TY - JOUR
T1 - Shortest path discovery of complex networks
AU - Fekete, Attila
AU - Vattay, Gábor
AU - Pósfai, Márton
PY - 2009/6/23
Y1 - 2009/6/23
N2 - In this Rapid Communication we present an analytic study of sampled networks in the case of some important shortest-path sampling models. We present analytic formulas for the probability of edge discovery in the case of an evolving and a static network model. We also show that the number of discovered edges in a finite network scales much more slowly than predicted by earlier mean-field models. Finally, we calculate the degree distribution of sampled networks and we demonstrate that they are analogous to a destroyed network obtained by randomly removing edges from the original network.
AB - In this Rapid Communication we present an analytic study of sampled networks in the case of some important shortest-path sampling models. We present analytic formulas for the probability of edge discovery in the case of an evolving and a static network model. We also show that the number of discovered edges in a finite network scales much more slowly than predicted by earlier mean-field models. Finally, we calculate the degree distribution of sampled networks and we demonstrate that they are analogous to a destroyed network obtained by randomly removing edges from the original network.
UR - http://www.scopus.com/inward/record.url?scp=67650099196&partnerID=8YFLogxK
U2 - 10.1103/PhysRevE.79.065101
DO - 10.1103/PhysRevE.79.065101
M3 - Article
AN - SCOPUS:67650099196
SN - 1539-3755
VL - 79
JO - Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
JF - Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
IS - 6
M1 - 065101
ER -