Wave localization in random networks

Localization in dense random sensor networks?

We propose a simple distributed learning algorithm for localization of nodes in dense random wireless sensor networks . We derive probabilistic error bounds, discuss the average complexity of the algorithm, and present some simulation results. Introduction Localization of nodes in wireless sensor networks is still a great challenge. Most existing localization systems rely heavily on expensive i...

Localization transition of biased random walks on random networks.

We study random walks on large random graphs that are biased towards a randomly chosen but fixed target node. We show that a critical bias strength bc exists such that most walks find the target within a finite time when b > bc. For b < bc, a finite fraction of walks drift off to infinity before hitting the target. The phase transition at b=bc is a critical point in the sense that quantities su...

Wave localization in complex networks with high clustering.

We show that strong clustering of links in complex networks, i.e., a high probability of triadic closure, can induce a localization-delocalization quantum phase transition (Anderson-like transition) of coherent excitations. For example, the propagation of light wave packets between two distant nodes of an optical network (composed of fibers and beam splitters) will be absent if the fraction of ...

A Distributed Algorithm for Localization in Random Wireless Networks

Motivation. In electrical engineering and computer science there has recently been a lot of interest in wireless sensor networks. The nodes of such a network are equipped with one or several sensors, a tiny computer, and a radio, and are therefore capable of sensing the environment, computation, and communication. The power supply of the nodes and computational power of the computer at each nod...

Wave propagation in cross-linked random fiber networks