Brief announcement: Universal data aggregation trees for sensor networks in low doubling metrics

Abstract

We describe a novel approach for constructing a single spanning tree for data aggregation towards a sink node. The tree is universal in the sense that it is static and independent of the number of data sources and fusion-costs at intermediate nodes. The tree construction is in polynomial time, and for low doubling dimension topologies it guarantees a O(log2 n)-approximation of the optimal aggregation cost. With constant fusion-cost functions our aggregation tree gives a O(logn)-approximation for every Steiner tree to the sink. © 2009 Springer-Verlag.