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A multi-hop network of wireless sensors can be used to gather spatio-temporal samples of a physical phenomenon and transmit these samples to a processing center. This paper addresses the important issue of minimizing the number of transmissions required to gather one sample from each sensor. The technique used to minimize communication costs combines analytical results from stochastic geometry with a distributed, randomized algorithm for generating clusters of sensors. The minimum communication energy achieved by this approach is significantly lower than the energy costs incurred in non-clustered networks and in clustered networks produced by such algorithms as the Max-Min d-cluster algorithm.