Complex Structures and Collective Dynamics in Networked Systems: Foundations for Self-Adaptation and Self-Organization

Abstract

The study of complex networks and collective dynamics occurring in biological, social and technical systems has experienced a massive surge of interest both from academia and industry. Many of the results on the mechanisms underlying the self-organized formation of complex dynamic networks in natural and man-made systems have been derived based on a statistical physics perspective. In this tutorial, we provide a basic introduction to this perspective which will help attendees to benefit from the vast literature on self-organization and self-adaptation phenomena available in the fields of network science and complex systems. We cover basic models and abstractions for the study of static complex networks as well as dynamical processes like, e.g., information diffusion, random walks, synchronization or the propagation of cascading failures. We further introduce recent advances in the study of dynamic (social) networks and demonstrate how the resulting methods can be practically applied in the engineering of self-organizing and self-adaptive distributed systems and protocols.