Ultra-Robust and Scalable Networks Based on Hierarchies
Peter Dodds, (ISERP, Columbia University), email@example.com,
Duncan Watts, (Sociology, Columbia University), firstname.lastname@example.org, and
Charles Sabel, (Law School, Columbia University), email@example.com
We report on the properties of a theoretical class of communication networks. We construct networks by adding links to an initial hierarchical network based on a two-parameter probability distribution. The networks produced range in form through random, team-based (links are added locally), core-periphery (links are added from the top down), to an intermediate class we term as multiscale networks. We observe certain multiscale networks to be ultra-robust in that they are both resilient to high loads of communication and remain highly connected in the unlikely event of a substantial, targeted loss of nodes. We find these networks require a minimal number of links to be added to achieve their characteristics, on the order of the number of nodes. We also show that ultra-robust networks perform well under a variety of communciation patterns and that their performance scales well with system size. Applications lie in the understanding and potentially the design of robust organizational networks.