A wide spectrum of extreme events ranging from traffic jams to floods take place on
networks. Motivated by these, we employ a random walk model for transport and obtain
analytical and numerical results for the extreme events on networks. They reveal an
unforeseen, and yet a robust, feature: small degree nodes of a network are more likely to
encounter extreme events than the hubs. Further, we also study the recurrence time
distribution and scaling of the probabilities for extreme events. These results suggest a …

The aim of the project was to study extreme events on complex networks. The study of
complex networks, especially that of scale free and small world networks, has been an
important topic of research in recent times. In this project, extreme events on complex
networks were studied by using random walks to model flow on the network. By considering
a set of independent random walkers to be moving on the network simultaneously, an
extreme event on the network was defined as an event when the number of walkers exceeds …