Grafting energy-harvesting leaves onto the sensornet tree

Authors:
Lohit Yerva;Brad Campbell;Apoorva Bansal;Thomas Schmid;Prabal Dutta
Affiliations:
University of Michigan, Ann Arbor, MI, USA;University of Michigan, Ann Arbor, MI, USA;University of Michigan, Ann Arbor, MI, USA;University of Utah, Salt Lake City, UT, USA;University of Michigan, Ann Arbor, MI, USA
Venue:
Proceedings of the 11th international conference on Information Processing in Sensor Networks
Year:
2012

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Abstract

We study the problem of augmenting battery-powered sensornet trees with energy-harvesting leaf nodes. Our results show that leaf nodes that are smaller in size than today's typical battery-powered sensors can harvest enough energy from ambient sources to acquire and transmit sensor readings every minute, even under poor lighting conditions. However, achieving this functionality, especially as leaf nodes scale in size, requires new platforms, protocols, and programming. Platforms must be designed around low-leakage operation, offer a richer power supply control interface for system software, and employ an unconventional energy storage hierarchy. Protocols must not only be low-power, but they must also become low-energy, which affects initial and ongoing synchronization, and periodic communications. Systems programming, and especially bootup and communications, must become low-latency, by eliminating conservative timeouts and startup dependencies, and embracing high-concurrency. Applying these principles, we show that robust, indoor, perpetual sensing is viable using off-the-shelf technology.