  In optimizing the topology of wireless networks built of a dynamic set of
spatially embedded agents, there are many trade-offs to be dealt with. The
network should preferably be as small (in the sense that the average, or
maximal, pathlength is short) as possible, it should be robust to failures, not
consume too much power, and so on. In this paper, we investigate simple models
of how agents can choose their neighbors in such an environment. In our model
of attachment, we can tune from one situation where agents prefer to attach to
others in closest proximity, to a situation where distance is ignored (and thus
attachments can be made to agents further away). We evaluate this scenario with
several performance measures and find that the optimal topologies, for most of
the quantities, is obtained for strategies resulting in a mix of most local and
a few random connections.
