  Modern communication networks are inherently complex in nature. First of all,
they have a large number of heterogeneous components. Secondly, their
connectivity is extremely dynamic. Nodes can come and go, links can be removed
and added over time. Traditional modeling and simulation techniques amalgamate
or ignore such dynamics and therefore, are unable to represent them. Complex
communication networks are therefore better modeled as mathematical structures
called graphs. Modeling as graphs allows for the application of complex
techniques such as various network based analysis techniques. While this is a
very important and much needed skill for communication networks researchers and
engineers, to the best of our knowledge, currently there is no resource
describing these details. In this paper, we give a concise but comprehensive
review of modeling complex communication networks as graphs. We also show how
to apply complex social network analysis on these models besides a
demonstration of formal modeling network dynamics.
