Physarum-inspired self-biased walkers for distributed clustering
In this report, we propose a distributed scheme to compute distance-based clusters. We first present a mechanism based on the flow of distributed tokens called walkers, circulating randomly between a source and a sink to compute a shortest path. This mechanism is a discrete emulation of
the slime mould (Physarum polycephalum) dynamics presented in : each node observes the flow of walkers going through each adjacent edge and uses this flow to compute the probabilities with which it sends the walkers through each edge. Then, based on this mechanism, we show how several sources compute a shortest path DAG to a given sink. Finally, given some clusterheads acting like sinks, we
prove that this process converges to distance-based clusters (i.e. nodes join the clusterhead to which
they are closest) with shortest-path DAGs. The algorithm is designed with a special focus on dynamic networks: the
ow locally adapts to the appearance and disappearance of links and nodes, including clusterheads.