Abstract: Many different random graph constructions are used to model large real life graphs, i.e., graphs that describe the structure of real systems. Often it is not clear, however, how the strength of the different models compare to each other, e.g., when does it hold that a certain model class contains another. We are particularly interested in random graph models that arise via abstract geometric constructions, motivated by the fact that these graphs can model wireless communication networks. We set up a general framework to compare the strength of random graph models, and present some results about the equality, inequality and proper containment of certain model classes, as well as some open problems.
In this chapter, we define percolation and random graph models, and survey the features of these mod...
This research aims to identify strong structural features of real-world complex networks, sufficient...
Complex networks describe a variety of systems found in nature and society. Traditionally these syst...
For many combinatorial objects we can associate a natural probability distribution on the members of...
This is a research report that is part of a Chapter of a PhD thesis. An updated version will be avai...
Empirical findings have shown that many real-world networks share fascinating features. Indeed, many...
In this book, we study random graphs as models for real-world networks. Since 1999, many real-world ...
The theory of random graphs has been mainly concerned with structural properties, in particular the ...
This rigorous introduction to network science presents random graphs as models for real-world networ...
Networks are ubiquitous. They arise naturally as models of communication networks, networks of frien...
This book supports researchers who need to generate random networks, or who are interested in the th...
This rigorous introduction to network science presents random graphs as models for real-world networ...
In many real life applications, network formation can be modelled using a spatial random graph model...
There are two aspects of randomness in topological models. In the first one, topological idealizatio...
In this chapter, we discuss complex networks as a prime example where the ideas from complexity theo...
In this chapter, we define percolation and random graph models, and survey the features of these mod...
This research aims to identify strong structural features of real-world complex networks, sufficient...
Complex networks describe a variety of systems found in nature and society. Traditionally these syst...
For many combinatorial objects we can associate a natural probability distribution on the members of...
This is a research report that is part of a Chapter of a PhD thesis. An updated version will be avai...
Empirical findings have shown that many real-world networks share fascinating features. Indeed, many...
In this book, we study random graphs as models for real-world networks. Since 1999, many real-world ...
The theory of random graphs has been mainly concerned with structural properties, in particular the ...
This rigorous introduction to network science presents random graphs as models for real-world networ...
Networks are ubiquitous. They arise naturally as models of communication networks, networks of frien...
This book supports researchers who need to generate random networks, or who are interested in the th...
This rigorous introduction to network science presents random graphs as models for real-world networ...
In many real life applications, network formation can be modelled using a spatial random graph model...
There are two aspects of randomness in topological models. In the first one, topological idealizatio...
In this chapter, we discuss complex networks as a prime example where the ideas from complexity theo...
In this chapter, we define percolation and random graph models, and survey the features of these mod...
This research aims to identify strong structural features of real-world complex networks, sufficient...
Complex networks describe a variety of systems found in nature and society. Traditionally these syst...