Event stream controllability on event-based complex networks

Abstract

In recent years, controllability on complex networks has become one of the most important issues among researchers. 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 communications 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.