Adaptive Execution Planning in Biomedical Workflow Management Systems

Workflow management systems try to move grid, cloud and high performance computing (HPC) services closer to scientific and industrial community by providing a user-friendly interface enabling definition of complex problems presented as workflows. Workflows provide a formal way to define and automate multi-step procedures reflecting real-world phenomena. However, this still places demands on users to decide how to execute particular tasks in workflows. k-Dispatch, a platform providing automated tasks execution, planning and monitoring, focuses on selected workflows from medical environment. For security reasons, only in-house code binaries tuned for specific HPC resources are used. k-Dispatch screens out users from the complexity of HPC systems. This paper describes how the presented framework deals with the task execution planning. Static planning that uses default execution parameters may not be sufficient for the effective execution since the results delivery is time-constrained, and there is an effort to minimize the computational cost. Adaptive planning discussed in this paper may improve this process.