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Minimisation de la consommation d’énergie des réseaux de capteurs dans les applications de couverture de cibles

Abstract : Wireless Sensor Networks (WSN) consist of tiny sensor nodes with embedded microcontrollers, low power radios, battery cells and sensors which are used to monitor environmental conditions such as temperature, pressure, humidity, and vibration. Today, these networks are used in a wide range of military, health, domestic, urban, industrial and environmental applications. Target coverage applications are those where several points of interest called targets must be continuously monitored by sensor nodes. In most target coverage applications, sensor nodes have a limited amount of energy and it is therefore critical to efficiently manage their energy consumption in order to extend the network lifetime. A common approach to tackle this problem is to alternate the operation of sensor nodes between active and sleep mode. The scheduling of appropriate subsets of sleep/active sensor nodes in order to maximize the network lifetime is an NP-hard problem called Maximum Lifetime Coverage Problem (MLCP). In this thesis, we aim at proposing new heuristics to the MLCP, while considering more realistic assumptions on lifetime and energy consumption of sensor nodes. Firstly, we propose two greedy heuristics with the assumption that the sensor nodes do not necessarily have the same lifetime. The first heuristic is based on an adaptive method while the second uses the idea of blacklist, which allows to optimize the management of least covered targets called critical targets. Secondly, by considering that the energy consumed by sensor nodes put in sleep mode is not negligible, we propose a third greedy heuristic that takes into account the remaining energy of the sensor nodes in the choice of the nodes to activate. Then, we propose a recurring approach for regular networks. We then study a family of hard instances of the MLCP, namely the sub-family of regular networks composed of odd-sized rings. We propose for this subclass, an analytical approach to obtain effective solutions which we conjecture optimality. Finally, we develop a system for air pollution monitoring and fire detection based on a wireless sensor network and we evaluate the network lifetime gain when an algorithm for the MLCP is integrated in such a system.
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  • HAL Id : tel-02520915, version 1

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Diane Tchuani Tchakonte. Minimisation de la consommation d’énergie des réseaux de capteurs dans les applications de couverture de cibles. Micro et nanotechnologies/Microélectronique. Université de Yaoundé I, 2019. Français. ⟨NNT : 2019GREAT043⟩. ⟨tel-02520915⟩

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