  We present an approach to the distributed storage of data across a swarm of
mobile robots that forms a shared global memory. We assume that external
storage infrastructure is absent, and that each robot is capable of devoting a
quota of memory and bandwidth to distributed storage. Our approach is motivated
by the insight that in many applications data is collected at the periphery of
a swarm topology, but the periphery also happens to be the most dangerous
location for storing data, especially in exploration missions. Our approach is
designed to promote data storage in the locations in the swarm that best suit a
specific feature of interest in the data, while accounting for the constantly
changing topology due to individual motion. We analyze two possible features of
interest: the data type and the data item position in the environment. We
assess the performance of our approach in a large set of simulated experiments.
The evaluation shows that our approach is capable of storing quantities of data
that exceed the memory of individual robots, while maintaining near-perfect
data retention in high-load conditions.
