Communication in Complex Networks

by   Omar De la Cruz Cabrera, et al.

The investigation of properties of networks has many applications and is receiving considerable attention. One of the properties of interest is the communicability, which measures how easy it is for the nodes of a network to communicate with each other, where communication takes place along the edges of the network. We are interested in how sensitive the global communicability is to local changes in the network. There are several reasons for our interest in the sensitivity. For instance, when the edges of a network represent roads, we may be interested in which road(s) to enlarge or make smaller to increase or decrease, respectively, the traffic flow the most. We also are interested in whether blocking a road, or building a new road, will have a large effect on the communicability in a network. In some applications, we might not know of all the edges of a network, and are interested in how this lack of knowledge may affect our measurement of communicability. Experiments with both synthetic and real networks illustrate the performance of the proposed methods.



There are no comments yet.


page 1

page 2

page 3

page 4


Learning to integrate vision data into road network data

Road networks are the core infrastructure for connected and autonomous v...

Iterative Deep Learning for Road Topology Extraction

This paper tackles the task of estimating the topology of road networks ...

On Network Embedding for Machine Learning on Road Networks: A Case Study on the Danish Road Network

Road networks are a type of spatial network, where edges may be associat...

Navigational Rule Derivation: An algorithm to determine the effect of traffic signs on road networks

In this paper we present an algorithm to build a road network map enrich...

Communication Costs in a Geometric Communication Network

A communication network is a graph in which each node has only local inf...

Towards Reliable Evaluation of Road Network Reconstructions

Existing performance measures rank delineation algorithms inconsistently...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.