Controlling One means Controlling All
Sarika Jalan - Indian Institute of Technology Indore, India
Session chair: Michael Lees

Abstract : Recent years have witnessed the emergence of the multilayer network (MN) framework, which provides more accurate insights into the behaviors of complex systems possessing multiple types of relations among the same units. For example, individual or collective behavior of a society, that is modeled by individuals interacting through the Facebook and Twitter social networks, can be better understood by considering an MN consisting of layers representing the network of connections of people in each social media. The interactions within a layer (intra-layer connection) for this particular network model of a social system encode friendship relations between pairs of two people within each social media, whereas the interactions between the layers (inter-layer connection) represent the impact of interactions in one layer on the other (for example, when two people actively interacting by Facebook increase their Twitter activity driven by their Facebook activities. Another example of a real-world system, which inherently has multiple types of relations, is the brain. In the brain MN, one layer corresponds to a physical network, and another to a functional relationship among neurons. Furthermore, the physical layer can also itself a MN in the synaptic level. Neurons can be connected by chemical or electric synapses forming a brain MN. Recently, Internet routing protocol IPv4 and IPv6 autonomous systems have also been analyzed through MN framework. We perform optimized evolution of multilayer networks to make them better synchronizable. We show that one can control the behavior of the entire multilayer network by controlling properties of only one layer.