DESC:FIELD OF THE INVENTION

The present disclosure relates to a computer-based system and method for real-time optimization and intelligent control of server resource and operation-cycle.

BACKGROUND OF THE INVENTION

A powerful framework for autoscaling task execution optimisation has been done. Here ‘Task’ is to anything that utilises resources on worker. Task may have wide scope of complexity and capsulated with information required for processing. This task execution may be carried out locally on user’s system or it may involve communication execution on or between multiple systems. By term ‘Task Sequencing’ it means the operation that are performed such as task store, execution check and finalization, task status updating, delete and all allowed operations that was unable to take actions itself or an authorised user.

By term ‘Task Orchestration’ it means the method of implementation by which task is assigned to appropriate resource based on the matrix defined by auto-scaling mechanism. The ‘Task Orchestration’ is capable of performing operation on task such as Task storing, task status updating, delete and all allowed actions itself or an authorised user. By term ‘Auto-scaling’ it means the structure of program that enables the task sequencing and resource optimisation based on predefined method of formulating a task in effective metrics that is used for prioritization.

In the view of the forgoing discussion, it is clearly portrayed that there is a need to have a computer-based system and method for real-time optimization and intelligent control of server resource and operation-cycle.

SUMMARY OF THE INVENTION

The present disclosure seeks to provide a computer-based system and method for real-time optimization and intelligent control of server resource and operation-cycle.

In an embodiment, a computer-based system for real-time optimization and intelligent control of server resource and operation cycle is disclosed. The system includes a plurality of sensing nodes for monitoring server utilization and task memory requirements. The system further includes a central processor interfaced with a network for monitoring tasks based on memory requirements, prioritization, and processing requirements. The system further includes a cloud server platform for storing tasks. The system further includes a task sequencing processor for checking execution and finalizing, updating task status, deleting, and enabling all allowed operations to take actions. The system further includes a task orchestration processor configured to an appropriate resource based on the matrix defined by an auto-scaling mechanism for performing operations on tasks such as Task storing, task status updating, deletion, and all allowed actions. The system further includes an auto-scaling processor for enabling task sequencing and resource optimization based on a predefined method of formulating a task in effective metrics that are used for prioritization.

In another embodiment, a computer-based method for real-time optimization and intelligent control of server resource and operation cycle is disclosed. The method includes monitoring server utilization and task memory requirements upon deploying a plurality of sensing nodes. The method further includes monitoring tasks based on memory requirements, prioritization, and processing requirements using a central processor through a network. The method further includes storing tasks in a cloud server platform. The method further includes checking execution and finalizing, updating task status, deleting, and enabling all allowed operations to take actions through a task sequencing processor. The method further includes performing operations on tasks such as Task storing, task status updating, deletion, and all allowed actions using a task orchestration processor configured to an appropriate resource based on the matrix defined by an auto-scaling mechanism. The method further includes enabling task sequencing and resource optimization based on a predefined method of formulating a task in effective metrics that are used for prioritization through an auto-scaling processor.

An object of the present disclosure is to monitor server utilization and task memory requirement.

Another object of the present disclosure is to allocate appropriate resources and schedule a task.

Yet another object of the present invention is to deliver an expeditious and cost-effective computer-based system and method for real-time optimization.

To further clarify advantages and features of the present disclosure, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.

BRIEF DESCRIPTION OF FIGURES

These and other features, aspects, and advantages of the present disclosure will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:

Figure 1 illustrates a block diagram of a computer-based system for real-time optimization and intelligent control of server resource and operation cycle in accordance with an embodiment of the present disclosure;
Figure 2 illustrates a flow chart of a computer-based method for real-time optimization and intelligent control of server resource and operation cycle in accordance with an embodiment of the present disclosure;
Figure 3 illustrates an architecture of a system for real-time optimization and intelligent control of server resources and operation cycle in accordance with an embodiment of the present disclosure;
Figures 4A and 4B illustrate the flow chart of task sequencing of workbook with single and multiple tasks to execute respectively in accordance with an embodiment of the present disclosure;
Figures 5A and 5B illustrate the task abort in task sequencing and task orchestration in accordance with an embodiment of the present disclosure;
Figure 6 illustrates the task execution with aborted by user in accordance with an embodiment of the present disclosure;
Figure 7 illustrates autoscaling of the system in accordance with an embodiment of the present disclosure;
Figure 8 illustrates the worker termination in autoscaling in accordance with an embodiment of the present disclosure;
Figure 9 illustrates the task sequencing with processor and without processor in accordance with an embodiment of the present disclosure; and
Figure 10 illustrates the n-task workbook with or without inter-connections in accordance with an embodiment of the present disclosure.

Further, skilled artisans will appreciate that elements in the drawings are illustrated for simplicity and may not have necessarily been drawn to scale. For example, the flow charts illustrate the method in terms of the most prominent steps involved to help to improve understanding of aspects of the present disclosure. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the drawings by conventional symbols, and the drawings may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the drawings with details that will be readily apparent to those of ordinary skill in the art having benefit of the description herein.

DETAILED DESCRIPTION:

For the purpose of promoting an understanding of the principles of the invention, reference will now be made to the embodiment illustrated in the drawings and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the invention is thereby intended, such alterations and further modifications in the illustrated system, and such further applications of the principles of the invention as illustrated therein being contemplated as would normally occur to one skilled in the art to which the invention relates.

It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the invention and are not intended to be restrictive thereof.

Reference throughout this specification to “an aspect”, “another aspect” or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, appearances of the phrase “in an embodiment”, “in another embodiment” and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment.

The terms "comprise", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such process or method. Similarly, one or more devices or sub-systems or elements or structures or components proceeded by "comprises...a" does not, without more constraints, preclude the existence of other devices or other sub-systems or other elements or other structures or other components or additional devices or additional sub-systems or additional elements or additional structures or additional components.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The system, methods, and examples provided herein are illustrative only and not intended to be limiting.

Embodiments of the present disclosure will be described below in detail with reference to the accompanying drawings.

Referring to Figure 1, a block diagram of a computer-based system for real-time optimization and intelligent control of server resource and operation cycle is illustrated in accordance with an embodiment of the present disclosure. The system 100 includes a plurality of sensing nodes 102 for monitoring server utilization and task memory requirements.

In an embodiment, a central processor 104 is interfaced with a network 106 for monitoring tasks based on memory requirements, prioritization, and processing requirements.

In an embodiment, a cloud server 108 platform is used for storing tasks.

In an embodiment, a task sequencing processor 110 is used for checking execution and finalizing, updating task status, deleting, and enabling all allowed operations to take actions.

In an embodiment, a task orchestration processor 112 is configured to an appropriate resource based on the matrix defined by an auto-scaling mechanism for performing operations on tasks such as Task storing, task status updating, deletion, and all allowed actions.

In an embodiment, an auto-scaling processor 114 is used for enabling task sequencing and resource optimization based on a predefined method of formulating a task in effective metrics that are used for prioritization.

Figure 2 illustrates a flow chart of a computer-based method for real-time optimization and intelligent control of server resource and operation cycle in accordance with an embodiment of the present disclosure. At step 202, the method 200 includes monitoring server utilization and task memory requirements upon deploying a plurality of sensing nodes.

At step 204, the method 200 includes monitoring tasks based on memory requirements, prioritization, and processing requirements using a central processor through a network.

At step 206, the method 200 includes storing tasks in a cloud server platform.

At step 208, the method 200 includes checking execution and finalizing, updating task status, deleting, and enabling all allowed operations to take actions through a task sequencing processor.

At step 210, the method 200 includes performing operations on tasks such as Task storing, task status updating, deletion, and all allowed actions using a task orchestration processor configured to an appropriate resource based on the matrix defined by an auto-scaling mechanism.

At step 212, the method 200 includes enabling task sequencing and resource optimization based on a predefined method of formulating a task in effective metrics that are used for prioritization through an auto-scaling processor.

In another embodiment, defining a single task to execute or may define a complete pipeline of tasks through a user computing device, wherein such single or multiple users simultaneously define multiple tasks or a task pipeline from distinct multiple systems, wherein the task pipeline is preferably a workbook to execute a single task or multiple tasks to execute.

In another embodiment, the task sequencing processor comprises: defining a task in a workbook through a graphical user interface, wherein every task defined in the workbook is having a method and a set of parameters to execute. Then, updating the task status to “TO RUN” thereby each task with “TO RUN” status from single or multiple users or workbooks that are pushed to execute are stacked in “TASK READY’ queue. Then, checking whether the task is single or multiple. Then, wherein in case if single task pushed from the workbook includes: executing push the task to “TASK TO EXECUTE” queue, if the predecessor of ‘TO RUN’ task is successfully executed else go to start, copying task with “TO RUN” status to “TASK TO EXECUTE” queue, updating status of task from “TO RUN” to “PENDING”, and deleting the entry from “TASK READY” queue. Then, wherein in case if multiple tasks pushed from the workbook includes: checking for all tasks with no predecessor task, copying all such Task with “TO RUN” status to “TASK TO EXECUTE” queue, updating to the status of Task from “TO RUN” to “PENDING”, deleting the entry from “TASK READY” queue, and checking for the tasks with “PENDING” status continuously and delete the entry of the successor Task from “TASK READY” queue.

In another embodiment, updating the status for Task from “PENDING TASK” to “TASK FAILED” if Task with “PENDING” status fails while execution, wherein the updating steps comprises; updating the status of the successor task from “TASK READY” to “TASK ABORTED”. Then, deleting the entry of the processed Task from “TASK TO EXECUTE” queue. Then, deleting the entry of the successor Task from “TASK READY” queue. Then, wherein if Task with “PENDING” status successfully executes then, updating the status for Task from “PENDING TASK” to “TASK SUCCESSFUL”, copying successor Task with “TO RUN” status to “TASK TO EXECUTE” queue, updating the status of the successor task from “TASK READY” to “PENDING”, deleting the entry of the processed Task from “TASK TO EXECUTE” queue, deleting the entry of the successor Task from “TASK READY” queue, wherein if Task with “PENDING” status is ABORTED by user manually or while execution then, updating the status for Task from “PENDING TASK” to “TASK ABORTED”, updating the status of the successor task from “TASK READY” to “TASK ABORTED”, deleting the entry of the processed Task from “TASK TO EXECUTE” queue, and deleting the entry of the successor Task from “TASK READY” queue.

In another embodiment, executing the Task Abortion in Task Sequencing by updating the status in a database of a task to ‘ABORT’ if the user aborts the Workbook execution and checking whether a task is in ‘TASK READY’ queue, wherein update the task in TASK TO ABORT queue, if True, or push the task to execute, Revoke the worker that is executing the task and update its status to ABORTED, if False.

In another embodiment, executing the Task Abortion in Task Orchestration upon continuously monitoring the TASK2ABORT queue, thereby removing task entry from both TASK2ABORT and TASK2EXECUTE queue, if the task is present in TASK2ABORT queue.

In another embodiment, employing the auto-scaling unit for autoscaling task execution for a specific workflow comprises: monitoring all task pushed in Task2Execute queue continuously, wherein if new entry in Task2Execute queue also present in Task2Abort queue then remove entry from Task2Execute and Task2Abort queue. Then, checking for the Autoscaling flag. Then, checking if the number of workers and available task are same, wherein push all task and task parameters to worker for future execution, if true. Then, checking if there are any worker that is triggered but are unavailable for execution, wherein add all triggered and available workers in one variable and take the difference of available tasks, and start workers that are needed for all task execution. Then, taking the difference of all available workers and task to execute and trigger the number of workers with the difference. Then, pushing task to available workers and monitor the remaining task to execute. Then, taking the difference between all available workers and task to execute. Then, pushing task to available workers and go to step 1 to monitor remaining task to execute.

In another embodiment, aborting worker in Autoscaling comprises: creating and maintaining a table with information of worker instances such worker ID, Worker running status, worker idle start time, worker idle time. Then, checking if the worker under consideration is running a task, wherein if the worker is busy and not idle, update the idle time status to zero, wherein if the worker is not idle that means idle time would not start hence, maintain it as Not defined. Then, checking if idle start time is Not defined, wherein if true, update the worker idle start time with current time stamp. Then, taking difference of Idle start time and current time stamp and updating the difference in idle time status. Then, checking if idle time status is more than some threshold, wherein if true, terminate the worker based on its credentials.

In another embodiment, a given task having multiple predecessors, all predecessor tasks are expected with successful status, wherein if any one of the predecessor tasks is yet to start or running, the task is not fetched to the worker, whereas if anyone predecessor task fails to execute the task and all next successor task to that branch are aborted.

Figure 3 illustrates an architecture of a system for real-time optimization and intelligent control of server resources and operation cycle in accordance with an embodiment of the present disclosure.

Figures 4A and 4B illustrate the flow chart of task sequencing of workbook with single and multiple tasks to execute respectively in accordance with an embodiment of the present disclosure. A user at a computer may define the single task to execute or may define a complete pipeline of task. Such single or multiple users simultaneously can define multiple tasks or task pipeline from distinct multiple systems. Here, it has been defined that task pipeline as ‘Workbook’. Hence, a Workbook can have a single task to execute or multiple tasks to execute.

The detail steps for workbook execution comprises: defining a task in a workbook to perform any task by a user. Then, defining every task with method and parameters in a workbook. Then, updating the status to “TO RUN” to execute the task defined in workbook. Task sequencing method is continuously check for all the task with “TO RUN” status. Then, copying the task with “TO RUN” status in “TASK READY’ Queue. Then, pushing the tasks with “TO RUN” status from single or multiple users or workbook to execute the stacked task in “TASK READY’ queue. If “TASK READY’ queue is empty that means no task is push for execution hence, execute the task defined in workbook the status is updated to “TO RUN”. If TASK READY queue is not empty. Check if single or multiple tasks are push from a workbook. Then, pushing single task from workbook including: If predecessor of ‘TO RUN’ task is successfully executed then push the task to “TASK TO EXECUTE” queue else go to start, Copy the task with “TO RUN” status to “TASK TO EXECUTE” queue, Update the status of Task from “TO RUN” to “PENDING”, delete the entry from “TASK READY” queue, updating the status to “TO RUN” to execute the task defined in workbook. Then, pushing the multiple tasks from workbook comprising: check for all tasks with no predecessor task. Copy all such Task with “TO RUN” status to “TASK TO EXECUTE” queue; update to status of Task from “TO RUN” to “PENDING”; delete the entry from “TASK READY” queue; updating the status to “TO RUN” to execute the task defined in workbook. Then, continuously checking the tasks with “PENDING” status comprises: if Task with “PENDING” status fails while execution comprises; Update the status for Task from “PENDING TASK” to “TASK FAILED”, Update the status of successor task from “TASK READY” to “TASK ABORTED”, delete the entry of processed Task from “TASK TO EXECUTE” queue, delete the entry of successor Task from “TASK READY” queue. Then, if Task with “PENDING” status successfully executes than comprises; update the status for Task from “PENDING TASK” to “TASK SUCCESSFUL”, copy successor Task with “TO RUN” status to “TASK TO EXECUTE” queue, update the status of successor task from “TASK READY” to “PENDING”, delete the entry of processed Task from “TASK TO EXECUTE” queue, delete the entry of successor Task from “TASK READY” queue. Then, if Task with “PENDING” status is ABORTED by user manually or while execution comprising: update the status for Task from “PENDING TASK” to “TASK ABORTED”, update the status of successor task from “TASK READY” to “TASK ABORTED”, delete the entry of processed Task from “TASK TO EXECUTE” queue, delete the entry of successor Task from “TASK READY” queue.

Figures 5A and 5B illustrate the task abort in task sequencing and task orchestration in accordance with an embodiment of the present disclosure. In figure 5(A) the detail steps for task abortion comprises: if user aborts the workbook execution, update the status in database of a task to ‘ABORT’. Then, check if task is in ‘TASK READY’ queue, if False, i.e., Task is push to execute, Revoke worker that is executing task and update its status to ABORTED. In figure 5(B) the detail steps for task orchestration comprises: continuously monitor the TASK2ABORT queue. Then, if task present in TASK2ABORT queue, remove task entry from both TASK2ABORT and TASK2EXECUTE queue, else go to start.

Figure 6 illustrates the task execution with aborted by user in accordance with an embodiment of the present disclosure. The case mentioned is consider with sample workbook that is proceeded for execution. This results in execution of ‘task 1’ as it has no predecessor. During this execution User aborted future execution of tasks while at Task 2, Task 3, Task 4 are ready to execute and Task 5, Task 6 and Task 7 are in queue to execute all status got updated to ABORT.

Figure 7 illustrates autoscaling task execution for specific workflow in accordance with an embodiment of the present disclosure. The detail steps for Autoscaling Task Execution comprises: monitoring all task pushed in Task2Execute queue Continuously. If new entry in Task2Execute queue also present in Task2Abort queue is true then remove entry from Task2Execute and Task2Abort queue else continue. If autoscaling flag is true then check if number of workers and available task are same else push task to available workers and go to step start to monitor remaining task to execute. If number of workers and available task are same then push all task and task parameters to worker for future execution else check if there are any worker that are triggered but are unavailable for execution. Check If there are any worker that are triggered but are unavailable for execution is true then add all triggered and available workers in one variable and take difference of available task, start workers that are needed for all task execution. Push task to available workers else take difference of all available workers and task to execute. Trigger number of worker with the difference. Take difference of all available workers and task to execute. Trigger number of worker with the difference. Then, pushing task to available workers and go to start to monitor remaining task to execute. Then, taking difference of all available workers and task to execute. Then, pushing task to available workers and go to start to monitor remaining task to execute.

Figure 8 illustrates the worker termination in autoscaling in accordance with an embodiment of the present disclosure. The detail steps for abort worker in Autoscaling comprises: Create and maintain table with information of worker instance such worker ID, Worker running status, worker idle start time, worker idle time. Check if worker under consideration is running a task is true then worker is busy and not idle, update the idle time status to zero (if not zero). As worker not idle that means idle time would not start hence, maintain it as Not defined else check if idle start time is Not defined. Check if idle start time is Not defined else go to start. Take difference of Idle start time and current time stamp. Update this difference in idle time status. Check if idle time status is more than some threshold is true terminate the worker based on its credentials available in table else go to start.

Figure 9 illustrates the task sequencing with processor and without processor in accordance with an embodiment of the present disclosure. The detail steps for execution of task with and without predecessor comprises: Task sequencing with no predecessor; check all new task with no predecessor and TO RUN status, Push task in TASK READY queue, verify if task is in TASK READY queue, if true, push task in TASK2EXECUTE queue.

Task sequencing with predecessor; Check all new task with no predecessor and TO RUN status, push task in TASK READY queue, verify if task is in TASK READY queue, check status of task running on worker is true then, check task type else change all successor task. Check task type weather it is merge task i.e., weather a task requires multiple predecessors is true then, check for all predecessor task status updated to successful else push all successor task from TASK READY queue to TASK2EXECUTE queue. Check for all predecessor task status updated too successful is true then, push all successor task from TASK READY queue to TASK2EXECUTE queue else wait until all task updated. If task status is apart from successful then change all successor task, push all successor task from TASK READY queue to TASK2EXECUTE queue. Go to start, and change all successor task to aborted and remove all entries of successor tasks from TASK READY queue. Go to start.

Collection of all task is one workbook. With all such collection of workbooks is possible to execute using task sequencing and task orchestration. The flow remains same, i.e., all task with no predecessor is considered as first task to execute while successor is fetch as explained in above flow. The execution depends on available workers while autoscaling takes into account the triggering and termination of any worker as conditioned to do so.

Figure 10 illustrates the n-task workbook with or without inter-connections in accordance with an embodiment of the present disclosure. Task is executed with the flow mentioned above while doing so, it also updates the status. The figure shows that task with status with successful are task with no predecessor or predecessor with successful status. The task with running status also has predecessor with successful status while the task that are successor of running task are task that are with status yet to start / Ready to run. The task with status with successful is task with no predecessor or predecessor with successful status. While task with status Failed, the successors status is updated to Aborted.

For a given task that has multiple predecessors, all predecessor tasks are expected with successful status. If any one of the predecessor tasks is yet to start or running, the task is not fetched to worker. If anyone predecessor task fails to execute the task and all next successor task to that branch are aborted.

A system for real-time optimization of server resource on computer-based system is disclosed. Intelligent layer is responsible to schedule a task and allocate appropriate resources. The system includes intelligence layer 102 to monitor server utilization and Task memory requirement. The server utilization comprises of disk space and network 108 usage while task monitoring is based on memory requirement, prioritization and processing requirements. Intelligent layer is responsible to schedule a task and allocate appropriate resources.

The drawings and the forgoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, orders of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts necessarily need to be performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples. Numerous variations, whether explicitly given in the specification or not, such as differences in structure, dimension, and use of material, are possible. The scope of embodiments is at least as broad as given by the following claims.

Benefits, other advantages, and solutions to problems have been described above with regard to specific embodiments. However, the benefits, advantages, solutions to problems, and any component(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as a critical, required, or essential feature or component of any or all the claims. ,CLAIMS:1. A computer-based method for real-time optimization and intelligent control of server resource and operation cycle, the method comprises:
monitoring server utilization and task memory requirements upon deploying a plurality of sensing nodes;
monitoring tasks based on memory requirements, prioritization, and processing requirements using a central processor through a network;
storing tasks in a cloud server platform;
checking execution and finalizing, updating task status, deleting, and enabling all allowed operations to take actions through a task sequencing processor;
performing operations on tasks such as Task storing, task status updating, deletion, and all allowed actions using a task orchestration processor configured to an appropriate resource based on the matrix defined by an auto-scaling mechanism; and
enabling task sequencing and resource optimization based on a predefined method of formulating a task in effective metrics that are used for prioritization through an auto-scaling processor.

2. The method as claimed in claim 1, further comprises defining a single task to execute or may define a complete pipeline of tasks through a user computing device, wherein such single or multiple users simultaneously define multiple tasks or a task pipeline from distinct multiple systems, wherein the task pipeline is preferably a workbook to execute a single task or multiple tasks to execute.

3. The method as claimed in claim 1, wherein the task sequencing processor comprises:
defining a task in a workbook through a graphical user interface, wherein every task defined in the workbook is having a method and a set of parameters to execute;
updating the task status to “TO RUN” thereby each task with “TO RUN” status from single or multiple users or workbooks that are pushed to execute are stacked in “TASK READY’ queue;
checking whether the task is single or multiple;
wherein in case if single task pushed from the workbook includes:
executing push the task to “TASK TO EXECUTE” queue, if the predecessor of ‘TO RUN’ task is successfully executed else go to start;
copying task with “TO RUN” status to “TASK TO EXECUTE” queue;
updating status of task from “TO RUN” to “PENDING”; and
deleting the entry from “TASK READY” queue; and
wherein in case if multiple tasks pushed from the workbook includes:
checking for all tasks with no predecessor task;
copying all such Task with “TO RUN” status to “TASK TO EXECUTE” queue;
updating to the status of Task from “TO RUN” to “PENDING”;
deleting the entry from “TASK READY” queue; and
checking for the tasks with “PENDING” status continuously and delete the entry of the successor Task from “TASK READY” queue.

4. The method as claimed in claim 1, further comprises updating the status for Task from “PENDING TASK” to “TASK FAILED” if Task with “PENDING” status fails while execution, wherein the updating steps comprises;
updating the status of the successor task from “TASK READY” to “TASK ABORTED”;
deleting the entry of the processed Task from “TASK TO EXECUTE” queue;
deleting the entry of the successor Task from “TASK READY” queue; and
wherein if Task with “PENDING” status successfully executes then;
updating the status for Task from “PENDING TASK” to “TASK SUCCESSFUL”;
copying successor Task with “TO RUN” status to “TASK TO EXECUTE” queue;
updating the status of the successor task from “TASK READY” to “PENDING”;
deleting the entry of the processed Task from “TASK TO EXECUTE” queue;
deleting the entry of the successor Task from “TASK READY” queue;
wherein if Task with “PENDING” status is ABORTED by user manually or while execution then;
updating the status for Task from “PENDING TASK” to “TASK ABORTED”;
updating the status of the successor task from “TASK READY” to “TASK ABORTED”;
deleting the entry of the processed Task from “TASK TO EXECUTE” queue; and
deleting the entry of the successor Task from “TASK READY” queue.

5. The method as claimed in claim 1, further comprises executing the Task Abortion in Task Sequencing by updating the status in a database of a task to ‘ABORT’ if the user aborts the Workbook execution and checking whether a task is in ‘TASK READY’ queue, wherein update the task in TASK TO ABORT queue, if True, or push the task to execute, Revoke the worker that is executing the task and update its status to ABORTED, if False.

6. The method as claimed in claim 1, further comprises executing the Task Abortion in Task Orchestration upon continuously monitoring the TASK2ABORT queue, thereby removing task entry from both TASK2ABORT and TASK2EXECUTE queue, if the task is present in TASK2ABORT queue.

7. The method as claimed in claim 1, further comprises employing the auto-scaling unit for autoscaling task execution for a specific workflow comprises:
monitoring all task pushed in Task2Execute queue continuously, wherein if new entry in Task2Execute queue also present in Task2Abort queue then remove entry from Task2Execute and Task2Abort queue;
checking for the Autoscaling flag;
checking if the number of workers and available task are same, wherein push all task and task parameters to worker for future execution, if true;
checking if there are any worker that is triggered but are unavailable for execution, wherein add all triggered and available workers in one variable and take the difference of available tasks, and start workers that are needed for all task execution;
taking the difference of all available workers and task to execute and trigger the number of workers with the difference;
pushing task to available workers and monitor the remaining task to execute;
taking the difference between all available workers and task to execute; and
pushing task to available workers and go to step 1 to monitor remaining task to execute.

8. The method as claimed in claim 1, further comprises aborting worker in Autoscaling comprises:
creating and maintaining a table with information of worker instances such worker ID, Worker running status, worker idle start time, worker idle time;
checking if the worker under consideration is running a task, wherein if the worker is busy and not idle, update the idle time status to zero, wherein if the worker is not idle that means idle time would not start hence, maintain it as Not defined;
checking if idle start time is Not defined, wherein if true, update the worker idle start time with current time stamp;
taking difference of Idle start time and current time stamp and updating the difference in idle time status; and
checking if idle time status is more than some threshold, wherein if true, terminate the worker based on its credentials.

9. The method as claimed in claim 1, wherein for a given task having multiple predecessors, all predecessor tasks are expected with successful status, wherein if any one of the predecessor tasks is yet to start or running, the task is not fetched to the worker, whereas if anyone predecessor task fails to execute the task and all next successor task to that branch are aborted.

10. A computer-based system for real-time optimization and intelligent control of server resource and operation cycle, the system comprises:
a plurality of sensing nodes for monitoring server utilization and task memory requirements;
a central processor interfaced with a network for monitoring tasks based on memory requirements, prioritization, and processing requirements;
a cloud server platform for storing tasks;
a task sequencing processor for checking execution and finalizing, updating task status, deleting, and enabling all allowed operations to take actions;
a task orchestration processor configured to an appropriate resource based on the matrix defined by an auto-scaling mechanism for performing operations on tasks such as Task storing, task status updating, deletion, and all allowed actions; and
an auto-scaling processor for enabling task sequencing and resource optimization based on a predefined method of formulating a task in effective metrics that are used for prioritization.