We consider various models of randomly grown graphs. In these models the vertices and the edges accumulate within time according to certain rules. We study a phase transition in these models along a parameter which refers to the mean life-time of an edge. Although deleting old edges in the uniformly grown graph changes abruptly the properties of the model, we show that some of the macro-characteristics of the graph vary continuously. In particular, our results yield a lower bound for the size of the largest connected component of the uniformly grown graph
33 pages, 3 figuresWe introduce a new oriented evolving graph model inspired by biological networks....
We study a large-time limit of a Markov process whose states are finite graphs. The number of the ve...
Abstract. The evolution of the largest component has been studied intensely in a variety of random g...
We introduce a very general model of an inhomogenous random graph with independence between the edge...
We study a model of grown graph where a vertex is added at each time step, then an edge is added wi...
The aim of this paper is to study the emergence of the giant component in the uniformly grown random...
Understanding what types of phenomena lead to discontinuous phase transitions in the connectivity of...
In this paper, we study the critical behavior of percolation on a configuration model with degree di...
In this paper, we study the critical behavior of percolation on a configuration model with degree di...
15 pages, 9 figures (color eps) [v2: published text with a new Title and addition of an appendix, a ...
Random graph processes are basic mathematical models for large-scale networks evolving over time. Th...
We consider a large class of inhomogeneous spatial random graphs on the real line. Each vertex carri...
We study a random graph model which is a superposition of bond percolation on Z(d) with parameter p,...
In every network, a distance between a pair of nodes can be defined as the length of the shortest pa...
Let G be an infinite, locally finite, connected graph with bounded degree. We show that G supports p...
33 pages, 3 figuresWe introduce a new oriented evolving graph model inspired by biological networks....
We study a large-time limit of a Markov process whose states are finite graphs. The number of the ve...
Abstract. The evolution of the largest component has been studied intensely in a variety of random g...
We introduce a very general model of an inhomogenous random graph with independence between the edge...
We study a model of grown graph where a vertex is added at each time step, then an edge is added wi...
The aim of this paper is to study the emergence of the giant component in the uniformly grown random...
Understanding what types of phenomena lead to discontinuous phase transitions in the connectivity of...
In this paper, we study the critical behavior of percolation on a configuration model with degree di...
In this paper, we study the critical behavior of percolation on a configuration model with degree di...
15 pages, 9 figures (color eps) [v2: published text with a new Title and addition of an appendix, a ...
Random graph processes are basic mathematical models for large-scale networks evolving over time. Th...
We consider a large class of inhomogeneous spatial random graphs on the real line. Each vertex carri...
We study a random graph model which is a superposition of bond percolation on Z(d) with parameter p,...
In every network, a distance between a pair of nodes can be defined as the length of the shortest pa...
Let G be an infinite, locally finite, connected graph with bounded degree. We show that G supports p...
33 pages, 3 figuresWe introduce a new oriented evolving graph model inspired by biological networks....
We study a large-time limit of a Markov process whose states are finite graphs. The number of the ve...
Abstract. The evolution of the largest component has been studied intensely in a variety of random g...