Characterizing and profiling scientific workflows
Future Generation Computer Systems
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As computational techniques for tracking provenance have become more widely used, applications are beginning to produce large quantities of provenance information. Furthermore, many of these applications are composed from distributed components (e.g. scientific workflows) that may, for reasons of scalability, security or policy, need to store this information across multiple sites. In this paper, we describe an algorithm, D-PQuery, for determining the provenance of data from distributed sources of provenance information in a parallel fashion. To enable scientist to use D-PQuery on already existing Grid infrastructure, we present an implementation of the algorithm as a Condor DAGMan workflow that works across Kickstart records, which are produced in several production e-Science applications including the example application used in this paper, the astronomy application, Montage. Initial performance benchmarks are also presented.