Network-adaptive management of computation energy in wireless sensor networks

Today's sensor nodes can be equipped with powerful microcontrollers to address the increasing need of real-time processing of sensed data. For instance, body sensor networks for gesture recognition require filtering of acceleration values at line rate. This requirement imposes a paradigm shift with regard to more traditional sensor networks characterized by low activity duty cycles. Therefore, energy conservation strategies applied to wireless sensor nodes to increase their lifetime must take into account computation power rather than focusing only on communication power. In this paper we present a novel approach which aims at exploiting the knowledge of network status to optimize the power consumption of the node microcontroller. The proposed approach is tested in various network conditions, both synthetic and realistic, in the context of IEEE 802.15.4 standard. Experimental results demonstrate that the proposed approach allows to achieve power savings of up to 70% with minimum performance penalty.