Workflow Definition Language for Data Flow Control
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Solution Overview
Problem
Traditional workflow services lack flexibility in specifying data flow manipulation and ensuring data flow integrity during state transitions, limiting user-defined workflows with complex computational tasks.
Innovation Solution
A workflow definition language that allows users to define workflows with detailed state transitions, data flow manipulation, and error handling through JSON syntax, enabling parallel execution and robust error management, and allowing workflows to be executed across multiple computing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional workflow tools are used to define sequences of tasks, then workflow execution is simple, but flexibility in specifying data flow manipulation and data flow object integrity is limited
Solution Approach 1:
The patent changes the parameters of workflow definition by introducing a general-purpose programming language instead of a domain-specific language. This allows users to leverage existing programming knowledge while defining workflows, thereby improving flexibility in data flow manipulation without proportionally increasing the learning curve. The system supports parameterized task definitions and dynamic data flow specifications.
Solution Approach 2:
The workflow system achieves universality by using a general-purpose programming language that can express both simple sequential tasks and complex data flow manipulations. The same language framework handles various workflow patterns including data flow object integrity constraints, parallel execution, and error handling, eliminating the need for multiple specialized languages.
2Reliability
If traditional workflow tools are used, then implementation is straightforward, but ability to ensure data flow integrity during state transitions is insufficient
Solution Approach 1:
The system implements feedback mechanisms through data flow object integrity constraints that monitor and verify data integrity during state transitions. The workflow engine provides feedback about data flow status, enabling users to define checks and validations that ensure integrity while the system automatically manages the complexity of enforcement.
Solution Approach 2:
The patent applies preliminary action by allowing users to pre-define data flow integrity constraints and error handling logic before workflow execution. These constraints are established in advance and automatically enforced during state transitions, ensuring data flow integrity without requiring complex real-time management during execution.
3Productivity
If workflows are executed sequentially, then resource allocation is simple, but processing efficiency and productivity are reduced
Solution Approach 1:
The workflow system transitions from static sequential execution to dynamic execution models that support parallel and concurrent task execution. The engine dynamically manages workflow states, allowing independent tasks to execute simultaneously while maintaining coordination through defined data flow constraints, thereby improving productivity without proportionally increasing management complexity.
Solution Approach 2:
The patent segments workflows into independent, executable units that can be processed in parallel. By dividing the workflow into discrete state transitions and tasks that can be executed concurrently, the system improves processing efficiency. The segmentation allows the execution manager to distribute work across multiple resources while maintaining overall workflow coherence.
Data Source
AI summary
A workflow interpreter service that interprets a workflow definition language for specifying a workflow definition. Further, the workflow definition language provides features for maintaining control over data flows for data that is passed from one state to another among states of a state machine for a workflow. Such control over data flow in between states allows for a given workflow to be processed incrementally, and among multiple different computing resources.