Data Pointer Project Management for Parallel Task Processing
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Solution Overview
Problem
Existing project management methods struggle with efficiently processing complex projects involving multiple tasks, leading to increased project duration and resource inefficiencies.
Innovation Solution
A project management method and device using a data pointer to transmit and process source data across multiple child projects, where result data from one project is used as source data for the next, optimizing task processing and resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a conventional single-task project structure is used, then the project structure is simple, but the project duration increases and productivity decreases when handling complex multi-task projects
Solution Approach 1:
The patent divides a complex project into multiple child projects, each representing a specific task type (e.g., transcription, translation, formatting). This segmentation allows each child project to be processed independently and in parallel, significantly improving overall project productivity while maintaining manageable complexity through modular organization.
Solution Approach 2:
The patent introduces a hierarchical dimension to project structure by creating parent-child project relationships. This dimensional change enables simultaneous processing of multiple child projects under a single parent project, transforming a linear single-task structure into a parallel multi-task structure that improves efficiency without proportionally increasing complexity.
2Duration of action of moving object
If multiple child projects are processed sequentially, then the project structure remains simple, but the project duration increases significantly
Solution Approach 1:
The patent performs preliminary actions by pre-defining the hierarchical project structure and task dependencies before execution. Child projects are prepared and configured in advance with their respective tasks, enabling them to be launched simultaneously rather than sequentially, thus reducing overall project duration while maintaining high throughput.
Solution Approach 2:
The patent ensures continuous useful action by overlapping the execution of multiple child projects. While one child project is being processed, another can simultaneously begin, eliminating idle time between tasks and maximizing resource utilization, thereby reducing project duration without sacrificing processing quality.
3Loss of time
If result data is copied to source data for the next child project, then data transmission is simple, but resource utilization decreases and processing time increases
Solution Approach 1:
The patent uses copying to create references to result data from parent projects and uses these as source data for child projects. Instead of physically duplicating large datasets, the system creates lightweight reference copies that point to the original data locations, minimizing resource consumption while enabling efficient data transmission across project hierarchies.
Solution Approach 2:
The patent introduces an intermediary data structure that acts as a bridge between parent project results and child project sources. This intermediary layer manages data references and transformations, reducing direct data copying operations and improving resource utilization by handling data transmission through an optimized intermediate interface.
Data Source
AI summary
Disclosed are a method and device for managing a project by using a data pointer. A project is efficiently operated by dividing a project based on a minimum unit task and designing a plurality of child projects connected in sequential order such that a plurality of child projects proceed in order.