3 research outputs found
Scaling of mean first-passage time as efficiency measure of nodes sending information on scale-free Koch networks
A lot of previous work showed that the sectional mean first-passage time
(SMFPT), i.e., the average of mean first-passage time (MFPT) for random walks
to a given hub node (node with maximum degree) averaged over all starting
points in scale-free small-world networks exhibits a sublinear or linear
dependence on network order (number of nodes), which indicates that hub
nodes are very efficient in receiving information if one looks upon the random
walker as an information messenger. Thus far, the efficiency of a hub node
sending information on scale-free small-world networks has not been addressed
yet. In this paper, we study random walks on the class of Koch networks with
scale-free behavior and small-world effect. We derive some basic properties for
random walks on the Koch network family, based on which we calculate
analytically the partial mean first-passage time (PMFPT) defined as the average
of MFPTs from a hub node to all other nodes, excluding the hub itself. The
obtained closed-form expression displays that in large networks the PMFPT grows
with network order as , which is larger than the linear scaling of
SMFPT to the hub from other nodes. On the other hand, we also address the case
with the information sender distributed uniformly among the Koch networks, and
derive analytically the entire mean first-passage time (EMFPT), namely, the
average of MFPTs between all couples of nodes, the leading scaling of which is
identical to that of PMFPT. From the obtained results, we present that although
hub nodes are more efficient for receiving information than other nodes, they
display a qualitatively similar speed for sending information as non-hub nodes.
Moreover, we show that the location of information sender has little effect on
the transmission efficiency. The present findings are helpful for better
understanding random walks performed on scale-free small-world networks.Comment: Definitive version published in European Physical Journal
Mean first-passage time for random walks on undirected networks
In this paper, by using two different techniques we derive an explicit
formula for the mean first-passage time (MFPT) between any pair of nodes on a
general undirected network, which is expressed in terms of eigenvalues and
eigenvectors of an associated matrix similar to the transition matrix. We then
apply the formula to derive a lower bound for the MFPT to arrive at a given
node with the starting point chosen from the stationary distribution over the
set of nodes. We show that for a correlated scale-free network of size with
a degree distribution , the scaling of the lower bound is
. Also, we provide a simple derivation for an eigentime
identity. Our work leads to a comprehensive understanding of recent results
about random walks on complex networks, especially on scale-free networks.Comment: 7 pages, no figures; definitive version published in European
Physical Journal
Topologies and Laplacian spectra of a deterministic uniform recursive tree
The uniform recursive tree (URT) is one of the most important models and has
been successfully applied to many fields. Here we study exactly the topological
characteristics and spectral properties of the Laplacian matrix of a
deterministic uniform recursive tree, which is a deterministic version of URT.
Firstly, from the perspective of complex networks, we determine the main
structural characteristics of the deterministic tree. The obtained vigorous
results show that the network has an exponential degree distribution, small
average path length, power-law distribution of node betweenness, and positive
degree-degree correlations. Then we determine the complete Laplacian spectra
(eigenvalues) and their corresponding eigenvectors of the considered graph.
Interestingly, all the Laplacian eigenvalues are distinct.Comment: 7 pages, 1 figures, definitive version accepted for publication in
EPJ