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 DELETING DATA FROM A STORAGE DEVICE
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 the field of wireless communication networks, more particularly relates to a method and a system for deleting data from a storage device.
BACKGROUND OF THE INVENTION
[0002] In recent times, data storage has become a significant global concern. Storing large volumes of data necessitates substantial investments in storage facilities and equipment. Depending on the data size, storage can be managed through databases, repositories, or internal memory with various configurations.
[0003] In the rapidly evolving world of technology, the interaction between consumers and servers has become increasingly complex. Consumers frequently send multiple requests to servers, often utilizing APIs (Application Programming Interfaces) to facilitate these interactions. The role of the load balancer in this scenario is crucial. It distributes the incoming requests across a pool of servers to ensure that no single server becomes overwhelmed, thus maintaining optimal performance and reliability. Each of these consumer requests typically contains data that needs to be processed and stored. The data is often housed in databases within the system, which are designed to handle large volumes of information. In addition to the stored data, the system creates objects and variables during the processing of these requests. These objects and variables are temporarily stored in the system's internal memory, which needs to be managed efficiently to maintain system performance.
[0004] Internal memory management is a critical aspect of maintaining system efficiency. As the system processes numerous requests, it generates a multitude of objects and variables. Over time, some of these objects and variables become irrelevant or obsolete. Identifying and segregating these objects and variables is not a straightforward task. It requires a thorough evaluation of the internal memory to determine which objects and variables are no longer needed. This evaluation process can be labor-intensive and time-consuming. It involves scanning the internal memory to identify the objects and variables. Once identified, these elements must be purged, cleaned, or deleted to free up memory space. Alternatively, they can be moved to secondary storage options, such as backup memory. However, this transfer process can also be time-consuming and may require additional resources.
[0005] The consequences of not managing internal memory effectively can be severe. If the objects and variables are not removed promptly, the internal memory can become cluttered. Such clutter can lead to slower response times, as the system struggles to sift through unnecessary data to find relevant information. In extreme cases, the system might stop functioning altogether, leading to significant downtime and loss of productivity. To mitigate these issues, there is a pressing need for a robust system and method for managing internal memory. An efficient memory management system would automate the process of identifying and purging data. By doing so, it would ensure that the internal memory remains uncluttered, and that the system continues to operate smoothly.
[0006] Such a system would involve several key components. First, it would include an automated evaluation tool that continuously scans the internal memory to identify the objects and variables. This tool would use predefined criteria to determine which elements are no longer needed, thereby eliminating the need for manual evaluation. Once the objects and variables are identified, the system would automatically purge or delete them from the internal memory. This process would be designed to occur seamlessly, without interrupting the system's ongoing operations. In cases where deletion is not feasible, the system would transfer the data to secondary storage options, such as backup memory, ensuring that the internal memory remains clear and efficient. It would need to be integrated into the existing infrastructure without causing disruptions. Additionally, the system would need to be scalable to accommodate varying levels of data and memory requirements. Security considerations would also be paramount, ensuring that the purging and transfer processes do not compromise sensitive data.
[0007] Moreover, an efficient memory management system would have a significant impact on overall system performance. By ensuring that internal memory remains clear of the data, the system would be able to respond to consumer requests more quickly and efficiently. This would enhance user experience, as consumers would benefit from faster response times and more reliable service.
[0008] Effective management of the internal memory is crucial to maintain system efficiency. The current process of identifying and purging the data is time-consuming and labor-intensive. Therefore, in view of the above, there is a dire need for a system and method that automates this process, ensuring that the internal memory remains uncluttered, and the system operates smoothly. By implementing such a system, organizations can enhance their overall performance, providing faster and more reliable service to consumers while maintaining the integrity and efficiency of the systems.
SUMMARY OF THE INVENTION
[0009] One or more embodiments of the present disclosure provide a method and a system for deleting data from a storage device.
[0010] In one aspect of the present invention, the method for deleting the data from the storage device is disclosed. The method includes the step of defining, by one or more processors, one or more polices related to the data stored in the storage device. The method includes the step of detecting, by the one or more processors, the data required to be deleted utilizing the one or more policies. The method includes the step of initiating, by the one or more processors, a cleaning process to delete the detected data.
[0011] In one embodiment, the data stored in the storage device pertains to at least one of one or more objects and variables.
[0012] In another embodiment, the step of detecting, by the one or more processors, the data required to be deleted utilizing the one or more policies, includes the step of collecting, by the one or more processors, metadata associated with the data stored in the storage device. The step of detecting, by the one or more processors, the data required to be deleted utilizing the one or more policies, includes the step of determining, by the one or more processors, the data required to be deleted utilizing the one or more policies on the collected metadata.
[0013] In another embodiment, the one or more policies is defined based on at least one of, tracking data record by timestamps of the last updated data in the storage device, tracking frequency of the data utilization, classifying the data as active or inactive, tracking soft deletion of the data to be restored later, tracking data created as draft with no recent updates and tracking past accessed data stored in the storage device.
[0014] In yet another embodiment, the one or more policies are defined by at least one of, a network operator and the one or more processors utilizing a trained model in real time.
[0015] In yet another embodiment, the cleaning process includes at least one of, purging the data, permanently deleting the data, and moving or transferring the data to an alternate storage device.
[0016] In yet another embodiment, the method includes the steps of setting, by the one or more processors, a time interval to initiate the cleaning process to delete the detected data from the storage device. The method includes the steps of storing, by the one or more processors, a plurality of logs associated with the deleted data.
[0017] In another aspect of the present invention, the system for deleting the data from a storage device is disclosed. The system includes a defining unit configured to define one or more polices related to the data stored in the storage device. The system includes a detecting unit configured to detect, the data required to be deleted utilizing the one or more policies. The system includes an initiating unit configured to initiate, a cleaning process in order to delete the detected data.
[0018] In another aspect of the present invention, a User Equipment (UE) is disclosed. The UE includes one or more primary processors. The one or more primary processors communicatively coupled to one or more processors and a memory. The memory stores instructions which when executed by the one or more primary processors causes the UE to transmit one or more requests including the data which is stored in the storage device to the one or more processors.
[0019] 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 define one or more polices related to the data stored in the storage device. The processor is configured to detect the data required to be deleted utilizing the one or more policies. The processor is configured to initiate a cleaning process to delete the detected data.
[0020] 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
[0021] 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.
[0022] FIG. 1 is an exemplary block diagram of an environment for deleting data from a storage device, according to one or more embodiments of the present disclosure;
[0023] FIG. 2 is an exemplary block diagram of a system for deleting the data from the storage device, according to one or more embodiments of the present disclosure;
[0024] FIG. 3 is a schematic representation of a workflow of the system of FIG. 2 communicably coupled with a User Equipment (UE), according to one or more embodiments of the present disclosure;
[0025] FIG. 4 is a block diagram of an architecture that can be implemented in the system of FIG.2, according to one or more embodiments of the present disclosure;
[0026] FIG. 5 is a signal flow diagram for deleting the data from the storage device, according to one or more embodiments of the present disclosure
[0027] FIG. 6 is a flow diagram illustrating a method for deleting the data from the storage device, according to one or more embodiments of the present disclosure.
[0028] The foregoing shall be more apparent from the following detailed description of the invention.
DETAILED DESCRIPTION OF THE INVENTION
[0029] 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.
[0030] 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.
[0031] 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.
[0032] The present disclosure of the invention provides a system and a method to delete data from a storage device. The disclosed system and method aim at enhancing the efficiency of the system by automatically cleaning and managing the historical data of objects and variables based on an Artificial Intelligence/Machine Learning (AI/ML) model. The historical data of objects and variables may be junk data that may not be used for long period of time. In particular, the present invention provides a unique approach to cleaning and managing the objects and the variables in real time depending on one or more policies.
[0033] Referring to FIG. 1, FIG. 1 illustrates an exemplary block diagram of an environment 100 for deleting data from a storage device 110, according to one or more embodiments of the present invention. The environment 100 includes a User Equipment (UE) 102, a server 104, a communication network 106, a system 108, and the storage device 110. The UE 102 aids a user to interact with the system 108 for transmitting one or more requests in order to delete the data from the storage device 110. The UE 102 generates the one or more requests that includes details such as the data to be deleted, any necessary authentication or authorization tokens, and the delete operation to be performed.
[0034] The data of objects and variables is required to be deleted when the objects and variables no longer contribute to the system 108 functionality. In one embodiment, the data required to be deleted is also termed as irrelevant data. The data include, but is not limited to, outdated, unused, or redundant information that no longer serves a functional purpose. The data can stem from various sources, including outdated logs, unused variables, and previous configuration files that no longer serve a purpose. Redundant backups and unfinished drafts also contribute to storage inefficiencies. Temporary files, duplicate data, and unused database entries further clutter the system 108. Further, the temporary files, the duplicate data, and the unused database entries lead to clutter storage, slow down system performance, and increase compliance risks. Identifying and deleting the data is essential to maintaining efficient operations, that ensures data integrity and optimizes storage capacity within the system 108.
[0035] For the purpose of description and explanation, the description will be /explained with respect to one or more user equipment’s (UEs) 102, or to be more specific, will be explained with respect 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. Each of the at least one UE 102 namely the first UE 102a, the second UE 102b, and the third UE 102c is configured to connect to the server 104 via the communication network 106. Each of the at least one UE 102 pertains to the user requesting to delete the data from the storage device 110.
[0036] In an embodiment, each of the first UE 102a, the second UE 102b, and the third UE 102c 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.
[0037] The communication network 106 includes, by way of example but not limited to, 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 communication 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.
[0038] The communication 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 communication 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.
[0039] The environment 100 includes the server 104 accessible via the communication network 106. The server 104 may include by way of example but is not limited to 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, a processor 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.
[0040] The environment 100 includes the storage device 110 communicably coupled to the server 104 via the communication network 106. The storage device 110 is an electronic device that is attached to the communication network 106, which is capable of creating, receiving, or transmitting information over the communication network 106. The storage device 110 may either be data communication equipment such as a modem, hub, bridge, or switch or data terminal equipment such as a digital telephone handset, a printer, or a host computer. The storage device 110 facilitates real-time data processing and monitoring within the network environment. This integration supports automated updates and synchronization across connected devices, providing consistent and up-to-date inventory records.
[0041] The environment 100 further includes the system 108 communicably coupled to the server 104, the storage device 110 and the UE 102 via the communication network 106. The system 108 is configured for deleting the data from the storage device 110. The system 108 is adapted to be embedded within the server 104 or embedded as the individual entity.
[0042] Operational and construction features of the system 108 will be explained in detail with respect to the following figures.
[0043] FIG. 2 is an exemplary block diagram of a system 108 for deleting the data from the storage device 110, according to one or more embodiments of the present disclosure.
[0044] As per the illustrated and preferred embodiment, the system 108 includes one or more processors 202, a memory 204, a user interface 206, and a database 216. For the purpose of description and explanation, the description will be explained with respect to the one or more processors 202, or to be more specific will be explained with respect to the processor 202 and should nowhere be construed as limiting the scope of the present disclosure. The one or more processor 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.
[0045] 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 is 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 for deleting the data from the storage device 110. The memory 204 may include any non-transitory storage device 110 including, for example, volatile memory such as RAM, or non-volatile memory such as disk memory, EPROM, FLASH memory, unalterable memory, and the like.
[0046] The user interface 206 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 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 the one or more components include, but are not limited to, the UE 102, and the database 216.
[0047] As per the illustrated embodiment, the storage device 110 is configured to store the data pertaining to the message formats. The storage device 110 is one of, but not limited to, a database 216, 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.
[0048] Further, the processor 202, 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 processor 202 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 202. 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.
[0049] In an embodiment, the UE 102 of the user transmits the one or more requests to the processor 202 in order to delete the data from the storage device 110. In an alternate embodiment, there is no requirement for the user to transmit the one or more requests for deletion of the data from the storage device 110 whereas the system 108 is capable of dynamically deleting the detected data from the storage device 110.
[0050] In order for the system 108 to delete the data from the storage device 110, the processor 202 includes a defining unit 208, a detecting unit 210, an initiating unit 212, and a trained model 214 communicably coupled to each other. In an embodiment, operations and functionalities of the defining unit 208, the detecting unit 210, the initiating unit 212, and the trained model 214 can be used in combination or interchangeably.
[0051] The defining unit 208 is configured to define one or more polices related to the data stored in the storage device 110. In an embodiment, the data stored in the storage device 110 pertains to at least one of, one or more objects and variables. The one or more objects and variables refer to distinct types of data that can be stored and managed within the storage device 110. Furthermore, the one or more objects refer to more complex data structures that include files, folders, databases, or other entities that store the data. In an embodiment, the one or more objects include, but not limited to, a document, an image file, a video, or a database record. The one or more variables are used to store data values that is changed during the execution of a program. The one or more variables represent single data points and hold various types of the data, such as numbers, strings, or other simple values. In an embodiment, the one or more variables include, but not limited to, data points such as integers variables, string variables, or Boolean variables.
[0052] In an embodiment, the one or more policies are defined by one of, but not limited to, a network operator. The one or more policies pertains to at least one of, tracking data record by timestamps of the last updated data in the storage device 110, tracking frequency of the data utilization, classifying the data as active or inactive, tracking soft deletion of the data to be restored later, tracking data created as draft with no recent updates and tracking past accessed data stored in the storage device 110. The tracking data record by timestamps of the last updated data refers to monitoring the timestamps associated with when the data is last updated in the storage device 110. In an exemplary embodiment, the file updated two years ago might be flagged for review to determine if the file should be archived or deleted to free up storage space. Old, stagnant data that is no longer in use is efficiently flagged for deletion, which reduces unnecessary storage and keeps the system optimized. The tracking frequency of the data utilization refers to monitoring the data is accessed or used. In an exemplary embodiment, a report that is accessed daily would be classified as frequently used, whereas a rarely viewed previous file might be marked for archival. Rarely used data is removed, making storage more efficient and accessible while freeing up resources.
[0053] As per the above one embodiment, classifying the data as active or inactive refers to categorizing the data based on a current usage status. In an exemplary embodiment, the active data includes ongoing files, while inactive data includes old, and completed files that are no longer in regular use. The system 120 can prioritize the deletion of inactive data, ensuring that the active data is retained, and only less critical data is deleted. The tracking soft deletion of the data to be restored later refers to monitoring the data that is marked for deletion but is not permanently erased, allowing for potential restoration if needed. The soft deletion prevents accidental loss of the data, allowing for a safety period where the data can be recovered before it's permanently erased. In an exemplary embodiment, the file deleted by the user is moved to a soft delete (similar to a recycle bin) where the file is restored if needed within a predefined time frame. The tracking data created as draft with no recent updates refers to track the data that is in a draft form and the data is not updated recently. In an exemplary embodiment, the draft document that is not updated in six months might be flagged for review, prompting the user to either complete or discard it. Unused draft data, which often clutters storage, is efficiently removed, making the system more organized and freeing up storage. The tracking past accessed data stored in the storage device 110 refers to track historical access to data, monitoring when and how often data has been accessed over time. In an exemplary embodiment, the file that has been accessed frequently over the past year but hasn’t been touched in the last few months might be analyzed to determine its current relevance.
[0054] Upon defining the one or more polices related to the data stored in the storage device 110, in one embodiment, the detecting unit 210 configured to detect the data required to be deleted utilizing the one or more policies. The detecting unit 210 is configured to collect metadata associated with the data stored in the storage device 110. The metadata refers to the information that describes and provides information about the data stored in the system 120, which aids to make informed decisions about which data needs to be deleted. The metadata includes creation date, last access date, modification date, file size, and category or tag. The detecting unit 210 is further configured to determine the data required to be deleted utilizing the one or more policies on the collected metadata. In this regard, a data cleaning and management engine 414 (as shown in FIG.4) is used to process the logic of the one or more policies. The data cleaning and management engine 414 automatically checks each policy from the one or more policies against the data and makes decisions regarding which data satisfies the deletion criteria. In an embodiment, the deletion criteria include, but not limited to, time based-criteria, access based-criteria, size based-criteria, and priority based-criteria. The one or more policies are executed and continuously scan the stored data for matches against the deletion criteria.
[0055] In another embodiment, the detecting unit 210 is configured to detect the data required to be deleted utilizing the trained model 214. In an embodiment, the trained model 214 includes, but not limited to, an Artificial Intelligence/Machine Learning (AI/ML) model. The AI/ML model utilizes a variety of ML techniques, such as supervised learning model, unsupervised learning model and reinforcement learning. In one embodiment, the supervised learning model is a type of machine learning algorithm, which is trained on a labeled dataset, which means that each training dataset is paired with an output label. The supervised learning model classifies the data as either relevant or obsolete based on historical usage patterns and predicts future data access needs based on the trends. In another embodiment, the unsupervised learning is a type of machine learning algorithm, which is trained on data without any labels. The unsupervised learning algorithm groups similar data together to identify which groups might be candidates for deletion. In yet another embodiment, the reinforcement learning is a type of machine learning where an agent learns to make decisions by performing actions in an environment to maximize cumulative reward.
[0056] In one embodiment, the AI/ML model aids the detecting unit 210 to identify the data for deletion by learning from the trends or patterns related to the data stored in the storage device 110. The trends and patterns refer to observable behaviors or recurring characteristics in data usage that inform decisions about which data to delete or retain. The trends are general directions in which something is developing or changing over time. In an exemplary embodiment, the report is frequently accessed in the first year but has seen steadily declining access rates each subsequent year. The trend suggests that the report might be less relevant now and could be considered for archiving or deletion. The patterns are recurring sequences or arrangements observed in the data, which aid to identify specific characteristics or behaviors that inform data management decisions. In an exemplary embodiment, the files related to a specific project or event might cluster together in terms of usage. If the project is complete and the files are not accessed frequently, the pattern can indicate that the entire cluster of files might be archived or deleted.
[0057] The AI/ML model is trained to recognize the trends and patterns from the historical data, which enables the system to predict future data needs and automate data management tasks accordingly. By analysing the trends and patterns, the system 108 can make informed decisions regarding the data required to be deleted or retained.
[0058] Upon detecting the data required to be deleted utilizing the one or more policies and the AI/ML model, the initiating unit 212 configured to initiate a cleaning process in order to delete the detected data. The initiating unit 212 receives a list of data elements identified for deletion by the detecting unit 210 and initiates the cleaning or deletion process. The initiating unit 212 involves executing scripts or commands to remove the data from the storage device 110, ensure that the data is permanently deleted, and free up storage space. In an embodiment, the cleaning process includes at least one of, purging the data, permanently deleting the data, and moving or transferring the data to an alternate storage device. Purging refers to the comprehensive removal of data from the storage device 110. The purging process involves deleting the data in a way that ensures it cannot be recovered or accessed again. Permanent deletion involves removing data such that the data is no longer recoverable or accessible, ensuring that the data is fully eradicated from the storage device 110. Instead of deleting the data, the data is transferred to the alternate storage device, which is an archive or a secondary storage device.
[0059] In another embodiment, the cleaning process includes, but is not limited to, immediate deletion, soft deletion, and archiving. The immediate deletion refers to the data that is immediately removed from the storage device 110, ensuring that the data is no longer accessible or retrievable. The soft deletion refers to the data that is marked for deletion but is kept in a recoverable state for a certain period before permanent deletion. The archiving refers to the data that might be moved to an archive before deletion, allowing the data to be stored for long-term retention but not actively used.
[0060] In an exemplary embodiment for initiating the cleaning process, a cloud storage service has identified old user files that have not been accessed in over three years. The one or more policies and the AI/ML model flagged the files for deletion. The initiating unit 212 triggers the cleaning process, which involves executing the script that removes the files from the storage device 110, freeing up space and ensuring the files are no longer accessible.
[0061] The initiating unit 212 is further configured to set a time interval to initiate the cleaning process to delete the detected data from the storage device 110. The initiation of the cleaning process ensures that the data deletion occurs at optimal time, which might be based on system load, or operational requirements. The system 108 allows the network operator to define the time interval for initiating the cleaning process. In an embodiment, the time interval includes, but not limited to, a specific time of day, and a daily or weekly schedule. Once the time interval is set, the initiating unit 212 automatically starts the cleaning process according to the defined schedule without requiring manual intervention. In an exemplary embodiment, the time interval is scheduled to run the system 108 every night during off-peak hours to minimize impact on system performance.
[0062] The initiating unit 212 is configured to store a plurality of logs associated with the deleted data. The initiating unit 212 stores the plurality of logs which provides a record of the data deletion activities, which is essential for auditing, tracking, and compliance purposes. In an embodiment, the plurality of logs includes details of deleted data, time of deletion, reason for deletion and status. The details of deleted data refer to information about what data was deleted, including identifiers or descriptions. The time of deletion refers to timestamps indicating when the deletion process occurred. The reason for deletion refers to information on why the data was deleted, such as policy adherence or system cleanup. The status refers to whether the deletion process is successful or encountered errors. The plurality of logs is stored in a secure and accessible location, such as a log management system or the database 216, where the plurality of logs is reviewed and analyzed.
[0063] By deleting the data from the storage device 110, the system 108 is able to, advantageously, maintain the system 108 efficiency by preventing degradation over time. Additionally, the system 108 allows for the real-time cleaning and management of the objects and variables, ensuring that the system 108 remains optimized. Furthermore, the one or more policies are defined for cleaning and managing the objects and variables, allowing the system 108 to adapt to changing conditions and requirements.
[0064] FIG. 3 is a schematic representation of a workflow of the system 108 of FIG. 2 communicably coupled with a User Equipment (UE), according to one or more embodiments of the present disclosure. More specifically, FIG. 3 illustrates the system 108 configured for deleting the data from the storage device 110. It is to be noted that the embodiment with respect to FIG. 3 will be explained with respect to the first UE 102a for the purpose of description and illustration and should nowhere be construed as limited to the scope of the present disclosure.
[0065] As mentioned earlier in FIG.1, in an embodiment, the first UE 102a may encompass electronic apparatuses. These devices are illustrative of, but not restricted to, modems, routers, switches, laptops, tablets, smartphones (including phones), or other devices enabled for web connectivity. The scope of the first UE 102a 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 102a can be associated with multiple users. Each of the first UE 102a is communicatively coupled with the processor 202.
[0066] The first UE 102a includes one or more primary processors 302 communicably coupled to the one or more processors 202 of the system 108. The one or more primary processors 302 are coupled with a memory 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 transmit the one or more requests to the one or more processors 202 for deleting the data from the storage device 110.
[0067] Furthermore, the one or more primary processors 302 within the first UE 102a are uniquely configured to execute a series of steps as described herein. This configuration underscores the processor 202 capability to delete the data from the storage device 110. The coordinated functioning of the one or more primary processors 302 and the additional processors, is directed by the executable instructions stored in the memory 304. The executable instructions facilitate seamless communication and compatibility among the one or more primary processors 302, optimizing performance and resource use.
[0068] As mentioned earlier in FIG.2, the system 108 includes the one or more processors 202, the memory 204, the user interface 206, and the database 216. The operations and functions of the one or more processors 202, the memory 204, the user interface 206, and the database 216 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.
[0069] Further, the processor 202 includes the defining unit 208, the detecting unit 210, the initiating unit 212, and the trained model 214. The operations and functions of the defining unit 208, the detecting unit 210, the initiating unit 212, and the trained model 214 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 provided for the system 108 in the FIG. 2 above, and should not be construed as limiting the scope of the present disclosure.
[0070] FIG. 4 is a 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. The architecture 400 pertains to the system 108 which includes, an API consumer 402, an Elastic Load Balancer (ELB) 404, an Identity and Access Management (IAM) 406, an API gateway 408, a data transformation 410, an API template configuration 412, the data cleaning and management engine 414, a data manipulation 416, a data ingestion 418, a data cleaning & management policy configuration 420, a Representational State Transfer (REST) protocol translation 422, an API integration 424, an API service repository 426 and a database system 428.
[0071] The architecture 400 of the system includes an API consumer 402. In an embodiment, the API consumer 402 develops applications or web sites using the APIs. In an embodiment, the API consumer 402 are the developers who integrate APIs with the applications or websites. In particular, API consumers 402 are the users of APIs. The API consumer 402 is communicably connected to the ELB 404. The ELB 404 is configured to route the API call request from the API consumer 402 to the destination application based on the one or more rules like round robin, context-based routing, header-based routing, or TCP based routing. The ELB 404 is configured to route the one or more requests from the API consumer 402 to the destination application based on rules like round robin, context-based routing, header-based routing, or TCP based routing. The ELB 404 automatically distributes incoming traffic from the API consumers 402 across multiple targets, such as servers.
[0072] The architecture 400 further includes the IAM 406. In an embodiment, the IAM 406 is a web service that facilitates securely control access to system resources. The IAM 406 is configured to centrally manage permissions or provides authentication to the API consumer 402.
[0073] The ELB 404 transmits the one or more requests to the API gateway 408. The API gateway 408 is a data-plane entry point for API calls that represent consumer requests to target applications and services. The API gateway 408 typically performs request processing based on the one or more policies, including authentication, authorization, access control, Secure Sockets Layer (SSL)/ Transport Layer Security (TLS) offloading, routing, and load balancing.
[0074] The API gateway 408 further includes the data transformation 410. The data transformation is the process of converting data from one format, such as a database file, XML document or Excel spreadsheet, into other formats. Transformations typically involve converting a raw data source into a cleansed, validated and ready-to-use format. The API gateway 408 further includes the API template configuration 412. The API template configuration 412 allows the user to define the API Gateway resources in a declarative manner, which makes it easier to manage and scale APIs.
[0075] The API gateway 408 further includes the data cleaning and management engine 414 and the data cleaning and management policy configuration 420. In the present invention, the data cleaning and management engine 414 and the data cleaning and the management policy configuration 420 include the AI/ML model for learning the trends and patterns for deleting the data from the storage device 110.
[0076] In an embodiment, the API gateway 408 includes the data manipulation 416 and the data ingestion 418. In an embodiment, the data manipulation 416 is the process of organizing or arranging the data in order to make it easier to interpret. The data manipulation 416 typically requires the use of a type of database language called Data Manipulation Language (DML). The data ingestion 418 is the process of importing large, assorted data files from multiple sources into a single cloud-based storage medium or a data warehouse or database where it can be accessed and analyzed.
[0077] The API gateway 408 further includes the REST protocol translation 422. The REST protocol translation 422 is an architectural style for designing networked applications. The REST relies on a stateless, client-server, cacheable communications protocol — typically HTTP. In a RESTful system, resources are identified by URLs, and interactions with these resources are done through standard HTTP methods like GET, POST, PUT, and DELETE. The REST protocol translation 422 is commonly used in web services and the one or more APIs.
[0078] The REST protocol translation 422 refers to the process of converting or mapping requests and responses between the REST protocol and other communication protocols. The REST protocol translation 422 is an outbound or active protocol and can be used as a gateway log source by using a custom log source type. In the API gateway 408, the REST protocol translation 422 enables seamless interaction between the system 108 via different protocols. The translation typically involves converting RESTful HTTP requests into the format required by the target protocol (e.g., Kafka), and then converting responses back into a REST-compliant format for the client. The aforementioned process allows for integration between systems that use different communication methods while maintaining the stateless and resource-oriented principles of REST.
[0079] The API gateway 408 further includes the API integration 424, which refers to the process of connecting two or more applications by using the one or more APIs to exchange data and perform actions. The system 108 further includes the API service repository 426. The API service repository 426 includes, at least one of, but not limited to, databases, data lakes, data containers, etc. The API service repository 426 includes a catalogue in which all the services available on the communication network 106 are stored.
[0080] The system 108 further includes the database system 428. The database system 428 includes, at least one of, but not limited to, Elastic search etc. In an embodiment, the database system 428 is configured to store the historical data of the user.
[0081] FIG. 5 is the signal flow diagram for deleting the data from the storage device 110, according to one or more embodiments of the present invention.
[0082] At step 502, the UE 102 transmits the one or more requests to the processor 202 of the system 108 in order to delete the data from the storage device 110. At step 504, the processor 202 of the system 108 is defined with the one or more policies based on the trained model 214 for deletion of the data from the storage device 110. In an embodiment, the data stored in the storage device 110 pertains to at least one of, one or more objects and variables.
[0083] At step 506, the processor 202 of the system 108 detects the data required to be deleted utilizing the one or more policies and the trained model 214. The detecting unit 210 analyzes the data in the storage device 110, comparing the data against the one or more policies. In an exemplary embodiment, if the one or more policies determines that the data older than two years should be deleted. The detecting unit 210 identifies the data elements such as files, records, and the like that need to be deleted based on the one or more policies. The AI/ML model is trained to recognize the trends and patterns from the historical data, which enables the system to predict future data needs and automate data management tasks accordingly. By analysing the trends and patterns, the system 108 can make more informed decisions about which data to delete or retain.
[0084] At step 508, the initiating unit 212 configured to initiate the cleaning process in order to delete the detected data. The initiating unit 212 receives the list of data elements identified for deletion by the detecting unit 210 and initiates the cleaning or deletion process. The initiating unit 212 involves executing scripts or commands to remove the data from the storage device 110, ensure that the data is permanently deleted, and free up storage space.
[0085] At step 510, the processor 202 of the system 108 transmits the plurality of logs to the UE 102. In an embodiment, the plurality of logs includes details of deleted data, time of deletion, reason for deletion and status. The plurality of logs is stored in secure and accessible location, such as the log management system or the database 216, where the plurality of logs is reviewed and analyzed.
[0086] FIG. 6 is a flow diagram illustrating a method 600 for deleting the data from the storage device 110, according to one or more embodiments of the present disclosure. For the purpose of description, the method 600 is described with the embodiments as illustrated in FIG. 2 and should nowhere be construed as limiting the scope of the present disclosure.
[0087] At step 602, the method 600 includes the step of defining the one or more polices related to the data stored in the storage device 110 by the defining unit 208. In an embodiment, the one or more policies are defined by at least one of, a network operator. The one or more policies pertains to at least one of, tracking data record by timestamps of the last updated data in the storage device 110, tracking frequency of the data utilization, classifying the data as active or inactive, tracking soft deletion of the data to be restored later, tracking data created as draft with no recent updates and tracking past accessed data stored in the storage device 110.
[0088] At step 604, the method 600 includes the step of detecting the data required to be deleted utilizing the one or more policies by the detecting unit 210. The detecting unit 210 analyzes the data in the storage device 110, comparing the data against the one or more policies. In an exemplary embodiment, if the one or more policies determines that the data older than two years should be deleted. The detecting unit 210 identifies the data elements such as files, records, and the like that need to be deleted based on the one or more policies. In another embodiment, the detecting unit 210 is configured to detect the data required to be deleted utilizing the trained model 214. In an embodiment, the trained model 214 includes, but not limited to, the Artificial Intelligence/Machine Learning (AI/ML) model.
[0089] At step 606, the method 600 includes the step of initiating the cleaning process in order to delete the detected data by the initiating unit 212. The initiating unit 212 receives the list of data elements identified for deletion by the detecting unit 210 and initiates the cleaning or deletion process. The initiating unit 212 involves executing scripts or commands to remove the data from the storage device 110, ensure that the data is permanently deleted, and free up storage space. In an embodiment, the cleaning process includes at least one of, purging the data, permanently deleting the data, and moving or transferring the data to the alternate storage device.
[0090] The initiating unit 212 is further configured to set a time interval to initiate the cleaning process to delete the detected data from the storage device 110. The initiation of the cleaning process ensures that the data deletion occurs at optimal time, which might be based on system load, or operational requirements. The system 108 allows the network operator to define the time interval for initiating the cleaning process. In an embodiment, the time interval includes, but not limited to, a specific time of day, and a daily or weekly schedule. Once the time interval is set, the initiating unit 212 automatically starts the cleaning process according to the defined schedule without requiring manual intervention. In an exemplary embodiment, the time interval is scheduled to run the system 108 every night during off-peak hours to minimize impact on system performance.
[0091] The initiating unit 212 is configured to store the plurality of logs associated with the deleted data. The initiating unit 212 stores the plurality of logs which provides the record of the data deletion activities, which is essential for auditing, tracking, and compliance purposes. In an embodiment, the plurality of logs includes details of deleted data, time of deletion, reason for deletion and status. The plurality of logs is stored in secure and accessible locations, such as the log management system or the database 216, where the plurality of logs is reviewed and analyzed.
[0092] In another aspect of the invention, a non-transitory computer-readable medium having stored thereon computer-readable instructions that, when executed by a processor. The processor 202 is configured to define one or more polices related to the data stored in the storage device 110. The processor 202 is configured to detect the data required to be deleted utilizing the one or more policies. The processor 202 is configured to initiate a cleaning process to delete the detected data.
[0093] 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.
[0094] The present disclosure provides technical advancement for defining the one or more policies and the trained model to delete the data, which is no longer in use. The present disclosure automates the detection and deletion process using the one or more policies, which streamlines the workflow and ensures the timely removal of data. The deletion process is crucial for maintaining system efficiency and reducing the need for manual intervention. By automating the deletion process, the system ensures that the data is promptly removed, freeing up storage space and maintaining optimal performance levels. Further, the present disclosure provides regular and automated cleaning processes that maintain optimal system performance by ensuring that the storage device is not clogged with outdated data. Further, the present disclosure assists in automated data management processes, which are inherently more scalable, allowing the system to handle larger volumes of data efficiently.
[0095] 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

[0096] Environment - 100
[0097] User Equipment (UE) - 102
[0098] Server - 104
[0099] Communication Network- 106
[00100] System -108
[00101] Storage device – 110
[00102] Processor - 202
[00103] Memory - 204
[00104] User Interface – 206
[00105] Defining unit– 208
[00106] Detection unit – 210
[00107] Initiating unit – 212
[00108] Trained Model –214
[00109] Database –216
[00110] Primary processor- 302
[00111] Memory- 304
[00112] API Consumer–402
[00113] Elastic Load Balancing – 404
[00114] Identity and Access Management – 406
[00115] API Gateway – 408
[00116] Data Transformation – 410
[00117] API Template Configuration – 412
[00118] Data Cleaning and Management Engine – 414
[00119] Data Manipulation – 416
[00120] Data Ingestion – 418
[00121] Data Cleaning & Management Policy Config – 420
[00122] REST Protocol Translation– 422
[00123] API Integration – 424
[00124] API Service Repository– 426
[00125] Database Systems – 428
,CLAIMS:CLAIMS
We Claim:
1. A method (600) for deleting data from a storage device (110), the method (600) comprising the steps of:
defining, by one or more processors (202), one or more polices related to the data stored in the storage device;
detecting, by the one or more processors (202), the data required to be deleted utilizing the one or more policies; and
initiating, by the one or more processors (202), a cleaning process to delete the detected data.

2. The method (600) as claimed in claim 1, wherein the data stored in the storage device (110) pertains to at least one of, one or more objects and variables.

3. The method (600) as claimed in claim 1, wherein the step of detecting, by the one or more processors (202), the data required to be deleted utilizing the one or more policies, includes the step of:
collecting, by the one or more processors (202), metadata associated with the data stored in the storage device (110); and
determining, by the one or more processors (202), the data required to be deleted utilizing the one or more policies on the collected metadata.

4. The method (600) as claimed in claim 1, wherein the one or more policies is defined based on at least one of, tracking data record by timestamps of the last updated data in the storage device (110), tracking frequency of the data utilization, classifying the data as active or inactive, tracking soft deletion of the data to be restored later, tracking data created as draft with no recent updates and tracking past accessed data stored in the storage device (110).

5. The method (600) as claimed in claim 1, wherein the one or more policies are defined by at least one of, a network operator and the one or more processors (202) utilizing a trained model (214) in real time.

6. The method (600) as claimed in claim 1, wherein the cleaning process includes at least one of, purging the data, permanently deleting the data, and moving or transferring the data to an alternate storage device (110).

7. The method (600) as claimed in claim 1, wherein the method comprises the steps of:
setting, by the one or more processors (202), a time interval to initiate the cleaning process to delete the detected data from the storage device (110).
storing, by the one or more processors (202), a plurality of logs associated with the deleted data.

8. A system (108) for deleting data from a storage device (110), the system (108) comprising:
a defining unit (208) configured to define, one or more polices related to the data stored in the storage device (110);
a detecting unit (210) configured to detect, the data required to be deleted utilizing the one or more policies; and
an initiating unit (212) configured to initiate, a cleaning process in order to delete the detected data.

9. The system as claimed in claim 8, wherein the data stored in the storage device (110) pertains to at least one of, one or more objects and variables.

10. The system as claimed in claim 8, wherein the detecting unit (210) is further configured to:
collect metadata associated with the data stored in the storage device (110); and
determine the data required to be deleted utilizing the one or more policies on the collected metadata.

11. The system as claimed in claim 8, wherein the one or more policies pertains to at least one of, tracking data record by timestamps of the last updated data in the storage device (110), tracking frequency of the data utilization, classifying the data as active or inactive, tracking soft deletion of the data to be restored later, tracking data created as draft with no recent updates and tracking past accessed data stored in the storage device (110).

12. The system as claimed in claim 8, wherein the one or more policies are defined by at least one of, a network operator and the one or more processors (202) utilizing a trained model (214) in real time.

13. The system as claimed in claim 8, wherein the cleaning process includes at least one of, purging the data, permanently deleting the data, and moving or transferring the data to an alternate storage device.

14. The system as claimed in claim 8, wherein the initiating unit (212) is configured to:
set, a time interval to initiate the cleaning process to delete the detected data from the storage device (110); and
store, a plurality of logs associated with the deleted data.

15. 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:
transmit, one or more requests comprising the data which is stored in the storage device (110) to the one or more processors (202); and
wherein the one or more processors (202) is configured to perform the steps as claimed in claim 1.