The maximum network lifetime is a well known and studied optimization problem. The aim is to appropriately schedule the activation intervals of the individual sensing devices composing a wireless sensor network used for monitoring purposes, in order to keep the network operational for the longest period of time (network lifetime). In this work, we extend this problem by taking into account the issue of charging the sensor batteries. More specifically, it has to be decided how much charge should be provided to each sensor, given the existence of a charging device with limited energy availability. An exact column generation algorithm embedding a genetic algorithm for the subproblem is proposed. Computational results reveal that by appropriately choosing the charge levels, remarkable network lifetime improvements can be obtained, in particular when the available energy is scarce.

Optimization of sensor battery charging to maximize lifetime in a wireless sensors network

Carrabs F.;D'Ambrosio C.
;
Raiconi A.
2021-01-01

Abstract

The maximum network lifetime is a well known and studied optimization problem. The aim is to appropriately schedule the activation intervals of the individual sensing devices composing a wireless sensor network used for monitoring purposes, in order to keep the network operational for the longest period of time (network lifetime). In this work, we extend this problem by taking into account the issue of charging the sensor batteries. More specifically, it has to be decided how much charge should be provided to each sensor, given the existence of a charging device with limited energy availability. An exact column generation algorithm embedding a genetic algorithm for the subproblem is proposed. Computational results reveal that by appropriately choosing the charge levels, remarkable network lifetime improvements can be obtained, in particular when the available energy is scarce.
2021
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4733585
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