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We address the problem of in-network processing of k-Maximizing Range Sum (k-MaxRS) queries inWireless Sensor Networks (WSN). The traditional, Computational Geometry version of the MaxRS problem considers the setting in which, given a set of (possibly weighted) 2D points, the goal is to determine the optimal location for a given (axes-parallel) rectangle R to be placed so that the sum of the weights (or, a simple count) of the input points in R’s interior is maximized. In WSN, this corresponds to finding the location of region R such that the sum of the sensors’ readings inside R is maximized. The k-MaxRS problem deals with maximizing the overall sum over k such rectangular regions. Since centralized processing – i.e., transmitting the raw readings and subsequently determining the k-MaxRS in a dedicated sink – incur communication overheads, we devised an efficient distributed algorithm for in-network computation of k-MaxRS. Our experimental observations show that the novel algorithm provides significant energy/communication savings when compared to the centralized approach.