scholarly journals Exponential Random Graphs as Models of Overlay Networks

2009 ◽  
Vol 46 (01) ◽  
pp. 199-220 ◽  
Author(s):  
M. Draief ◽  
A. Ganesh ◽  
L. Massoulié

In this paper we give an analytic solution for graphs with n nodes and E = cn log n edges for which the probability of obtaining a given graph G is µn (G) = exp (- β ∑i=1 n d i 2), where d i is the degree of node i. We describe how this model appears in the context of load balancing in communication networks, namely peer-to-peer overlays. We then analyse the degree distribution of such graphs and show that the degrees are concentrated around their mean value. Finally, we derive asymptotic results for the number of edges crossing a graph cut and use these results (i) to compute the graph expansion and conductance, and (ii) to analyse the graph resilience to random failures.

2009 ◽  
Vol 46 (1) ◽  
pp. 199-220 ◽  
Author(s):  
M. Draief ◽  
A. Ganesh ◽  
L. Massoulié

In this paper we give an analytic solution for graphs withnnodes andE=cnlognedges for which the probability of obtaining a given graphGisµn(G) = exp (-β∑i=1ndi2), wherediis the degree of nodei. We describe how this model appears in the context of load balancing in communication networks, namely peer-to-peer overlays. We then analyse the degree distribution of such graphs and show that the degrees are concentrated around their mean value. Finally, we derive asymptotic results for the number of edges crossing a graph cut and use these results (i) to compute the graph expansion and conductance, and (ii) to analyse the graph resilience to random failures.


2009 ◽  
Vol 102 (13) ◽  
Author(s):  
Yakir Berchenko ◽  
Yael Artzy-Randrup ◽  
Mina Teicher ◽  
Lewi Stone

2013 ◽  
Vol 23 (6) ◽  
pp. 2458-2471 ◽  
Author(s):  
Charles Radin ◽  
Mei Yin

2014 ◽  
Vol 25 (09) ◽  
pp. 1450040 ◽  
Author(s):  
Marwa Benyoussef ◽  
Hamid Ez-Zahraouy ◽  
Abdelilah Benyoussef

The behavior of the degree distribution of two interdependent Barabasi–Albert (BA) sub-networks has been investigated numerically. The final complex structure obtained after connection of the two BA subnets exhibits two different kind of degree distribution law, which depends strongly on the manner in which the connection between the two subnets has been made. When connecting two existing BA subnets, the degree distribution follows a Gaussian distribution, while ensuring that the highest frequency level is still around the average degree of the final network. Whereas, when the connection is established progressively at the same time of the formation of the two BA subnets, the degree distribution follows a power-law scaling observed in real networks. It is also found that the evolution of links formed over a time for a specific node follows the same behavior, as the BA networks.


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