  Detecting the driver nodes of complex networks has garnered significant
attention recently to control complex systems to desired behaviors, where nodes
represent system components and edges encode their interactions. Driver nodes,
which are directly controlled by external inputs, play a crucial role in
controlling all network nodes. While many approaches have been proposed to
identify driver nodes of static networks, we still lack an effective algorithm
to control ubiquitous temporal networks, where network structures evolve over
time. Here we propose an effective online time-accelerated heuristic algorithm
(OTaHa) to detect driver nodes of temporal networks. Together with theoretical
analysis and numerical simulations on synthetic and empirical temporal
networks, we show that OTaHa offers multiple sets of driver nodes, and
noticeably outperforms existing methods in terms of accuracy and execution
time. We further report that most edges are redundant in controlling temporal
networks although the complete instantaneous signal-carrying edges cannot be
guaranteed. Moreover, removing edges with high edge betweenness (the number of
all-pairs shortest paths passing through the edge) significantly impedes the
overall controllability. Our work provides an effective algorithm and paves the
way for subsequent explorations on achieving the ultimate control of temporal
networks.
