Moving Volunteer Computing towards Knowledge-Constructed, Dynamically-Adaptive Modeling and Scheduling

Volunteer computing projects supported by BOINC have been exploring new research directions. For example, mature projects like Folding@home are moving towards the use of a broader range of architectures and computers. Other projects such as Docking@Home are exploring multi-scale, resource-driven and application-driven adaptations of the volunteer system. This paper presents results that enforce the need for knowledge-constructed capabilities in volunteer computing projects, i.e., the capability to drive simulations based on application-results and resource-status. The Docking@Home project, which uses volunteer resources to study putative drugs by computationally simulating the behavior of small molecules (ligands) when docking to a protein, serves as a case study to positively assess two key hypotheses. The first hypothesis claims that the adaptive selection of computational models for docking simulations based on the features of the protein and ligand can positively affect the final accuracy of the prediction. The second hypothesis claims that the adaptive selection of volunteer resources can ultimately improve project throughput.