IMC '05, 2005 Internet Measurement Conference Abstract
Pp. 139152 of the Proceedings
An Empirical Approach to Modeling Inter-AS Traffic Matrices
Hyunseok Chang, Sugih Jamin, and Z. Morley Mao, University of Michigan; Walter Willinger, AT&T LabsResearch
Recently developed techniques have been very successful
in accurately estimating intra-Autonomous System (AS)
These techniques rely on link measurements,
flow measurements, or routing-related data to infer
traffic demand between every pair of ingress-egress
points of an AS. They also illustrate an inherent
mismatch between data needed (e.g., ingress-egress demand)
and data most readily available (e.g., link measurements).
This mismatch is exacerbated when we try to estimate
inter-AS traffic matrices, i.e., snapshots of
Internet-wide traffic behavior over coarse time scale
(a week or longer) between ASs. We present a method
for modeling inter-AS traffic demand that
relies exclusively on publicly available/obtainable
measurements. We first perform extensive Internet-wide
measurement experiments to infer the ``business rationale''
of individual ASs. We then use these business profiles to
characterize individual ASs, classifying them by
their ``utility'' into ASs providing Web hosting, residential
access, and business access.
We rank ASs by their utilities which drive our gravity-model based
approach for generating inter-AS traffic demand. In a first attempt to
validate our methodology, we test our inter-AS traffic
generation method on an inferred Internet AS graph
and present some preliminary findings about the resulting
inter-AS traffic matrices.
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