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• Many of these 7 models considered produce similar
macroscopic features (degree distribution, clustering, diameter,
• Delve into microscopic details and let the data distinguish
between the 7 models.
• Must start with models that are accurate statistical ﬁts to data!
(different type of model validation). (Acompanying commentary,
Rice et al PNAS 2005, DMC does not reproduce giant
• Vladimir Filkov lecture next time 2/7/11 “Understanding Internet Topology:
Principles, Models, and Validation”
D. Alderson, L. Li, W. Willinger, and J. C. Doyle, IEEE/ACM Trans. on
Networking, 13 (6), 2005. • I chose this paper since they explicitly claim to deal with
• “First principles” approach to router-level Internet modeling.
• Consider capability of real routers (annotated graph).
• Consider core versus edge requirements.
• From this design “optimal” networks.
• Compare with sampled topologies of actual internet, and show
that constraint-capacity performance curve of real routers ﬁt
with their hypothesis. Motivation – Need accurate models of the internet
• Testing and evaluating protocols
• Protecting against and detecting attacks
• Improved designs and resource provisioning
→ need annotated graphs, with bandwidth capacity explicit (also
router buffer capacity).
• Given topology generated from a model, which statistical
properties to test?
• Ascribing meaning to model details. (Why would a random
construction relate to an engineered network?) Router level connectivity
• Layer 2 (data-link layer) connectivity
Open Systems Interconnection (OSI) Reference Model
7 Application Layer
6 Presentation Layer
5 Session Layer
4 Transport Layer
3 Network Layer
2 Data Link Layer
1 Physical Layer Past work – structural topology generators
• Random connectivity (e.g., Waxman model)
• Transit-stub models of Zegura (Georgia Tech Internetwork
• But this miss the broad-scale (power-law-like) distributions in
connectivity presumed to b...
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This document was uploaded on 03/12/2014 for the course CSCI 289 at UC Davis.
- Winter '11