Abstract. An approach to dynamic workflow management and optimisation using near-realtime performance data is presented. Strategies are discussed for choosing an optimal service (based on user-specified criteria) from several semantically equivalent Web services. Such an approach may involve finding "similar" services, by first pruning the set of discovered services based on service metadata, and subsequently selecting an optimal service based on performance data. The current implementation of the prototype workflow framework is described, and demonstrated with a simple workflow. Performance results are presented that show the performance benefits of dynamic service selection. A statistical analysis based on the first order statistic is used to investigate the likely improvement in service response time arising from dynamic service selection.
Work described in REF presents an approach for dynamic workflow management and optimisation using near-realtime performance with strategies for choosing an optimal service, based on user-specified criteria, from several semantically equivalent Web services.
Dynamic service selection in workflows using performance data
Scientific Programming
Scientific Programming
Computer Science