DESC:
FORM 2
THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENTS RULES, 2003

COMPLETE SPECIFICATION
(See section 10 and rule 13)
1. TITLE OF THE INVENTION
METHOD AND SYSTEM FOR DYNAMIC CORRELATION WITH FAULT MANAGEMENT
2. APPLICANT(S)
NAME NATIONALITY ADDRESS
JIO PLATFORMS LIMITED INDIAN OFFICE-101, SAFFRON, NR. CENTRE POINT, PANCHWATI 5 RASTA, AMBAWADI, AHMEDABAD 380006, GUJARAT, INDIA
3.PREAMBLE TO THE DESCRIPTION

THE FOLLOWING SPECIFICATION PARTICULARLY DESCRIBES THE NATURE OF THIS INVENTION AND THE MANNER IN WHICH IT IS TO BE PERFORMED.

FIELD OF THE INVENTION
[0001] The present invention generally relates to wireless communication networks, and more particularly relates to a method and system for dynamic correlation with fault management.
BACKGROUND OF THE INVENTION
[0002] In a data processing system, one or more Key Performance Indicators (KPIs) are used to gauge the performance efficiency of the system. When one of the KPIs exceeds predefined minimum or maximum thresholds, an alarm must be raised to initiate actions to normalize the KPI that has breached the threshold. In this, analyzing the KPIs and comparing the KPI values to the predefined thresholds is a time-consuming process. Further, since rectification for the breached thresholds is performed by another person or entity, communicating the breached thresholds from one person or entity to the other also consumes time.
[0003] Therefore, there is a need for an efficient system and method for identifying threshold breaches by KPIs and providing alarms for the breaches instantaneously.
SUMMARY OF THE INVENTION
[0004] One or more embodiments of the present disclosure provide a method and a system for dynamic correlation with fault management.
[0005] In one aspect of the present invention, the method for dynamic correlation with fault management is disclosed. The method includes the step of receiving, by one or more processors, policies for one of Key Performance Indicators (KPIs) and counter data. The method includes the step of receiving, by the one or more processors, a dashboard execution request for checking thresholds predefined corresponding to the policies. The method includes the step of processing, by the one or more processors, the KPIs and counter data by checking with the policies. The method includes the step of fetching, by the one or more processors, alarm identifications (IDs) from a database. The method includes the step of forwarding, by the one or more processors, the alarm IDs to a Fulfillment Management System (FMS) by correlating dynamically with states of the alarms for the policies breaching the KPIs and the counter data.
[0006] In one embodiment, the step of pushing or removing, by the one or more processors, the alarms IDs based on the state of the alarms.
[0007] In another embodiment, the step of displaying, by the one or more processors, one of the KPIs and the counter data to the user.
[0008] In yet another embodiment, the step of categorizing, by the one or more processors, the alarms into active alarms and deactivated alarms based on the state of the alarms.
[0009] In yet another embodiment, the step of creating, by the one or more processors, the alarm IDs for one of the KPIs and the counter data having values below or above the thresholds.
[0010] In yet another embodiment, the step of clearing, by the one or more processors, the alarm IDs that are within the thresholds.
[0011] In yet another embodiment, the step of checking, by the one or more processors, the alarm IDs for determining whether the alarms are new or existing alarms.
[0012] In yet another embodiment, the step of removing, by the one or more processors, the alarms IDs if an alarm is an existing alarm.
[0013] In another aspect of the present invention, the system for dynamic correlation with fault management is disclosed. The system includes a receiving unit configured to receive policies for one of Key Performance Indicators (KPIs) and counter data. The receiving unit receives a dashboard execution request for checking predefined thresholds corresponding to the policies. The processing unit processes the KPIs and counter data by checking with the policies and predefined thresholds corresponding to the policies. The checking unit checks the thresholds and fetches one or more alarms from a database. The checking unit is configured to categorize the one or more alarms into active alarms and deactivated alarms based on the state of the alarms. The correlating unit is configured to correlate alarm identifications (IDs) with the policies breaching the KPIs and the counter data.
[0014] In another aspect of the present invention, a first User Equipment (UE) is disclosed. One or more primary processors communicatively coupled to one or more processors. The one or more primary processors coupled with a first memory. The first memory stores instructions which when executed by the one or more primary processors causes the first UE to transmit a dashboard execution request to the one or more processors.
[0015] In another aspect of the present invention, a second User Equipment (UE) is disclosed. One or more secondary processors communicatively coupled to one or more processors. The one or more secondary processors coupled with a second memory. The second memory stores instructions which when executed by the one or more primary processors causes the second UE to receive the new alarms or removal request of the alarms from the FMS to display the new alarms or removed alarms to the user via an FMS UI.
[0016] In another aspect of the present invention, a non-transitory computer-readable medium having stored thereon computer-readable instructions that, when executed by a processor is disclosed. The processor is configured to receive policies for one of Key Performance Indicators (KPIs) and counter data. The processor is configured to receive a dashboard execution request for checking predefined thresholds corresponding to the policies. The processor is configured to process the KPIs and counter data by checking with the policies and predefined thresholds corresponding to the policies. The processor is configured to check the thresholds and fetches alarms from a database. The processor is configured to categorize the alarms into active alarms and deactivated alarms based on the state of the alarms. The processor is configured to send alarm identifications (IDs) to a Fulfillment Management System (FMS) by correlating dynamically with states of the alarms for the policies breaching the KPIs and the counter data.
[0017] Other features and aspects of this invention will be apparent from the following description and the accompanying drawings. The features and advantages described in this summary and in the following detailed description are not all-inclusive, and particularly, many additional features and advantages will be apparent to one of ordinary skill in the relevant art, in view of the drawings, specification, and claims hereof. Moreover, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes and may not have been selected to delineate or circumscribe the inventive subject matter, resort to the claims being necessary to determine such inventive subject matter.
BRIEF DESCRIPTION OF THE DRAWINGS
[0018] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that disclosure of such drawings includes disclosure of electrical components, electronic components or circuitry commonly used to implement such components.
[0019] FIG. 1 is an exemplary block diagram of an environment for dynamic correlation with fault management, according to one or more embodiments of the present disclosure;
[0020] FIG. 2 is an exemplary block diagram of a system for dynamic correlation with fault management, according to one or more embodiments of the present disclosure;
[0021] FIG. 3 is a schematic representation of workflow of the system of FIG. 2, according to one or more embodiments of the present disclosure;
[0022] FIG. 4 is an exemplary block diagram of an architecture which can be implemented in the system of FIG. 2, according to one or more embodiments of the present disclosure;
[0023] FIG. 5 is a signal flow diagram illustrating the system for dynamic correlation with fault management, according to one or more embodiments of the present disclosure; and
[0024] FIG. 6 is a flow diagram illustrating a method for dynamic correlation with fault management, according to one or more embodiments of the present disclosure.
[0025] The foregoing shall be more apparent from the following detailed description of the invention.
DETAILED DESCRIPTION OF THE INVENTION
[0026] Some embodiments of the present disclosure, illustrating all its features, will now be discussed in detail. It must also be noted that as used herein and in the appended claims, the singular forms "a", "an" and "the" include plural references unless the context clearly dictates otherwise.
[0027] Various modifications to the embodiment will be readily apparent to those skilled in the art and the generic principles herein may be applied to other embodiments. However, one of ordinary skill in the art will readily recognize that the present disclosure including the definitions listed here below are not intended to be limited to the embodiments illustrated but is to be accorded the widest scope consistent with the principles and features described herein.
[0028] A person of ordinary skill in the art will readily ascertain that the illustrated steps detailed in the figures and here below are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosed embodiments.
[0029] Various implementations of the present disclosure provide dynamic correlation with fault management. The system of the present disclosure automatically highlights one or more Key Performance Indicators (KPIs) and counter data that have breached one or more predefined thresholds. Further, a Fulfillment Management System (FMS) automatically creates and provides alarms on display as long as the breach repeats itself in future.
[0030] In an embodiment, the system dynamically correlates alarm IDs based on states of the alarms with the policies breaching the KPIs and the counter data. The system is configured for creating the alarm-ids for the breaching KPIs and counter data. The system is configured for checking whether the alarms are new alarms or existing alarms. Further, the alarms are active, the system updates its state or severity. If not, the system is configured to generate a new alarm with an alarm identification. The FMS is configured to display the new alarm via the FMS UI. As new data comes in, the system re-evaluates the new alarm. If the previously breached threshold returns to normal, the system is configured to deactivate the alarm. Subsequently, the FMS is configured to display the removed alarms via an FMS User Interface (UI).
[0031] FIG. 1 illustrates an exemplary block diagram of an environment 100 for dynamic correlation with fault management, according to one or more embodiments of the present disclosure. The environment 100 includes a network 105, a User Equipment (UE) 110, a server 115, and a system 120. The UE 110 aids a user to interact with the system 120 to transmit a dashboard execution request to the one or more processors 205 (shown in FIG.2). The user includes at least one of, but not limited to, a network operator, or a service provider.
[0032] For the purpose of description and explanation, the description will be explained with respect to the UE 110, or to be more specific will be explained with respect to a first UE 110a, a second UE 110b, and a third UE 110c, and should nowhere be construed as limiting the scope of the present disclosure. Each of the UE 110 from the first UE 110a, the second UE 110b, and the third UE 110c is configured to connect to the server 115 via the network 105.
[0033] In an embodiment, each of the first UE 110a, the second UE 110b, and the third UE 110c is one of, but not limited to, any electrical, electronic, electro-mechanical or an equipment and a combination of one or more of the above devices such as virtual reality (VR) devices, augmented reality (AR) devices, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other computing device.
[0034] The network 105 includes, by way of example but not limitation, one or more of a wireless network, a wired network, an internet, an intranet, a public network, a private network, a packet-switched network, a circuit-switched network, an ad hoc network, an infrastructure network, a Public-Switched Telephone Network (PSTN), a cable network, a cellular network, a satellite network, a fiber optic network, or some combination thereof. The network 105 may include, but is not limited to, a Third Generation (3G), a Fourth Generation (4G), a Fifth Generation (5G), a Sixth Generation (6G), a New Radio (NR), a Narrow Band Internet of Things (NB-IoT), an Open Radio Access Network (O-RAN), and the like.
[0035] The network 105 may also include, by way of example but not limitation, at least a portion of one or more networks having one or more nodes that transmit, receive, forward, generate, buffer, store, route, switch, process, or a combination thereof, etc. one or more messages, packets, signals, waves, voltage or current levels, some combination thereof, or so forth. The network 105 may also include, by way of example but not limitation, one or more of a wireless network, a wired network, an internet, an intranet, a public network, a private network, a packet-switched network, a circuit-switched network, an ad hoc network, an infrastructure network, a Public-Switched Telephone Network (PSTN), a cable network, a cellular network, a satellite network, a fiber optic network, a VOIP or some combination thereof.
[0036] The environment 100 includes the server 115 accessible via the network 105. The server 115 may include by way of example but not limitation, one or more of a standalone server, a server blade, a server rack, a bank of servers, a server farm, hardware supporting a part of a cloud service or system, a home server, hardware running a virtualized server, one or more processors executing code to function as a server, one or more machines performing server-side functionality as described herein, at least a portion of any of the above, some combination thereof. In an embodiment, the entity may include, but is not limited to, a vendor, a network operator, a company, an organization, a university, a lab facility, a business enterprise side, a defense facility side, or any other facility that provides service.
[0037] The environment 100 further includes the system 120 communicably coupled to the server 115 and each of the first UE 110a, the second UE 110b, and the third UE 110c via the network 105. The system 120 is adapted to be embedded within the server 115 or is embedded as the individual entity. In an embodiment, the system 120 is also referred to as a Performance Management (PM) unit 410 (shown in FIG.3). The PM unit 410 helps the user to interrelate a set of activities, connecting the metrics, processes and systems used to monitor and manage business performance. The constant monitoring of the performance counters and Key Performance Indicators (KPIs) of the network elements minimizes the risk of failure and improves the quality, agility and relevance of business outcomes. The PM unit 410 is a platform where the user can perform all the requirements related to performance counters. However, for the purpose of description, the system 120 is illustrated as remotely coupled with the server 115, without deviating from the scope of the present disclosure.
[0038] The system 120 is further configured to employ Transmission Control Protocol (TCP) connection to identify any connection loss in the network 105 and thereby improving overall efficiency. The TCP connection is a communication standard enabling applications and the system 120 to exchange information over the network 105.
[0039] Operational and construction features of the system 120 will be explained in detail with respect to the following figures.
[0040] FIG. 2 illustrates an exemplary block diagram of the system 120 for dynamic correlation with fault management, according to one or more embodiments of the present disclosure. The system 120 includes one or more processors 205, a memory 210, the user interface 215, a distributed data lake 220, and a database 225. The one or more processors 205, hereinafter referred to as the processor 205 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, single board computers, and/or any devices that manipulate signals based on operational instructions. As per the illustrated embodiment, the system 120 includes one processor 205. However, it is to be noted that the system 120 may include multiple processors as per the requirement and without deviating from the scope of the present disclosure.
[0041] Among other capabilities, the processor 205 is configured to fetch and execute computer-readable instructions stored in the memory 210. The memory 210 may be configured to store one or more computer-readable instructions or routines in a non-transitory computer-readable storage medium, which may be fetched and executed to create or share data packets over a network service. The memory 210 may include any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROMs, FLASH memory, unalterable memory, and the like.
[0042] The user interface 215 includes a variety of interfaces, for example, interfaces for a Graphical User Interface (GUI), a web user interface, a Command Line Interface (CLI), and the like. The user interface 215 facilitates communication of the system 120. In one embodiment, the user interface 215 provides a communication pathway for one or more components of the system 120. Examples of the one or more components include, but are not limited to, the UE 110, the distributed data lake 220 and the database 225.
[0043] The distributed data lake 220 is a data repository providing storage and computing for structured and unstructured data, such as for machine learning, streaming, or data science. The distributed data lake 220 allows users and/or organizations to ingest and manage large volumes of data in an aggregated storage solution for business intelligence or data products. In an embodiment, the distributed data lake 220 and the database 225 are configured for storing the data. The distributed data lake 220 is configured to retrieve the data for a shorter period. In an exemplary embodiment, the shorter period corresponds to typically three to four days. The database 225 is configured to retrieve the data for a longer period such as on a monthly or a yearly basis.
[0044] The database 225 provides structured storage, support for complex queries, and enables efficient data retrieval and analysis. The database 225 is one of, but is not limited to, one of a centralized database, a cloud-based database, a commercial database, an open-source database, a distributed database, an end-user database, a graphical database, a No-Structured Query Language (NoSQL) database, an object-oriented database, a personal database, an in-memory database, a document-based database, a time series database, a wide column database, a key value database, a search database, a cache databases, and so forth. The foregoing examples of database types are non-limiting and may not be mutually exclusive e.g., a database can be both commercial and cloud-based, or both relational and open-source, etc.
[0045] Further, the processor 205, in an embodiment, may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processor 205. In the examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processor 205 may be processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for processor 205 may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the memory 210 may store instructions that, when executed by the processing resource, implement the processor 205. In such examples, the system 120 may comprise the memory 210 storing the instructions and the processing resource to execute the instructions, or the memory 210 may be separate but accessible to the system 120 and the processing resource. In other examples, the processor 205 may be implemented by electronic circuitry.
[0046] In order for the system 120 to dynamic correlation with fault management, the processor 205 includes a receiving unit 230, a processing unit 235, a creating unit 240, a fetching unit 245, a checking unit 250, a correlating unit 255, and the FMS 260 communicably coupled to each other for performing dynamic correlation with fault management. The operation and functionalities of the receiving unit 230, the processing unit 235, the creating unit 240, the fetching unit 245, the checking unit 250, the correlating unit 255, and the FMS 260 can be used in combination or interchangeably.
[0047] The receiving unit 230, the processing unit 235, the creating unit 240, the fetching unit 245, the checking unit 250, the correlating unit 255, and the FMS 260 in an embodiment, may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processor 205. In the examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processor 205 may be processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processor may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the memory 210 may store instructions that, when executed by the processing resource, implement the processor. In such examples, the system 120 may comprise the memory 210 storing the instructions and the processing resource to execute the instructions, or the memory 210 may be separate but accessible to the system 120 and the processing resource. In other examples, the processor 205 may be implemented by electronic circuitry.
[0048] The receiving unit 230 is configured to receive policies for one of Key Performance Indicators (KPIs) and counter data. The KPI is a quantifiable measure of performance over time for a specific objective. The KPIs include at least one of, but is not limited to, network availability, call drop rate, average call setup time, data throughput, latency, packet loss, and service activation time. In an exemplary embodiment, the determining percentage of time the network is operational and available for use within a month. The counter data includes at least one of, but is not limited to, number of active sessions, number of faults/trouble tickets, total data usage, call attempts, bandwidth utilization, and error rates. In an exemplary embodiment, the counter data includes the calculated count of reported faults or trouble tickets opened for network issues, which maybe, 100 trouble tickets per day. In an embodiment, the policies include one or more parameters. The one or more parameters include, but are not limited to, a call summary ratio, a call failure ratio, and the like. If the one or more parameters breaches the threshold of the KPI and the counter data, an alarm is generated. The policies for KPIs and counter data are designed to manage, measure, and evaluate the performance of various aspects of the network 105, the system 120, or organization. The policies for the KPIs and the counter data are stored in the distributed data lake 220.
[0049] Upon receiving the policies for one of the KPIs and counter data, further the receiving unit 230 is configured to receive the dashboard execution request for checking the predefined thresholds corresponding to the policies. The predefined thresholds involve comparing the one of the KPI and counter data against the set thresholds defined in the policies. The predefined thresholds corresponding to the policies are stored in the distributed data lake 220.
[0050] Upon receiving the dashboard execution request for checking the predefined thresholds, the processing unit 235 is configured to process the KPIs and counter data by checking with the predefined thresholds corresponding to the policies. The required KPIs and counter data are collected from the distributed data lake 220. The required KPIs and counter data are processed as required (e.g., hourly, daily, monthly). Upon processing the KPIs and counter data by checking with the policies and predefined thresholds, the fetching unit 245 is configured to fetch the alarms from the distributed data lake 220 and checks whether the one or more alarms are new or existing alarms. The one or more alarms are notifications or alerts generated by network elements, or systems to indicate the occurrence of issues or anomalies that may affect the performance, reliability, or security of the network. The one or more alarms help network operators detect, diagnose, and resolve problems quickly to maintain optimal network operation and service quality. Further, the one or more alarms can be categorized based on their severity, type, and source. The checking unit 250 is configured to check whether the KPIs and counter data breaches the predefined thresholds. If the KPIs and counter data breaches the predefined thresholds, then alarm IDs are created.
[0051] Upon fetching the one or more alarms from the distributed data lake 220, the creating unit 240 is configured to create the alarm IDs for the KPIs and counter data having values below or above the thresholds. Further, the creating unit 240 is configured to retrieve the existing alarms from the distributed data lake 220. The existing alarms are based on previously defined KPIs and counter data thresholds. For each KPI or counter data that breaches the threshold, the creating unit 240 is configured to generate an alarm ID. The created alarm IDs, along with relevant details (e.g., KPI name, threshold breached, severity, node identifier, actual value), are stored in the database 225 for further processing.
[0052] Upon creating the alarm IDs for the KPIs and counter data, the checking unit 250 is configured to categorize the one or more alarms into active alarms and deactivated alarms based on state of the one or more alarms. The active alarms are currently breaching thresholds of the KPIs and counter data. The deactivated alarms are within the thresholds of the KPIs and counter data. The checking unit 250 is further configured to request the FMS 260 to remove the alarm IDs that are within the thresholds of the KPIs and counter data. Upon clearing the alarm IDs, the cleared alarm IDs are updated in the database 225, for ensuring accurate and current alarm status. In an embodiment, the FMS 260 is configured to manage and automate the entire process of delivering telecom services to customers. The FMS 260 ensures that customer orders for services such as voice, data, internet, and other telecom services are accurately and efficiently processed from order initiation to service activation. Further, the FMS 260 enhances the efficiency and accuracy of service delivery, reduces fulfillment times, improves customer satisfaction, and optimizes the use of network resources.
[0053] As per one or more embodiments, upon creating the alarm IDs for KPIs and counter data, the correlating unit 255 is configured to dynamically correlate the alarm IDs based on with the policies breaching the KPIs and the counter data. For instance, if the KPI and counter data related to the network latency exceeds the predefined threshold, the correlating unit 255 is configured for checking whether the existing alarms are related to the network latency. If the one or more alarms is already active, the correlating unit 255 updates the state or the severity of the one or more alarms. If not, the correlating unit 255 is configured to generate the new alarm. The FMS 260 is configured to display the new alarm via a FMS User Interface (UI) 505 (as shown in FIG.5). As new data comes in the system 120, the correlating unit 255 re-evaluates the alarms. If the previously breached threshold of the KPI and counter data returns to a normal range (within the threshold), the correlating unit 255 is configured to deactivate the alarm. By doing so, the system 120 maintains sync and separation between two parties responsible for two different roles, performs automated alarm process, which reduces the processing time. The user can compare the data with the historical data where the checking unit 250 makes the comparison feasible, and using this, the one or more alarms are raised if the thresholds of the KPIs and counter data are breached.
[0054] FIG. 3 is a schematic representation of the system 120 in which various entities operations are explained, according to one or more embodiments of the present disclosure. Referring to FIG. 3, describes the system 120 for dynamic correlation with fault management. It is to be noted that the embodiment with respect to FIG. 3 will be explained with respect to the first UE 110a and the second UE 110b for the purpose of description and illustration and should nowhere be construed as limited to the scope of the present disclosure.
[0055] As mentioned earlier in FIG.1, in an embodiment, the first UE 110a may encompass electronic apparatuses. These devices are illustrative of, but not restricted to, personal computers, laptops, tablets, smartphones (including phones), or other devices enabled for web connectivity. The scope of the first UE 110a explicitly extends to a broad spectrum of electronic devices capable of executing computing operations and accessing networked resources, thereby providing users with a versatile range of functionalities for both personal and professional applications. This embodiment acknowledges the evolving nature of electronic devices and their integral role in facilitating access to digital services and platforms. In an embodiment, the first UE 110a can be associated with multiple users. Each user equipment 110 is communicatively coupled with the processor 205 via the network 105.
[0056] The first UE 110a includes one or more primary processors 305a communicably coupled to the one or more processors 205 of the system 120. The one or more primary processors 305a are coupled with a first memory 310a storing instructions which are executed by the one or more primary processors 305a. Execution of the stored instructions by the one or more primary processors 305a enables the first UE 110a to transmit the dashboard execution request to the one or more processors 205. In an embodiment, the dashboard execution request includes one or more KPI, one or more counters, and the policies created for breaching the thresholds of the KPI and the counter data.
[0057] Furthermore, the one or more primary processors 305a within the first UE 110a are uniquely configured to execute a series of steps as described herein. This configuration underscores the processor 205 capability to dynamic correlation with fault management. The operational synergy between the one or more primary processors 305a and the additional processors, guided by the executable instructions stored in the first memory 310a, facilitates a seamless dynamic correlation with the fault management.
[0058] As mentioned earlier in FIG.1, in an embodiment, the second UE 110b may encompass electronic apparatuses. The second UE 110b is one of, but not restricted to, personal computers, laptops, tablets, smartphones (including phones), or other devices enabled for web connectivity. The scope of the second UE 110b explicitly extends to a broad spectrum of electronic devices capable of executing computing operations and accessing networked resources, thereby providing users with a versatile range of functionalities for both personal and professional applications. This embodiment acknowledges the evolving nature of electronic devices and their integral role in facilitating access to digital services and platforms. In an embodiment, the second UE 110b can be associated with multiple users. Each user equipment 110 is communicatively coupled with the processor 205 via the network 105.
[0059] The second UE 110b includes one or more secondary processors 305b communicably coupled to the one or more processors 205 of the system 120. The one or more secondary processors 305b are coupled with a second memory 310b storing instructions which are executed by the one or more secondary processors 305b. Execution of the stored instructions by the one or more secondary processors 305b enables the second UE 110b to receive the new alarms or remove alarms from the FMS 260 to display the new alarms or remove alarms to the user via the FMS UI 505.
[0060] Furthermore, the one or more secondary processors 305b within the UE 110b are uniquely configured to execute a series of steps as described herein. This configuration underscores the processor 205 capability to dynamic correlation with fault management. The operational synergy between the one or more secondary processors 305b and the additional processors, guided by the executable instructions stored in the second memory 310b, facilitates a seamless dynamic correlation with the fault management.
[0061] As mentioned earlier in FIG.2, the system 120 includes the one or more processors 205, the memory 210, the user interface 215, the distributed data lake 220 and the database 225. The operations and functions of the one or more processors 205, the memory 210, the user interface 215, the distributed data lake 220 and the database 225 are already explained in FIG. 2. For the sake of brevity, a similar description related to the working and operation of the system 120 as illustrated in FIG. 2 has been omitted to avoid repetition.
[0062] Further, the processor 205 includes the receiving unit 230, the processing unit 235, the creating unit 240, the fetching unit 245, the checking unit 250, the correlating unit 255, and the FMS 260. The operations and functions of the receiving unit 230, the processing unit 235, the creating unit 240, the fetching unit 245, the checking unit 250, the correlating unit 255, and the FMS 260 are already explained in FIG. 2. Hence, for the sake of brevity, a similar description related to the working and operation of the system 120 as illustrated in FIG. 2 has been omitted to avoid repetition. The limited description provided for the system 120 in FIG. 3, should be read with the description provided for the system 120 in the FIG. 2 above, and should not be construed as limiting the scope of the present disclosure.
[0063] FIG. 4 is an exemplary block diagram of an architecture 400 that can be implemented in the system of FIG. 2, according to one or more embodiments of the present disclosure.
[0064] The architecture 400 of the system 120 includes the user interface 215, the distributed data lake 220, the database 225, a load balancer 405, the PM unit 410, a computation layer 415, an Operation and Management (OAM) unit 420, and the FMS 260.
[0065] The user provides the policies for the KPIs and counter data through the user interface 215. The load balancer 405 is configured to distribute the user requests or network traffic across multiple servers, preventing any single server from being overloaded. The load balancer 405 is configured to transmit the policies for the KPIs and counter data to the PM unit 410.
[0066] The PM unit 410 receives the policy creation request from the user interface 215 and stores the received policies on the distributed data lake 220. Upon storing the received policies in the distributed data lake 220, the PM unit 410 transmits the acknowledgement of the received policies to the user via the user interface 215. Subsequently, the user creates the dashboard execution request containing the required KPIs. The PM unit 410 is configured to compute the execution results for dashboards and report with the help of the computation layer 415 if needed. The PM unit 410 sends the data back to the user interface 215 and the user interface 215 displays the dashboard to the user. In parallel, the PM unit 410 creates the alarm-ids for the breaching KPIs and counter data. Then the PM unit 410 sends the request to the OAM unit 420 for pushing the alarms to the FMS 260. The OAM unit 420 is a centralized component within the system 120 that handles the overall management, monitoring, and operational control tasks. The OAM unit 420 ensures the system's optimal performance, reliability, and efficiency by executing a range of functions including configuration management, fault management, performance management, security management, and maintenance tasks.
[0067] The alarm IDs are created if the values of the KPI and counter data are below or above the threshold values. After creation of the new alarm IDs, the already raised alarm IDs are fetched from the distributed data lake 220. The PM unit 410 is configured to categorize the one or more alarms into active or deactivated alarms based on the state of the one or more alarms. If the KPI and the counter data of the one or more alarms breaches the predefined thresholds, then the one or more alarms are active to update its state or severity. In case the KPI and the counter data of the one or more alarms do not breach the predefined thresholds, the new alarm is generated with the unique alarm ID. In this regard, the already raised alarms (existing alarms) are fetched from the distributed data lake 220. In an embodiment, KPIs and counter data thresholds of the existing alarms are based on previously defined KPIs and counter data thresholds. Further, the PM 410 is configured to check whether the new alarm IDs are present in the existing alarms.
[0068] In addition, if the KPI and the counter data of the one or more alarms is not breaching the threshold values, the PM 410 transmits the removal request of the one or more alarms to the FMS 260 to deactivate the raised alarms by using the generated unique alarm ID. Then, the remove raised alarm is pushed to the FMS 260.

[0069] FIG. 5 is a signal flow diagram illustrating the system for dynamic correlation with fault management, according to one or more embodiments of the present disclosure.
[0070] At step 505, the user provides the policies for one of Key Performance Indicators (KPIs) and counter data to the user interface 215. The user interface is configured to request the load balancer 405 for transmitting one of the KPIs and counter data. The policies for KPIs and counter data are designed to manage, measure, and evaluate the performance of various aspects of the network 105, the system 120, or organization. The policies for KPIs and counter data are stored in the distributed data lake 220.
[0071] At step 510, the PM unit 410 transmits the acknowledgement of the policies stored and saved in the distributed data lake 220 to the load balancer 405. The load balancer 405 is configured to transmit the acknowledgement of the policies stored and saved in the distributed data lake 220 to the user via the user interface 215.
[0072] At step 515, upon receiving the stored policies for one of the KPIs and counter data, the user interface 215 of the user is configured to transmit the dashboard execution request for checking the predefined thresholds corresponding to the policies to the load balancer 405. In an embodiment, the at least one of, the KPI and the counter data is compared with the predefined thresholds corresponding to the policies. The predefined thresholds corresponding to the policies are stored in the distributed data lake 220. The load balancer 405 is configured to transmit the dashboard execution request to an available instance in the PM unit 410.
[0073] At step 520, upon receiving the dashboard execution request, the PM unit 410 is configured to transmit the dashboard execution request to the computation layer 415 if the data is in the shorter period (within three to four days). The computation layer 415 is configured to transmit acknowledgement of the received dashboard execution request to the PM unit 410. The computation layer 415 is configured to transmit the dashboard execution request to the database 225. The database 225 is configured to transmit the required KPI and counter data to the computation layer 415 to perform data computation process. Subsequently, the computation layer 415 is configured to transmit the KPIs and counter data to the PM unit 410.
[0074] At step 525, in an alternate embodiment, the PM unit 410 is configured to transmit the dashboard execution request to the distributed data lake 220 if the data is over the longer period (such as monthly, yearly basis). The distributed data lake 220 is configured to transmit the required KPI and counter data to the PM unit 410.
[0075] At step 530, upon computing the KPI and counter data, the PM unit 410 is configured to check the KPI and counter data with the predefined thresholds corresponding to the policies. The required KPIs and counter data are collected from the distributed data lake 220. The required KPIs and counter data are processed as required (e.g., hourly, daily, monthly). Upon processing the KPIs and counter data by checking with the policies and predefined thresholds, the computation layer 415 is configured to fetch the KPIs and counter data from the database 225. The computation layer 415 is configured to check whether the KPIs and counter data breaches the predefined thresholds or not. If the KPIs and counter data breaches the predefined thresholds, then the new alarm IDs are created.
[0076] At step 535, upon checking whether the KPIs and counter data breaches the predefined thresholds or not, the PM unit 410 is configured to fetch the alarms from the distributed data lake 220. The PM unit 410 is configured to create the alarm IDs for the KPIs and counter data having values below or above the thresholds. Further, the PM unit 410 is configured to retrieve the existing alarms from the distributed data lake 220. The existing alarms are based on previously defined KPIs and counter data thresholds. The created alarm IDs, along with relevant details (e.g., KPI name, threshold breached, severity, node identifier, actual value), are stored in the database 225 for further processing.
[0077] At step 540, upon creating the alarm IDs for the KPIs and counter data, the PM unit 410 is configured to categorize the one or more alarms into active alarms and deactivated alarms based on the state of the one or more alarms. The active alarms include those alarms which are currently breaching predefined thresholds of at least one of, the KPIs and counter data. The deactivate alarms are those alarms which are within the pre-defined thresholds of one of, the KPIs and counter data. If the one or more alarms are within the predefined thresholds, then there is no need for the alarms. In this regard, the PM unit 410 is configured to transmit the removal request of the alarm based on the state of the one or more alarms to the OAM 420.
[0078] At step S545, the OAM 420 is configured to transmit the removal request of the one or more alarms to the FMS 260 to deactivate the one or more alarms if the one or more alarms are within the thresholds of the KPIs and counter data. Further, the OAM 420 is configured to clear the alarm IDs of the one or more alarms that are within the thresholds of the KPIs and counter data. Upon clearing the alarm IDs, the cleared alarm IDs are updated in the database 225, for ensuring accurate and current alarm status.
[0079] As per one or more embodiments, upon creating the alarm IDs for KPIs and counter data, the OAM 420 is configured to transmit the alarm IDs to the FMS 260 by correlating dynamically the alarm IDs with the policies breaching the KPIs and the counter data. At step S550, the FMS UI 505 is configured to display the new alarms and already raised alarms to the user.
[0080] At step S555, Simultaneously, the PM unit 410 transmits the delta computed data along with a notification to the load balancer 405. The load balancer 405 is configured to transmit the delta computed data to the user interface 215. Then, the user interface 215 is configured to transmit an output of the delta computed data to the user.
[0081] FIG. 6 is a flow diagram illustrating a method 600 for dynamic correlation with fault management, according to one or more embodiments of the present disclosure.
[0082] At step 605, the method 600 includes the step of receiving the policies for one of Key Performance Indicators (KPIs) and counter data by the receiving unit 230. The policies for KPIs and counter data are rules or guidelines designed to manage, measure, and evaluate the performance of various aspects of the network 105, the system 120, or organization. The policies for KPIs and counter data are stored in the distributed data lake 220.
[0083] At step 610, the method 600 includes the step of receiving the dashboard execution request for checking the predefined thresholds corresponding to the policies by the receiving unit 230. The predefined thresholds involve comparing one of the KPI and counter data against the pre-defined thresholds defined in the policies. The predefined thresholds corresponding to the policies are stored in the distributed data lake 220 and the database 225.
[0084] At step 615, the method 600 includes the step of processing the KPIs and counter data by checking with the predefined thresholds corresponding to the policies by the processing unit 235. The required KPIs and counter data are collected from the distributed data lake 220. The required KPIs and counter data are processed as required (e.g., hourly, daily, monthly).
[0085] At step 620, the method 600 includes the step of fetching the alarms from the distributed data lake 220 by the fetching unit 245 and checks whether the one or more alarms are new or existing alarms. The checking unit 250 is configured to check whether the KPIs and counter data breaches the predefined thresholds. If the KPIs and counter data breaches the predefined thresholds, then the alarm IDs are created.
[0086] Upon fetching the alarms from the distributed data lake 220, the creating unit 240 is configured to create the alarm IDs for the KPIs and counter data having values below or above the thresholds. Further, the creating unit 240 is configured to retrieve the existing alarms from the distributed data lake 220. The existing alarms are based on previously defined KPIs and counter data thresholds. For each KPI or counter data that breaches the threshold, the creating unit 240 is configured to generate a unique alarm ID. The unique alarm ID is used to track and manage the alarm. The created alarm IDs, along with relevant details (e.g., KPI name, threshold breached, severity, node identifier, actual value), are stored in the database 225 for further processing.
[0087] Upon creating the alarm IDs for the KPIs and counter data, the checking unit 250 is configured to categorize the one or more alarms into active alarms and deactivated alarms based on state of the one or more alarms. In an embodiment, the active alarms are alarms which are currently breaching thresholds of the KPIs and the counter data. The deactivated alarms are alarms which are within the thresholds of the KPIs and counter data. The checking unit 250 is further configured to clear the alarm IDs that are within the thresholds of the KPIs and counter data. Upon clearing the alarm IDs, the cleared alarm IDs are updated in the database 225, for ensuring accurate and current alarm status. Further, the checking unit 250 is configured to request the FMS 260 to remove the alarms IDs if the alarm is the existing alarm.
[0088] At step 625, the method 600 includes the step of dynamically correlating the alarm IDs based on states of the alarms with the policies breaching the KPIs and the counter data by the correlating unit 255. If the alarm is already active, the correlating unit 255 updates its state or severity. If not, the correlating unit 255 is configured to generate the new alarm. The FMS 260 is configured to display the new alarm via the FMS UI 505. As new data comes in the system 120, the correlating unit 255 re-evaluates the alarms. If the previously breached threshold returns to normal, the correlating unit 255 is configured to deactivate the alarm in real-time.
[0089] The present invention discloses a non-transitory computer-readable medium having stored thereon computer-readable instructions. The computer-readable instructions are executed by a processor 205. The processor 205 is configured to receive policies for one of Key Performance Indicators (KPIs) and counter data. The processor 205 is configured to receive a dashboard execution request for checking predefined thresholds corresponding to the policies. The processor 205 is configured to process the KPIs and counter data by checking with the policies and predefined thresholds corresponding to the policies. The processor 205 is configured to check the thresholds and fetches alarms from a database. The processor 205 is configured to categorize the alarms into active alarms and deactivated alarms based on the state of the alarms. The processor 205 is configured to send alarm identifications (IDs) to a Fault Management System (FMS) by correlating dynamically with states of the alarms for the policies breaching the KPIs and the counter data.
[0090] A person of ordinary skill in the art will readily ascertain that the illustrated embodiments and steps in description and drawings (FIG.1-6) are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosed embodiments.
[0091] The present disclosure incorporates technical advancement of fetching the alarm IDs and transmitting the alarm IDs to the FMS by correlating dynamically with states of the alarms for the policies breaching the KPIs and the counter data. The present disclosure maintains sync and separation between two parties responsible for two different roles. The user has the flexibility to define the policies for the KPIs and counters according to the understanding for minimum and maximum thresholds. Further, the PM unit raises an alarm according to their severity whenever the thresholds with the respective policies are breached in the dashboard outputs. These alarms are forwarded to the FMS through the OAM unit which acts as a connector between the two.
[0092] The present invention provides various advantages which lies in the automation of alarm raising flow, which reduces the processing time. The user can compare one of, the KPI and counter data with the historical data pertaining to the KPI and the counter data using the PM unit, where the computation layer makes the comparison feasible, and using this, the alarms are raised if one of, the KPIs and the counter data breaches the predefined thresholds.
[0093] The present invention offers multiple advantages over the prior art and the above listed are a few examples to emphasize on some of the advantageous features. The listed advantages are to be read in a non-limiting manner.

REFERENCE NUMERALS
[0094] Environment – 100
[0095] Network – 105
[0096] User Equipment – 110
[0097] Server – 115
[0098] System – 120
[0099] Processor -205
[00100] Memory – 210
[00101] User Interface– 215
[00102] Distributed data lake – 220
[00103] Database- 225
[00104] Receiving unit – 230
[00105] Processing unit – 235
[00106] Creating unit – 240
[00107] Fetching unit- 245
[00108] Checking unit- 250
[00109] Correlating unit-255
[00110] Fault Management System- 260
[00111] One or more primary processors – 305a
[00112] First memory– 310a
[00113] One or more secondary processors – 305b
[00114] Second memory– 310b
[00115] Load balancer- 405
[00116] Performance Management unit- 410
[00117] Computation layer- 415
[00118] Operation and management- 420
[00119] FMS UI- 505

,CLAIMS:CLAIMS
We Claim:
1. A method (600) of dynamic correlation with fault management, the method (600) comprising the steps of:
receiving, by one or more processors (205), policies for one of Key Performance Indicators (KPIs) and counter data;
receiving, by the one or more processors (205), a dashboard execution request for checking predefined thresholds corresponding to the policies;
processing, by the one or more processors (205), the KPIs and counter data by checking with the policies;
fetching, by the one or more processors (205), one or more alarms from a database based on processing the KPIs and counter data, wherein the one or more alarms are generated with alarm identifications (IDs); and
dynamically correlating, by the one or more processors (205), the alarm IDs with the policies breaching the KPIs and the counter data.

2. The method (600) as claimed in claim 1, comprising the step of forwarding or removing, by the one or more processors (205), the alarms IDs to a Fulfillment Management System (FMS) (260) based on a state of the one or more alarms.

3. The method (600) as claimed in claim 1, comprising the step of displaying, by the one or more processors (205), one of the KPIs and the counter data to the user.

4. The method (600) as claimed in claim 1, comprising the step of categorizing, by the one or more processors (205), the one or more alarms into active alarms and deactivate alarms based on the state of the one or more alarms.

5. The method (600) as claimed in claim 1, comprising the step of creating, by the one or more processors (205), new alarm IDs for one of the KPIs and the counter data having values below or above the thresholds.

6. The method (600) as claimed in claim 1, comprising the step of clearing, by the one or more processors (205), the alarm IDs that are within the thresholds.

7. The method (600) as claimed in claim 1, correlating comprising the step of checking, by the one or more processors (205), the alarm IDs for determining whether the one or more alarms are new or existing alarms.

8. The method (600) as claimed in claim 6, comprising the step of transmitting, by the one or more processors (205), removal request of the one or more alarms to the FMS (260) if the one or more alarms are the existing alarm.

9. A system (120) for dynamic correlation with fault management, the system (120) comprising:
a receiving unit (230) configured to receive policies for one of Key Performance Indicators (KPIs) and counter data, wherein the receiving unit (230) receives a dashboard execution request for checking predefined thresholds corresponding to the policies;
a processing unit (235) configured to process the KPIs and counter data by checking with the policies and predefined thresholds corresponding to the policies,
a checking unit (250) configured to check the thresholds and fetches alarms from a database (225), wherein the checking unit (250) categorizes the alarms into active alarms and deactivated alarms based on state of the alarms, and
a correlating unit (255) configured to dynamically correlate alarm identifications (IDs) with the policies breaching the KPIs and the counter data.

10. The system (120) as claimed in claim 9, wherein a creating unit (240) is configured to create the new alarm IDs for one of the KPIs and counter data having values below or above the thresholds.

11. The system (120) as claimed in claim 9, wherein the checking unit (250) is further configured to clear the alarm IDs that are within the thresholds.

12. The system (120) as claimed in claim 9, wherein the correlating unit (255) is further configured to determine whether the one or more alarms are new or existing alarms.

13. The system (120) as claimed in claim 12, wherein the fetching unit (245) is configured to transmit the removal request of the alarms IDs to the FMS (260) if an alarm is an existing alarm.

14. The system (120) as claimed in claim 9, wherein the FMS (260) is configured to display the new or removed alarms.

15. A first User Equipment (UE) (110a) comprising:
one or more primary processors (305a) communicatively coupled to one or more processors (205), the one or more primary processors (305a) coupled with a first memory (310a), wherein said first memory (310a) stores instructions which when executed by the one or more primary processors (305a) causes the first UE (110a) to:
transmit a dashboard execution request to the one or more processors (205);
wherein the one or more processors (205) are configured to perform the steps as claimed in claim 1.

16. A second User Equipment (UE) (110b) comprising:
one or more secondary processors (305b) communicatively coupled to one or more processors (205), the one or more secondary processors (305b) coupled with a second memory (310b), wherein said second memory (310b) stores instructions which when executed by the one or more secondary processors (305b) causes the second UE (110b) to:
receive the new alarms or removal request of the alarms from the FMS (260) to display the new alarms or removed alarms to the user via an FMS UI (505).
wherein the one or more processors (205) are configured to perform the steps as claimed in claim 1.