Transformation of Cloud Workflow Graphs into Computational Models

Cloud applications can be modeled as workflows. These workflows can be represented as Directed Acyclic Graphs (DAGs) or non-DAGs. A graph shows the relationship between tasks that compose a workflow and the dependencies between them. In this paper, we introduce a method for transforming a workflow application graph into its computational model graph. The generated model provides all possible execution times with their respective probabilities to generate more precise execution time estimates which can be used in better scheduling and resource allocation.