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European Conference on Complex Systems
Pascal

New Insights on the Traceroute Process of Network Exploration

author: Luca Dall'Asta, ICTP - International Centre for Theoretical Physics

Description

Dynamical processes taking place on real networks define on them evolving subnetworks whose topology is not necessarily the same of the underlying one. We investigate the problem of determining the emerging degree distribution, focusing on a class of tree-like processes, such as those used to explore the Internet's topology. A general theory based on mean-field arguments is proposed, both for single-source and multiple-source cases, and applied to the specific example of the traceroute exploration of networks. Our results provide a qualitative improvement in the understanding of dynamical sampling and of the interplay between dynamics and topology in large networks like the Internet.

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Slides
0:00 New insights on the traceroute process of networks explorations
0:09 Motivation
1:05 Observed (statistical) features common to many real networks:
2:02 Networks
4:32 Sampling the Internet: known results
6:02 Sampling the Internet: traceroutelike - part 1
8:30 Statistical properties of sampled graphs may sharply differ from the original ones (in particular the degree distribution) - part 1
9:33 Statistical properties of sampled graphs may sharply differ from the original ones (in particular the degree distribution) - part 2
9:58 Statistical properties of sampled graphs may sharply differ from the original ones (in particular the degree distribution) - part 1
10:01 Statistical properties of sampled graphs may sharply differ from the original ones (in particular the degree distribution) - part 2
11:46 Partial Conclusions; Open Issues
13:00 Unifying single-source and multi-source views
14:22 Single-source traceroute sampling generates a growing (spanning) tree
14:48 Dynamic Bernoulli sampling at the leaves of the growing tree
17:26 Timedependent single-source sampling ... sum over time steps
18:23 Degree-dependent approach:
19:48 Homogeneous and Heterogeneous Network
21:48 Merging single-source trees: MF-like uncorrelated approach - part 1
24:08 Merging single-source trees: MF-like uncorrelated approach - part 2
25:01 Poisson random graph
27:26 Scale-free random graph
28:03 Conclusions

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