Quality of data driven simulation workflows

Abstract

Simulations are characterized by long running calculations and complex data handling tasks accompanied by non-trivial data dependencies. The workflow technology helps to automate and steer such simulations. Quality of Data frameworks are used to determine the goodness of simulation data, e.g., they analyze the accuracy of input data with regards to the usability within numerical solvers. In this paper, we present generic approaches using evaluated Quality of Data to steer simulation workflows. This allows for ensuring that the predefined requirements such as a precise final result or a short execution time will be met even after the execution of simulation workflow has been started. We discuss mechanisms for steering a simulation on all relevant levels - workflow, service, algorithms, and define a unifying approach to control such workflows. To realize Quality of Data-driven workflows, we present an architecture realizing the presented approach and a WS-Policy-based language to describe Quality of Data requirements and capabilities.