Towards Structural Controllability of Temporal Complex Networks

Abstract

Temporal complex networks are ubiquitous in human daily life whose topologies evolve with time, such as communication networks and transportation networks. Investigations on the structural controllability of temporal complex networks show the properties and performances of controllability when the weights of edges in temporal networks are arbitrary values rather than exact ones. There are two frameworks proposed in this chapter to analyze the structural controllability of temporal networks. In the first framework, a temporal network is treated as a sequence of characteristic subgraphs with different characteristic time stamps. After finding the maximum characteristic subgraph set from these subgraphs, priority maximum methods are applied to improve the controlling efficiency by which temporal information of the network remains. On the other hand, in the later framework, a temporal network is represented by time-ordered graph (TOG). Instead of calculating the rank of controllability matrix directly, finding and classifying temporal trees of the time-ordered graph provides an effective way to estimate the controlling centrality of a node in the network.