Energy Scavenging for Mobile and Wireless Electronics
IEEE Pervasive Computing
Micro power meter for energy monitoring of wireless sensor networks at scale
Proceedings of the 6th international conference on Information processing in sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
IEEE Communications Magazine
Power, spatio-temporal bandwidth, and distortion in large sensor networks
IEEE Journal on Selected Areas in Communications
Implications of energy profile and storage on energy harvesting sensor link performance
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Voluntary energy harvesting relays and selection in cooperative wireless networks
IEEE Transactions on Wireless Communications
Testing selective transmission with low power listening
REALWSN'10 Proceedings of the 4th international conference on Real-world wireless sensor networks
Energy-efficient opportunistic spectrum access in cognitive radio networks with energy harvesting
Proceedings of the 4th International Conference on Cognitive Radio and Advanced Spectrum Management
A Markovian model for harvested power from human motion
BodyNets '13 Proceedings of the 8th International Conference on Body Area Networks
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Energy harvesting from the working environment has received increasing attention in the research of wireless sensor networks. Recent developments in this area can be used to replenish the power supply of sensors. However, power management is still a crucial issue for such networks due to the uncertainty of stochastic replenishment. In this paper, we propose a generic mathematical framework to characterize the policy for single hop transmission over a replenishable sensor network. Firstly, we introduce a Markov chain model to describe different modes of energy renewal. Then, we derive the optimal transmission policy for sensors with different energy budgets. Depending on the energy status of a sensor and the reward for successfully transmitting a message, we prove the existence of optimal thresholds that maximize the average reward rate. Our results are quite general since the reward values can be made application-specific for different design objectives. Compared with the unconditional transmit-all policy, which transmits every message as long as the energy storage is positive, the proposed optimal transmission policy is shown to achieve significant gains in the average reward rate.