A framework for the design and reuse of grid workflows

Grid workflows can be seen as special scientific workflows involving high performance and/or high throughput computational tasks. Much work in grid workflows has focused on improving application performance through schedulers that optimize the use of computational resources and bandwidth. As high-end computing resources are becoming more of a commodity that is available to new scientific communities, there is an increasing need to also improve the design and reusability "performance" of scientific workflow systems. To this end, we are developing a framework that supports the design and reuse of grid workflows. Individual workflow components (e.g., for data movement, database querying, job scheduling, remote execution etc.) are abstracted into a set of generic, reusable tasks. Instantiations of these common tasks can be functionally equivalent atomic components (called actors) or composite components (so-called composite actors or subworkflows). In this way, a grid workflow designer does not have to commit to a particular Grid technology when developing a scientific workflow; instead different technologies (e.g. GridFFP, SRB, and scp) can be used interchangeably and in concert. We illustrate the application of our framework using two real-world Grid workflows from different scientific domains, i.e., cheminformatics and bioinformatics, respectively.