Abstract :
In this paper, a weighted directed random graph is used as network model. The graph contains a fixed number N of nodes and a variable number of edges: in particular, each edge is present with probability p. Some statistical properties (such as strong connection, global and local efficiency, cost, etc) are computed and their reliance on probability p is studied. Some probability distributions (such as shortest path, edge (node) load) are also drawn and, by using the method of stages, the best fitting curves are computed. Finally, the way as parameters characterizing such curves change when p varies is investigated.
Keywords :
curve fitting; directed graphs; large-scale systems; statistical analysis; complex networks identification; fitting curves; network model; probability distributions; statistical properties; weighted directed random graph; Cities and towns; Communication networks; Complex networks; Costs; Curve fitting; Distributed computing; IP networks; Probability distribution; Social network services; Web sites;
