Robustness Elasticity in Complex Networks by Timothy C. Matisziw, Tony H. Grubesic, and Junyu Guo. (Matisziw TC, Grubesic TH, Guo J (2012) Robustness Elasticity in Complex Networks. PLoS ONE 7(7): e39788. doi:10.1371/journal.pone.0039788)
Abstract:
Network robustness refers to a network’s resilience to stress or damage. Given that most networks are inherently dynamic, with changing topology, loads, and operational states, their robustness is also likely subject to change. However, in most analyses of network structure, it is assumed that interaction among nodes has no effect on robustness. To investigate the hypothesis that network robustness is not sensitive or elastic to the level of interaction (or flow) among network nodes, this paper explores the impacts of network disruption, namely arc deletion, over a temporal sequence of observed nodal interactions for a large Internet backbone system. In particular, a mathematical programming approach is used to identify exact bounds on robustness to arc deletion for each epoch of nodal interaction. Elasticity of the identified bounds relative to the magnitude of arc deletion is assessed. Results indicate that system robustness can be highly elastic to spatial and temporal variations in nodal interactions within complex systems. Further, the presence of this elasticity provides evidence that a failure to account for nodal interaction can confound characterizations of complex networked systems.
As you might expect, I am reading this paper from the perspective of connections between nodes of information and not, for example, nodes on the Internet. I suspect it is particularly relevant for models of (or the lack thereof) information sharing between agencies for example.
With only anecdotal evidence about sharing, it isn’t possible to determine what structural, organization or other barriers are blocking the flow of information. Or what changes would result in the largest amount of effective information sharing. If shared information is mired at upper management levels, then it is of little use to actual analysts.
BTW, you can rest assured this work will not be used inappropriately:
Matisziw’s model was documented in the publicly available journal PLoS ONE. Making such a powerful tool widely available won’t be a danger, Matisziw said. To use his model, a network must be understood in detail. Since terrorists and other criminals don’t have access to enough data about the networks, they won’t be able to use the model to develop doomsday scenarios. [From: Cyberwarfare, Conservation and Disease Prevention Could Benefit from New Network Model, where I first saw this story.
Do terrorists develop anything other than “doomsday scenarios?” Or is that just PR? Like Y2K or the recent DNS issue. Everyone gets worked up, small bump, life goes on.