ACM Home Page
Please provide us with feedback. Feedback
On power-law relationships of the Internet topology
Full text pdf formatPdf (1.35 MB)
Source Applications, Technologies, Architectures, and Protocols for Computer Communication archive
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication table of contents
Cambridge, Massachusetts, United States
Pages: 251 - 262  
Year of Publication: 1999
ISBN:1-58113-135-6
Also published in ...
Authors
Michalis Faloutsos  Carnegie Mellon Univ., Dept. of Comp. Science
Petros Faloutsos
Christos Faloutsos
Sponsor
SIGCOMM: ACM Special Interest Group on Data Communication
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 96,   Downloads (12 Months): 808,   Citation Count: 225
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
Save this Article to a Binder    Display Formats: BibTex  EndNote ACM Ref   
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/316188.316229
What is a DOI?

ABSTRACT

Despite the apparent randomness of the Internet, we discover some surprisingly simple power-laws of the Internet topology. These power-laws hold for three snapshots of the Internet, between November 1997 and December 1998, despite a 45% growth of its size during that period. We show that our power-laws fit the real data very well resulting in correlation coefficients of 96% or higher.Our observations provide a novel perspective of the structure of the Internet. The power-laws describe concisely skewed distributions of graph properties such as the node outdegree. In addition, these power-laws can be used to estimate important parameters such as the average neighborhood size, and facilitate the design and the performance analysis of protocols. Furthermore, we can use them to generate and select realistic topologies for simulation purposes.


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.

1
 
2
J. Chuang and M. Sirbu. Pricing multicast communications: A cost based approach. In Proc. of the {NET'98, 1998.
3
 
4
D. M. Cvetkovii~, M. Boob, and H. Sachs. Spectra of Graphs. Academic press, 1979.
 
5
M. Doar. A better model for generating test networks. Proc. Global Internet, IEEE, Nov. 1996.
6
7
 
8
M. Faloutsos, P. FaIoutsos, and C. Faloutsos. Power-laws of the Internet topology. Technical Report UCR-CS-99-01, University of California Riverside, Computer Science, 1999.
 
9
National Laboratory for Applied Network Research. Routing data. Supported by NSF, http://moat.nlanr.net/Routing/rawdata/, 1998.
 
10
 
11
 
12
B. Mandelbrot. Fractal Geometry of Nature. W.H. Freeman, New York, I977.
13
14
 
15
 
16
17
 
18
William H. Press, Saul A. Teukolsky, William T. Vetterling, and Brian P. Flannery. Numerical Recipes in C. Cambridge University Press, 2nd edition, 1992.
 
19
Y. Rekhter and T. Li (Eds). A Border Gateway Protocol 4 (BGP-4). Internet-Draft:draft-ietf-idr-bgp4-08.txt available from ftp://ftp.ietf, org/internet-drafts/, 1998.
 
20
S. R. Resnick. Heavy tail modeling and teletraffic data. Annals of Statistics, 25(5):1805-1869, 1997.
 
21
Manfred Schroeder. Fructals, Chaos. Power Laws: Minutes from an Infinite Paradise. W.H. Freeman and Company, New York, 1991.
 
22
D. Waitzman, C. Partridge, and S. Deering. Distance vector multicast routing protocol. IETF RFC 1075, 1998.
 
23
B. M. Waxman. Routing of multipoint connections. IEEE Journal of Selected Areas in Communications, pages 1617- 1622, 1988.
 
24
25
 
26
D. Zappala, D. Estrin, and S. Shenker. Alternate path routing and pinning for interdomain multicast routing. Technical Report USC CS TR 97-655, U. of South California, 1997.
 
27
 
28
G.K. Zipf. Human Behavior and Principle of Least Effort: An Introduction to Human Ecology. Addison Wesley, Cambridge, Massachusetts, 1949.

CITED BY  225