Traditional data aggregation methods use data originating from all sensor nodes of the wireless sensor network (WSN). Unfortunately, the use of all available sensors is not a resource efficient approach for such environments. Therefore, in this paper, we propose a novel aggregation procedure based on a hypothesis testing, where a subset of reporting nodes is intermittently selected. Neyman-Pearson lemma is used to select reporting nodes and the critical value, which is used in this aggregation procedure. Furthermore, a performance evaluation is discussed to illustrate how the proposed aggregation procedure outperforms the existing detection methods, and the dependency of the aggregation procedure and network attributes.
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