Random graph models and their applications
This thesis explores different models of random graphs. The first part treats a change from the preferential attachment model where the network incorporates new vertices and attach them preferentially to the previous vertices with a large number of connections. We introduce on top of this model the deletion of the oldest connections in the system and discuss the impact on the degree of the vertice