Dynamic Workflow Management Using Performance Data

An approach to dynamic workflow management and optimisation using performance data is presented. We discuss strategies for choosing an optimal service (based on user specified criteria) from several semantically equivalent Web Services. Such an approach involves finding "similar" services, by first pruning the set of discovered services based on service metadata, and subsequently selecting an optimal service based on data recorded during prior executions of a service and/or current machine loads. We describe the current implementation of the system, and demonstrate this by a BLAST (used in BioInformatics for Protein-alignment) example by using the Ganglia monitoring tool to get performance data