Scale-Free Networks: A Discrete Event Simulation Approach

This work is motivated by the need to reconsider the methods for the analysis and design of air transportation networks in order to meet increasing demands in the face of the current hub-and-spoke network near-saturation. In the late 1990s a number of researchers noticed that networks in biology, sociology, and telecommunications exhibited similar characteristics unlike traditional random networks. Three properties—small-world, power law, and constant clustering coefficient—describe what are now most commonly referred to as scale-free networks. How do scale-free networks form? It is well documented that a network generated by adding nodes and edges preferentially will be scale-free. Are there other mechanisms? Why do networks organize themselves in this way? What causes a scale-free network to degrade? The focus of our research is to understand what drives a collection of nodes to organize as a scale-free network. Furthermore, once a network is scale-free what disrupts this apparently natural structure. To answer these questions we build a discrete-event simulation, nominally of an air transport system. The simulation is written in C.