Graph Annotations in Modeling Complex Network Topologies
Xenofontas Dimitropoulos, Dmitri Krioukov, Amin Vahdat, George Riley

TL;DR
This paper introduces a framework for modeling complex network topologies using annotations to capture internal structures and correlations, enabling realistic network simulations and better understanding of Internet-like networks.
Contribution
It presents a novel algorithm to rescale network annotations for generating networks of different sizes that preserve original correlation profiles.
Findings
Accurately captures annotation correlation structures in Internet AS topology
Reproduces key properties of the Internet topology in synthetic graphs
Enables realistic simulation of network evolution and protocols
Abstract
The coarsest approximation of the structure of a complex network, such as the Internet, is a simple undirected unweighted graph. This approximation, however, loses too much detail. In reality, objects represented by vertices and edges in such a graph possess some non-trivial internal structure that varies across and differentiates among distinct types of links or nodes. In this work, we abstract such additional information as network annotations. We introduce a network topology modeling framework that treats annotations as an extended correlation profile of a network. Assuming we have this profile measured for a given network, we present an algorithm to rescale it in order to construct networks of varying size that still reproduce the original measured annotation profile. Using this methodology, we accurately capture the network properties essential for realistic simulations of…
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