English

Anomalous biased diffusion in networks

Physics and Society 2013-08-05 v1 Computational Physics

Abstract

We study diffusion with a bias towards a target node in networks. This problem is relevant to efficient routing strategies in emerging communication networks like optical networks. Bias is represented by a probability pp of the packet/particle to travel at every hop towards a site which is along the shortest path to the target node. We investigate the scaling of the mean first passage time (MFPT) with the size of the network. We find by using theoretical analysis and computer simulations that for Random Regular (RR) and Erd\H{o}s-R\'{e}nyi (ER) networks, there exists a threshold probability, pthp_{th}, such that for p<pthp<p_{th} the MFPT scales anomalously as NαN^\alpha, where NN is the number of nodes, and α\alpha depends on pp. For p>pthp>p_{th} the MFPT scales logarithmically with NN. The threshold value pthp_{th} of the bias parameter for which the regime transition occurs is found to depend only on the mean degree of the nodes. An exact solution for every value of pp is given for the scaling of the MFPT in RR networks. The regime transition is also observed for the second moment of the probability distribution function, the standard deviation.

Keywords

Cite

@article{arxiv.1308.0198,
  title  = {Anomalous biased diffusion in networks},
  author = {Loukas Skarpalezos and Aristotelis Kittas and Panos Argyrakis and Reuven Cohen and Shlomo Havlin},
  journal= {arXiv preprint arXiv:1308.0198},
  year   = {2013}
}

Comments

13 Pages, To appear in PRE

R2 v1 2026-06-22T01:02:14.372Z