A new optimization phase for scientific workflow management systems
Proposal of a novel optimization phase to the common scientific workflow life cycle. Development of an automated optimization framework implementing the optimization phase. Plugin mechanism to support the development of arbitrary optimization methods. Implementation of a Genetic Algorithm-based parameter optimization plugin. Optimization of two use cases to demonstrate ease of use and computational efficiency.
workflow life cycle e-science workflow optimization taverna genetic algorithm