Provided by: University of Udine
Topic: Big Data
In this paper, the authors show how flexibility can be realized for distributed workflows. The capability to dynamically adapt workflow instances during runtime (e.g., to add, delete or move activities) constitutes a fundamental challenge for any Workflow Management System (WfMS). While there has been significant research on ad-hoc workflow changes and on related correctness issues, there exists only little work on how to provide respective runtime flexibility in an enterprise-wide context as well. Here, scalability at the presence of high loads constitutes an essential requirement, often necessitating distributed (i.e., piecewise) control of a workflow instance by different workflow servers, which should be as independent from each other as possible.