Abstract:

Centralised orchestration of service-oriented workflows presents significant scalability challenges, these include: the consumption of network bandwidth, degradation of performance, and single points of failure. These challenges are particularly prominent when dealing with highly distributed data-intensive workflows, which involve large quantities of intermediate data that need to be routed through a centralised engine. In this talk we present a dataflow specification language and a distributed architecture that attempt to address these scalability challenges. Our language provides simple abstractions for orchestrating large-scale web service workflows and separates between the workflow logic and its execution. It is based on a data-driven execution model that permits parallelism to improve the workflow performance. Unlike classical approaches of distributed computing, our architecture allows the computation to be moved “closer” to services in the workflow; this is achieved by partitioning the workflow specification into smaller fragments which may be sent to remote locations for execution.

Bio:

Ward is a research student supervised by Dr. Adam Barker and Prof. Alan Dearle. He completed an M.Sc. in Software Engineering at the University of St Andrews. His research interests span the areas of software engineering, distributed computing, and service-oriented architecture, with a focus on building practical solutions for improving the scalability and performance of software systems.