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A first-principles approach to understanding the internet's router-level topology
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Source Applications, Technologies, Architectures, and Protocols for Computer Communication archive
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications table of contents
Portland, Oregon, USA
SESSION: Network geometry and design table of contents
Pages: 3 - 14  
Year of Publication: 2004
ISBN:1-58113-862-8
Also published in ...
Authors
Lun Li  California Institute of Technology
David Alderson  California Institute of Technology
Walter Willinger  California Institute of Technology
John Doyle  California Institute of Technology
Sponsors
ACM: Association for Computing Machinery
SIGCOMM: ACM Special Interest Group on Data Communication
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 27,   Downloads (12 Months): 273,   Citation Count: 25
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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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CITED BY  25
 
 
 
 
 
 
 
 
 

Collaborative Colleagues:
Lun Li: colleagues
David Alderson: colleagues
Walter Willinger: colleagues
John Doyle: colleagues