Deriving network topologies from real world constraints

Realistic network topologies are crucial for network research and are commonly used for the analysis, simulation, and evaluation of various mechanisms and protocols. In this paper, we discuss network topology models to generate physical topologies for backbone networks. In order to gain better understanding of current topologies and engineer networks for the future, it is necessary to generate realistic physical topologies that are governed by the infrastructure as opposed to only logical topologies that are governed by policy or higher-layer abstractions. The objective of this work is to present the principles that are key to node distributions of realistic topologies and the challenges involved. We argue that the dominant factors that influence the location of the PoPs are population density distribution and the technology penetration of a given region. Hence we implement a clustering algorithm to accurately predict the location of PoPs and later explore cost constrained models to generate realistic physical topologies.