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The observable part of a network
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Source IEEE/ACM Transactions on Networking (TON) archive
Volume 17 ,  Issue 1  (February 2009) table of contents
Pages 93-105  
Year of Publication: 2009
ISSN:1063-6692
Authors
Piet Van Mieghem  Delft University of Technology, Delft, The Netherlands
Huijuan Wang  Delft University of Technology, Delft, The Netherlands
Publisher
IEEE Press  Piscataway, NJ, USA
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DOI Bookmark: 10.1109/TNET.2008.925089

ABSTRACT

The union of all shortest path trees GUspt is the maximally observable part of a network when traffic follows shortest paths. Overlay networks such as peer to peer networks or virtual private networks can be regarded as a subgraph of GUspt. We investigate properties of GUspt in different underlying topologies with regular i.i.d. link weights. In particular, we show that the overlay GUspt in an Erdös-Rényi random graph Gp (N) is a connected GPc (N) where Pc ∼ log N/N is the critical link density, an observation with potential for ad-hoc networks.

Shortest paths and, thus also the overlay GUspt, can be controlled by link weights. By tuning the power exponent α of polynomial link weights in different underlying graphs, the phase transitions in the structure of GUspt are shown by simulations to follow a same universal curve FT (α) = Pr[GUspt is a tree]. The existence of a controllable phase transition in networks may allow network operators to steer and balance flows in their network. The structure of GUspt in terms of the extreme value index α is further examined together with its spectrum, the eigenvalues of the corresponding adjacency matrix of GUspt.


REFERENCES

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1
 
2
A. Ganesh, L. Massoulie, and D. Towsley, "The effect of network topology on the spread of epidemics," in Proc. IEEE INFOCOM 2005, Mar. 2005, vol. 2, pp. 1455-1466.
 
3
L. Zhao, K. Park, and Y.-C. Lai, Phys. Rev., vol. E 70, no. 035101, 2004.
 
4
T. Watanabe, Y. Higashi, and A. Nakamura, "An approach to robust network construction from graph augmentation problems," in Proc. 1990 IEEE Int. Symp. Circuits Syst. (ISCAS), May 1990, vol. 4, pp. 2861-2864.
 
5
P. Van Mieghem and S. M. Magdalena, Phys. Rev., vol. E 72, no. 056138, 2005.
 
6
A. Lakhina, J. Byers, M. Crovella, and P. Xie, "Sampling biases in IP topology measurements," in Proc. IEEE INFOCOM 2003, Mar.-Apr. 2003, vol. 1, pp. 332-341.
 
7
A. Clauset and C. Moore, Phys. Rev. Lett., vol. 94, no. 018701, 2005.
8
 
9
 
10
N. Biggs, Algebraic Graph Theory, 2nd ed. Cambridge, U.K.: Cambridge Univ. Press, 1996.
 
11
 
12
 
13
 
14
P. Van Mieghem, G. Hooghiemstra, and R. W. van der Hofstad, "A scaling law for the hopcount," Delft Univ. Technol., Delft, The Netherlands, report2000125, 2000.
 
15
 
16
B. Bollobas, Random Graphs, 2nd ed. Cambridge, U.K.: Cambridge Univ. Press, 2001.
 
17
G. Chartrand and R. O. Ortrud, Applied and Algorithmic Graph Theory. New York: McGraw-Hill, 1992.
 
18
 
19
R. Albert and A. Barabasi, "Emergence of scaling in random networks," Science, vol. 286, pp. 509-512, 1999.
 
20
P. Van Mieghem and S. van Langen, Phys. Rev., vol. E71, no. 056113, 2005.
 
21
E. W. Dijkstra, "A note on two problems in connection with graphs," Num. Math., vol. 1, pp. 269-271, 1959.
22
 
23
J. J. Binney, N. J. Dowrick, A. J. Fisher, and M. E. J. Newman, The Theory of Critical Phenomena: An Introduction to the Renormalization Group. Oxford, U.K.: Clarendon, 1992.
 
24
S. N. Dorogovtsev, A. V. Goltsev, J. F. F. Mendes, and A. N. Samukhin, Phys. Rev., vol. E 68, no. 046109, 2003.
 
25
L. He, X. Liu, and G. Strang, "Trees with Cantor eigenvalue distribution," Stud. Appl. Math., vol. 110, pp. 123-123, 2003.
 
26
 
27
D. M. Cvetkovic, M. Doob, and H. Sachs, Spectra of Graphs. Berlin, Germany: VEB Deutscher Verlag der Wissenschaften, 1980.
 
28
E. D. van Dam and W. H. Haemers, "Which graphs are determined by their spectrum?," Linear Algebra and its Applicat., vol. 373, pp. 241-272, 2003.
 
29
E. Wigner, "On the distribution of the roots of certain symmetric matrices," Ann. Math., vol. 67, pp. 325-327, 1958.
 
30
I. J. Farkas, I. Deréyi, A.-L. Barabási, and T. Vicsek, Phys. Rev., vol. E 64, no. 026704, 2001.
31
 
32
R. Hekmat and P. Van Mieghem, "Study of connectivity in wireless ad-hoc networks with an improved radio model," in Proc. 2nd Workshop on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt'04), Cambridge, U.K., Mar. 24-26, 2004, pp. 142-151.
 
33
RIPE Test Traffic Measurements. RIPE NCC, Amsterdam, The Netherlands [Online]. Available: http://www.ripe.net/ripencc/mem-services/ ttm/
 
34
M. Janic, F. Kuipers, X. Zhou, and P. Van Mieghem, "Implications for QoS provisioning based on traceroute measurements," in Proc. 3nd Int. Workshop on Quality of Future Internet Services (QofIS2002), Zurich, Switzerland, Oct. 16-18, 2002, pp. 3-14.
 
35
 
36
M. Drmota and H.-K. Hwang, "Profiles of random trees: Correlation and width of random recursive trees and binary search trees," Adv. Appl. Probabil., vol. 37, pp. 321-341, 2005.
 
37

Collaborative Colleagues:
Piet Van Mieghem: colleagues
Huijuan Wang: colleagues