University of Toronto, 2013.
In this work, we develop an approach for safe distribution and parallel execution of data-centric workflows over the publish/subscribe abstraction. In essence, we present a novel re-formulation of data-centric workflows that is designed to utilize the loosely coupled and distributed nature of publish/subscribe systems. Furthermore, we argue for the practicality and expressiveness of our approach by mapping an industry-based data-centric workflow, namely, IBM Business Artifacts with Guard-Stage-Milestone (GSM), into the publish/subscribe abstraction. In short, the contributions of this work are three-fold: (1) mapping of data-centric workflow into publish/subscribe to achieve distributed and parallel execution; (2) detailed theoretical analysis of our mapping; and (3) formalizing the complexity of optimal workflow distribution over the publish/subscribe abstraction.