Connectivity of the $k$-nearest-neighbours random geometric graph model
Many real-life networks have an inherent geometry, which should be reflected in the random graph models used to analyse their behaviour. A typical example is that of radio networks: radio devices may find it easier to exchange information if they lie close to each other than if they lie far apart. This and other examples have motivated research into specifically geometric models of random graphs.
In this talk I will present one such model, the $k$-nearest-neighbours random geometric graph model, and discuss its connectivity properties.