Finite State Machine Workflow Management in Data Processing Systems
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Solution Overview
Problem
Conventional workflow management systems for data processing systems are inefficient and error-prone, particularly when managing workflows for large numbers of data objects, as they require low-level coding and lack integration with the data processing system, leading to synchronization issues and increased complexity.
Innovation Solution
The integration of a workflow management system with the data processing system using finite state machines (FSMs) to manage workflows for data objects, allowing for efficient identification of authorized actors based on data object attributes and relationships, and enabling the generation of graphical user interfaces for workflow task execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional workflow management systems are used to manage workflows for large numbers of data objects, then the system can handle multiple data objects, but the system becomes inefficient and error-prone due to lack of integration and requirement for low-level coding
Solution Approach 1:
The patent merges the workflow management system with the data processing system by integrating FSM execution directly into the data processing engine. This eliminates the need for separate workflow management infrastructure and low-level coding, allowing workflows to be managed natively within the data processing system, thereby improving productivity while reducing integration complexity
Solution Approach 2:
The data processing system is designed to perform both data processing and workflow management functions through the FSM mechanism. This multi-functionality allows the same system infrastructure to handle both computational tasks and workflow orchestration, eliminating the need for dedicated workflow management systems and reducing overall system complexity
2Reliability
If conventional workflow management systems are used, then workflows can be executed, but synchronization issues occur due to lack of integration with the data processing system
Solution Approach 1:
By merging workflow management with data processing through integrated FSM execution, the system eliminates synchronization issues that arise from separate systems. The FSM state machine executes directly within the data processing workflow, ensuring that workflow state changes and data processing operations are tightly synchronized without requiring complex inter-system communication protocols
3Adaptability or versatility
If low-level coding is required for workflow management, then workflows can be implemented, but the system becomes error-prone and difficult to maintain
Solution Approach 1:
The FSM approach allows workflow behavior to be defined through state transitions and conditions rather than low-level coding. Workflow logic is expressed as configurable state machine parameters (states, transitions, guard conditions) that can be modified without changing underlying code, thereby maintaining adaptability while significantly improving ease of operation and reducing errors
Solution Approach 2:
The integrated FSM system automatically manages workflow execution, state tracking, and transition logic within the data processing system. This self-service capability eliminates the need for manual low-level coding of workflow control logic, reducing implementation difficulty and maintenance burden while preserving workflow customization through configurable state machine definitions
4Productivity
If workflow management is integrated into the data processing system using FSMs, then speed and throughput improve, but the system requires sophisticated state machine implementation
Solution Approach 1:
The workflow management functionality is segmented into discrete FSM components that can be independently defined and executed. Each data object can have its own FSM instance with specific states and transitions, allowing complex workflow logic to be broken down into manageable segments that improve processing speed through structured execution while making implementation more tractable through modular design
Data Source
AI summary
Techniques for using finite state machines (FSMs) to implement workflows in a data processing system comprising at least one data store storing data objects and a workflow management system (WMS). The WMS is configured to perform: determining a current value of an attribute of a first data object by accessing the current value in the at least one data store; identifying, using the current value and metadata specifying relationships among at least some of the data objects, an actor authorized to perform a workflow task for the first data object; generating a GUI through which the actor can provide the input that the workflow task is to be performed; and in response to receiving, from the actor and through the GUI, input specifying that the workflow task is to be performed: performing the workflow task; and updating the current workflow state of the first FSM to a second workflow state.