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A model-driven workflow fragmentation framework for collaborative workflow architectures and systems
Authors:Kwanghoon Kim
Affiliation:Collaboration Technology Research Lab, Department of Computer Science, Kyonggi University, South Korea
Abstract:This paper focuses on a workflow distribution methodology for rationally deploying workflow models onto a distributed workflow system running on cloud computing environments, and we particularly lay a stress upon that those workflow systems operable on cloud computing environments are dubbed collaborative workflow systems, which are not only built upon the collaborative workflow architectures proposed in the paper, but pursuing the so-called collaborative computing paradigm characterized by focusing collaboration over cloud computing environments. The essential idea of the workflow distribution methodology is about how to fragment a workflow model and how to allocate its fragments to each of the architectural components configuring the underlying collaborative workflow architecture and system. As a reasonable solution to realize the essential idea, the paper proposes a model-driven workflow fragmentation framework, which provides a series of fragmentation algorithms that semantically fragmentate a workflow model by considering the semantic factors - performer, role, control-flow, data-flow, etc. - of the ICN-based workflow model as fragmentation criteria. The algorithms are classified into the vertical fragmentation approach, the horizontal fragmentation approach, and the hybrid approach of both. Conclusively, this paper conceives a possible set of collaborative workflow architectures embedding the collaborative computing paradigm, and describes the detailed formalism of the framework and about how the framework works on those collaborative workflow architectures and systems.
Keywords:Structured ICN workflow model   System-driven workflow fragmentation   Model-driven workflow fragmentation   Collaborative workflow architecture   Workflow resource allocation   Collaborative computing paradigm   Cloud computing environments
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