Abstract
A conditionally Poissonian power-law random graph with
infinite degree variance is considered as a random
network model. A method for elegant analytical
computation of accurate approximations for various
network characteristics is introduced, based on slight
redefinition of the model in terms of non-homogeneous
Poisson point processes and on the replacement of certain
random variables by their expectations. The applications
include characterization of the `top clique' around the
node of highest capacity, density of nodes falling
outside of the giant component of the random graph,
availability of disjoint paths and the distribution of
traffic in the network, assuming a traffic matrix
following a gravity rule. (13 refs.)
Original language | English |
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Title of host publication | Proceedings of the 21st International Teletraffic Congress, ITC 21 |
Place of Publication | Piscataway |
Publisher | IEEE Institute of Electrical and Electronic Engineers |
Number of pages | 8 |
ISBN (Print) | 978-1-4244-4744-2 |
Publication status | Published - 2009 |
MoE publication type | A4 Article in a conference publication |
Event | 21st International Teletraffic Congress, ITC 21 - Paris, France Duration: 15 Sept 2009 → 17 Sept 2009 |
Conference
Conference | 21st International Teletraffic Congress, ITC 21 |
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Country/Territory | France |
City | Paris |
Period | 15/09/09 → 17/09/09 |