Modeling of data communication networks using dynamic complex networks and its performance studies

Abstract

To study the underlying organizing principles of various complex systems, designing an efficient graph-based model for data representation, is a fundamental aspect. As the topological structure of the network changes over time, it is a challenging task to design a communication system having ability to respond to randomly changing traffic. We are interested to find out the suitable and fair traffic flow rates to each system for getting optimal system utility using dynamic complex network model. In this context, we design and simulate a growth model of the data communication network based on the dynamics of in-flowing links which is motivated by the concept that newly added node will connect to the most influential nodes already present in the system. The connectivity distribution of the evolved communication networks follows power law form, free from network scale. We analyze Kelly’s optimization framework for a rate allocation problem in communication networks at different time instants, and optimal rates are obtained with the consideration of arbitrary communication delays.