Propagation phenomena in complex networks

Traditionally, the term 'propagation phenomenon' is used to describe information diffusion, message broadcasting, rumour dissemination, disease spreading and economic fluctuations. The characteristics of propagation mechanisms depend heavily on the network topology and individual or collective behaviour.

Understanding propagation is of importance when designing, implementing, maintaining and developing complex networks. A team of scientists investigated to what extend design principles for networks can be derived from the study of error propagation phenomena. Within the project EPP (To what extent can design principles for complex networks be derived from the study of error propagation in smart and bio-inspired network structures?), they studied random, small-world and scale-free network structures. A wide range of diffusion properties such as speed and duration were analysed.

For this purpose, a new diffusion-based algorithm was developed that applies to a wide range of scenarios. The algorithm is based on the widely employed independent cascade model and linear threshold model. Extensive simulations on real-world and artificial networks demonstrated the algorithm's robustness.

Contributions on critical issues involved in error propagation, spread and their combat were also solicited from the wider scientific community working on this subject area. These were published in a special issue of the New Generation Computing journal and the book 'Propagation phenomena in real-world networks'.

Through the introduction of new perspectives on propagation processes in complex networks, the EPP project provided an important starting point for future research. This should encourage further research on epidemic and social spreading, failure and information cascades as well as agent-based population learning.