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The paper presents a complete solution for modeling scientific and business workflow applications, static and just-in-time QoS selection of services and workflow execution in a real environment. The workflow application is modeled as an acyclic directed graph where nodes denote tasks and edges denote dependencies between the tasks. The BeesyCluster middleware is used to allow providers to publish services from sequential or parallel applications, from their servers or clusters. Optimization algorithms are proposed to select a capable service for each task so that a global criterion is optimized such as a product of workflow execution time and cost, a linear combination of those or minimization of the time with a cost constraint. The paper presents implementation details of the multithreaded workflow execution engine implemented in JEE. Several tests were performed for three different optimization goals for two business and scientific workflow applications. Finally, the overhead of the solution is presented.

Modeling, run-time optimization and execution of distributed workflow applications in the JEE-based BeesyCluster environment