Improving energy predictions in EH-WSNs with Pro-Energy-VLT

Authors:
Alessandro Cammarano;Chiara Petrioli;Dora Spenza
Affiliations:
University of Rome "La Sapienza";University of Rome "La Sapienza";University of Rome "La Sapienza"
Venue:
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
Year:
2013

Citing 3
Cited 0

Power management in energy harvesting sensor networks

ACM Transactions on Embedded Computing Systems (TECS) - Special Section LCTES'05
Balanced energy allocation scheme for a solar-powered sensor system and its effects on network-wide performance

Journal of Computer and System Sciences
Pro-Energy: A novel energy prediction model for solar and wind energy-harvesting wireless sensor networks

MASS '12 Proceedings of the 2012 IEEE 9th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS)

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Abstract

The increasing popularity of micro-scale energy-scavenging techniques for wireless sensor networks (WSNs) is opening new opportunities for the development of energy-autonomous systems. To sustain perpetual operations, however, environmentally-powered motes must adapt their workload to the stochastic nature of ambient power sources. Energy prediction algorithms, which forecast the source availability and estimate the expected energy intake in the near future, are precious tools to support the development of proactive power management strategies. In this work, we propose Pro-Energy-VLT, an enhancement of the Pro-Energy prediction algorithm that improves the accuracy of energy predictions, while reducing its memory and energy overhead.