If the topologies to be created are artificial, then these references are invaluable:
@InProceedings{mahadevan:_degree_correl,
author = {Priya Mahadevan and Dmitri Krioukov and Kevin Fall
and Amin Vahdat},
title = {Systematic Topology Analysis and Generation Using
Degree Correlations},
crossref = {sigcomm06},
comment = {Fascinating article on ways to generate synthetic topologies
like the Internet. Good summary of prior work:
spectrum, distance distribution, betweenness, node
degree distribution, likelihood, assortativity
coefficient, clustering. They introduce dK
graphs. (topology generator)}
}
@article{mahadevan2006ilt,
title={{The internet AS-level topology: three data sources and one definitive metric}},
author={Mahadevan, P. and Krioukov, D. and Fomenkov, M. and Dimitropoulos, X. and Vahdat, A.},
journal={ACM SIGCOMM Computer Communication Review},
volume={36},
number={1},
pages={17--26},
year={2006},
publisher={ACM Press New York, NY, USA}
}
@article{JohnCDoyle10112005,
author = {Doyle, John C. and Alderson, David L. and Li, Lun and Low, Steven and Roughan, Matthew and Shalunov, Stanislav and Tanaka, Reiko and Willinger, Walter},
title = {{The "robust yet fragile" nature of the Internet}},
journal = {Proceedings of the National Academy of Sciences},
volume = {102},
number = {41},
pages = {14497-14502},
doi = {10.1073/pnas.0501426102},
year = {2005},
abstract = {The search for unifying properties of complex networks is
popular, challenging, and important. For modeling
approaches that focus on robustness and fragility as
unifying concepts, the Internet is an especially
attractive case study, mainly because its
applications are ubiquitous and pervasive, and
widely available expositions exist at every level of
detail. Nevertheless, alternative approaches to
modeling the Internet often make extremely different
assumptions and derive opposite conclusions about
fundamental properties of one and the same
system. Fortunately, a detailed understanding of
Internet technology combined with a unique ability
to measure the network means that these differences
can be understood thoroughly and resolved
unambiguously. This article aims to make recent
results of this process accessible beyond Internet
specialists to the broader scientific community and
to clarify several sources of basic methodological
differences that are relevant beyond either the
Internet or the two specific approaches focused on
here (i.e., scale-free networks and highly optimized
tolerance networks).
},
URL = {http://www.pnas.org/cgi/content/abstract/102/41/14497},
eprint = {http://www.pnas.org/cgi/reprint/102/41/14497.pdf}
}