IMDEA Networks Institute Publications Repository

Node Sampling using Random Centrifugal Walks

Sevilla, Andrés and Mozo, Alberto and Fernández Anta, Antonio (2015) Node Sampling using Random Centrifugal Walks. [Journal Articles]

Download (988Kb) | Preview


A distributed algorithm is proposed for sampling networks, so that nodes are selected by a special node (source), with a given probability distribution. We define a new class of random walks, that we call Random Centrifugal Walks (RCW). A RCW starts at the source and always moves away from it. The algorithm assumes that each node has a weight, so the nodes are selected with a probability proportional to its weight. It requires a preprocessing phase before the sampling of nodes. This preprocessing is done only once, regardless of the number of sources and the number of samples taken from the network. The length of RCW walks are bounded by the network diameter. The RCW algorithms that do not require preprocessing are proposed for grids and networks with regular concentric connectivity, for the case when the probability of selecting a node is a function of its distance to the source.

Item Type: Journal Articles
Uncontrolled Keywords: Node sampling; Random walks; Randomized algorithms; Distributed algorithms.
Depositing User: Antonio Fernandez
Date Deposited: 10 Sep 2015 09:06
Last Modified: 11 Jul 2016 20:31

Actions (login required)

View Item View Item