Navigability of complex networks

Abstract

Routing information through networks is a universal phenomenon in both natural and manmade complex systems. When each node has full knowledge of the global network connectivity, finding short communication paths is merely a matter of distributed computation. However, in many real networks nodes communicate efficiently even without such global intelligence. Here we show that the peculiar structural characteristics of many complex networks support efficient communication without global knowledge. We also describe a general mechanism that explains this connection between network structure and function. This mechanism relies on the presence of a metric space hidden behind an observable network. Our findings suggest that real networks in nature have underlying metric spaces that remain undiscovered. Their discovery would have practical applications ranging from routing in the Internet and searching social networks, to studying information flows in neural, gene regulatory networks, or signaling pathways.

Matching–centrality decomposition and the forecasting of new links in networks

“…The model, called the matching-centrality model, is implemented in such a way that the closer the matching traits of two nodes, the greater the probability that they are linked, and the higher the centrality trait of a node, the greater the probability that this node makes links. This model belongs to the general class of 'hidden' variables models [5,[19][20][21][22][23][24], for which some variables are unknown a priori, but can be estimated from the data a posteriori. In our model, these 'hidden' variables are the latent traits of matching and centrality.…”

Ordinary percolation with discontinuous transitions

“…Yet, the engineering of artificial networks with well-controlled features seems desirable. Indeed, there has been considerable interest in the properties of spatial networks, linking real-world geometry with small-world effects [3][4][5] . In particular, networks possessing hierarchical features 4,[6][7][8][9][10] relate to actual transport systems such as for air travel, routers and social interactions.…”

“…Indeed, there has been considerable interest in the properties of spatial networks, linking real-world geometry with small-world effects [3][4][5] . In particular, networks possessing hierarchical features 4,[6][7][8][9][10] relate to actual transport systems such as for air travel, routers and social interactions. Certain hierarchical networks, with a self-similar structure, have been shown to exhibit novel features 8,[11][12][13][14][15] .…”

Suppressing traffic-driven epidemic spreading by use of the efficient routing protocol

“…Epidemic spreading [1,2,3,4,5,6,7,8,9,10,11,12] and traffic dynamics [13,14,15,16,17,18,19,20] on complex networks have attracted much attention in the past decade. For a long time, the two types of dynamical processes have been studied independently.…”