Abstract:This paper proposes a self-adaptive sampling scheme for WSNs, which aims at capturing accurately the behavior of the physical parameters of interest in each specific WSN context yet reducing the overhead in terms of sensing events. The sampling scheme relies on a set of low-complexity rules capable of auto-regulate the sensing frequency in accordance with each parameter behavior. As proof-of-concept, based on real environmental datasets, we provide statistical indicators illustrating the added value of the pro… Show more
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