data from a plurality of network nodes in a communication network using
one or more units configured within the computing device [500], wherein said one
36

or more units are capable of implementing the features as disclosed in the present disclosure.
[0110] The computing device [500] may include a bus [502] or other
5 communication mechanism for communicating information, and a hardware
processor [504] coupled with bus [502] for processing information. The hardware
processor [504] may be, for example, a general-purpose microprocessor. The
computing device [500] may also include a main memory [506], such as a random-
access memory (RAM), or other dynamic storage device, coupled to the bus [502]
10 for storing information and instructions to be executed by the processor [504]. The
main memory [506] also may be used for storing temporary variables or other
intermediate information during execution of the instructions to be executed by the
processor [504]. Such instructions, when stored in non-transitory storage media
accessible to the processor [504], render the computing device [500] into a special-
15 purpose machine that is customized to perform the operations specified in the
instructions. The computing device [500] further includes a read only memory
(ROM) [508] or other static storage device coupled to the bus [502] for storing static
information and instructions for the processor [504].
20 [0111] A storage device [510], such as a magnetic disk, optical disk, or solid-state
drive is provided and coupled to the bus [502] for storing information and instructions. The computing device [500] may be coupled via the bus [502] to a display [512], such as a cathode ray tube (CRT), Liquid crystal Display (LCD), Light Emitting Diode (LED) display, Organic LED (OLED) display, etc. for
25 displaying information to a computer user. An input device [514], including
alphanumeric and other keys, touch screen input means, etc. may be coupled to the bus [502] for communicating information and command selections to the processor [504]. Another type of user input device may be a cursor controller [516], such as a mouse, a trackball, or cursor direction keys, for communicating direction
30 information and command selections to the processor [504], and for controlling
cursor movement on the display [512]. This input device typically has two degrees
37

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.
[0112] The computing device [500] may implement the techniques described
5 herein using customized hard-wired logic, one or more ASICs or FPGAs, firmware
and/or program logic which in combination with the computing device [500] causes or programs the computing device [500] to be a special-purpose machine. According to one implementation, the techniques herein are performed by the computing device [500] in response to the processor [504] executing one or more
10 sequences of one or more instructions contained in the main memory [506]. Such
instructions may be read into the main memory [506] from another storage medium, such as the storage device [510]. Execution of the sequences of instructions contained in the main memory [506] causes the processor [504] to perform the process steps described herein. In alternative implementations of the present
15 disclosure, hard-wired circuitry may be used in place of or in combination with
software instructions.
[0113] The computing device [500] also may include a communication interface
[518] coupled to the bus [502]. The communication interface [518] provides a two-
20 way data communication coupling to a network link [520] that is connected to a
local network [522]. For example, the communication interface [518] 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 [518] may be a
25 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 [518] sends and receives electrical,
electromagnetic or optical signals that carry digital data streams representing
various types of information.
30
38

[0114] The computing device [500] can send messages and receive data, including program code, through the network(s), the network link [520] and the communication interface [518]. In the Internet example, a server [530] might transmit a requested code for an application program through the Internet [528], the ISP [526], the host [524], the local network [522] and the communication interface [518]. The received code may be executed by the processor [504] as it is received, and/or stored in the storage device [510], or other non-volatile storage for later execution.
[0115] The present disclosure further relates to a non-transitory computer readable storage medium storing instruction for parsing a set of counter data from a plurality of network nodes in a communication network. The instructions include executable code which, when executed by one or more units of a system [100A], causes: a receiving unit [102A] of the system [100A] to receive a set of counter data periodically from the plurality of network nodes, wherein each counter data of the set of counter data comprises a plurality of values within a single Report Output Period (ROP). Further, the instructions include executable code, which when executed causes a parsing unit [104A] of the system [100A] to parse the received set of counter data based on a parsing procedure capable of processing the plurality of values in at least one format. Further, the instructions include executable code, which when executed causes an analysis unit [106A] of the system [100A] to segregate the parsed plurality of values into one or more sub-counters based on a set of service-related parameters. Further, the instructions include executable code, which when executed causes a display unit [108A] of the system [100A] to display, a user interface (UI) for defining Key Performance Indicators (KPIs) utilizing the one or more sub-counters.
[0116] As is evident from the above, the present disclosure provides a technically advanced solution for parsing counters with multiple values in single ROP. Parsing counters with multiple values and interpreting the individual values is not hardcoded in the backend and is handled in a flexible manner. This interpretation

of individual values for multiple value counters makes it possible to refer the individual performance statistics for different services like voice and data separately. Like in case of 5G, voice related statistics are captured under 5QI1 (5G Quality of Service Indicatior-1) and Data related statistics are captured under 5QI9 (5G Quality of Service Indicatior-9) even though values for both is available in same counter from the vendor EMS raw data. With this feature of parsing counters with multiple values, one may also be able to define the key performance metrics for individual services like voice and data. In future even if furthermore quality of service indicators is introduced in the network related to a particular class of service, the solution disclosed in the present disclosure will be able to parse the values and assign it to the individual counters without any additional development efforts.
[0117] While considerable emphasis has been placed herein on the disclosed implementations, it will be appreciated that many implementations can be made and that many changes can be made to the implementations without departing from the principles of the present disclosure. These and other changes in the implementations 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.
[0118] 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.

I/We Claim:
1. A method [200] for parsing a set of counter data from a plurality of network
nodes in a communication network, said method comprising:
receiving, by a receiving unit [102A], the set of counter data periodically from the plurality of network nodes, wherein each counter data of the set of counter data comprises a plurality of values within a single Report Output Period (ROP);
parsing, by a parsing unit [104A], the received set of counter data based on a parsing procedure for processing the plurality of values in at least one format;
segregating, by an analysis unit [106A], the plurality of parsed values into one or more sub-counters based on a set of service-related parameters; and
displaying, by a display unit [108A], a User Interface (UI) for defining a set of Key Performance Indicators (KPIs) utilizing the one or more sub-counters.
2. The method [200] as claimed in claim 1, wherein the set of counter data comprises one or more non-zero values of each of the set of service-related parameters.
3. The method [200] as claimed in claim 1, wherein the at least one format comprises at least one of a compressed format and a non-compressed format.
4. The method [200] as claimed in claim 3, wherein the at least one format is identified based on a compression attribute, wherein the compression attribute comprises one of a true flag and a false flag, wherein in an event the compression attribute is a true flag, the at least one format is identified as the compressed format, and in an event the compression attribute is a false flag, the at least one format is identified as the non-compressed format.

5. The method [200] as claimed in claim 1, wherein the segregation of the plurality of parsed values into the one or more sub-counters is further based on one or more size attributes of the received set of counter data.
6. The method [200] as claimed in claim 1, wherein the plurality of network nodes comprises two or more components selected from a group consisting of a base station, a router, a switch, and a network unit assisting in managing a network traffic in the communication network.
7. The method [200] as claimed in claim 1, wherein the set of counter data corresponds to one or more performance metrics reflecting one or more aspects comprising at least one of a latency, a throughput, dropped calls, and a signal strength.
8. The method [200] as claimed in claim 1, wherein the set of counter data is received from a plurality of Original Equipment Manufacturers (OEMs).
9. A system [100A] for parsing a set of counter data from a plurality of network nodes in a communication network, the system [100A] comprises:
a receiving unit [102A], configured to receive the set of counter data periodically from the plurality of network nodes, wherein each counter data of the set of counter data comprises a plurality of values within a single Report Output Period (ROP);
a parsing unit [104A] connected to the receiving unit [102A], the parsing unit [104A] is configured to parse the received set of counter data based on a parsing procedure for processing the plurality of values in at least one format;
an analysis unit [106A] connected to the parsing unit [104A], the analysis unit [106A] is configured to segregate the plurality of parsed values into one or more sub-counters based on a set of service-related parameters; and

a display unit [108A] connected to the analysis unit [106A], the display unit [108A] is configured to display a user interface (UI) for defining a set of key performance indicators (KPIs) utilizing the one or more sub-counters.
10. The system [100A] as claimed in claim 9, wherein the set of counter data comprises one or more non-zero values of each of the set of service-related parameters.
11. The system [100A] as claimed in claim 9, wherein the at least one format comprises at least one of a compressed format and a non-compressed format.
12. The system [100A] as claimed in claim 11, wherein the at least one format is identified based on a compression attribute, wherein the compression attribute comprises one of a true flag and a false flag, wherein in an event the compression attribute is a true flag, the at least one format is identified as the compressed format, and in an event the compression attribute is a false flag, the at least one format is identified as the non-compressed format.
13. The system [100A] as claimed in claim 9, wherein the segregation of the plurality of parsed values into the one or more sub-counters is further based on one or more size attributes of the received set of counter data.
14. The system [100A] as claimed in claim 9, wherein the plurality of network nodes comprises two or more components selected from a group consisting of a base station, a router, a switch, and a network unit assisting in managing a network traffic in the communication network.
15. The system [100A] as claimed in claim 9, wherein the set of counter data corresponds to one or more performance metrics reflecting one or more

aspects comprising at least one of a latency, a throughput, dropped call, and a signal strength.
16. The system [100A] as claimed in claim 9, wherein the set of counter data is received from a plurality of Original Equipment Manufacturers (OEMs).