Data Flow Management System with Dynamic Branching and Shunting
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Solution Overview
Problem
Current methods for handling business data flow in Enterprise Resource Planning (ERP) systems lack the capability to perform data branching and data shunting operations, leading to redundant executions of business tasks and inefficient use of computing resources.
Innovation Solution
A data flow management system and method that utilize a processor to execute task nodes in a data flow, determining whether to acquire the next task node based on the data state reaching a target state, and deciding whether to execute it in a data branching mode, data shunting mode, or path selection mode according to a data feature set and branch identifier.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional business processing flow is used without data branching and shunting capabilities, then the system can execute business tasks, but computing resources are wasted due to redundant executions
Solution Approach 1:
The patent introduces dynamic decision-making capabilities to the data flow execution process. The system can dynamically determine whether to execute a task node in data branching mode, data shunting mode, or path selection mode based on real-time data state assessment. This dynamic adaptation eliminates redundant executions by selecting the most appropriate execution path, thereby improving computing efficiency and reducing resource waste.
Solution Approach 2:
The patent changes the execution parameters of task nodes based on data state conditions. By assessing whether data state reaches a target state and using data feature sets with branch identifiers, the system adjusts execution parameters to enable branching, shunting, or path selection modes. This parameter adjustment prevents redundant task executions and optimizes computing resource utilization.
2Productivity
If data branching and shunting operations are added to the data flow, then computing efficiency improves, but system complexity increases
Solution Approach 1:
The patent segments the data flow execution into distinct modes: data branching mode, data shunting mode, and path selection mode. Each mode corresponds to a specific execution strategy based on data state conditions. This segmentation simplifies the overall complexity by breaking down the decision-making process into manageable segments, making it easier to implement and maintain while achieving improved processing efficiency.
Solution Approach 2:
The patent introduces an intermediary assessment mechanism that evaluates data state against target states and matches data features with branch identifiers before execution. This intermediary layer acts as a mediator between data input and task execution, simplifying the control logic by centralizing the decision-making function. The intermediary structure makes the system more manageable while enabling efficient data processing through branching and shunting operations.
Data Source
AI summary
A data flow management system and a data flow management method are provided. The data flow management system includes a memory and a processor electrically connected to the memory and executing a data flow. The processor executes task nodes in the data flow, generates output data, and determines whether a data state of the output data reaches a target data state to decide whether to acquire a next task node in the data flow. When the processor determines the data state of the output data does not reach the target data state, the processor acquires the next task node and decides to execute the next task node in a data branching mode or a data shunting mode according to a data feature set and a branch identifier. When the processor determines the data state of the output data reaches the target data state, the processor ends the data flow.