Abstract:
The field of optimisation covers a great multitude of
principles, methods and frameworks aimed at maximisation
of an objective under constraints. However, the classical
optimisation can not be easily applied in the context
of computer-based systems architecture as there is not
enough knowledge concerning the dependencies between
non-functional qualities of the system. Out approach is
based on the simulation optimisation methodology where
the system simulation is first created to assess the current
state of the design with respect to the objectives. The results
of the simulation are used to construct a Bayesian Belief
Network which effectively becomes a base for an objective
function and serves as the main source of the decision
support pertaining to the guidance of the optimisation process.
The potential effects of each proposed change or
combination of changes is then examined by updating and
re-evaluating the system simulation.
