DocumentCode :
1600077
Title :
Grafting energy-harvesting leaves onto the sensornet tree
Author :
Yerva, Lohit ; Campbell, Bradford ; Bansal, Ankur ; Schmid, Thomas ; Dutta, Pranab
Author_Institution :
Comput. Sci. & Eng. Div., Univ. of Michigan, Ann Arbor, MI, USA
fYear :
2012
Firstpage :
197
Lastpage :
207
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.
Keywords :
energy harvesting; protocols; synchronisation; telecommunication power management; telecommunication power supplies; wireless sensor networks; battery-powered sensornet trees; energy storage hierarchy; energy-harvesting leaf nodes; energy-harvesting leave grafting; lighting conditions; low-leakage operation; off-the-shelf technology; periodic communications; power supply control interface; protocols; synchronization; system software; systems programming; Batteries; Capacitors; Photovoltaic cells; Power supplies; Regulators; Sensors; Voltage control; energy; harvesting sensor node; low power wireless networking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Processing in Sensor Networks (IPSN), 2012 ACM/IEEE 11th International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/IPSN.2012.6920957
Filename :
6920957
Link To Document :
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