Real-world data networks are large, making them difficult to an-
alyze. Thus, analysts often generate network models of a more
tractable scale to perform simulations and analyses, but even these
models need to be fairly large. Because these networks do not di-
rectly correspond to any particular network, it is often difficult for
the user to construct a mental model of the network. We present
a network model visualization system developed with networking
researchers to help improve the design and analysis of these topolo-
gies. In particular, this systemsupportsmanipulation of the network
layout based on hierarchical information; a novel display technique
to reduce clutter around transit routers; and the mixture of manual
and automatic interaction in the layout phase.
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