The wireless epidemic

The wireless epidemic by Jon Kleinberg

At one end are network models that reflect strong spatial effects, with nodes at fixed positions in two dimensions, each connected to a small number of other nodes a short distance away [9]. At the other end are ‘scale-free’ networks, which are essentially unconstrained by physical proximity, and in which the number of contacts per node are widely spread [14]. Models based on human travel data occupy an intermediate position in this spectrum of spatial constraints. The different network structures lead in turn to qualitative differences in the way epidemics spread: whereas epidemics can persist at arbitrarily low levels of virulence in scale-free networks[14,15], epidemics in simple two-dimensional models need a minimum level of virulence to prevent
them from dying out quickly [9].

Bluetooth ...is disrupting this dichotomy by making possible computer-virus outbreaks whose progress closely tracks human mobility patterns. These types of wireless worm are designed to infect mobile devices such as cell phones, and then to continuously scan for other devices within a few tens of metres or less, looking for new targets. A computer virus thus becomes something you catch not necessarily from a compromised computer halfway around the world, but possibly from the person sitting next to you on a bus, or at a nearby table in a restaurant.

9. Durrett, R. SIAM Rev. 41, 677–718 (1999).
14. Pastor-Satorras, R. & Vespignani, A. Phys. Rev. Lett. 86, 3200–3203 (2000).
15. Berger, N., Borgs, C., Chayes, J. T. & Saberi, A. I. Proc. 16th ACM Symp. Discr. Algor. 301–310 (ACM, New York, 2005).