Abstract
This paper introduces a novel algorithm for dynamically constructing and traversing Directed Acyclic Graphs (DAGs) in workflow systems, particularly targeting distributed computation and data processing domains. Traditional workflow management systems rely on explicitly defined, rigid DAGs, which can be cumbersome to maintain, especially in response to frequent changes or updates in the system. Our proposed algorithm circumvents the need for explicit DAG construction, instead opting for a dynamic approach that iteratively builds and executes the workflow based on available data and operations, through a combination of entities like Data Kinds, Operators, and Data Units, the algorithm implicitly forms a DAG, thereby simplifying the process of workflow management. We demonstrate the algorithm’s functionality and assess its performance through a series of tests in a simulated environment. The paper discusses the implications of this approach, especially focusing on cycle avoidance and computational complexity, and suggests future enhancements and potential applications.
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