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:

  1. develop model-to-model transformations from BPMN
    into layered queueing networks (LQNs) that can ex-
    ploit the speci c features of matrix-analytic methods
  2. to accurately and eciently evaluate BPMN models,
    de ning novel LQN analysis algorithms based on de-
    composition methods and MAM;
  3. develop a case study on work ow optimisation with our
    partner BOC, validating our algorithms on real-world
    BPMN instances;
  4. integrate the developed and validated algorithms in
    Line, our open source LQN solver.

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