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Sensors 2017, 17(7), 1642; doi:10.3390/s17071642

Extending Wireless Rechargeable Sensor Network Life without Full Knowledge

Computer Science and Engineering Department, University of Nebraska, Lincoln, NE 68588, USA
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Received: 29 May 2017 / Revised: 3 July 2017 / Accepted: 12 July 2017 / Published: 17 July 2017
(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)
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Abstract

When extending the life of Wireless Rechargeable Sensor Networks (WRSN), one challenge is charging networks as they grow larger. Overcoming this limitation will render a WRSN more practical and highly adaptable to growth in the real world. Most charging algorithms require a priori full knowledge of sensor nodes’ power levels in order to determine the nodes that require charging. In this work, we present a probabilistic algorithm that extends the life of scalable WRSN without a priori power knowledge and without full network exploration. We develop a probability bound on the power level of the sensor nodes and utilize this bound to make decisions while exploring a WRSN. We verify the algorithm by simulating a wireless power transfer unmanned aerial vehicle, and charging a WRSN to extend its life. Our results show that, without knowledge, our proposed algorithm extends the life of a WRSN on average 90% of what an optimal full knowledge algorithm can achieve. This means that the charging robot does not need to explore the whole network, which enables the scaling of WRSN. We analyze the impact of network parameters on our algorithm and show that it is insensitive to a large range of parameter values. View Full-Text
Keywords: charging algorithm; no knowledge charging; wireless recharging sensor network; wireless power transfer; unmanned aerial vehicle charging algorithm; no knowledge charging; wireless recharging sensor network; wireless power transfer; unmanned aerial vehicle
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Najeeb, N.W.; Detweiler, C. Extending Wireless Rechargeable Sensor Network Life without Full Knowledge. Sensors 2017, 17, 1642.

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