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In this paper, we propose a grid-based working node (WN) selection approach for wireless sensor networks. Due to coverage redundancy, it is highly desirable to identify a minimum subset of sensors in a wireless sensor network to serve as WNs, while the remaining sensors are deactivated to save power and reduce potential interference. The basic idea of our solution approach is to represent the coverage of the sensors by a number of sample points, i.e., the intersection points of the established grid. A simple approximation algorithm and a linear programming method are employed to select as few sensors as possible to cover all sample points. In order to reduce the computational time, clusters are formed and WN selection is performed within each cluster. The performance of the proposed WN selection schemes is quantified and the tradeoff among accuracy, communication overhead and computational time is evaluated via analyses and simulations.