A selective-abstraction modeling approach for simplifying computer network studies
Author
Che, Xianhui
Wells, Ian
Attention
2299/16882
Abstract
Modeling and simulation technique is an essential skill on the pathway of learning and researching computer networks. However, the complexity and scale of the network nowadays often challenges the modeling techniques, as high-specification hardware environment is usually required and the simulation can be inevitably time-consuming. The selective abstraction technique leaves out redundant codes and only implements mandatory threads that can have impact on the simulation results. The investigation of this technique is done through a case study of a star-topology local area network which offers collision-free packet switching. Results show that the abstraction approach effectively reduces the length and complication of the source code and also makes the program-debugging process much easier, hence brings users valuable experience in time-saving learning and research throughout computer network study based on modeling and simulations.