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 DYNAMICALLY MANAGING BULK PROVISIONING
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 relates to fulfillment management systems, more particularly relates to a system and a method dynamically managing bulk provisioning in the fulfillment management systems.
BACKGROUND OF THE INVENTION
[0002] Telecommunication service provisioning and activation systems, such as those that provision voice, data and/or video, are constantly evolving to fulfill the market request in a very competitive environment. Many provisioning and service activation systems today have been built for a few services and for specific network technology and may require the coding of new adapters as new network elements are added to the system. Further, provisioning of new services and changes may also require coding of new service logic to fulfill the activation of those services toward the network.
[0003] In the context of 3GPP (3rd Generation Partnership Project), provisioning is essential for service providers to efficiently allocate resources, activate services, and manage configurations, leading to enhanced network performance, subscriber satisfaction, and overall operational efficiency. With growth in the number and complexity of available services, bulk provisioning services toward the network created challenges across different networks and organizational departments. In the case of bulk provisioning, files are created for the provisioning, and copied to a remote server. The same files are fetched from the server based on request and response from a user. In conventional methods, when a file is created, changes in API, server credentials or details, for example changes in username and password, or location of the server, coding and deployment changes are required for bulk provisioning, which might be time consuming as it requires full time from change to deployment of application.
[0004] Hence, there exists a need for an improved method and system for dynamic bulk provisioning in fulfillment management system, particularly for changes in details of API, files and servers, which should make the process easy and faster for provisioning changes and reduces the time for the development and deployment of application at code level.
SUMMARY OF THE INVENTION
[0005] One or more embodiments of the present disclosure provide a method and a system for dynamically managing bulk provisioning.
[0006] In one aspect of the present invention, the system for dynamically managing bulk provisioning is disclosed. The system includes a transceiver configured to receive a bulk provisioning request from a Northbound Interface (NBI). The system further includes a creating unit configured to create, utilizing a model, a workflow for the bulk provisioning utilizing one or more parameters retrieved based on the received bulk provisioning request from the NBI. The system further includes a workflow manager configured to execute the workflow for the bulk provisioning based on the one or more parameters.
[0007] The system further includes a dynamic activator, configured to detect utilizing the model, changes in the one or more parameters based on monitoring the one or more parameters during executing the workflow. Further, the dynamic activator is configured to dynamically modify in real time, the workflow for the bulk provisioning based on the changes detected in the one or more parameters.
[0008] In an embodiment, the workflow manager is configured to execute the workflow for the bulk provisioning based on the one or more parameters, by creating, a bulk file for the bulk provisioning, replicating, the created bulk file at a server and transmitting, the bulk provisioning request to one or more southbound nodes for a file transfer requirement and the bulk provisioning.
[0009] In an embodiment, the model is at least one of an Artificial Intelligence/Machine Learning (AI/ML) model. In an embodiment, the one or more parameters include at least one of, Application Programming Interface (API) details, bulk file details, bulk file name, bulk file format, bulk file path, details and credentials of the server where the created bulk file is replicated. In an embodiment, the model is trained with historical data pertaining to the one or more parameters of the workflow. In an embodiment, the server is at least one of a Secure Copy Protocol (SCP) server.
[0010] In an embodiment, the dynamic activator detects, utilizing the model, changes in the one or more parameters based on monitoring the one or more parameters during executing the workflow, by detecting, a change in one or more current parameters of the workflow based on comparing the one or more current parameters with historical data pertaining to the one or more parameters of the workflow.
[0011] In an embodiment, the dynamic activator enables a user to modify the one or more parameters via a user interface required for the bulk provisioning and the file transfer details.
[0012] In another aspect of the present invention, the method for dynamically managing bulk provisioning is disclosed. The method includes the step of receiving a bulk provisioning request from a Northbound Interface (NBI). The method further includes the step of creating, utilizing a model, a workflow for the bulk provisioning utilizing one or more parameters retrieved based on the received bulk provisioning request from the NBI. The method further includes the step of executing the workflow for the bulk provisioning based on the one or more parameters. The method further includes the step of detecting, utilizing the model, changes in the one or more parameters based on monitoring the one or more parameters during executing the workflow. The method further includes the step of dynamically modifying in real time, the workflow for the bulk provisioning based on the changes detected in the one or more parameters.
[0013] 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
[0014] 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.
[0015] FIG. 1 is an exemplary block diagram of an environment for dynamically managing bulk provisioning, according to one or more embodiments of the present invention;
[0016] FIG. 2 an exemplary block diagram of a system for dynamically managing bulk provisioning, according to one or more embodiments of the present invention;
[0017] FIG. 3 is a schematic representation of a workflow of the system of FIG. 1, according to the one or more embodiments of the present invention;
[0018] FIG. 4 is an exemplary block diagram of an architecture of the system of dynamically managing bulk provisioning, according to one or more embodiments of the present invention;
[0019] FIG. 5 is a schematic representation of a method for dynamically managing bulk provisioning, according to one or more embodiments of the present invention; and
[0020] FIG. 6 is an exemplary flow diagram for dynamically managing bulk provisioning, according to one or more embodiments of the present invention.
[0021] The foregoing shall be more apparent from the following detailed description of the invention.
DETAILED DESCRIPTION OF THE INVENTION
[0022] 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.
[0023] 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.
[0024] 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.
[0025] As per various embodiments depicted, the present invention discloses a system and a method for dynamically managing bulk provisioning.
[0026] FIG. 1 illustrates an exemplary block diagram of an environment 100 for dynamically managing bulk provisioning, according to one or more embodiments of the present disclosure. In this regard, the environment 100 includes a User Equipment (UE) 102, a server 104, a network 106 and a system 108 communicably coupled to each other for dynamically managing bulk provisioning. The UE 102 aids a user to interact with the system 108 for executing the workflow for the bulk provisioning.
[0027] As per the illustrated embodiment and for the purpose of description and illustration, the UE 102 includes, but not limited to, a first UE 102a, a second UE 102b, and a third UE 102c, and should nowhere be construed as limiting the scope of the present disclosure. In alternate embodiments, the UE 102 may include a plurality of UEs as per the requirement. For ease of reference, each of the first UE 102a, the second UE 102b, and the third UE 102c, will hereinafter be collectively and individually referred to as the “User Equipment (UE) 102”.
[0028] In an embodiment, the UE 102 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.
[0029] The environment 100 includes the server 104 accessible via the network 106. The server 104 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 defence facility side, or any other facility that provides service.
[0030] The network 106 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 106 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.
[0031] The network 106 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 106 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.
[0032] The environment 100 further includes the system 108 communicably coupled to the server 104 and the UE 102 via the network 106. The system 108 is configured to dynamically manage bulk provisioning. As per one or more embodiments, the system 108 is adapted to be embedded within the server 104 or embedded as an individual entity.
[0033] Operational and construction features of the system 108 will be explained in detail with respect to the following figures.
[0034] FIG. 2 is an exemplary block diagram of the system 108 for dynamically managing bulk provisioning, according to one or more embodiments of the present invention.
[0035] As per the illustrated embodiment, the system 108 includes one or more processors 202, a memory 204, a user interface 206, and a database 208. For the purpose of description and explanation, the description will be explained with respect to one processor 202 and should nowhere be construed as limiting the scope of the present disclosure. In alternate embodiments, the system 108 may include more than one processors 202 as per the requirement of the network 106. The one or more processors 202, hereinafter referred to as the processor 202 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.
[0036] As per the illustrated embodiment, the processor 202 is configured to fetch and execute computer-readable instructions stored in the memory 204. The memory 204 may be configured to store one or more computer-readable instructions or routines in a non-transitory computer-readable storage medium, which may be fetched and executed to create or share data packets over a network service. The memory 204 may include any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as disk memory, EPROMs, FLASH memory, unalterable memory, and the like.
[0037] In an embodiment, the user interface 206 includes a variety of interfaces, for example, interfaces for a graphical user interface, a web user interface, a Command Line Interface (CLI), and the like. The user interface 206 facilitates communication of the system 108. In one embodiment, the user interface 206 provides a communication pathway for one or more components of the system 108. Examples of such components include, but are not limited to, the UE 102 and the database 208.
[0038] The database 208 is one of, but not limited to, 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 308 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.
[0039] In order for the system 108 to dynamically manage bulk provisioning, the processor 202 includes one or more modules. In one embodiment, the one or more modules includes, but not limited to, a transceiver 210, a creating unit 212, a workflow manger 214, and a dynamic activator 216 communicably coupled to each other to dynamically manage bulk provisioning.
[0040] The transceiver 210, the creating unit 212, the workflow manger 214, and the dynamic activator 216 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 202. 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 202 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 204 may store instructions that, when executed by the processing resource, implement the processor. In such examples, the system 108 may comprise the memory 204 storing the instructions and the processing resource to execute the instructions, or the memory 204 may be separate but accessible to the system 108 and the processing resource. In other examples, the processor 202 may be implemented by electronic circuitry.
[0041] In one embodiment, the transceiver 210 of the system 108 is configured to receive a bulk provisioning request from a Northbound Interface (NBI). The bulk provisioning refers to the process of simultaneously provisioning multiple items or resources in large quantities. The bulk provisioning request typically involves but not limited to, the simultaneous creation, modification, or allocation of multiple resources or items based on a single request. The NBI is an application programming interface (API) or protocol that allows a lower-level network component to communicate with a higher-level or more central component. The lower-level network component includes but not limited to, switches, routers, Access Points (APs), Network Interface Cards (NICs), hubs, firewalls and network load balancers. The higher-level or more central component includes but not limited to, Software-Defined Networking (SDN) controller, Network Management System (NMS), orchestration platform, policy management server, network analytics platform, Service Function Chaining (SFC) controller, and cloud orchestrator.
[0042] Upon receiving the bulk provisioning request, the creating unit 212 is configured to create a workflow for the bulk provisioning. The workflow of the bulk provisioning is created by utilizing a model and the one or more parameters. The one or more parameters are retrieved based on the received bulk provisioning request from the NBI. The workflow is a series of steps or tasks that are executed in a specific sequence to achieve a particular goal or objective. The workflow includes but is not limited to, policy-based workflow, service provisioning workflow, traffic engineering workflow, event-driven workflow, and analytics-driven workflow. The model is at least one of an Artificial Intelligence/Machine Learning (AI/ML) model. The AI/ML models is at least one of supervised learning models, unsupervised learning models, reinforcement learning models, deep learning models, and Natural Language Processing (NLP) models. The model is trained with historical data pertaining to the one or more parameters of the workflow. The historical data refers to part data collected over a period of time that is relevant to the parameters and processes involved in the workflow. The historical data includes, but not limited to, past request data, workflow parameters data, performance metrics, user and system interaction logs, environmental data, outcome data. The one or more parameters include at least one of but not limited to, Application Programming Interface (API) details, bulk file details, bulk file name, bulk file format, bulk file path, details and credentials of the server 104 where the created bulk file is replicated. The API details refer to the specification and information required to interact with the API. The API details include, but not limited to, endpoint Uniform Resource Locators (URLs), Hyper Text Transfer Protocol (HTTP) methods such as (GET, POST, PUT, DELETE), authentication information, headers, request and response formats, rate limits. The bulk file details refer to the comprehensive information about the bulk file to be processed. The bulk file details include, but not limited to bulk file name, bulk file format, bulk file path, file size, data structure. The bulk file name is a specific name assigned to the bulk file. The bulk file format refers to the structure and encoding of the data within the file. The bulk file format includes, but is not limited to, Comma-Separated Values (CSV), JavaScript Object Notation (JSON), Extensible Markup Language (XML), plain text (TXT). The bulk file path is the directory or location where the bulk file is stored. The bulk file path includes, but is not limited to, absolute path, relative path, network path.
[0043] Upon creating the workflow, the workflow manager 214 is configured to execute the workflow for the bulk provisioning based on the one or more parameters. The workflow manager 214 executes the workflow for the bulk provisioning based on the one or more parameters by creating a bulk file for the bulk provisioning. Upon creating the bulk file for the bulk provisioning, the workflow manager 214 replicates the created bulk file at the server 104. The server 104 is at least one of a but not limited to, Secure Copy Protocol (SCP) server.
[0044] On replicating the created bulk file, the workflow manager 214 transmits the bulk provisioning request to one or more southbound nodes for a file transfer requirement and the bulk provisioning. The one or more southbound nodes refer to devices, components, or interfaces that are responsible for communication between higher-level network management systems (such as controllers or orchestrators) and the physical or virtual network infrastructure. The one or more southbound nodes includes but not limited to, network functions, switches and routers, Access Points (APs), firewalls and security appliances, load balancers, virtual switches, Software- Defined Networking (SDN) controllers.
[0045] Upon transmitting the bulk provisioning request to one or more southbound nodes by workflow manager 214, the dynamic activator 216 is configured to detect the changes in one or more parameters. The changes in the one or more parameters are detected based on monitoring the one or more parameters during executing the workflow by utilizing the model. The dynamic activator 216 detects the changes in one or more parameters by detecting a change in a one or more current parameters of the workflow. The one or more current parameters refers to the one or more parameters present in real time. More specifically, the change in the one or more current parameters of the workflow is detected based on comparing the one or more current parameters with historical data pertaining to the one or more parameters of the workflow.
[0046] Upon detecting the change in the one or more current parameters, the dynamic activator 216 enables a user using the UE 102 to modify the one or more parameters. The user modifies the one or more parameters via the user interface 206 required for the bulk provisioning and the file transfer details. Thereafter, the dynamic activator 216 dynamically modifies the workflow for the bulk provisioning based on the changes detected in the one or more parameters. Thus, the bulk provisioning is managed dynamically. By doing so, the system 108 improves the processing speed of the processor 202 by configuring the bulk requests without requiring any change at code level. Thus, the development and deployment time of the processor 202 is saved.
[0047] In an embodiment, the system 108 also automatically detects the number of requests. If the number of requests is more, the system 108 pushes the number of requests in bulk instead of single pushing and fall back to single once the load is stabilized. The sudden increase in number of requests can be due to any failure on Southbound Interface (SBI) leading to queuing or sudden push of orders or requests from NBI etc.

[0048] FIG. 3 describes a preferred embodiment of the system 108 of FIG. 2, according to various embodiments of the present invention. It is to be noted that the embodiment with respect to FIG. 3 will be explained with respect to the first UE 102a and the system 108 for the purpose of description and illustration and should nowhere be construed as limited to the scope of the present disclosure.
[0049] As mentioned earlier in FIG. 1, each of the first UE 102a the second UE 102b, and the third UE 102c may include an external storage device, a bus, a main memory, a read-only memory, a mass storage device, communication port(s), and a processor. The exemplary embodiment as illustrated in FIG. 3 will be explained with respect to the first UE 102a. The first UE 102a includes one or more primary processors 302 communicably coupled to the one or more processors 202 of the system 108.
[0050] The one or more primary processors 302 are coupled with a memory unit 304 storing instructions which are executed by the one or more primary processors 302. Execution of the stored instructions by the one or more primary processors 302 enables the first UE 102a to change the one or more parameters, in a real time while executing the workflow for the bulk provisioning based on an input received from the user via the user interface of the UE 102.
[0051] As mentioned earlier in FIG. 2, the one or more processors 202 of the system 108 is configured to dynamically manage bulk provisioning. As per the illustrated embodiment, the system 108 includes the one or more processors 202, the memory 204, the user interface 206, and the database 208. The operations and functions of the one or more processors 202, the memory 204, the user interface 206, and the database 208 are already explained in FIG. 2. For the sake of brevity, a similar description related to the working and operation of the system 108 as illustrated in FIG. 2 has been omitted to avoid repetition.
[0052] Further, the processor 202 includes the transceiver 310, the creating unit 212, the workflow manager 214, and the dynamic activator 216. The operations and functions of the transceiver 310, the creating unit 212, the workflow manager 214, and the dynamic activator 216 are already explained in FIG. 2. Hence, for the sake of brevity, a similar description related to the working and operation of the system 108 as illustrated in FIG. 2 has been omitted to avoid repetition. The limited description provided for the system 108 in FIG. 3, should be read with the description as provided for the system 108 in the FIG. 2 above, and should not be construed as limiting the scope of the present disclosure.
[0053] FIG. 4 is an exemplary block diagram of an architecture 400 of the system 108 of dynamically managing bulk provisioning, according to one or more embodiments of the present invention.
[0054] According to the exemplary embodiment, the system 108 includes, but may not be limited to, an operation and management unit 402, the workflow manager 214, the dynamic activator 216, a message broker 404, a graph database 406, a distributed data lake database 408, a cache data store 410, a load balancer 412, the user interface 206, and a dynamic routing management 414.
[0055] In an embodiment, the user interface 206 receives the bulk provisioning request form the UE 102. Upon receiving the bulk provisioning request, the user interface 206 transmits the bulk provisioning request to the operation and management unit 402. The operation and management unit 402 creates the workflow for the bulk provisioning. The workflow for the bulk provisioning is created by utilizing the model and the one or more parameters retrieved based on the received bulk provisioning request. The model is at least one of the Artificial Intelligence/Machine Learning (AI/ML) model. The model is trained with historical data pertaining to the one or more parameters of the workflow. The one or more parameters include at least one of, Application Programming Interface (API) details, bulk file details, bulk file name, bulk file format, bulk file path, details and credentials of the server 104 where the created bulk file is replicated.
[0056] Upon creating the workflow for the bulk provisioning, the operation and management unit 402 transmits the created workflow to the workflow manager 214. The workflow manager 214 executes the workflow for the bulk provisioning based on the one or more parameters. The workflow manager 214 executes the workflow for the bulk provisioning by creating the bulk file for the bulk provisioning. Upon creating the bulk file, the workflow manager 214 replicates the created bulk file at the server 104. Thereafter the workflow manager 214 transmits the bulk provisioning request to one or more southbound nodes for the file transfer requirement and the bulk provisioning. Further, the workflow manager 214 includes a message broker 404 and a graph database 406. The message broker 404 and the graph database 406 stores the executed workflow for the bulk provisioning.
[0057] The workflow manager 214 executes the workflow with the help of the dynamic activator 216. The dynamic activator 216 detects the changes in the one or more parameters by utilizing the model. The changes in the one or more parameters are detected based on monitoring the one or more parameters during executing the workflow. The dynamic activator 216 detects the changes in one or more parameters by detecting a change in the one or more current parameters of the workflow. The detection is performed based on comparing the one or more current parameters with historical data pertaining to the one or more parameters of the workflow. The historical data pertaining to the one or more parameters of the workflow are fetched from a distributed data lake 408 and a cache data store 410.
[0058] The distributed data lake 408 is a data storage repository that centralizes, organizes, and protects large amounts of structured, semi-structured, and unstructured data pertaining to the details associated with the execution of the workflow from the dynamic activator 216. The cache data store 410 helps in storing recently stored data or frequently accessed data pertaining to the details associated with the execution of the workflow. Further, the dynamic routing manager 414 is configured to fetch details associated with the execution of the workflow from the distributed data lake 408 and the cache data store 410.
[0059] In an embodiment, the dynamic activator 216 enables the user to modify the one or more parameters via the user interface 206 required for the bulk provisioning and the file transfer details. Thereafter, the dynamic activator 216 dynamically modifies the workflow for the bulk provisioning based on the changes detected in the one or more parameters. For instance, in case of a change in the bulk provisioning API, then the user may log into the user interface and change the workflow and the same workflow may be reflected in the provisioning and the workflow manager may execute the same workflow as the same way for the previous workflow.
[0060] In an embodiment, the load balancer 412 is communicably coupled with the dynamic activator 216 and the user interface 206. The load balancer 412 dynamically balances the workflows for the bulk provisioning at the dynamic activator 216.
[0061] FIG. 5 is a flow diagram of a method 500 for dynamically managing bulk provisioning, according to one or more embodiments of the present invention. For the purpose of description, the method 500 is described with the embodiments as illustrated in FIG. 2 and should nowhere be construed as limiting the scope of the present disclosure.
[0062] At step 502, the method 500 includes the step of receiving the bulk provisioning request from the NBI by the transceiver 210.
[0063] At step 504, the method 500 includes the step of creating the workflow for the bulk provisioning by the creating unit 212. The workflow for the bulk provisioning is created by utilizing the model and the one or more parameters retrieved based on the received bulk provisioning request from the NBI.
[0064] At step 506, the method 500 includes the step of executing the workflow for the bulk provisioning based on the one or more parameters by the workflow manager 214. The step of executing the workflow for the bulk provisioning includes the step of creating the bulk file for the bulk provisioning. The step of executing the workflow for the bulk provisioning further includes the step of replicating the created bulk file at the server 104. The step of executing the workflow for the bulk provisioning further includes the step of transmitting the bulk provisioning request to one or more southbound nodes for a file transfer requirement and the bulk provisioning.
[0065] At step 508, the method 500 includes the step of detecting, utilizing the model, changes in the one or more parameters based on monitoring the one or more parameters during executing the workflow by the dynamic activator 216. The step of detecting the changes in the one or more parameters includes the step of detecting a change in one or more current parameters of the workflow. The detection is performed based on comparing the one or more current parameters with historical data pertaining to the one or more parameters of the workflow.
[0066] At step 510, the method 500 includes the step of dynamically modifying the workflow for the bulk provisioning based on the changes detected in the one or more parameters in real time by dynamic activator 216.
[0067] FIG. 6 is an exemplary flow diagram for dynamically managing bulk provisioning, according to one or more embodiments of the present invention.
[0068] According to the illustrated flow diagram, the bulk provisioning request is received from the NBI 602. The NBI 602 transmits the bulk provisioning request to FMS 604 for creating the workflow for the bulk provisioning request by utilizing the model and the one or more parameters. Upon receiving the bulk provisioning request, the FMS 604 creates the workflow and transfers the file to the SCP server 606. Simultaneously, the FMS 604 transmits the request of bulk provision to a state one, then to a state two in an order and then completes the response for the request of bulk provision. The state 1 and the state 2 are basically the Application Programming Interface (API) invocation which gets executed sequentially to different network nodes such as Policy Control Function (PCF), Unified Data Management (UDM) etc. If the API gets changed to state one or state two, or if any username and password of the SCP server 606 gets changed or the location of the server gets changed, then from FMS user interface 608 these details may be changed using the FMS user interface 608.
[0069] The present invention further discloses a non-transitory computer-readable medium having stored thereon computer-readable instructions. The computer-readable instructions are executed by the processor 202. The processor 202 is configured to receive, a bulk provisioning request from a Northbound Interface (NBI). The processor 202 is further configured to create, utilizing a model, a workflow for the bulk provisioning utilizing one or more parameters retrieved based on the received bulk provisioning request from the NBI. The processor 202 is further configured to execute, the workflow for the bulk provisioning based on the one or more parameters. The processor 202 is further configured to detect utilizing the model, changes in the one or more parameters based on monitoring the one or more parameters during executing the workflow. The processor 202 is further configured to dynamically modify in real time, the workflow for the bulk provisioning based on the changes detected in the one or more parameters.
[0070] 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.
[0071] The present disclosure incorporates technical advancement that the system has the capability to configure bulk requests and no code level changes are required in the system. Thus, the development and deployment time is saved. All the details used for bulk provisioning and file transfer are made configurable so that any changes are easily performed in very trifling time frame.
[0072] 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

[0073] Environment- 100
[0074] User Equipment (UE)- 102
[0075] Server- 104
[0076] Network- 106
[0077] System -108
[0078] Processor- 202
[0079] Memory- 204
[0080] User Interface- 206
[0081] Database- 208
[0082] Transceiver- 210
[0083] Creating Unit- 212
[0084] Workflow Manager- 214
[0085] Dynamic activator- 216
[0086] Primary processor- 302
[0087] Memory- 304
[0088] Operation and Management Unit- 402
[0089] Message Broker- 404
[0090] Graph Database- 406
[0091] Distributed Data Lake- 408
[0092] Cache Data store- 410
[0093] Load Balancer- 412
[0094] Dynamic Routing Manager- 414

,CLAIMS:CLAIMS:

We Claim:
1. A method (500) for dynamically managing bulk provisioning, the method (500) comprising the steps of:
receiving, by one or more processors (202), a bulk provisioning request from a Northbound Interface (NBI);
creating, by the one or more processors (202), utilizing a model, a workflow for the bulk provisioning utilizing one or more parameters retrieved based on the received bulk provisioning request from the NBI;
executing, by the one or more processors (202), the workflow for the bulk provisioning based on the one or more parameters;
detecting, by the one or more processors (202), utilizing the model, changes in the one or more parameters based on monitoring the one or more parameters during executing the workflow; and
dynamically modifying in real time, by the one or more processors (202), the workflow for the bulk provisioning based on the changes detected in the one or more parameters.

2. The method (500) as claimed in claim 1, wherein the step of, executing, the workflow for the bulk provisioning based on the one or more parameters, includes the steps of:
creating, by the one or more processors (202), a bulk file for the bulk provisioning;
replicating, by the one or more processors (202), the created bulk file at a server (104); and
transmitting, by the one or more processors (202), the bulk provisioning request to one or more southbound nodes for a file transfer requirement and the bulk provisioning.

3. The method (500) as claimed in claim 1, wherein the model is at least one of, an Artificial Intelligence/Machine Learning (AI/ML) model.

4. The method (500) as claimed in claim 1, wherein the one or more parameters include at least one of, Application Programming Interface (API) details, bulk file details, bulk file name, bulk file format, bulk file path, details and credentials of the server (104) where the created bulk file is replicated.

5. The method (500) as claimed in claim 1, wherein the model is trained with historical data pertaining to the one or more parameters of the workflow.

6. The method (500) as claimed in claim 1, wherein the server (104) is at least one of a Secure Copy Protocol (SCP) server.

7. The method (500) as claimed in claim 1, wherein the step of, detecting, utilizing the model, changes in the one or more parameters based on monitoring the one or more parameters during executing the workflow, includes the step of:
detecting, by the one or more processors (202), a change in one or more current parameters of the workflow based on comparing the one or more current parameters with historical data pertaining to the one or more parameters of the workflow.

8. The method (500) as claimed in claim 1, wherein the one or more processor (202) enables a user to modify the one or more parameters via a user interface required for the bulk provisioning and the file transfer details.

9. A system (108) for dynamically managing bulk provisioning, the system (108) comprising:
a transceiver (210), configured to, receive, a bulk provisioning request from a Northbound Interface (NBI);
a creating unit (212) configured to, create, utilizing a model, a workflow for the bulk provisioning utilizing one or more parameters retrieved based on the received bulk provisioning request from the NBI;
a workflow manager (214), configured to, execute, the workflow for the bulk provisioning based on the one or more parameters;
a dynamic activator (216), configured to:
detect utilizing the model, changes in the one or more parameters based on monitoring the one or more parameters during executing the workflow; and
dynamically modify in real time, the workflow for the bulk provisioning based on the changes detected in the one or more parameters.

10. The system (108) as claimed in claim 9, wherein the workflow manager (214) is configured to execute, the workflow for the bulk provisioning based on the one or more parameters, by:
creating, a bulk file for the bulk provisioning;
replicating, the created bulk file at a server; and
transmitting, the bulk provisioning request to one or more southbound nodes for a file transfer requirement and the bulk provisioning.

11. The system (108) as claimed in claim 9, wherein the model is at least one of, an Artificial Intelligence/Machine Learning (AI/ML) model.

12. The system (108) as claimed in claim 9, wherein the one or more parameters include at least one of, Application Programming Interface (API) details, bulk file details, bulk file name, bulk file format, bulk file path, details and credentials of the server where the created bulk file is replicated.

13. The system (108) as claimed in claim 9, wherein the model is trained with historical data pertaining to the one or more parameters of the workflow.

14. The system (108) as claimed in claim 9, wherein the server (104) is at least one of a Secure Copy Protocol (SCP) server.

15. The system (108) as claimed in claim 9, wherein the dynamic activator (216) detects, utilizing the model, changes in the one or more parameters based on monitoring the one or more parameters during executing the workflow, by:
detecting, a change in one or more current parameters of the workflow based on comparing the one or more current parameters with historical data pertaining to the one or more parameters of the workflow.

16. The system (108) as claimed in claim 9, wherein the dynamic activator (216) enables a user to modify the one or more parameters via a user interface required for the bulk provisioning and the file transfer details.

17. A User Equipment (UE) (102), comprising:
one or more primary processors (302) communicatively coupled to one or more processors (202), the one or more primary processors (302) coupled with a memory (304), wherein said memory (304) stores instructions which when executed by the one or more primary processors (302) causes the UE (102) to:
changing, the one or more parameters, in a real time while executing the workflow for the bulk provisioning based on an input received from the user via a user interface (206) of the UE (102); and
wherein the one or more processors (202) is configured to perform the steps as claimed in claim 1.