Cost and accuracy sensitive dynamic workflow composition over grid environments

A myriad of recent activities can be seen towards dynamic workflow composition for processing complex and data in-tensive problems. Meanwhile, the simultaneous emergence of the grid has marked a compelling movement towards making datasets and services available for ubiquitous access. This development provides new challenges for workflow systems, including heterogeneous data repositories and high process-ing and access times. But beside these problems lie oppor-tunities for exploration: The grid’s magnitude offers many paths towards deriving essentially the same information al-beit varying execution times and errors. We discuss a frame-work for incorporating QoS in a dynamic workflow compo-sition system in a geospatial context. Specific contributions include a novel workflow composition algorithm which em-ploys QoS-aware apriori pruning and an accuracy adjust-ment scheme to flexibly adapt workflows to given time re-strictions. A performance evaluation of our system suggests that our pruning mechanism provides significant efficiency towards workflow composition and that our accuracy adjust-ment scheme adapts gracefully to time and network limita-tions.