Communication In Complex Networks

Complex networks describe a wide range of systems in nature and society. It includes not only the internet, but also the other systems, such as world wide web, society networks, science collaboration networks, citation networks, phone call networks, business networks, neural networks, food networks and human linguistic networks. The empirical data shows that the topology and evolution of complex networks are not disorder but governed by robust organizing principles. Such as the power law degree distribution and the small-world property. In this paper, we discuss the communication in complex networks. The model of epidemic and rumor propagation on networks is studied, and our results show that the final density of refractory increases nonlinearly with both the average degree of nodes and the adjustable random parameter of network structure. For the packets delivering in complex networks, we assume that the creation and delivery probability are both node-dependent. Our results show that when we choose a path to deliver the packet, we should considered not only the distance from the source node to the destination, but also the amount packets of the whole path. We can make the communication much more efficient when we considered both the two factors.