We propose a general framework to index very large datasets of spatial data in a distributed system. Our proposal is built on the recently proposed Scalable Distributed Rtree (SD-Rtree)~\cite{MLR07} and addresses specifically the server allocation problem. In SD-Rtree, a new server is assigned to the network whenever a split of a full node is required. We describe a more flexible allocation protocol which copes with a temporary shortage of storage resources. Our algorithm is especially based on $k$-NN query processing we introduce as well. We analyze the cost of this protocol, describe its features, and propose practical hints to use it. We also present experiments validating our approach.