Event stream controllability on event-based complex networks

In recent years, controllability on complex networks has become one of the most important issues among re-searchers. This study addresses the problem of controllability on an event-based complex network using events and their resulting dynamics to fully control the network. A particular type of event-based complex network, named event-based social networks (EBSNs), has been selected as a case study. In these networks, the com-munications between users are established by different event streams. A new control method, called Event Stream Controllability, is provided that uses the concept of maximum controllable subspace and maintains the data required for controlling the network using a tree structure. The experimental results demonstrate that the proposed method fully controls the network with a small number of control nodes (13.86%). In addition, it has been compared with the structural controllability based on the layer model. The results demonstrate that the proposed method outperforms the structural controllability method by 39.85%, 39.42%, and 34.98% increases in the number of driver nodes, runtime, and overload, respectively. Finally, the results show that the hub nodes (2%) and the organizer nodes (0.75%) are presented in the set of driver nodes, indicating that the proposed method is highly robust.