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On the scaling of congestion in the internet graph
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Volume 34 ,  Issue 3  (July 2004) table of contents
SESSION: Special Section on Science of Network Design table of contents
Pages: 43 - 56  
Year of Publication: 2004
ISSN:0146-4833
Authors
Aditya Akella  Carnegie Mellon University, Pittsburgh, PA
Shuchi Chawla  Carnegie Mellon University, Pittsburgh, PA
Arvind Kannan  Carnegie Mellon University, Pittsburgh, PA
Srinivasan Seshan  Carnegie Mellon University, Pittsburgh, PA
Publisher
ACM  New York, NY, USA
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ABSTRACT

As the Internet grows in size, it becomes crucial to understand how the speeds of links in the network must improve in order to sustain the pressure of new end-nodes being added each day. Although the speeds of links in the core and at the edges improve roughly according to Moore's law, this improvement alone might not be enough. Indeed, the structure of the Internet graph and routing in the network might necessitate much faster improvements in the speeds of key links in the network.

In this paper, using a combination of analysis and extensive simulations, we show that the worst congestion in the Internet AS-level graph in fact scales poorly with the network size (<i>n</i><sup>1+ω(1)</sup>, where <i>n</i> is the number of nodes), when shortest-path routing is used to route traffic between ASes. We also show, somewhat surprisingly, that policy-based routing <i>does not</i> exacerbate the maximum congestion when compared to shortest-path routing.

Our results show that it is crucial to identify ways to alleviate this congestion to avoid some links from being perpetually congested. To this end, we show that the congestion scaling properties of Internet-like graphs can be improved dramatically by introducing moderate amounts of redundancy in the graph in terms of parallel edges between pairs of adjacent nodes.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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BGP Tables from the University of Oregon RouteViews Project. http://moat.nlanr.net/AS/data.
 
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National Laboratory for Applied Network Research. Routing data. http://moat.nlanr.net/Routing/rawdata/.
 
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Akella, A., Chawla, S., Kannan, A., and Seshan, S. Scaling Properties of the Internet Graph. Technical Report CMU-CS-03-131, CMU, Pittsburgh, Pennsylvania, May 2003.
 
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Albert, R., and Barabasi, A.-L. Topology of Evolving Networks: Local Events and Universality. Physical Review Letters 85(24) (2000), 5234--5237.
 
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Barabasi, A.-L., and Albert, R. Emergnece of Scaling in Random Networks. Science 286 (1999), 509--512.
 
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Fenner, T., Flaxman, A., and Frieze, A. High Degree Vertices and Eigenvalues in the Preferential Attachment Graph. In RANDOM 03 (2003), pp. 264--274.
 
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Okamura, H., and Seymour, P. Multicommodity Flows in Planar Graphs. Journal of Combinatorial Theory B 31 (1981), 75--81.
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Subramanian, L., Agarwal, S., Rexford, J., and Katz, R. H. Characterizing the Internet Hierarchy from Multiple Vantage Points. In Proceedings of IEEE INFOCOM (June 2002).
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Winick, J., and Jamin, S. Inet-3.0: Internet Topology Generator. Tech. rep., University of Michigan, 2002. Technical Report, CSE-TR-456-02.


Collaborative Colleagues:
Aditya Akella: colleagues
Shuchi Chawla: colleagues
Arvind Kannan: colleagues
Srinivasan Seshan: colleagues