Abstract:
Maintaining and operating manual main distribution frames is labour-intensive. As a result, Automated
Main Distribution Frames (AMDFs) have been developed to alleviate the task of maintaining
subscriber loops. Commercial AMDFs are currently employed in telephone exchanges in some parts
of the world. However, the most significant factors limiting their widespread adoption are costeffective
scalability and reliability. Therefore, an impelling incentive is provided to create a simulation
framework in order to explore typical implementations and scenarios. Such a framework will
allow the evaluation and optimisation of a design in terms of both internal and external redundancies.
One of the approaches to improve system performance, such as system reliability, is to allocate the
optimal redundancy to all or some components in a system. Redundancy at the system or component
levels can be implemented in one of two schemes: parallel redundancy or standby redundancy. It is
also possible to mix these schemes for various components. Moreover, the redundant elements may
or may not be of the same type. If all the redundant elements are of different types, the redundancy
optimisation model is implemented with component mixing. Conversely, if all the redundant components are identical, the model is implemented without component mixing.
The developed framework can be used both to develop new AMDF architectures and to evaluate
existing AMDF architectures in terms of expected lifetimes, reliability and service availability. Two
simulation models are presented. The first simulation model is concerned with optimising central
office equipment within a telephone exchange and entails an environment of clients utilising services.
Currently, such a model does not exist. The second model is a mathematical model incorporating
stochastic simulation and a hybrid intelligent evolutionary algorithm to solve redundancy allocation
problems.
For the first model, the optimal partitioning of the model is determined to speed up the simulation
run efficiently. For the second model, the hybrid intelligent algorithm is used to solve the redundancy
allocation problem under various constraints. Finally, a candidate concept design of an AMDF is
presented and evaluated with both simulation models.
