OptiMAM is a research project on the optimisation of model-driven service design based on stochastic analysis methods. The OptiMAM project focuses on the definition of novel algorithms to enable the optimisation of service-oriented architecture design and business
process management. The project has a modelling scope and wants to deliver better methods for evaluating and optimising the design of workflows underpinning service-oriented architectures and business processes.
Research objectives of this project are therefore to:
- develop model-to-model transformations from BPMN
into layered queueing networks (LQNs) that can ex-
ploit the specic features of matrix-analytic methods
(MAM); - to accurately and eciently evaluate BPMN models,
dening novel LQN analysis algorithms based on de-
composition methods and MAM; - develop a case study on work ow optimisation with our
partner BOC, validating our algorithms on real-world
BPMN instances; - integrate the developed and validated algorithms in
Line, our open source LQN solver.