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In this paper, authors develop tractable mathematical models and approximate solution algorithms for a class of integer optimization problems with probabilistic and deterministic constraints, with applications to the design of distributed sensor networks that have limited connectivity. For a given deployment region size, authors calculate the Pareto frontier of the sensor network utility at the desired probabilities for d-connectivity and k-coverage. As a result of the analysis, they determine the number of sensors of different types to deploy from a sensor pool, which offers a cost vs. performance trade-off for each type of sensor.
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