Dynamic Timeout Adjustment for Workflow Nodes
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional timeout settings in service-oriented architecture (SOA) systems are rigid and do not account for varying execution contexts, leading to unnecessary workflow failures.
Innovation Solution
Dynamic optimization of timeout settings for nodes in a workflow by calculating the difference between the actual execution time of a parent node and its timeout setting, and adding this difference to the timeout setting of a child node to prevent premature timeouts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional rigid timeout settings are used for workflow nodes, then the system structure is simple and easy to manage, but the workflow may fail needlessly due to not accounting for different execution contexts
Solution Approach 1:
The patent implements dynamic timeout adjustment by calculating the difference between parent node timeout and actual execution time, then applying this adjustment to child node timeouts. This transforms static timeout settings into dynamic ones that adapt to actual runtime conditions, resolving the contradiction between reliability and complexity.
Solution Approach 2:
The system changes the timeout parameter values based on actual execution performance. By monitoring the difference between configured timeout and actual execution time of parent nodes, the system adjusts child node timeout parameters accordingly, improving workflow reliability without requiring complex manual configuration.
2Adaptability or versatility
If fixed timeout values are assigned to all nodes, then configuration is simple, but the system cannot adapt to varying execution contexts and may cause premature timeouts
Solution Approach 1:
The system performs preliminary timeout adjustment by calculating the time difference between parent node timeout setting and actual execution time before child nodes start execution. This preliminary action allows child nodes to benefit from the time savings without requiring complex real-time monitoring during their execution.
Solution Approach 2:
The system uses feedback from parent node execution performance (the difference between timeout and actual execution time) to adjust child node timeout settings. This feedback mechanism enables the system to adapt to varying execution contexts automatically, improving versatility while keeping configuration simple.
3Productivity
If timeout settings are optimized dynamically at runtime, then workflow execution becomes smoother and more reliable, but the system complexity increases
Solution Approach 1:
The patent applies local quality by optimizing timeout settings specifically for child nodes based on their parent node's execution performance, rather than uniformly adjusting all nodes. This targeted approach improves workflow execution efficiency while minimizing the complexity increase to only the necessary parts of the system.
Data Source
AI summary
A unidirectional workflow execution engine is accessed. The unidirectional workflow includes at least a first node and a second node, where the first node is executed before the second node. A timeout setting of the first node is retrieved. An actual execution time of the first node is determined. A difference between the retrieved timeout setting and the actual execution time of the first node is calculated. A timeout setting of the second node is retrieved. The timeout setting of the second node is modified by adding, to the retrieved timeout setting of the second node, the calculated difference between the retrieved timeout setting and the execution time of the first node.