Supporting and Optimizing Interactive Decision Processes in Grid Environments with a Model-Driven Approach

Increasing the complexity of products and processes in engineering domains, accompanied by time as well as cost pressures, lead to complex decision processes comprising human expert's interaction and excessive use of sophisticated tools from computational engineering. Grid technology offers both basic concepts and tools to automate decision processes as Grid workflows and to integrate distributed resources for computational engineering. Grid computing infrastructures and service-oriented architectures commonly rely on web services as their implementation technology. This technology allows complex workflows to be designed and executed by workflow engines in either Grid or standard web service environments. Nevertheless, the integration of human intervention in Grid workflows is still a manual, therefore time-consuming and error-prone task, caused by the lack of software support for designing workflows that incorporate human tasks in Grid environments. Furthermore, service-oriented architecturess (and especially dynamic Grid infrastructures) are subject to frequent changes, influencing the workflows running on them. This fact makes a good workflow design a non-trivial task, making IT support for automatically optimizing workflows running on service-oriented architectures in Grid environments a valuable issue. In this paper, we present a model-driven approach for designing efficient Grid workflows covering both the topics of human tasks and automatic transformation and optimization of a workflow regarding the underlying infrastructure and its performance characteristics. The solution also covers the automatic creation of user interfaces for human interventions. The approach is implemented and validated by a virtual prototyping process from metal casting.