System and method for performance comparison of nodes in a communication network

Abstract

Disclosed is a system (100) and a method (500) for monitoring performance of nodes (120) in a communication network. The method (500) comprises receiving an input including a selection of attributes associated with vendors and Key Performance Indicators (KPIs) and initiating an Application Programming Interface (API) call request to a first microservice based on the input. The KPIs are associated 10 with a type of a set of nodes associated with the vendors. The method further comprises creating a record of the attributes in a first database (150) and triggering a scheduler (146) to fetch values of the KPIs from a second database (160) upon creation of the record. Furthermore, the method comprises generating a comparative performance metrics report indicating a performance comparison between the type of the set of nodes of at least a first vendor and a second vendor based on the fetched values of the KPIs.

Description

SYSTEM AND METHOD FOR PERFORMANCE COMPARISONOF NODES IN A COMMUNICATION NETWORKCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of Indian patent application No. 202421023084 filed on March 24, 2024, Indian patent application No. 202421023393, titled “A User Interface Framework For Comparing And Visualizing Product Performance Metrics” filed on March 25, 2024, and Indian patent application No. 202421024195, titled “System And Method For Handling Call Flow For Product- Wise KPI Visualisation Trend Of Performance Metrics” filed on March 26, 2024. The disclosure of the prior applications is considered part of and is incorporated by reference into this patent application.TECHNICAL FIELD

[0002] The embodiments of the present disclosure generally relate to the field of wireless communication networks. More particularly, the present disclosure relates to a system and a method for monitoring performance of nodes in a communication network.BACKGROUND OF THE INVENTION

[0003] The subject matter disclosed in the background section should not be assumed or construed to be prior art merely because of its mention in the background section. Similarly, any problem statement mentioned in the background section or its association with the subject matter of the background section should not be assumed or construed to have been previously recognized in the prior art.

[0004] With diverse and ever-increasing consumer demand for network connectivity, there has been an expansion of network resources by telecom operators to meet the consumer demand. To meet the consumer demand, physical network infrastructure such as transmission nodes are being dynamically placedthroughout the network. The network infrastructures encompass diverse technologies and protocols and work together in cohesion to provide seamless telecom service to customers. Along with expansion, efforts are being put to monitor, analyze, and optimize performance of the wireless networks for efficient utilization of the network resources by interpreting performance data of network elements.

[0005] The wireless communication networks comprise millions of nodes and diverse product types from different vendors so that optimal performance and quality can be maintained across wireless network’s infrastructure. With the introduction of new product types across various vendors, there arose a need for the telecom operators and network administrators to compare and assess the quality of these products comprehensively. During initial phases in the development of the wireless networks, the monitoring of the wireless networks relied majorly on raw data collected from various network elements and devices. However, interpreting the collected data in its raw form was often cumbersome and time-consuming, thereby posing inability to identify faults, and areas for improvement effectively.

[0006] Heretofore, comparative analysis of performance metrics of different telecom products from multiple vendors has been performed manually, which suffered from certain challenges and limitations. The telecom products correspond to different types of equipment or devices used in the wireless communication network.

[0007] A manual process of aggregating and analyzing performance of the different telecom products in a complex wireless network is labor-intensive, time-consuming, and prone to errors. Furthermore, it is exhaustive to encompass all relevant performance metrics due to a large volume of node related statistical data. Thus, these limitations hinder the ability of network operation teams to conduct thorough evaluations to detect performance degradation or outages and take appropriate actions promptly.

[0008] In order to overcome aforementioned challenges, there lies a need for a system and a method that enables comparative analysis of performance metrics corresponding to nodes associated with one or more vendors in a communication network.SUMMARY

[0009] The following embodiments present a simplified summary to provide a basic understanding of some aspects of the disclosed invention. This summary is not an extensive overview, and it is not intended to identify key / critical elements or to delineate the scope thereof. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.

[0010] According to an aspect of the present disclosure, disclosed herein is a method for monitoring performance of nodes in a communication network. The method comprises receiving, from a user device, by an acquisition module, an input including a selection of one or more attributes associated with one or more vendors of a plurality of vendors and one or more Key Performance Indicators (KPIs). The one or more KPIs are associated with a type of a set of nodes among a plurality of nodes associated with the one or more vendors. The method further comprises initiating, by an execution module, an Application Programming Interface (API) call request to a first microservice among a plurality of microservices based on the input and creating, by the execution module using the first microservice, a record of the one or more attributes in a first database upon initiation of the API call request. Furthermore, the method comprises triggering, by the execution module, a scheduler to fetch values of the one or more KPIs from a second database upon creation of the record and generating, by a data processing module, a comparative performance metrics report indicating a performance comparison between the type of the set of nodes of at least a first vendor and a second vendor among the plurality of vendors based on the fetched values of the one or more KPIs.

[0011] In one or more implementations, for creating the record of the one or more attributes, the method comprises storing, by the extraction module, the one or more attributes in the first database.

[0012] In one or more implementations, to fetch the values of the one or more KPIs from the second database, the method comprises detecting the creation of the record of the one or more attributes in the first database and mapping, upon detecting the creation of the record, the one or more attributes in the first database to the corresponding KPI values stored in the second database. The method further comprises retrieving the mapped KPI values from the second database.

[0013] In one or more implementations, the method comprises executing, by the data processing module, via a second microservice among the plurality of microservices, a process for generating the comparative performance metrics report and generating, by the data processing module, the comparative performance metrics report based on the fetched values of the one or more KPIs upon execution of the process. The method further comprises controlling, by the data processing module, a User Interface (UI) of the user device to display the comparative performance metrics report.

[0014] In one or more implementations, the method comprises determining, by the data processing module from the comparative performance metrics report, a count of alarms raised at the set of nodes for each vendor of the one or vendors and determining, by the data processing module, a performance trend based on the count of alarms. The count of alarms is determined in a service area with respect to a predefined time-period. Th method further comprises controlling, by the data processing module, the UI to display the determined performance trend.

[0015] In one or more implementations, the one or more attributes comprise at least one of details of the one or more vendors, the type of the set of nodes, a geographical location of a service area of the set of nodes, a time period, and a frequency for generating the comparative performance metrics report.

[0016] In one or more implementations, the first database corresponds to a relational database and the second database corresponds to a distributed file system.

[0017] In one or more implementations, the method further comprises controlling, by the data processing module, the user device to display, on the UI, a list of the one or more attributes corresponding to the one or more vendors and the one or more KPIs. The input corresponds to a selection operation to select at least one attribute from the list of the one or more attributes.

[0018] In one or more implementations, the type of the set of nodes comprises one or more of an outdoor small node, an indoor small node, and a macro node. The type of the set of nodes is same for each vendor of the one or more vendors.

[0019] In one or more implementations, the API call request comprises a Representational State Transfer (REST) based API call request corresponding to the plurality of microservices.

[0020] According to another aspect of the present disclosure, a system for monitoring performance of nodes in a communication network is disclosed. The system comprises an acquisition module, an execution module, and a data processing module. The acquisition module is configured to receive, from a user device, an input including a selection of one or more attributes associated with one or more vendors of a plurality of vendors and one or more Key Performance Indicators (KPIs). The one or more KPIs are associated with a type of a set of nodes among a plurality of nodes associated with the one or more vendors. The execution module is configured to initiate, based on the input, an Application Programming Interface (API) call request to a first microservice among a plurality of microservices and create, using the first microservice, a record of the one or more attributes in a first database upon initiation of the API call request. The API call request comprises a Representational State Transfer (REST) based API call request corresponding to the plurality of microservices. The execution module is further configured to trigger a scheduler to fetch, upon creation of the record, values of the one or more KPIs from a second database. The data processing module is configuredto generate, based on the fetched values of the one or more KPIs, a comparative performance metrics report indicating a performance comparison between the type of the set of nodes of at least a first vendor and a second vendor among the plurality of vendors. The type of the set of nodes comprises one or more of an outdoor small node, an indoor small node, and a macro node. The type of the set of nodes is same for each vendor of the one or more vendors.

[0021] In one or more implementations, for creating the record of the one or more attributes, the extraction module is configured to store the one or more attributes in the first database.

[0022] In one or more implementations, to fetch, using the scheduler, the values of the one or more KPIs from the second database, the execution module is configured to detect the creation of the record of the one or more attributes in the first database and map, upon detecting the creation of the record, the one or more attributes in the first database to the corresponding KPI values stored in the second database. The execution module is further configured to retrieve the mapped KPI values from the second database. The one or more attributes comprise at least one of details of the one or more vendors, the type of the set of nodes, a geographical location of a service area of the set of nodes, a time period, and a frequency for generating the comparative performance metrics report. The first database corresponds to a relational database and the second database corresponds to a distributed file system.

[0023] In one or more implementations, the data processing module is configured to execute, via a second microservice among the plurality of microservices, a process for generating the comparative performance metrics report and generate, upon execution of the process, the comparative performance metrics report based on the fetched values of the one or more KPIs. The data processing module is further configured to control a User Interface (UI) of the user device to display the comparative performance metrics report.

[0024] In one or more implementations, the data processing module is configured to determine, from the comparative performance metrics report, a count of alarmsraised at the set of nodes for each vendor of the one or vendors. The count of alarms is determined in a service area with respect to a predefined time-period. The data processing module is configured to determine a performance trend based on the count of alarms and control the UI to display the determined performance trend.

[0025] In one or more implementations, the data processing module is configured to control the user device to display, on the UI, a list of the one or more attributes corresponding to the one or more vendors and the one or more KPIs. The input corresponds to a selection operation to select at least one attribute from the list of the one or more attributes.BRIEF DESCRIPTION OF DRAWINGS

[0026] Various embodiments disclosed herein will become better understood from the following detailed description when read with the accompanying drawings. The accompanying drawings constitute a part of the present disclosure and illustrate certain non-limiting embodiments of inventive concepts. Further, components and elements shown in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. For consistency and ease of understanding, similar components and elements are annotated by reference numerals in the exemplary drawings.

[0027] FIG. 1 illustrates a block diagram depicting a communication system for monitoring performance of nodes in a communication network, in accordance with an embodiment of the present disclosure.

[0028] FIG. 2 illustrates a block diagram depicting various components of a processor of the communication system, in accordance with an embodiment of the present disclosure.

[0029] FIG. 3 illustrates a block diagram depicting a call flow between a user device and components of a server, in accordance with an embodiment of the present disclosure.

[0030] FIG. 4 illustrates an example User Interface (UI) for visualizing trends of performance metrics corresponding to multiple nodes in the communication network, in accordance with an embodiment of the present disclosure.

[0031] FIG. 5 illustrates a flowchart depicting a method for monitoring the performance of nodes in the communication network, in accordance with an embodiment of the present disclosure.

[0032] FIG. 6 illustrates a schematic architecture diagram depicting a computing system, in accordance with an embodiment of the present disclosure.DETAILED DESCRIPTION OF THE INVENTION

[0033] Inventive concepts of the present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, in which examples of one or more embodiments of inventive concepts are shown. Inventive concepts may, however, be embodied in different forms and should not be construed as limited to the embodiments set forth herein. Further, the one or more embodiments disclosed herein are provided to describe the inventive concept thoroughly and completely, and to fully convey the scope of each of the present inventive concepts to those skilled in the art. Furthermore, it should be noted that the embodiments disclosed herein are not mutually exclusive concepts. Accordingly, one or more components from one embodiment may be tacitly assumed to be present or used in any other embodiment.

[0034] The following description presents various embodiments of the present disclosure. The embodiments disclosed herein are presented as teaching examples and are not to be construed as limiting the scope of the present disclosure. The present disclosure should in no way be limited to the illustrative implementations, drawings, and techniques illustrated below, including the exemplary design and implementation illustrated and described herein, but may be modified, omitted, or expanded upon without departing from the scope of the present disclosure.

[0035] The following description contains specific information pertaining to embodiments in the present disclosure. The detailed description uses the phrases “in some embodiments” or “some implementations” which may each refer to one or more or all of the same or different embodiments or implementations. The term “some” as used herein is defined as “one, or more than one, or all.” Accordingly, the terms “one,” “more than one,” “more than one, but not all” or “all” would all fall under the definition of “some.” In view of the same, the terms, for example, “in an embodiment” or “in an implementation” refers to one embodiment or one implementation and the term, for example, “in one or more embodiments” refers to “at least one embodiment, or more than one embodiment, or all embodiments”. Further, the term, for example, “in one or more implementations” refers to “at least one implementation, or more than one implementation, or all implementations”.

[0036] The term “comprising,” when utilized, means “including, but not necessarily limited to;” it specifically indicates open-ended inclusion in the so-described one or more listed features, elements in a combination, unless otherwise stated with limiting language. Furthermore, to the extent that the terms “includes,” “has,” “have,” “contains,” and other similar words are used in either the detailed description, such terms are intended to be inclusive in a manner similar to the term “comprising.”

[0037] In the following description, for the purposes of explanation, various specific details are set forth to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features.

[0038] The description provided herein discloses exemplary embodiments only and is not intended to limit the scope, applicability, or configuration of the present disclosure. Rather, the foregoing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing anyof the exemplary embodiments. Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it may be understood by one of the ordinary skilled in the art that the embodiments disclosed herein may be practiced without these specific details.

[0039] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein the description, the singular forms "a", "an", and "the" include plural forms unless the context of the invention indicates otherwise.

[0040] The terminology and structure employed herein are for describing, teaching, and illuminating some embodiments and their specific features and elements and do not limit, restrict, or reduce the scope of the present disclosure. Accordingly, unless otherwise defined, all terms, and especially any technical and / or scientific terms, used herein may be taken to have the same meaning as commonly understood by one having ordinary skill in the art.

[0041] The present disclosure relates to a system and a method for monitoring performance of multiple nodes associated with one or more telecom vendors (hereinafter also referred to as the “vendors”) in a wireless network. An aspect of the present disclosure is to provide a system and a method that can enable a Quality Assurance (QA) team to select any performance metrics corresponding to the multiple nodes associated with the vendors so that the QA team can take remedial actions timely and with ease.

[0042] Another aspect of the present disclosure is to provide a system and a method that can enable an end user to visualize a node wise trend of the performance metrics for user selected Key Performance Indicators (KPIs) for the multiple nodes associated with the vendors in the wireless network.

[0043] Another aspect of the present disclosure is to provide a system and a method that can assess the performance of the multiple nodes for any geography in one gothereby reducing time and effort spent on manual comparison of the node wise trend of the performance metrics.

[0044] Another aspect of the present disclosure is to provide a system and a method that can eliminate the need for an exhaustive analysis of the performance metrics, thereby reducing the time and effort required.

[0045] In order to facilitate an understanding of the disclosed invention, a number of terms are defined below.

[0046] A node refers to an individual network entity involved in data transmission or service delivery within a communication network.

[0047] A Network Element (NE) refers to any individual device or logical entity within a telecommunication network, such as a router, a switch, or a base station, which are monitored and managed by the EMS. The NE is the lowest manageable unit in a network and supports execution of specific network functions.

[0048] The performance metrics refers to quantitative measures that are used to assess the performance of a communication network such as a throughput, a latency, packet loss, and error rates. These metrics help in evaluating quality and efficiency of communication services.

[0049] A bandwidth usage refers to amount of data transmitted over a communication network during a specific time period. The bandwidth usage is often measured in bits per second (bps) and is a key performance metric in communication networks.

[0050] A latency refers to time taken for a data packet to travel from a source to a destination across the communication network. The latency is a critical factor for real time applications like voice and video calling, and it is typically measured in milliseconds (ms).

[0051] A packet loss occurs when one or more data packets fail to reach the destination. The packet loss is usually caused by network congestion, faulty hardware, or signal interference. The packet loss is often measured as a percentage of total data packets sent.

[0052] A throughput refers to a rate at which data is successfully transmitted from one point to another over a communication network. The throughput is commonly measured in bps and reflects the capacity of the communication network.

[0053] An error rate corresponds to a frequency at which an error occurs in transmission of data, often expressed as a percentage or ratio of number of error bits to total number of bits sent.

[0054] A microservices framework corresponds to a network architecture, where independent microservices communicate over Application Programming Interfaces (APIs), enabling modular, scalable, and resilient network management applications.

[0055] A microservice refers to individual components that perform specific tasks within a system, for example, a test execution microservice could be responsible for running the network tests, while data processing microservice could handle data transformation and storage.

[0056] The KPIs refer to quantifiable metrics that are used to assess the performance of the network elements within the communication network or a service in relation to predefined objectives. The KPIs help in monitoring a Quality of Service (QoS), resource utilization, and user experience.

[0057] An attribute refers to a configurable parameter that defines how the KPIs are filtered, grouped, or visualized in a performance metrics report. The attribute may include as an example, vendor specific filtering, geographical location (node, city, region, cell site identifier (ID)), an aggregation type (per node, per sector, per cluster).

[0058] A performance metrics report refers to a detailed document or report that summarizes the performance of a communication network or system based on key metrics such as the throughput, the latency, the packet loss, and the error rates. The performance metrics report is used for network monitoring and troubleshooting.

[0059] Vendors may include service providers who are responsible for fulfilling operational and technological requirements and host services including but not limited thereto, invoicing, streamlining a company’s wireless services, and providing seamless internet access. The vendors may also include supplier or manufacturer of telecommunications equipment or software.

[0060] The term “user” in the present disclosure may correspond to a field staff, or an administrator or a person from the QA team assigned for monitoring and performing study on the products belonging to the same vendor or the different vendors in a particular geography.

[0061] A comparative performance metrics report refers to a structured report that provides a quantitative and / or qualitative comparison of performance of nodes associated with same or different vendors. In the context of the present disclosure, the comparative performance metrics report enables network operators, and administrators to assess vendor specific performance, identified discrepancies, and optimize network resource allocation based on real time and historical KPI data.

[0062] A service area refers to a specific geographical region within a communication network where nodes are deployed to provide connectivity and network services. The service area may be defined based on parameters such as geographical boundaries, network segmentation, coverage region, and the like.

[0063] A count of alarms refers to a number of alerts or notifications triggered within a network monitoring system when predefined thresholds or anomalies are detected.

[0064] A performance trend represents historical and real-time variations in network performance based on values of the KPIs. The performance trends help in understanding network stability, vendor efficiency, and service quality and maybe derived from time-series analysis, anomaly detection, predictive insights, and the like.

[0065] A relational database refers to a structured data storage system that organizes information into tables with predefined relationships between entities. In the context of the present disclosure, the relational database is used to store structured data such as vendor attributes, node types and metadata associated with KPI evaluations. The relational database enables structured querying and indexing.

[0066] A distributed file system refers to a network-based storage architecture that enables data to be stored across multiple nodes or servers rather than a single centralized location. In the context of the present disclosure, the distributed file system is used to store KPI values related to network performance and generated performance metrics reports.

[0067] An Application Programming Interface (API) call request refers to a mechanism used by software applications to request data or services from an external system via an API.

[0068] A Representational State Transfer (REST) based API call request refers to an API request that follows the REST architectural principles. In the context of the present disclosure, the REST based API call request enables seamless communication between different micro services, allowing efficient retrieval of KPI values and performance related data from relational and distributed databases.

[0069] Embodiments of the present disclosure will be described below in detail with reference to the accompanying drawings. FIG. 1 through FIG. 6, discussed below, and the one or more embodiments used to describe the principles of the present disclosure are by way of illustration only and should not be construed in any way to limit the scope of the present disclosure. Those skilled in the art will understand thatthe principles of the present disclosure may be implemented in any suitably arranged system or device.

[0070] FIG. 1 illustrates a block diagram depicting a communication system 100 (hereinafter may also be referred to as a “system 100”) for monitoring the performance of nodes in a communication network, in accordance with an embodiment of the present disclosure. The embodiment of the communication system 100 shown in FIG. 1 is for illustration only. Other embodiments of the communication system 100 may be used without departing from the scope of the present disclosure.

[0071] As shown in FIG. 1, the communication system 100 includes a network 110, wireless nodes 120 (hereinafter may also be referred to as a “wireless node 120” or “nodes 120” or simply a “node 120”) such as a gNodeB (gNB for e.g., base station), a user device 130, a server 140, a first database 150, and a second database 160.

[0072] The wireless node 120 communicates with the network 110, such as an Internet, a proprietary Internet Protocol (IP) network, or other data network. The network 110 may include wired and / or wireless networks. For example, the network 110 may include a cellular network for e.g., a Fifth Generation (5G) network, a Long-Term Evolution (LTE) network, a Third Generation (3G) network, a Code Division Multiple Access (CDMA) network, etc.), a Public Land Mobile Network (PLMN), a Local Area Network (LAN), a Wide Area Network (WAN), a Metropolitan Area Network (MAN), a telephone network (e.g., the Public Switched Telephone Network (PSTN)), a private network, an ad hoc network, an intranet, the Internet, a fiber optic-based network, or the like, and / or a combination of these or other types of networks.

[0073] The wireless node 120 communicates with the server 140 via the network 110. The wireless node 120 provides wireless broadband access to the network 110. The wireless node 120 may communicate with the user device 130 or the server 140 using any one of a 5G / New Radio (NR), LTE, LTE Advanced (LTE- A), Worldwide Interoperability for Microwave Access (WiMAX), Wireless Fidelity (Wi-Fi), orother wireless communication techniques. In an implementation, the wireless node 120 may be referred to as “base station”.

[0074] The term “base station” may refer to any component (or collection of components) configured to provide wireless access to a network, such as Transmit Point (TP), Transmit-Receive point (TRP), an Evolved Base Station (eNodeB or eNB), a 5G / NR base station (gNB), a macrocell, a femtocell, a WiFi Access Point (AP), or other wirelessly enabled devices. The base stations may provide wireless access in accordance with wireless communication protocols, e.g., 5G / NR 3GPP new radio interface / access (NR), LTE, LTE-A, High Speed Packet Access (HSPA), Wi-Fi 802.11a / b / g / n / ac, etc.

[0075] The user device 130 includes a User Interface (UI) 130-1 and a communication unit 130-2. The UI 130-1 facilitates display of the list of the vendors, the node types of the nodes associated with the vendors, a geographical location, a time period, a frequency for generating the comparative performance metrics report and the KPI metrics corresponding to the node types. The UI 130-1 enables the end users to select and specify their preferences for generation of the comparative performance metrics report.

[0076] The communication unit 130-2 may include antennas, Radio Frequency (RF) transceivers, a transmit processing circuitry, and a receive processing circuitry. Additionally, the user device 130 may further include circuitry, programing, applications, or a combination thereof. Further, the “user device” may refer to any component such as “mobile station,” “subscriber station,” “remote terminal,” “wireless terminal,” “receive point,” or “end user device,”. For the sake of convenience, the term “user device” used in this disclosure refers to a remote wireless equipment that wirelessly accesses the wireless node 120 and the server 140 via the network 110.

[0077] The server 140 is configured to control functionalities of the system 100, process user inputs, and generate performance metrics reports. The server 140 is further configured to handle a call flow between the UI 130-1 of the user device 130and components of the server 140, for generating the comparative performance metrics report and determining a performance metrics trend corresponding to multiple nodes associated with the same or different vendors. The server 140 is configured to control the UI 130-1 of the user device 130 and components of the server 140, for displaying the determined performance trend. The embodiment of the server 140 as shown in FIG. 1 is for illustration only. However, the server 140 may come in a wide variety of configurations, and FIG. 1 does not limit the scope of the present disclosure to any particular implementation of the server 140.

[0078] The server 140 includes a memory 142, a processor 144, a scheduler 146, and a communication interface 148 including communication circuitry.

[0079] The memory 142 stores a set of instructions required by the processor 144 of the server 140 for controlling its overall operations. Specifically, the memory 142 stores a microservices framework 142-1 via which the processor 144 initiates an Application Programming Interface (API) call request, when an input including a selection of attributes associated with the vendors and Key Performance Indicators (KPIs) associated with a type of a set of nodes among the nodes associated with the vendors is received by the processor 144. The microservices framework 142-1 represents individual services for specific tasks, such as handling requests and processing data. The microservices framework 142-1 within the memory 142 allows the server 140 to break down entire operations of the server 140 into smaller, independent services that may be developed, deployed, and scaled independently. Each of the microservices framework may adhere to a well-defined API.

[0080] Further, the memory 142 may include non-volatile storage elements. Examples of such non-volatile storage elements may include magnetic hard discs, optical discs, floppy discs, flash memories, or forms of Electrically Programmable Memories (EPROM) or Electrically Erasable and Programmable Memories (EEPROM). In addition, the memory 142 may, in some examples, be considered a non-transitory storage medium. The "non-transitory" storage medium is not embodied in a carrier wave or a propagated signal. However, the term "non-transitory" should not be interpreted as the memory 142 is non-movable. In some examples, the memory 142 may be configured to store larger amounts of information. In certain examples, a non-transitory storage medium may store data that can, over time, change (e.g., in Random Access Memory (RAM) or cache). The memory 142 may be an internal storage unit or an external storage unit of the server 140, cloud storage, or any other type of external storage.

[0081] The processor 144 is configured to execute programs and other processes stored in the memory 142. The processor 144 is further configured to store data in the memory 142 and fetch the data from the memory 142 as required by an execution process. The processor 144 may also be coupled to a network interface that may allow the server 140 to communicate with other devices or systems over a network. The network interface may support communications over any suitable wired or wireless connect! on(s). The processor 144 may further include a plurality of processors, including a general -purpose processor, such as, for example, and without limitation, a Central Processing Unit (CPU), an Application Processor (AP), a dedicated processor, or the like, a graphics-only processing unit such as a Graphics Processing Unit (GPU).

[0082] The scheduler 146 is communicatively connected to the processor 144. The scheduler 146 is configured to schedule execution of analytical tasks and job workflows allocated by the processor 144 such as data aggregation, triggering of analytics, and updating in-memory data caches. The scheduler 146 triggers regular data pulls from the second database 160. This ensures that the system 100 always works with the most recent data.

[0083] The communication interface 148 includes an electronic circuit specific to a standard that enables wired or wireless communication. The communication interface 148 is configured to communicate internally between internal hardware components. The communication interface 148 may be further configured to communicate with external devices via one or more networks.

[0084] The first database 150 may correspond to a centralized database system configured to store and manage structured data, such as network-related data and configurations. The first database 150 may be a relational database organizing related data such as in a table, or a non-relational database organizing graphical and time series data. The first database 150 may be utilized by the processor 144 for storing request configurations from the end users. The first database 150 further stores selected attributes for generating the comparative performance metrics report. The first database 150 may be utilized by the processor 144 for storing the request configurations from the users and data related to the determined trends from the comparative performance metrics report.

[0085] The second database 160 may be integrated within the server 140 for storing the comparative performance metrics report generated by the processor 144 and other operational data. The comparative performance metrics report includes the data associated with a count of alarms associated with a plurality of nodes of one or more vendors in the communication network. The second database 160 is configured to provide a scalable and fault-tolerant storage system, capable of handling entire operation specific data across distributed clusters of files associated with the server 140. In an implementation, the second database 160 corresponds to a distributed file system.

[0086] The second database 160 further stores values of the KPIs associated with the type of the set of nodes. The type of the set of nodes is from the nodes associated with the vendors within one or more geographical regions. The type of the set of nodes comprises an outdoor small node, an indoor small node, a macro node, and the like. The outdoor small node may correspond to a low power, short-range base station deployed outdoors to improve network capacity and coverage in areas with high user density. Examples of the outdoor small node may include microcells (installed on streetlights, traffic signals, utility poles, and the like, in urban areas to boost 5G coverage), outdoor Wi-Fi hotspots (deployed in public parks, stadiums, transport hubs, etc. for broadband Internet), and the like.

[0087] The indoor small node may correspond to a low power cellular, or Wi-Fi network device deployed inside buildings to improve signal coverage and network capacity in indoor environments. The indoor small node may help in overcoming signal loss due to walls, furniture, and other obstacles that weaken macro cell signals. Examples of the indoor small node may include femtocells, picocells, and the like.

[0088] The macro node corresponds to a high-powered base station designed to provide wide area coverage, typically forming the backbone of mobile networks. Examples of the macro node may include cell towers (traditional 4G LTE and 5G towers covering highways, cities, rural areas), rural base stations, and the like. The type of the set of nodes is same for each vendor of the one or more vendors.

[0089] Although FIG. 1 illustrates one example of a communication system 100, various changes may be made to FIG. 1. For example, the communication system 100 may include any number of nodes and any number of user devices in any suitable arrangement. Further, in another example, the server 140 may include any number of components in addition to the components shown in FIG. 1. Further, various components in FIG. 1 may be combined, further subdivided, or omitted and additional components may be added according to particular needs.

[0090] FIG. 2 illustrates a block diagram depicting various components of the processor 144 of the communication system 100, in accordance with an embodiment of the present disclosure.

[0091] The processor 144 may include units / modules selected from any of an acquisition module 144-1, an execution module 144-2 and a data processing module 144-3. The processor 144 may include, but are not limited to, other modules such as a generation module, an analytics module, a monitoring module, and the like. Each of the modules of the processor 144 may be communicatively connected to one another.

[0092] In an implementation, the processor 144, using the acquisition module 144- 1, is configured to receive, via the UI 130-1 of the user device 130, an input including a selection of the attributes associated with the vendors and the KPIs associated with the type of the set of nodes corresponding to the vendors within the geographical regions. In an implementation, the KPIs comprise a throughput, a latency, a payload, a signal strength, bandwidth utilization, packet loss during data transmission, and the like. In an example implementation, the user may select the attributes by applying filters such as vendors, a geographical region, product type, and a time period, and the KPIs such as a downlink throughput, the packet loss during data transmission, etc.

[0093] Furthermore, the processor 144, using the execution module 144-2 is configured to initiate the API call request to a first microservice i.e., microservice 1 among the microservices in response to the input from the end user via the UI 130- 1 of the user device 130. The microservice 1 acts as a request handler and a data manager. The microservice 1 processes user requests, stores configurations, and initiates further actions. The microservice 1 saves user request configurations into the first database 150.

[0094] For initiating the API call request to the first microservice, the execution module 144-2 is configured to create a request configuration associated with the API call request and store the created request configuration in the first database 150. The processor 144, using the execution module 144-2 is further configured to create, using the first microservice, a record of the selected attributes in the first database 150 upon initiation of the API call request. In an implementation, for creating the record of the attributes, the execution module 144-2 is configured to store the attributes in the first database 150. The API call request comprises a REST based API call request corresponding to the microservices.

[0095] The processor 144, using the execution module 144-2 is further configured to trigger the scheduler 146 to fetch values of the KPIs from the second database 160 upon creation of the record. In an implementation, to fetch the values of theKPIs from the second database 160, the execution module 144-2 is configured to detect the creation of the record of the attributes in the first database 150 and map, upon detecting the creation of the record, the attributes in the first database 150 to the corresponding KPI values stored in the second database 160. A mapping refers to a process of linking the attributes (such as the vendor details, node types, locations, or time periods, or the like) to their corresponding KPIs. The mapping ensures that the system 100 can correctly fetch and analyze performance data based on user inputs. The mapping process occurs between the first database 150 and the second database 160. For instance, in an example implementation of the mapping process, a network administrator wants to compare the latency and the throughput of Vendor A’s macro nodes with Vendor B's indoor small nodes over the last 24 hours. The execution module 144-2 of the processor 144 maps the attributes to the corresponding KPIs and retrieves the mapped KPI values from the second database 160. For instance, the execution module 144-2 retrieves: For Vendor A, macro node - Latency 30ms and throughput 100 Mbps and For Vendor B, indoor small node - Latency 20 ms and throughput 50 Mbps.

[0096] The processor 144, using the data processing module 144-3 is further configured to control the UI 130-1 to display the attributes for selection of the attributes. In an implementation, the attributes comprise at least one of details of the vendors, the type of the set of nodes, a geographical location of a service area of the set of nodes, a time period, a frequency for generating the comparative performance metrics report, and the like.

[0097] Further, the processor 144, using the data processing module 144-3, is configured to execute, via a second microservice i.e., microservice 2 among the plurality of microservices, a process for generating the comparative performance metrics report. The microservice 2 is responsible for communicating with other server components for data processing and report generation. The microservice 2 interacts with the second database 160 to store and provide generated reports. The microservice 1 is a lightweight service focused on managing the user requests, storing configurations, and triggering processing while the microservice 2 is acomputationally heavy service that helps in execution of data processing tasks and reports generation.

[0098] Further, the processor 144, using the data processing module 144-3, is configured to generate the comparative performance metrics report based on the fetched values of the KPIs upon execution of the process and control the UI 130-1 of the user device 130 to display the comparative performance metrics report.

[0099] The processor 144, using the data processing module 144-3, is further configured to determine, from the comparative performance metrics report, a count of alarms raised at the set of nodes for each vendor of the vendors. The count of alarms is determined in a service area with respect to a predefined time-period. Further, the processor 144, using the data processing module 144-3, is configured to determine a performance trend based on the count of alarms, and control the UI 130-1 to display the determined performance trend.

[0100] FIG. 3 illustrates a block diagram 300 depicting the call flow between the user device 130 and components of the server 140, in accordance with an embodiment of the present disclosure.

[0101] At step 302, the user device 130 sends the input to the acquisition module 144-1 of the processor 144 indicating the selection of the attributes associated with the vendors and the KPIs associated with one or more vendors of a plurality of vendors associated with the type of the set of nodes of the vendors. At step 304, the execution module 144-2 of the processor 144 initiates the API call request to the microservice 1 by creating the request configuration associated with the API call request. At step 306, the execution module 144-2 of the processor 144 stores the request configuration to the first database 150.

[0102] At step 308, a second microservice i.e., the microservice 2 retrieves the saved request configuration from the first database 150. At step 310, upon retrieving the saved request configuration from the first database 150, the processor 144 transmits the API call to the data processing module 144-3. At step 312, the dataprocessing module 144-3 of the processor 144 receives the values of the KPIs (fetched by the execution module 144-2 via the scheduler 146) from the second database 160. The data processing module 144-3 of the processor 144 is configured to generate the comparative performance metrics report indicating the performance comparison between the type of the set of nodes of at least a first vendor and a second vendor based on the fetched values of the KPIs. At step 314, the processor 144 is further configured to store the generated comparative performance metrics report in the second database 160. At step 316, the comparative performance metrics report is available for download (through a download option on the UI 130- 1) to the end user.

[0103] FIG. 4 illustrates an example UI 400 of a cognitive platform provided with multiple selectable attributes for visualizing the trends of performance metrics corresponding to the multiple nodes in the communication network, in accordance with an embodiment of the present disclosure.

[0104] The UI 400 is a part of a cognitive platform dashboard, designed for monitoring the alarm trends across the different vendors, technologies, and geographical locations. The UI 400 contains several key sections such as a main navigation panel (left side), a module search bar 412, a filter panel 414, a data visualization section (depicting bar chart), control buttons (apply, cancel, export and others). The main navigation panel includes a RAN tab 410 indicating that the user is currently monitoring RAN alarm trends. A navigation path 416 shows the user’s current path within the cognitive platform.

[0105] The module search bar 412 allows the users to quickly find specific modules, or reports without manually browsing the UI 400. The module search bar 412 may further include an auto suggestion feature for faster navigation.

[0106] The filter panel 414 allows the users to refine the displayed performance metrics data based on selection of the attributes and the KPIs, offering customization to meet needs of the users for generating the comparative performance metrics report. The filter panel 414 includes various options such as a technology selector414-1, a vendor selector 414-2, a geography selector 414-3, a product type selector 414-4, a vendor KPI selector 414-5, a date range selector 414-6, and the like.

[0107] The technology selector 414-1 corresponds to a dropdown menu for selecting different network technologies (3G, 4G, 5G, etc.). The vendor selector 414-2 allows the users to choose between multiple network vendors (vendor 1, vendor 2 etc.). The vendor selector 414-2 may allow the users to compare the performance of the nodes of same or different vendors. The geography selector 414- 3 allows the users to filter the performance metrics data based on a geographical location of a service area of the product types to analyze the alarm trends.

[0108] The product type selector 414-4 allows the users to filter alarms based on network product type (an outdoor small node, an indoor small node, a macro node, or the like). The product type selector 414-4 may thus allow the users to specify the node type the users want to compare. The users may choose the node type(s) from the list of available nodes. The UI 400 may support the selection of node(s) of the same vendor or across multiple vendors, providing flexibility in comparative analysis.

[0109] The vendor KPI selector 414-5 includes dropdown menus for selecting the KPIs rated to the multiple vendors for performance comparisons. The date range selector 414-6 allows the users to select a date range to visualize the alarm trends. The date range selector 414-6 may allow the users to specify a time duration over which the users want to analyze performance data of the nodes. In an embodiment, the users may choose from predefined time intervals (e.g., daily, weekly, monthly, quarterly, or annually) or specify custom date ranges.

[0110] The UI 400 further incudes an apply button and a cancel button. The apply button allows the users to update the data visualization based on the selected filters. The cancel button resets the filters to their default state. The data visualization panel may include a bar chart visualization representing the alarm trends across different geographical locations or time intervals. The X axis in the bar chart may represent the time period, while the Y axis may represent an alarm count.

[0111] The UI 400 thus allows the users to select the KPIs including one or more of a reliability, speed, retainability and the like corresponding to the one or more node types. The users may select a frequency of data updates, ensuring that the analysis reflects most current information available about the nodes. By enabling the users to select the vendors, the geographies, the node types, the KPIs, the time period and the frequency for generating the comparative performance metrics report, the UI 400 empowers the network operation teams to gain valuable insights and make data-driven decisions to improve product quality.

[0112] FIG. 5 illustrates a flowchart depicting a method 500 (hereinafter may also be interchangeably referred to as a “process 500”) for monitoring the performance of the nodes in the communication network, in accordance with an embodiment of the present disclosure. The method 500 comprises a series of operation steps indicated by blocks 502 through 516. Although the method 500 shows example blocks of steps 502 to 516, in some embodiments, the method 500 may include additional steps, fewer steps or steps in different order than those depicted in FIG. 5. In other embodiments, the steps 502 to 516 may be combined or may be performed in parallel. The method 500 starts at block 502.

[0113] At block 502, the acquisition module 144-1 of the processor receives, via the UI 130-1 of the user device 130, the input including the selection of the attributes associated with the vendors and the KPIs associated with the type of the set of nodes corresponding to the vendors within the one or more geographical regions.

[0114] At block 504, the execution module 144-2 of the processor 144 initiates the API call request to the first microservice i.e., the microservice 1 among the microservices in response to the input from the end user via the UI 130-1 of the user device 130.

[0115] At block 506, the execution module 144-2 of the processor 144 creates the record of the selected attributes in the first database 150 upon initiation of the API call request.1

[0116] At block 508, the execution module 144-2 of the processor 144 triggers the scheduler 146 to fetch values of the KPIs from the second database 160 upon creation of the record.

[0117] At block 510, the data processing module 144-3 of the processor 144 generates the comparative performance metrics report based on the fetched values of the KPIs upon execution of a report generation process. The data processing module 144-3 then controls the UI 130-1 of the user device 130 to display the comparative performance metrics report.

[0118] At block 512, the data processing module 144-3 of the processor 144 stores the generated comparative performance metrics report in the second database 160. The comparative performance metrics report is available for download (through the download option on the UI 130-1) to the end user.

[0119] At block 514, the data processing module 144-3 of the processor 144 determines, from the comparative performance metrics report, the performance trend based on the count of alarms raised at the set of nodes for each vendor. The count of alarms is determined in the service area with respect to the predefined timeperiod.

[0120] At block 514, the data processing module 144-3 of the processor 144 stores data related to the determined trend of the generated performance metrics report in the first database 150.

[0121] FIG. 6 illustrates a schematic architecture diagram depicting a computing system 600, in accordance with an embodiment of the present disclosure. The computing system 600 includes a network 602, a network interface 604, a processor 606 (similar in functionality to the processor 144 of FIG. 2), an Input / Output (I / O) interface 608 and a non-transitory computer readable storage medium 610 (hereinafter may also be referred to as the “storage medium 610” or the “storage media 610”).

[0122] The network interface 604 includes wireless network interfaces such as Bluetooth, Wi-Fi, Worldwide Interoperability for Microwave Access (WiMAX), General Packet Radio Service (GPRS), or Wideband Code Division Multiple Access (WCDMA) or wired network interfaces such as Ethernet, Universal Serial Bus (USB), or Institute of Electrical and Electronics Engineers-864 (IEEE-864).

[0123] The processor 606 may include various processing circuitry and communicate with the storage medium 610 and the VO interface 608. The processor 606 is configured to execute instructions stored in the storage medium 610 and to perform various processes. The processor 606 may include an intelligent hardware device including a general-purpose processor, such as, for example, and without limitation, the CPU, the AP, the dedicated processor, or the like, the graphics-only processing unit such as the GPU, the microcontroller, the FPGA, the programmable logic device, the discrete hardware component, or any combination thereof. The processor 606 may be configured to execute computer-readable instructions 610-1 stored in the storage medium 610 to cause the server 140 to perform various functions.

[0124] The storage medium 610 stores a set of instructions i.e., computer program instructions 610-1 (hereinafter may also be referred to as instructions 610-1) required by the processor 606 for controlling its overall operations and a UI framework 710-2 to control the UI 130-1 of the user device 130.

[0125] The storage media 610 may include an electronic storage medium, a magnetic storage medium, an optical storage medium, a quantum storage medium, or the like. For example, the storage media 610 may include, but are not limited to, hard drives, floppy diskettes, optical disks, ROMs, RAMs, EPROMs, EEPROMs, flash memory, magnetic or optical cards, solid-state memory devices, or other types of physical media suitable for storing electronic instructions. In one or more embodiments, the storage media 610 includes a Compact Disk-Read Only Memory (CD-ROM), a Compact Disk-Read / Write (CD-R / W), and / or a Digital Video Disc (DVD).

[0126] In one or more implementations, the storage medium 610 stores computer program code configured to cause the computing system 600 to perform at least a portion of the processes and / or methods. Accordingly, in at least one implementation, the computing system 600 performs the method for monitoring the performance of the nodes in the communication network.

[0127] Embodiments of the present disclosure have been described above with reference to flowchart illustrations of methods and systems according to embodiments of the disclosure, and / or procedures, algorithms, steps, operations, formulae, or other computational depictions, which may also be implemented as computer program products. In this regard, each block or step of the flowchart, and combinations of blocks (and / or steps) in the flowchart, as well as any procedure, algorithm, step, operation, formula, or computational depiction can be implemented by various means, such as hardware, firmware, and / or software including one or more computer program instructions embodied in computer-readable program code. As will be appreciated, any such computer program instructions may be executed by one or more computer processors, including without limitation a general -purpose computer or special purpose computer, or other programmable processing apparatus to perform a group of operations comprising the operations or blocks described in connection with the disclosed method.

[0128] Further, these computer program instructions, such as embodied in computer-readable program code, may also be stored in one or more computer- readable memory or memory devices (for example, the memory 142 or the storage medium 610) that can direct a computer processor or other programmable processing apparatus to function in a particular manner, such that the instructions 610-1 stored in the computer-readable memory or memory devices produce an article of manufacture including instruction means which implement the function specified in the block(s) of the flowchart(s).

[0129] It will further be appreciated that the term “computer program instructions” as used herein refer to one or more instructions that can be executed by the one ormore processors (for example, the processor 144 or the processor 606) to perform one or more functions as described herein. The instructions 610-1 may also be stored remotely such as on a server, or all or a portion of the instructions can be stored locally and remotely.

[0130] Now, referring to the technical abilities and advantageous effect of the present disclosure, operational advantages that may be provided by one or more embodiments may include providing provide a system and a method that enables the Q A team to select any performance metrics corresponding to the multiple nodes associated with the vendors so that the QA team can take remedial actions timely and with ease.

[0131] Another noteworthy advantage offered by one or more embodiments of the present disclosure may include, but not limited thereto, providing a system and a method that enable the end user to visualize the node wise trend of the performance metrics for the user selected KPIs for the multiple nodes associated with the vendors in the wireless network.

[0132] Ayet another advantage offered by one or more embodiments of the present disclosure may include providing a system and a method that facilitates assessing the performance of the multiple nodes for any geography in one go thereby reducing time and effort spent on the manual comparison of the node wise trend of the performance metrics.

[0133] Apotential advantage of the one or more embodiments disclosed herein may include providing a system and a method that eliminates the need for an exhaustive analysis of the performance metrics, thereby reducing the time and effort required.

[0134] Those skilled in the art will appreciate that the methodology described herein in the present disclosure may be carried out in other specific ways than those set forth herein in the above disclosed embodiments without departing from essential characteristics and features of the present invention. The above-describedembodiments are therefore to be construed in all aspects as illustrative and not restrictive.

[0135] The drawings and the forgoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, orders of processes described herein may be changed and are not limited to the manner described herein. Any combination of the above features and functionalities may be used in accordance with one or more embodiments.

[0136] In the present disclosure, each of the embodiments has been described with reference to numerous specific details which may vary from embodiment to embodiment. The foregoing description of the specific embodiments disclosed herein may reveal the general nature of the embodiments herein that others may, by applying current knowledge, readily modify and / or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications are intended to be comprehended within the meaning of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and is not limited in scope.LIST OF REFERENCE NUMERALS

[0137] The following list is provided for convenience and in support of the drawing figures and as part of the text of the specification, which describe innovations by reference to multiple items. Items not listed here may nonetheless be part of a given embodiment. For better legibility of the text, a given reference number is recited near some, but not all, recitations of the referenced item in the text. The same reference number may be used with reference to different examples or different instances of a given item. The list of reference numerals is:100 - Communication System / System110 - Network120 - Wireless Node / Node130 - User Device130-1 - User Interface (UI)130-2 - Communication Unit140 - Server142 - Memory142-1 - Microservices Framework144 - Processor144-1 - Acquisition Module144-2 - Execution Module144-3 - Data Processing Module146 - Scheduler148 - Communication Interface150 - First Database / Database160 - Second Database / Distributed File System300- Block diagram depicting call flow between user device and server components400 - Example UI410 - RAN tab412 - Module Search Bar414 - Filter Panel414-1 - Technology selector414-2 - Vendor option414-3 - Geography selector414-4 - Product type selector414-5 - Vendor KPI selector414-6 - Date range selector416 - Navigation path500 - Method for monitoring performance of nodes600 - Computing System602 - Network604 - Network interface606 - Processor 608 - I / O Interface610 - Storage Medium 610-1 - Instructions 610-2 - UI framework

Claims

We Claim:

1. A method (500) for monitoring performance of nodes (120) in a communication network, the method (500) comprising: receiving, from a user device (130) by an acquisition module (144-1), an input including a selection of one or more attributes associated with one or more vendors of a plurality of vendors and one or more Key Performance Indicators (KPIs), wherein the one or more KPIs are associated with a type of a set of nodes among a plurality of nodes (120) associated with the one or more vendors; initiating, by an execution module (144-2), an Application Programming Interface (API) call request to a first microservice among a plurality of microservices based on the input; creating, by the execution module (144-2) using the first microservice, a record of the one or more attributes in a first database (150) upon initiation of the API call request; triggering, by the execution module (144-2), a scheduler (146) to fetch values of the one or more KPIs from a second database (160) upon creation of the record; and generating, by a data processing module (144-3), a comparative performance metrics report indicating a performance comparison between the type of the set of nodes of at least a first vendor and a second vendor among the plurality of vendors based on the fetched values of the one or more KPIs.

2. The method (500) as claimed in claim 1, wherein for creating the record of the one or more attributes, the method (500) comprises storing, by the extraction module (144-2), the one or more attributes in the first database (150).

3. The method (500) as claimed in claim 1, wherein to fetch the values of the one or more KPIs from the second database (160), the method (500) comprises: detecting the creation of the record of the one or more attributes in the first database (150);mapping, upon detecting the creation of the record, the one or more attributes in the first database (150) to the corresponding KPI values stored in the second database (160); and retrieving the mapped KPI values from the second database (160).

4. The method (500) as claimed in claim 1, comprising: executing, by the data processing module (144-3), via a second microservice among the plurality of microservices, a process for generating the comparative performance metrics report; generating, by the data processing module (144-3), the comparative performance metrics report based on the fetched values of the one or more KPIs upon execution of the process; and controlling, by the data processing module (144-3), a User Interface (UI) (130-1) of the user device (130) to display the comparative performance metrics report.

5. The method (500) as claimed in claim 4, comprising: determining, by the data processing module (144-3) from the comparative performance metrics report, a count of alarms raised at the set of nodes for each vendor of the one or vendors, wherein the count of alarms is determined in a service area with respect to a predefined time-period; determining, by the data processing module (144-3), a performance trend based on the count of alarms; and controlling, by the data processing module (144-3), the UI (130-1) to display the determined performance trend.

6. The method (500) as claimed in claim 1, wherein the one or more attributes comprise at least one of details of the one or more vendors, the type of the set of nodes, a geographical location of a service area of the set of nodes, a time period, and a frequency for generating the comparative performance metrics report, andthe first database (150) corresponds to a relational database and the second database (160) corresponds to a distributed file system.

7. The method (500) as claimed in claim 1, further comprising controlling, by the data processing module (144-3), the user device (130) to display, on the UI (130- 1), a list of the one or more attributes corresponding to the one or more vendors and the one or more KPIs, wherein the input corresponds to a selection operation to select at least one attribute from the list of the one or more attributes.

8. The method (500) as claimed in claim 1, wherein: the type of the set of nodes comprises one or more of an outdoor small node, an indoor small node, and a macro node; and the type of the set of nodes is same for each vendor of the one or more vendors.

9. The method (500) as claimed in claim 1, wherein the API call request comprises a Representational State Transfer (REST) based API call request corresponding to the plurality of microservices.

10. A system (100) for monitoring performance of nodes in a communication network, the system (100) comprising: an acquisition module (144-1) configured to receive, from a user device (130), an input including a selection of one or more attributes associated with one or more vendors of a plurality of vendors and one or more Key Performance Indicators (KPIs), wherein the one or more KPIs are associated with a type of a set of nodes among a plurality of nodes (120) associated with the one or more vendors; and an execution module (144-2) configured to: initiate, based on the input, an Application Programming Interface (API) call request to a first microservice among a plurality of microservices;create, using the first microservice, a record of the one or more attributes in a first database (150) upon initiation of the API call request; and trigger a scheduler (146) to fetch, upon creation of the record, values of the one or more KPIs from a second database (160); and a data processing module (144-3) configured to generate, based on the fetched values of the one or more KPIs, a comparative performance metrics report indicating a performance comparison between the type of the set of nodes of at least a first vendor and a second vendor among the plurality of vendors.

11. The system (100) as claimed in claim 1, wherein for creating the record of the one or more attributes, the extraction module (144-2) is configured to store the one or more attributes in the first database (150).

12. The system (100) as claimed in claim 10, wherein to fetch, using the scheduler (146), the values of the one or more KPIs from the second database (160), the execution module (144-2) is configured to: detect the creation of the record of the one or more attributes in the first database (150); map, upon detecting the creation of the record, the one or more attributes in the first database (150) to the corresponding KPI values stored in the second database (160); and retrieve the mapped KPI values from the second database (160).

13. The system (100) as claimed in claim 10, wherein the data processing module (144-3) is configured to: execute, via a second microservice among the plurality of microservices, a process for generating the comparative performance metrics report; generate, upon execution of the process, the comparative performance metrics report based on the fetched values of the one or more KPIs; and control a User Interface (UI) (130-1) of the user device (130) to display the comparative performance metrics report.

14. The system (100) as claimed in claim 13, wherein the data processing module (144-3) is configured to: determine, from the comparative performance metrics report, a count of alarms raised at the set of nodes for each vendor of the one or vendors, wherein the count of alarms is determined in a service area with respect to a predefined timeperiod; determine a performance trend based on the count of alarms; and control the UI (130-1) to display the determined performance trend.

15. The system (100) as claimed in claim 10, wherein the one or more attributes comprise at least one of details of the one or more vendors, the type of the set of nodes, a geographical location of a service area of the set of nodes, a time period, and a frequency for generating the comparative performance metrics report, and the first database (150) corresponds to a relational database and the second database (160) corresponds to a distributed file system.

16. The system (100) as claimed in claim 10, wherein the data processing module (144-3) is configured to control the user device (130) to display, on the UI (130-1), a list of the one or more attributes corresponding to the one or more vendors and the one or more KPIs, and wherein the input corresponds to a selection operation to select at least one attribute from the list of the one or more attributes.

17. The system (100) as claimed in claim 10, wherein: the type of the set of nodes comprises one or more of an outdoor small node, an indoor small node, and a macro node; and the type of the set of nodes is same for each vendor of the one or more vendors.

18. The system (100) as claimed in claim 10, wherein the API call request comprises a Representational State Transfer (REST) based API call request corresponding to the plurality of microservices.

19. A computer program product comprising computer-executable instructions that are stored on a non-transitory computer-readable medium and that, when executed by at least one processor (144) performs operations comprising: receiving, from a user device (130), an input including a selection of one or more attributes associated with one or more vendors of a plurality of vendors and one or more Key Performance Indicators (KPIs), wherein the one or more KPIs is associated with a type of a set of nodes among a plurality of nodes (120) associated with the one or more vendors; initiating, based on the input, an Application Programming Interface (API) call request to a first microservice among a plurality of microservices; creating, using the first microservice, a record of the one or more attributes in a first database (150) upon initiation of the API call request; triggering a scheduler (146) to fetch, upon creation of the record, values of the one or more KPIs from a second database (160); and generating, based on the fetched values of the one or more KPIs, a comparative performance metrics report indicating a performance comparison between the type of the set of nodes of at least a first vendor and a second vendor among the plurality of vendors.

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