Impact of degree heterogeneity on the behavior of trapping in Koch networks

Abstract

Previous work shows that the mean first-passage time (MFPT) for random walks to a given hub node (node with maximum degree) in uncorrelated random scale-free networks is closely related to the exponent $\gamma$ of power-law degree distribution $P(k)\sim k^{-\gamma }$, which describes the extent of heterogeneity of scale-free network structure. However, extensive empirical research indicates that real networked systems also display ubiquitous degree correlations. In this paper, we address the trapping issue on the Koch networks, which is a special random walk with one trap fixed at a hub node. The Koch networks are power-law with the characteristic exponent $\gamma$ in the range between 2 and 3, they are either assortative or disassortative. We calculate exactly the MFPT that is the average of first-passage time from all other nodes to the trap. The obtained explicit solution shows that in large networks the MFPT varies lineally with node number $N$, which is obviously independent of $\gamma$ and is sharp contrast to the scaling behavior of MFPT observed for uncorrelated random scale-free networks, where $\gamma$ influences qualitatively the MFPT of trapping problem.

Definitive version accepted for publication in Chaos

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• Determination of multifractal dimensions of complex networks by means of the sandbox algorithm
• Exact calculations of first-passage properties on the pseudofractal scale-free web
• Mean first-passage time for random walks in general graphs with a deep trap
• Structure Properties of Koch Networks Based on Networks Dynamical Systems