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A first-principles approach to understanding the internet's router-level topology

Published:30 August 2004Publication History

ABSTRACT

A detailed understanding of the many facets of the Internet's topological structure is critical for evaluating the performance of networking protocols, for assessing the effectiveness of proposed techniques to protect the network from nefarious intrusions and attacks, or for developing improved designs for resource provisioning. Previous studies of topology have focused on interpreting measurements or on phenomenological descriptions and evaluation of graph-theoretic properties of topology generators. We propose a complementary approach of combining a more subtle use of statistics and graph theory with a first-principles theory of router-level topology that reflects practical constraints and tradeoffs. While there is an inevitable tradeoff between model complexity and fidelity, a challenge is to distill from the seemingly endless list of potentially relevant technological and economic issues the features that are most essential to a solid understanding of the intrinsic fundamentals of network topology. We claim that very simple models that incorporate hard technological constraints on router and link bandwidth and connectivity, together with abstract models of user demand and network performance, can successfully address this challenge and further resolve much of the confusion and controversy that has surrounded topology generation and evaluation.

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    • Published in

      cover image ACM Conferences
      SIGCOMM '04: Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
      August 2004
      402 pages
      ISBN:1581138628
      DOI:10.1145/1015467
      • cover image ACM SIGCOMM Computer Communication Review
        ACM SIGCOMM Computer Communication Review  Volume 34, Issue 4
        October 2004
        385 pages
        ISSN:0146-4833
        DOI:10.1145/1030194
        Issue’s Table of Contents

      Copyright © 2004 ACM

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      Publication History

      • Published: 30 August 2004

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