Of course, there are also theoretical approaches for analyzing the performance of workflows like e.g. the quality of service model introduced by Cardoso et al. [42] and the performance ontologies of Truong et al. [43].
To evaluate the performance of the workflow we performed a comparative lipid analysis of human milk, cow milk, and Lacprodan® PL-20, a phospholipid-enriched milk protein concentrate for infant formula.
In this sense, rescheduling techniques are usually adopted to correct potential deviations from an original guess of the performance of a workflow on a system [61, 127].
The overall shape of the prioritized candidate list (Fig. 2) suggests that the performance of our workflow is consistent with an accurate classification strategy.
Although a formal evaluation of the accuracy of variant calling pipelines remains unfeasible for nonsimulated sequence data (Li 2014), we estimated the performance of the workflow using both sorghum and Arabidopsis sequence data.
This dataset was chosen to evaluate the performance of this workflow in identifying the known LHON-causative mutations since 42 % of these genomes was expected to harbor at least one of the primary mutations included in the panel of the 'Top 14 LHON' annotated in Mitomap (Lott et al. 2013).
However, several issues related to data-intensive loads, complex infrastructures such as hybrid and multicloud environments to support large-scale execution of workflows, performance fluctuations, and reliability, pose as challenges to truly position clouds as viable high-performance infrastructures for scientific computing.
In order to improve the performance of automated workflows the respective systems and workflows have to be monitored [1, 2].
Thus showing the universal applicability of analyzing the performance of automated workflows by means of aggregated task views.
These add-on's are useful for the developers and users of the Taverna and Galaxy systems to scale up their resources and enhance the performance of their workflows.
