We consider the problem of deploying wireless sensors in a three dimensional space to achieve a desired degree of coverage, while, minimizing the number of sensors placed. Typical sensor deployment scenarios impose constraints on possible locations of the sensors, and on the desired coverage, but currently there is no unified way to handle these constraints in optimizing the number of sensors placed. We present a novel approach called discretization which allows us to cast the sensor deployment problem as a discrete optimization problem, and hence apply well-understood and flexible discrete optimization techniques for sensor deployment. Our results show that this approach yields solutions that nearly minimize the number of sensors used, while providing a high degree of coverage. Further, unlike typical approaches to sensor deployment, where 3D coverage is significantly more complex than 2D coverage, discretization is equally easy to apply for 2D as well as 3D coverage.
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