Topological Structure of Complex Networks and its Importance in Diffusion

The availability of huge data, due to the tremendous storage capacity of modern computers has allowed the systematic  collection, and  high processing speed has permitted  analysis  on  that  data by researchers on a scale far  larger than previously  possible. Due to this, complex  network formation has been seen and observed in many real and artificial complex systems. As these  systems are very large and complex, we cannot get an understanding of these complex systems just by only examining the separate components which constitute these systems. Therefore, modeling  the way these components are interconnected in a system is very  important  for understanding  the system as a whole. Further, despite the enormous variation in their components, functions, and sizes, these networks  are  surprisingly similar in  topology, leading to the conjecture that complex systems  are  governed  by  the ubiquitous self-organizing principle. In this research, we emphasize  on  the  importance of heterogeneous topological structure of real-world complex networks and its importance in understanding the phenomenon of diffusion in these networks.