One relatively unexplored question about the Internet's physical
structure concerns the geographical location of its components:
routers, links and autonomous systems (ASs). We study this question
using two large inventories of Internet routers and links, collected
by different methods and about two years apart. We first map each
router to its geographical location using a state-of-the-art
tool. We then study the relationship between router
location and population density; between geographic distance and link
density; and between the size and geographic extent of ASs.
Our findings, which are consistent across the two datasets, have
significant implications for representative network topology generation.
First, as expected, router density per person varies widely
over different economic regions; however, in economically homogeneous
regions, router density shows a strong superlinear relationship to
population density. Second, the probability that two routers are
directly connected is strongly dependent on distance; our data is consistent
with a model in which a majority (up to 75-95\%) of link formation is
based on geographical distance (as in the Waxman topology generation
method). Finally, we find that ASs show high variability in geographic
size, which is correlated with other measures of AS size (degree and
number of interfaces). Among small to medium ASs,
ASs show wide variability in their geographic dispersal;
however, all ASs exceeding a certain threshold in size are maximally
dispersed geographically.
(This is joint work with with Anukool Lakhina, John Byers, and Ibrahim Matta.)
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