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In this paper, the authors have developed a general optimization framework for solving the problem of maximizing revenue in data aggregation trees when a deadline is imposed by the sink. They considered a one-hop interference model and proposed a polynomial time algorithm that uses only local information at each hop to obtain the optimal solution. The problem can be extended to a general interference model. However, the complexity of scheduling transmissions may become high depending on the interference model used. Finally, they discussed a number of interesting applications and interpretations to the solution, such as, incorporating sleep-wake scheduling, maximizing weighted revenue and maximizing accuracy.
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